A Systems Biology Approach to Understand Leaf Growth ...

University of Antwerp Laboratory for Molecular Plant Physiology and Biotechnology

Department of Biology

A Systems Biology Approach to Understand Leaf Growth Regulation in Arabidopsis thaliana

Een systeembiologische benadering voor het begrijpen van

de regulatie van bladgroei in Arabidopsis thaliana

Shweta Kalve

Promotor Prof. dr. ir. Gerrit T.S. Beemster

Thesis submitted in partial fulfillment of the requirements to obtain the degree of Doctor of Philosophy (PhD) in Biology

Academic year 2014-2015

University of Antwerp CGB building U 6th floor, 171 Groenenborgerlaan,

B-2020 Antwerp, Belgium

ISBN: 9789057284670

Depot Number: D/2014/12.293/29

@ Shweta KalveThe author and promotor allow to consult and copy parts of this work for personal use. Further reproduction or transmission in any form or by any means, without the prior permission of the author is strictly forbidden.

This work is dedicated to my father and late mother, Kishor Kalve and Kirti Kalve, who

have always loved me unconditionally and emphasized the importance of education

and whose good examples have taught me to work hard for the things that I aspire to

achieve. This work is also dedicated to my husband and best friend, Shree Kulkarni, I

give my deepest expression of love and appreciation for the encouragement that you

gave and the sacrifices you made during this graduate program. I am truly thankful

for having you in my life.

Examination Board

Chair

Prof. dr. Els Prinsen Department of Plant Growth and Development University of Antwerp

Promotor

Prof. dr. ir. Gerrit T.S. Beemster Laboratory for Molecular Plant Physiology and Biotechnology University of Antwerp

Members

Prof. dr. Kris Vissenberg Department of Plant Growth and Development University of Antwerp

Prof. dr. Arp Schnittger Department of Developmental Biology University of Hamburg

Prof. dr. Lieven De Veylder Department of Plant Systems Biology VIB, Ghent University

Prof. dr. Han Asard Laboratory for Molecular Plant Physiology and Biotechnology University of Antwerp

Dr. Dirk De Vos Laboratory for Molecular Plant Physiology and Biotechnology University of Antwerp

TABLE OF CONTENTS

Summary 1 Samenvatting 4 Scope, aims and thesis outline 7 Chapter1 Leaf development: a cellular perspective

Abstract 11

Introduction 12

Process that control leaf growth

The shoot apical meristem (SAM) 14

Leaf initiation 17

Leaf polarity 19

Cytoplasmic growth 22

Cell division 25

Endoreduplication 32

Regulation of transition between cell division

and expansion 36

Turgor driven cell growth 40

Cell differentiation

o Guard cell formation 43

o Vascular differentiation 46

o Trichome development 49

A system’s perspective on leaf growth 51

Acknowledgements 55

Chapter 2 Three-dimensional patterns of cell division and expansion throughout the development of Arabidopsis thaliana leaves Abstract 91

Introduction 92

Results

Whole leaf expansion 95

Cell type specific anticlinal expansion 96

Anticlinal cell division and periclinal expansion

rates 97

Effect of light on leaf growth 100

Discussion

Differences in growth rates across the developing

leaf 105

Cell layer specific contributions to leaf thickness 107

Anticlinal cell division and size evolution differ

between cell layers 108

Low light differentially affects leaf growth in

three dimensions 110

Implications of kinematic analysis 112

Conclusion 112

Material and Methods 113

Acknowledgements 115

Chapter 3 Crosstalk between auxin signaling and osmotic stress response in the regulation of leaf growth of Arabidopsis thaliana Abstract 125

Introduction 126

Results

Crosstalk between osmotic stress response

induced by mannitol and NAA 128

Cellular basis of the leaf growth response to

NAA and mannitol 131

Kinematic analysis of leaf growth 131

DR5::GUS expression 134

Endogenous IAA concentration 135

Transcriptome analysis 136

Gene enrichment 139

Auxin biosynthesis pathway 142

Auxin conjugation and degradation 144

Auxin transport 147

Auxin signaling 148

Cell cycle regulation 149

Regulation of cell expansion 151

Regulation of redox metabolism 152

Discussion

The cellular basis of the growth response

to auxin and osmotic stress 154

Osmotic stress affects auxin homeostasis

and signaling 155

Growth regulation 157


Supplemental Data 165


Chapter 4 Downregulation of KRPs promotes cell division and endoreduplication in the leaves of Arabidopsis thaliana Abstract 185

Introduction 186

Results

Identification of the T-DNA insertion mutants 188

Differential expression of seven Arabidopsis

KRPs during leaf development 189

Inhibition of KRPs causes enhanced leaf growth

by increasing cell number 191

Kinematic analysis shows no difference in cell division

rates between Col-0 and the krp4/6/7 mutant 192

Increased leaf size in the krp4/6/7 mutant is the

result of enlarged seed and embryo size 194

Transcriptome analysis of krp4/6/7 reveals upregulation

of genes related to cell cycle and DNA replication

in leaves 196

Downregulation of KRP genes stimulates

endoreplication 202

Discussion 205


Supplemental data 215


Chapter 5 Mild overexpression of CDKB2;2 accelerates plant growth in Arabidopsis thaliana Abstract 233

Introduction 234

Results

Mild overexpression of CDKB2;2 enhances plant

growth 235

Enhanced leaf growth of PROCDKA;1:CDKB2;2 is mainly

due to an increase in cell number 237

CDKB2;2 overexpression line makes larger seeds

and embryo 240

Transcriptome analysis 241

Discussion 245


Supplemental Data 251


Chapter 6 General discussion and future perspectives 259 Curriculum Vitae 271


1

SUMMARY

Adaptation of growth of individual organs in the context of an entire organism is crucial for

plants, and influenced by various genetic and environmental factors. Besides its direct

function as a food source, the leaf is the main photosynthetic organ that perceives light and

converts solar energy into organic carbon. Moreover, from an evolutionary point of view,

all floral organs (e.g. flowers and fruits) are modified leaves. Therefore, understanding the

regulation of leaf growth is important and has two main objectives. The first one is to

comprehend the molecular/biological processes that control leaf growth and development,

and determine the final shape and size in response to the surrounding environment. The

second aim is to improve crop yield in the context of changing climatic conditions, such as

increase in temperature, salinity and drought by means of genetic engineering approaches.

The development of leaves is an intriguing process, which is the result of a complex

interplay of different (yet often overlapping) pathways. At the cellular level, leaf growth is

strictly determined by spatial and temporal regulation of (only) two processes: cell

proliferation which involves cell growth (i.e. enlargement of cell volume by increasing

cytoplasmic volume) in combination with cell division (the process of dividing cellular

content over two daughter cells and placing a new cell wall) and cell expansion (mostly

vacuolar enlargement and turgor driven cell wall extension in absence of cell division),

which are regulated at the molecular level by chemical concentrations (metabolites such as

sugars, hormones and signaling peptides) and physical interactions (particularly turgor,

wall stresses). This means that the plethora of molecular pathways, that have been

demonstrated to be involved in leaf development, must be linked to these two processes.

Therefore, it is essential to use an interdisciplinary approach to unravel the complex

networks involved in leaf growth and development, instead of studying these regulatory

processes separately.

To comprehend leaf growth regulation in more detail, we performed a first analysis of the

dynamics of cell division and expansion in all three dimensions throughout the

development of Arabidopsis leaf. To achieve this, we extended the existing kinematic

analysis from a single tissue layer to the full three dimensional structure of the leaf. The

2

analysis showed that the leaf growth is highly anisotropic, where expansion rates in the

lateral direction are higher than in the longitudinal direction. While, expansion rates in the

anticlinal direction are an order of magnitude lower throughout leaf development.

Moreover, petiole elongation rates are higher than longitudinal expansion rates in the

blade. Detailed analysis of tissue layers showed that anticlinal expansion rates differ

between cell types, with mesophyll tissues having higher expansion rates than epidermal

cells. We subsequently demonstrated that low light affects cell division and expansion at

different developmental stages of the leaf. Low light reduces leaf expansion rates, which

are partly compensated by an increased duration of expansion. We found that the reduced

leaf thickness caused by low light is associated with a reduced number of palisade cell

layers, established prior to emergence of the leaf.

We also studied the role of the phytohormone auxin in the response of leaf development to

osmotic stress. Our work provides the first evidence of crosstalk between auxin signaling

and osmotic stress response. Kinematic analysis showed the dual nature of auxin where it

promotes leaf growth under optimal concentration but increases sensitivity under osmotic

stress. Interestingly, transcript profiling of proliferating leaves shows the upregulation of

auxin biosynthesis genes under stress while downregulation in response to exogenous

auxin. In contrast, increased expression of transcripts related to deconjugation and

degradation suggest low levels of conjugated auxin under osmotic stress, which was

confirmed by detailed hormone measurements. Moreover, increased growth by exogenous

auxin is also reflected by increased expression of transcripts related to cell division and

expansion, while their reduced expression under stress is consistent with the decreased

leaf growth under osmotic stress.

One of the key findings from our work is that cell division plays a central role in leaf growth

responses to environmental conditions. Therefore, to increase the understanding of the

regulators controlling cell cycle, we studied the role of negative regulators of the cell cycle,

Kip Related Proteins (KRPs) during leaf development. As KRPs is a family of seven genes

having redundant function, single and multiple mutants were studied. It is demonstrated

that single mutants cause only minor or no significant change in leaf growth, while double

3

and triple mutants display increased leaf growth as a result of enhanced cell proliferation.

Remarkably, the enlarged leaf of these mutants is a consequence of an increased embryo

size. Furthermore, transcriptome analysis revealed the upregulation of the DNA synthesis

machinery during leaf growth, which was also reflected in increased endoreduplication. In

addition, we developed a mathematical model of the cell cycle which provides a theoretical

explanation for the two-fold increase in endoreplication by inhibition of KRPs.

In addition to KRPs, we also studied the effect of mild overexpression of positive cell cycle

regulator CDKB2, which also results in enlarged leaves due to increased cell proliferation

while cell expansion is not affected. In addition, embryo development is also found to be

responsible for part of the increased leaf growth in the CDKB2 overexpression line.

4

SAMENVATTING

Aanpassing van de groei van individuele organen is cruciaal voor planten en wordt

beïnvloed door meerdere omgevings- en genetische factoren. Het blad is, naast een

voorname voedselbron, een belangrijk fotosynthetisch orgaan, dat zonne-energie omzet

naar organische koolstof. Vanuit een evolutionair standpunt zijn alle bloemorganen (vb.

bloemen en vruchten) eveneens gemodificeerde bladeren. Bijgevolg is een goed begrip van

de werking van bladgroei zeer belangrijk en deze werking kan worden bestudeerd met

meerdere doelen voor ogen. Een eerste doel is het begrip van de moleculaire/biologische

processen die bladgroei en –ontwikkeling beïnvloeden en de definitieve vorm en grootte

van het blad bepalen in respons op omgevingsfactoren. Een tweede doel is het verbeteren

van gewasopbrengsten bij snel veranderende klimaatcondities zoals een toename in

temperatuur, zoutgehalte en droogte, met behulp van genetische modificatie.

Bladontwikkeling is een intrigerend proces, bestaande uit een complex samenspel van

verschillende (vaak overlappende) mechanismen. Op cellulair niveau wordt bladgroei

bepaald door ruimtelijke en temporele regeling van (slechts) twee processen:

celproliferatie, wat celgroei (de toename in celvolume door een verhoging van het

cytoplasmatisch volume) inhoudt, in combinatie met celdeling (het proces waarbij de

cellulaire inhoud wordt verdeeld over twee dochtercellen door de aanmaak van een

nieuwe celwand) en celexpansie (voornamelijk vacuolaire vergroting en turgor-gedreven

celwandextensie die niet gevolgd wordt door een celdeling). Deze processen worden op

hun beurt op het moleculair niveau gereguleerd door chemische concentraties

(metabolieten zoals suikers, hormonen and signaalpeptiden) en fysische interacties (vooral

turgor en wandstress). Dit betekent dat de overvloed aan moleculaire mechanismen die

betrokken zijn in bladontwikkeling, gelinkt moeten zijn met deze processen. Het is

essentieel om gebruik te maken van een geïntegreerde visie op de regulerende processen

om zo het complexe netwerk, betrokken bij bladgroei en –ontwikkeling, te begrijpen. Deze

visie is mogelijk met behulp van een interdisciplinaire aanpak.

Om de regeling van bladgroei in meer detail te begrijpen, voerden we een eerste analyse uit

van de dynamiek van celdeling en –expansie in drie dimensies gedurende de volledige

5

ontwikkeling van het Arabidopsis blad. Om dit te bereiken, hebben we de bestaande

kinematische analyse uitgebreid van een enkele weefsellaag naar de volledige

driedimensionele structuur van het blad. De analyse toonde aan dat bladgroei

anisotropisch is, waarbij de expansiesnelheid in de laterale richting groter is dan die in de

longitudinale richting. Expansiesnelheden in de anticlinale richting zijn daarentegen een

grootteorde kleiner gedurende de bladontwikkeling. Bovendien is de elongatiesnelheid van

de bladsteel groter dan de longitudinale expansiesnelheid van het blad. Een gedetailleerde

analyse van weefsellagen toonde aan dat anticlinale expansiesnelheden verschillen tussen

celtypes, waarbij mesofiele cellen hogere expansiesnelheden hebben dan epidermale

cellen. We hebben vervolgens aangetoond dat een lage lichtintensiteit de celdeling en –

expansie beïnvloeden tijdens verschillende ontwikkelingsfasen van het blad. Een lage

lichtintensiteit reduceert de expansiesnelheid van bladeren, maar dit wordt deels

gecompenseerd door de duur van expansie. We vonden ook dat de gereduceerde bladdikte

veroorzaakt door een lage lichtintensiteit, wordt veroorzaakt door een gereduceerd aantal

cellagen in het palissadeweefsel en dat dit reeds wordt bepaald voor de verschijning van

het blad.

We bestudeerden ook de rol van het plantenhormoon auxine in de response van

bladontwikkeling op osmotische stress. Ons werk levert het eerste bewijs voor een

verband tussen auxine signalering en osmotische stress. Een kinematische analyse toonde

de dualiteit van auxine aan, waarbij het bladgroei promoot onder optimale concentraties,

maar gevoeligheid voor osmotische stess verhoogt. Transcript profiling van prolifererende

bladeren toont een opregulatie aan van auxinebiosynthese-genen tijdens stress, en een

neerregulatie als respons op exogeen auxine. Omgekeerd suggereerde een verhoogde

expressie van transcripten, gerelateerd aan deconjugatie en afbraak, lage niveaus van

geconjugeerd auxine tijdens osmotische stress. Dit werd bevestigd door gedetailleerde

hormoonmetingen. Daarnaast wordt een toegenomen groei bij exogeen auxine

weerspiegeld door een verhoogde expressie van transcripten gerelateerd aan celdeling en

–expansie, terwijl hun verlaagde expressie tijdens stress overeenstemt met de afgenomen

bladgroei tijdens osmotische stress.

6

Eén van de belangrijkste bevindingen is dat celdeling een belangrijke rol speelt in de

respons van bladgroei op omgevingsfactoren. Daarom bestudeerden we om de rol van

celcyclusregulatie tijdens bladgroei beter te begrijpen, de functie van Kip Related Proteins

(KRP’s), een klasse van negatieve regulatoren van de celcyclus. Omdat de KRP-familie 7

genen omvat, met een redundante functie, bestudeerden we het effect op bladgroei van

zowel enkele als meervoudige mutanten. We toonden daarbij aan dat enkelvoudige

mutanten weinig tot geen significante verschil vertonen in bladgroei, terwijl meervoudige

mutanten een toegenomen bladgroei hebben, als resultaat van een verhoogde

celproliferatie. Opvallend is dat de toegenomen bladgrootte bij de mutanten het gevolg is

van een toegenomen embryogrootte. Transcriptoom-analyse wees ook op een opregulatie

van het DNA-synthesemechanisme tijdens de bladgroei. Dit werd eveneens weerspiegeld in

een toegenomen endoreplicatie. Daarnaast ontwikkelden we een nieuw mathematisch

model van de celcyclus dat een theoretisch mechanisme beschijft dat de tweevoudige

toename in endoreplicatie door de remming van KRP’s verklaart.

Naast KRPs bestudeerden we ook het effect van milde overexpressie van de positieve

celcyclusregulator CDKB2, wat ook resulteert in vergrote bladeren dankzij een toegenomen

celproliferatie, terwijl celexpansie niet wordt beïnvloed. De embryonale ontwikkeling blijkt

ook hier een belangrijk proces te zijn dat die de verhoogde bladgroei in de CDKB2

overexpressie-lijnen gedeeltelijk verklaart.

7

SCOPE, AIMS AND THESIS OUTLINE

The aim of this PhD is to study the mechanisms whereby cell division and cell expansion

control leaf growth. The present work utilizes the model species Arabidopsis thaliana

because of it’s short life cycle, self-pollinating characteristic, small and fully sequenced

genome. We aimed to study how cell division and expansion translate the effect of

environmental and genetic factors through a number of recognized regulatory pathways,

including phytohormone signaling into a whole leaf phenotype. Finally, we aimed to

integrate the obtained knowledge into a mathematical model to improve the understanding

of cell cycle regulation in the context of the leaf growth processes. The research work

during PhD is described in following 6 chapters:

Chapter 1 includes a review of the regulatory processes controlling the development of

individual cells in the context of leaf growth and development. This chapter serves as an

introduction and gives an overview of the current knowledge of the major regulatory

mechanisms essential for leaf growth.

In Chapter 2, we expand the kinematic analysis to enable quantification of the spatial

dynamics of cell division and expansion in 3D. Hereby, it allows us to determine how the

rates of cell division and expansion vary in three dimensions (length, width and thickness)

of the leaf to determine the final leaf morphology in normal conditions and in response to

low light conditions.

Leaf growth and development are controlled by the concerted action of various

phytohormones and auxin is a key growth regulator, whereas water deficit is a major

growth limiting environmental factor. In Chapter 3, we explore the crosstalk between

auxin and osmotic stress in the control of leaf growth. This crosstalk is studied by

combining organ and cell level growth analysis with measurements of auxin

concentrations, response activity and genome-wide transcriptional study.

Cell division is a key process to control leaf growth and development. Therefore, to expand

our knowledge about the regulation of cell cycle activity during leaf growth, the role of Kip

8

Related Proteins (KRPs), a class of CDK inhibitors is studied in Chapter 4, whereas the

function of the plant specific B2-type cyclin dependent kinase is studied in Chapter 5. In

addition, mathematical modeling is used to gain a better and more detailed insight into the

complex molecular interactions of cell cycle regulation that are at the basis of leaf growth.

Finally, Chapter 6 contains a general discussion, which summarizes the main results and

gives an integrated overview of all the studied processes controlling leaf growth. Moreover,

it provides a common conclusion drawn from all the findings and possibilities for further

research.

Chapter 1

Leaf development: a cellular perspective

Shweta Kalve1, Dirk De Vos1, 2 and Gerrit T.S. Beemster1*

1Department of Biology, University of Antwerp, Antwerp, Belgium

2Department of Mathematics and Computer Science, University of Antwerp,

Antwerp, Belgium

*Corresponding Author

This chapter is published as a Review in Frontiers in Plant Science, 5:362, 2014

(doi:10.3389/fpls.2014.00362)

Contribution of S.K.- Performed the literature survey and wrote the manuscript


11

Abstract

Through its photosynthetic capacity the leaf provides the basis for growth of the whole

plant. In order to improve crops for higher productivity and resistance for future climate

scenarios, it is important to obtain a mechanistic understanding of leaf growth and

development and the effect of genetic and environmental factors on the process. Cells are

both the basic building blocks of the leaf and the regulatory units that integrate genetic and

environmental information into the developmental program. Therefore, to fundamentally

understand leaf development, one needs to be able to reconstruct the developmental

pathway of individual cells (and their progeny) from the stem cell niche to their final

position in the mature leaf. To build the basis for such understanding, we review current

knowledge on the spatial and temporal regulation mechanisms operating on cells,

contributing to the formation of a leaf. We focus on the molecular networks that control

exit from stem cell fate, leaf initiation, polarity, cytoplasmic growth, cell division,

endoreduplication, transition between division and expansion, expansion and

differentiation and their regulation by intercellular signaling molecules, including plant

hormones, sugars, peptides, proteins and microRNAs. We discuss to what extent the

knowledge available in the literature is suitable to be applied in systems biology

approaches to model the process of leaf growth, in order to better understand and predict

leaf growth starting with the model species Arabidopsis thaliana.


12

Introduction

Understanding the regulation of plant growth and its constituent organs is an important

objective in biology. It forms the basis for crop yield, turn-over in ecosystems and the

means for the plant to adapt to environmental conditions and experimental treatments.

The development of leaves in dicotyledonous plant species is an intriguing process,

resulting from a complex interplay of a multitude of regulatory pathways. On the one hand

it is so strictly regulated that the resultant leaf morphology is a reliable characteristic for

taxonomic classification. On the other hand however, the process is so plastic that

environmental factors can affect mature leaf size by an order of magnitude. Curiously, leaf

shape is often largely conserved between related species with genetic variations in

thousands of genes, while a single mutation can sometimes induce morphological

differences similar to those that distinguish species and even families (e.g. Barkoulas et al.,

2008). Due to these intriguing characteristics and the importance of leaves for plant

performance and function, many aspects of leaf development have been extensively

studied.

In recent decades, remarkable progress has been made in understanding the regulation of

leaf development via molecular/genetic approaches. Moreover, increasing use of high-

throughput technologies is constantly providing new biological information at various

organizational levels. In this context, systems biology provides a means to integrate the

accumulating knowledge into holistic mechanistic models to get a complete understanding

of biological processes. These models are often implemented through computer

simulations of normal and/or experimentally perturbed systems to test how well they

resemble the real situation and increase our understanding of its mechanistic basis.

A mechanistic understanding of leaf development should encompass an integrated view on

the regulatory networks that control developmental decisions and processes of cells as

they migrate in space and time from the shoot apical meristem (SAM) to their final position

in the leaf (Figure 1). Therefore, we review the subsequently acting developmental


13

networks that guide individual cells on their way from the SAM to their differentiated state

somewhere in a fully differentiated leaf. Based on this description we delineate to what

extent we understand how variations in the regulation at the cell level affect the shape and

size of the leaf as a whole, and what the implications are for implementing this knowledge

into fully-fledged simulation models.

Figure 1. Overview of the regulatory processes that determine the development of a leaf: The

cells that form the leaf originate from the stem cell niche at the shoot apical meristem. As a first step

in their development, cells need to loose stem cell identity (1). A leaf primordium is initiated in

groups of cells that migrate into the lateral regions of the SAM (2), which further acquires upper

(adaxial) and lower (abaxial) sides through leaf-polarity control (3). Afterwards, the transformation

of the small leaf primordium to a mature leaf is controlled by at least six distinct processes:

cytoplasmic growth (4), cell division (5), endoreduplication (6), transition between division and

expansion (7), cell expansion (8) and cell differentiation (9) into stomata (9a), vascular tissue (9b)

and trichomes (9c). Most of these processes are tightly controlled by different signaling molecules,

including the phytohormones. The developmental path of cells is indicated with red arrows, key

regulatory processes are numbered and indicated and regulation of these processes by

phytohormones/sugar is shown by blue arrows (pointed and T shaped arrows indicate positive and

negative regulation, respectively).


14

Process That Control Leaf Growth

The development of a leaf is a dynamic process where independent regulatory pathways

instruct component cells at different stages of their development to make differentiation

switches and to regulate the rate at which developmental processes are executed. Each of

these regulatory control points is essential to steer the development of individual cells.

When integrated over the entire cell population of a leaf, its growth and ultimately size and

shape are emergent properties that can be compared to real leaves. Because developmental

signals are perceived and executed at the level of individual cells, it is essential to

understand how these signals are integrated in the leaf developmental process, which can

be achieved by modeling the path of an individual cell (and its progeny) from shoot apical

meristem to the mature leaf. Although many of the pathways involved have been

extensively reviewed, to our mind the perspective of the individual cells has not been

explored systematically. Therefore the main aim of the present review is to provide this

cellular perspective to leaf development.

The shoot apical meristem (SAM)

The SAM is the source of all cells that ultimately form the shoot, including the subset that

ends up building the leaves. Generally, cells in the central zone (CZ) of the SAM divide at a

relatively low rate and remain in an undifferentiated state, whereas cells at the peripheral

zone (PZ) divide faster and differentiate into organs such as leaves, axillary nodes and

floral parts (Braybrook and Kuhlemeier, 2010; Veit, 2004). In dicots, the SAM consists of

three layers L1, L2 and L3; epidermal (L1) and subepidermal (L2) layers are known as

tunica and the inner layer (L3) is called the corpus (Satina et al., 1940).

From the cellular perspective, on-going (slow) division in the stem cell niche will cause

cells to become displaced away from the quiescent centre, where at some well-defined

place they lose their stem cell fate and acquire the actively dividing state. This transition is

controlled by the interplay of a regulatory loop involving the homeodomain transcription

factor WUSCHEL (WUS) in the rib zone (RZ) and CLAVATA gene products (CLV1, CLV2 and


15

CLV3) expressed in the central zone (CZ) of the SAM (Brand et al., 2000; Carles and

Fletcher, 2003; Schoof et al., 2000; Yadav and Reddy, 2011). The WUS and CLV based

pathway operates through two mobile signals: CLV3 and a hypothetical WUS mediated

signal (Figure 2). CLV3 encodes a small secreted ligand that is produced specifically in L1

and L2 cells, and moves into the underlying L3 cells where it binds with receptor like

proteins CLV1 (LRR receptor kinase) and/or CLV2 (receptor-like protein), which in turn

inhibit WUS activity (Carles and Fletcher, 2003; Clark, 2001). WUS activity in the L3 cells

induces the production of a non-cell-autonomous signal that moves to the stem cells and

activates the expression of CLV3 there (Braybrook and Kuhlemeier, 2010; Haecker and

Laux, 2001). It was proposed that the L1 produced miR394 signal is necessary for spatial

organization of the SAM. This mobile microRNA regulates WUS mediated stem cell

maintenance by inhibition of F box protein LEAF CURLING RESPONSIVENESS (LCR)

(Knauer et al., 2013).

Upon mutation in WUS the stem cells precociously transit into the peripheral actively

dividing zone, ultimately consuming the stem cell niche and thereby the meristem.

Inversely, in clv1 and clv3 mutants WUS activity of SAM cells is maintained much longer,

whereby the stem cell niche and consequently the SAM as a whole enlarge dramatically

(Laux et al., 1996; Steven E. Clark, 1993, 1995). Several mathematical models have focused

on the WUS-CLV interaction, predicting to various degrees how their expression domains

are modulated through mutation or misexpression (Hohm et al., 2010; Jonsson et al., 2005;

Nikolaev et al., 2007). Recent experimental studies supported by mathematical modeling

have shown that WUS movement is essential for direct transcriptional repression of the

differentiation program (Yadav et al., 2013) as well as in restricting its own accumulation

through activating its negative regulator CLV3 (Yadav et al., 2011).


16

Figure 2. Maintenance of stem cells in shoot apical meristem: The SAM is organized in three

functional zones [central zone (CZ), peripheral zone (PZ) and rib zone (RZ)] and three layers where

the antagonistic relation between WUS and CLV is essential to preserve cells in the meristem. WUS

activates CLV3, which further binds with CLV1/2 and in turn inhibits expression of WUS. Cytokinin

positively controls WUS expression where ARRs are negative regulators of cytokinin and are

inhibited by WUS. The L1 specific miR394 negatively affects the LCR protein, which interferes in

WUS/CLV based stem cell maintenance (pointed and T shaped arrows indicate positive and

negative regulation, respectively).

It has been postulated that signaling by the plant hormone cytokinin regulates WUS

expression via CLV-dependent and CLV-independent mechanisms (Gordon et al., 2009) to

promote SAM growth and maintenance with WUS repressing the transcription of

ARABIDOPSIS type-A RESPONSE REGULATORS (ARRs), which are the negative regulators of

cytokinin signaling (Leibfried et al., 2005; Sablowski, 2007; Figure 2) (Figure 2). Indeed,

mutations in cytokinin receptors (Higuchi et al., 2004) and over-expression of the cytokinin

dehydrogenase gene family of Arabidopsis (AtCKX) (Werner et al., 2003) reduce meristem

size and leaf area, indicating a relation between the SAM and leaf size. It appears however

that that the number of leaf founder cells is not an important determinant of the final leaf

size. For instance, a meta-analysis across a wide range of cactus species indicates that the

size of the SAM correlates closely to the number of leaves formed and has only minor

implications for their ultimate size (Mauseth, 2004).


17

Leaf initiation

Once progenitor cells are outside the stem cell niche, they need to decide whether they will

contribute to the main axis or will differentiate into lateral appendices such as leaf

primordia. This decision is primarily governed by the accumulation of the plant hormone

auxin it’s influx carrier [AUXIN RESISTANT (AUX1)] and its PIN1 (PIN-FORMED1) efflux

transporter (Bayer et al., 2009; Guenot et al., 2012). The efflux carriers orient the transport

of auxin towards neighboring cells with a higher auxin concentration, leading to the

formation of accumulation patterns across the cell population. Several mathematical

modeling studies (reviewed in De Vos et al., 2012) have simulated phyllotactic patterning

based on feedback interactions between auxin and PIN distribution. Some models postulate

that AUX1 creates auxin accumulation mainly in L1 layer cells, whereas PIN1 is initially

localized in the protodermal (L1) layer cells and causes drainage of auxin towards the base

of the shoot by inducing vascular strand differentiation in L2/3 layer cells of the SAM (de

Reuille et al., 2006; Reinhardt et al., 2003) (Figure 3).

Arabidopsis leaf differentiation from the apical meristem is abolished in the auxin

biosynthetic triple mutant yuc1 yuc4 pin1 (Cheng et al., 2007), whereas longer plastochron

and irregular vegetative growth occurs in the pin1 mutant (Guenot et al., 2012). Cells in the

SAM, which serve as a stem cell population, differ from the cells in the leaf primordium.

This distinction is controlled by complex and still poorly characterized regulatory

networks in which the antagonistic relation between two families of transcription factors,

KNOX1 (KNOTTED-like homeobox) and ARP (ASYMMETRIC LEAF1/ROUGH

SHEATH2/PHANTASTICA) proteins (Byrne et al., 2002; Hay and Tsiantis, 2006, 2010)

plays a crucial role (Figure 3). KNOX is expressed in all meristem cells except those at the

site of the organ initiation (Jackson et al., 1994; Long et al., 1996), whereas the (ARP family)

AS1 mRNA is expressed in the primordia forming cells, but not in the meristem (Byrne et

al., 2000). KNOX1 is required to maintain undifferentiated cells in the SAM (Scofield and

Murray, 2006) and increases cytokinin biosynthesis (Yanai et al., 2005), whereas ARP

initiates differentiation in the leaf primordium (Byrne et al., 2002). High levels of auxin

restrain cytokinin biosynthesis by the repression of KNOX1 activity (Su et al., 2011) (Figure


18

3). High auxin and AS1 expression also suppress the expression of the KNOX gene

BREVIPEDICELLUS (BP), which is required for leaf initiation (Hay et al., 2006). In

Arabidopsis, the KNOX1 gene SHOOTMERISTEMLESS (STM) acts antagonistically with ARP

gene products to control the induction of leaf primordia. The loss of function mutant stm

fails to produce a SAM, also preventing leaf formation (Long et al., 1996), whereas the as1

and as2 mutants have small and round leaves (Byrne et al., 2002).

Figure 3. Decision of leaf initiation: Accumulation peaks of auxin at the flank of the SAM through

PIN1/AUX1 mediate polar auxin transport, triggers development of a primordium where KNOX1

plays key role in stem cell maintenance. Additionally, KNOX1 positively regulates CK whereas it

negatively affects GA signaling through IPT7 and GA20 oxidases respectively. Opposite to it, ARP

regulates the emergence of a young primordium (pointed and T shaped arrows indicate positive

and negative regulation, respectively).

It has been demonstrated that the KNOX proteins trigger cytokinin (CK) biosynthesis

through the activation of IPT7 (encodes the CK biosynthetic enzyme isopentenyl

transferase) and repress the transcription of gibberellin (GA) biosynthetic genes that

encode GA20-oxidases (Jasinski et al., 2005; Sakamoto et al., 2001) (Figure 3). Thus, high

CK and low GA maintain stem cell identity in SAM cells by preventing cell differentiation

(Gordon et al., 2009; Veit, 2009).


19

Leaf polarity

After acquiring ‘leaf’ identity, the cells in the primordium have to develop a polarity

gradient along the dorso-ventral axis. Once the position of the leaf primordium is

established, a further increase in cell proliferation rates stimulates primordium outgrowth

from the SAM. If this growing primordium is removed by tangential incision, another

primordium arises which is cylindrical and abaxialized (lacking a flat leaf blade). This

highlights the importance of signals originating in the SAM and received by cells in the

primordium to determine polarity. This so called Sussex signal is yet to be identified

(Sussex, 1951). Waites and Hudson (1995) proposed that the dorsal and ventral sides of

the leaf are specified in the early development of the leaf primordium, when it is still

located within the SAM. They showed that the PHAN gene (encoding a MYB type

transcription factor) in Antirrhinum majus is involved in ab/ad-axial leaf polarity.

Subsequently the phabulosa-1 (phb-1d) mutant was characterized in Arabidopsis, whose

leaves were unable to develop a blade and were radially symmetrical (McConnell and

Barton, 1998).

Our knowledge of the regulation of antagonistic transcription factors specifying upper and

lower sides has greatly increased, but the molecular signals exchanged between cells on

both sides of the primordium to create this polarity are yet to be identified. Adaxial domain

identity is determined by the expression of PHABULOSA (PHB), PHAVOLUTA (PHV) and

REVOLUTA (REV) genes, which encode class III homeodomain-leucine zipper (HD-ZIPIII)

proteins (McConnell et al., 2001). The identity of cells in the abaxial domain depends on the

expression of KANADI (KAN; which encodes a Golden2/Arabidopsis response-

regulator/Psr1 (GARP) transcription factor) (Eshed et al., 2001; Kerstetter et al., 2001) and

the YABBY gene family (Eshed et al., 2004; Siegfried et al., 1999). These two classes of genes

produce signals that suppress each other’s expression: the expression of PHB/PHV/REV

genes in cells located at the abaxial side is inhibited by KAN and inversely KAN expression

in abaxially located cells in inhibited by the activity of PHB/PHV/REV genes, providing a

feedback communication between the two sides (Tsukaya, 2013b) (Figure 4).


20

Two small RNAs, the 21-nucleotide microRNA (miR165/166) and the 24- nucleotide

transacting small interfering RNA (ta-siRNA), ta-siR-ARF, are also involved in determining

leaf polarity (Chitwood et al., 2007; Chitwood et al., 2009; Nogueira et al., 2007).

ARGONAUTE1 (AGO1) affects the regulation of miR165/166, which stimulates the cleavage

of HD-ZIPIIIs transcripts in cells located on the adaxial side (Kidner and Martienssen, 2004)

whereas, AGO7/ZIPPY (ZIP) stabilizes ta-siR-ARF, which further targets the degradation of

auxin-related transcription factors, ETTIN (ETT)/ARF3 and ARF4 on the abaxial side

(Adenot et al., 2006; Hunter et al., 2006). FILAMENTOUS FLOWER/YABBY3 (FIL/YAB3), a

member of the YABBY family, upregulates KAN1 and ARF4, which establishes a positive

feedback loop (Bonaccorso et al., 2012) (Figure 4).

Figure 4. Polarity control: The young leaf primordium has three domains which are determined

by domain specific transcription factors such as HD-ZIP III, KANADI and PRS WOX1 for adaxial,

abaxial and middle regions, respectively. These transcription factors inhibit expression of each

other and thereby control their expression in another domain. AGO1 regulates miR165/66 which

inhibits HD-ZIP III whereas AGO7 stabilizes ta-siR-ARF which causes the degradation of ARF3/4,

which itself is controlled by auxin. YABBY determines the abaxial side in cross talk with KANADI

(pointed and T shaped arrows indicate positive and negative regulation, respectively).

Differences in cell growth rates along the principal developmental axes are crucial in

determining final leaf shape. In addition to specification of adaxial and abaxial side of the

leaf, the margin specific cell fate is induced in cells residing at the boundary between these


21

two surfaces (McHale, 1993). In contrast to regulation of leaf blade outgrowth, the

influence of ad/abaxial specific genes on marginal cells is yet to be explored. Recently,

middle leaf domain specific WUSCHEL-RELATED HOMEOBOX (WOX) genes were reported,

which affect leaf blade outgrowth and margin specific development (Figure 4). These

transcription factors (WOX1 and PRESSED FLOWER (PRS) i.e. WOX3) are repressed by

KANADI. The loss of function of WOX1 and PRS causes instable organization of ad-abaxial

polarity (Nakata et al., 2012; Nakata and Okada, 2012).

A relatively simple computational model supported by time-lapse data and clonal analysis

by Kuchen et al. (2012) accounts for local differences in cell growth rates and direction

driving organ level shape changes during early Arabidopsis leaf development. A central

model assumption is a yet uncharacterised early tissue polarity system that deforms during

growth. CUP-SHAPED COTYLEDON (CUC) genes are emerging as prime candidate organizers

of tissue polarity (Hasson et al., 2011). Correspondence of cell polarity and PIN1 auxin

transporter patterns points to their involvement in such an organizer-based model

(Scarpella et al., 2006). Moreover, it was reported that the outgrowth of lobes at the leaf

margin is specified by a local auxin maximum as a result of the polar distribution of the

PIN1 transporter (Hay et al., 2006). The transcription factor CUC2 which is expressed at the

leaf sinuses and is negatively regulated by miR164 (Nikovics et al., 2006), promotes the

generation of these PIN1-dependent auxin maxima, which was supported by computer

simulations (Bilsborough et al., 2011). Recently, a homeodomain protein REDUCED

COMPEXITY (RCO) was reported to enhance serration by repressing growth at the flanks of

initiating leaves (Vlad et al., 2014). Interestingly, CUC2, PIN1, TCP (TEOSINTE BRANCHED/

CYCLOIDEA/PCF) and KNOX have been implicated in compound leaf development

illustrating that this regulatory system has the capacity to take more extreme forms than

observed in Arabidopsis leaves (Barkoulas et al., 2008; Hay and Tsiantis, 2010; Koyama et

al., 2010). A better understanding of the regulatory mechanisms operating at the cell level

during the early phases of leaf outgrowth will likely provide invaluable insights into how

diverse leaf morphologies are established.


22

Cytoplasmic growth

In contrast to the morphology of the leaf primordium, the final size and shape of the leaf

differ widely among species. Differences in leaf outgrowth are often interpreted as the

result of cell division producing a certain number of cells and subsequent cell expansion

determining their mature size. However, this is an overly simplistic view. Firstly, the

relationship between cell division and expansion is complex and the two processes can

mutually compensate each other (Beemster et al., 2003; Tsukaya, 2002). A theoretical

framework to understand this phenomenon was provided by Green (1976), who proposed

that cell growth and partitioning (division sensu-strictu) are two processes that co-occur in

proliferating cells, whereas in expanding cells cell-growth continues in absence of

partitioning. Clearly, this framework allows for continued growth irrespective of inhibited

or stimulated cell division activity, at least until cells get too small or too large to function

normally. However, the view that cell growth in proliferating cells is equivalent to that in

expanding cells is overly simplistic. It is clear that whereas dividing cells grow by

increasing cytoplasmic volume, expanding cells primarily increase their internal volume by

expanding their vacuolar volume.

Cytoplasmic growth is mainly based on macromolecular synthesis and therefore consumes

a lot of energy. A crucial role in ensuring a sufficient supply of elementary building blocks is

played by the TOR pathway. Target of Rapamycin (TOR), a Serine/Threonine kinase of the

phosphatidylinositol-3-kinase-related kinase (PIKK) family is an essential controller of

cytoplasmic growth and metabolism in plant cells. It controls a range of cellular responses

such as ribosome biogenesis, translational initiation, cell proliferation, cell expansion and

autophagy (Sablowski and Dornelas, 2013; Zhang et al., 2013) (Figure 5).


23

Figure 5. Cytoplasmic growth: TOR is the central regulator of diverse growth processes. TOR,

RAPTOR and LST8 are major components of TORC1 in plants. TOR has been reported to regulate

different metabolic processes and positively controls cell expansion, cell cycle, translation,

ribosome biogenesis (through phosphorylation of S6 kinase/EBP1). TOR activity inhibits autophagy

and accumulation of carbon resources such as starch and lipids like triacylglycerides (TAGs). Auxin

positively regulates EBP1 proteins. It has been reported that sucrose positively affects TOR activity

(pointed and T shaped arrows indicate positive and negative regulation and the question mark

indicates an unknown mechanism, respectively).

In yeast and animals, there are two TOR complexes; TORC1 and TORC2 whereas in plants

there is only evidence for TORC1. TOR, RAPTOR (Regulatory associated protein of TOR)

and LST8 (Lethal with Sec13 protein 8) are three key components of TORC1 in Arabidopsis

(Moreau et al., 2012). In contrast to other eukaryotes, much less is known about TOR

signaling in plants. Arabidopsis thaliana is insensitive to the drug rapamycin, which is

extensively used to study TOR function in yeast and animal systems, which has formed a

major obstacle to study TOR in plants (Anderson et al., 2005; Deprost et al., 2007; Menand

et al., 2002; Sormani et al., 2007). However, a recent study shows that plants do respond to

rapamycin at the concentration of 10 µM, which is 100 times more than the concentration

used for yeast and mammals (Xiong and Sheen, 2012). Mutation in TOR is embryo-lethal in

plants (Menand et al., 2002; Ren et al., 2011) and therefore, an alternative approach of


24

inducible knockout for conditional inhibition of TOR have to be used for functional studies

(Caldana et al., 2013; Deprost et al., 2007).

An Arabidopsis T-DNA insertion line which overexpresses AtTOR produces bigger leaves

containing larger cells (Deprost et al., 2007). Accordingly, downregulation of TOR by

inducible artificial microRNA produced smaller leaves with fewer cells along with

upregulation of metabolic pathways like the Krebs cycle. These lines also accumulated

storage products such as starch and lipids like triacylglycerides (TAGs) displaying reduced

growth (Caldana et al., 2013). Mutation of LST8, a member of the TOR complex (TORC1)

decreased plant size by producing fewer and smaller leaves alongside a higher amount of

starch and amino acids and reduced sucrose concentrations. Moreover, downregulation of

genes involved in cell wall formation like expansins and CELLULOSE SYNTHASE-LIKE G3 in

this mutant demonstrates a role for TOR in cell expansion (Moreau et al., 2012). The TORC1

component RAPTOR accumulates in dividing and expanding cells whereas mutation in

AtRaptor1B slows down the leaf initiation. A double mutant of AtRaptor1A and AtRaptor1B

exhibited normal seedling growth, but was unable to maintain post embryonic

development (Anderson et al., 2005).

TORC1 promotes the phosphorylation of S6 kinase (S6K) and eIF4E-binding proteins (E-

BP1), which controls translation and ribosome biogenesis (Krizek, 2009). Again, auxin is

involved through the regulation of EBP1 protein stability in Arabidopsis (Horvath et al.,

2006) (Figure 5). TORC1 also regulates autophagocytosis which ensures synthesis,

degradation and recycling of cellular components (Sablowski and Dornelas, 2013). Recent

studies have revealed that the TOR pathway is an essential controller for cellular

development, which regulates cell expansion and cell cycle simultaneously. The TOR

pathway is directly connected to cell cycle regulation by mediating E2Fa phosphorylation

and activation of DNA synthesis genes (Xiong et al., 2013) and regulates cell wall

modification and degradation processes like senescence and autophagy (Caldana et al.,

2013). Importantly, there is a link between the TOR pathway and the nutrient status. TOR


25

plays a central role in connecting growth related genes to glucose signaling (Xiong et al.,

2013).

Given this central role in connecting growth regulation to nutritional status, the TOR

pathway is a key regulatory hub in organ development. Although molecular insight of its

functioning in animal systems is rapidly increasing, currently we are not aware of

mechanistic models that include this knowledge, a void that we expect to be filled in the

coming years.

Cell division

In addition to cell volume increase by cytoplasmic growth, cell proliferation exponentially

increases the number of cells in the developing leaf. In general cell growth needs to be

sufficiently balanced by cell division for stable tissue growth (Sablowski and Dornelas,

2013). The cell division cycle is a unidirectional process, tightly regulated by a molecular

mechanism that is largely conserved between all eukaryotes (Dewitte and Murray, 2003;

Inze and De Veylder, 2006; Inze et al., 1999) (Figure 6).

The plant cell cycle is controlled by the activity of complexes consisting of a cyclin-

dependent kinase as the catalytic subunit and a cyclin as the regulatory subunit. CDKA (A-

type cyclin dependent kinase) and CYCD (D-type cyclin) are central to the G1/S phase

transition in which the cell activates DNA duplication. CDKA is a key protein to control cell

division in Arabidopsis thaliana, and is present at a constant level throughout the cell cycle

(Gaamouche et al., 2010; Joubes et al., 2004; Porceddu et al., 2001). Overexpression of a

dominant negative CDKA;1 of Arabidopsis thaliana in tobacco plants inhibited cell division

rate, resulting in the formation of fewer, but larger cells resulting in an overall reduction of

leaf area (Hemerly et al., 1995). It has also been demonstrated that the CDKA;1 activity

maintains the SAM cells in an undifferentiated state. Expressing a dominant negative allele

of CDKA;1 in the SHOOTMERISTEMLESS (STM) domain of the shoot apex produces smaller

leaves with a reduced number of epidermal cells (Gaamouche et al., 2010). Interestingly,

irregularly shaped epidermal cells observed in a CDKA;1 dominant negative mutant


26

expressed from the STM promoter point towards CDKA influencing cell wall and

cytoskeleton properties (Borowska-Wykret et al., 2013). A triple cycd3;1-3 loss of function

mutant in the Arabidopsis leaf shows a decreased cell number and reduced cytokinin

response (Dewitte et al., 2007). The plant hormones auxin, cytokinin (CK), brassinosteroid

(BR) and gibberellins (GAs) increase the level of CYCD, thereby activating CDKA (Francis

and Sorrell, 2001; Inze and De Veylder, 2006; Perrot-Rechenmann, 2010; Riou-Khamlichi et

al., 1999). The repression of ABP1 (AUXIN BINDING PROTEIN1) negatively influences

transcript levels of D-type cyclins, which results in impaired cell division in the leaf (Braun

et al., 2008), whereas brassinosteroids upregulate the expression of CYCD3 and promote

cell division through a mechanism that requires de novo protein synthesis (Hu et al., 2000).

The BR biosynthesis mutant det2 (de-etiolated2 = cro1) and dwf1 (dwarf1 = cro2) produce

fewer cells and a smaller leaf, which can be reversed by brassinolide application, indicating

a dual role of BR in division and expansion (Nakaya et al., 2002).

The activity of CDKA/CYCD complexes is itself controlled by CDK activating kinases CDKD

and CDKF coupled with CYCH, which activates the complex through a phosphorylation

cascade. CDKF;1 was also found to activate CDKD;2 and CDKD;3 by T-loop phosphorylation

(Takatsuka et al., 2009; Umeda et al., 2005). The active CDKA/CYCD complex triggers the

dissociation of E2F/DP heterodimeric complex from RBR (retinoblastoma-related protein)

through phosphorylation. Additionally, it initiates the destruction of E2Fc/DP/RBR

transcriptional repressor complex by the Skp-Cullin1-F-Box (SCF) E3-ubiquitin protein

ligase (Inze and De Veylder, 2006). The RBR protein regulates the activity of E2F

transcription factors to control cell proliferation. It is an essential regulator of the cell cycle

to coordinate between cell division, differentiation and homeostasis (Borghi et al., 2010;

Desvoyes et al., 2006). Once the E2F/DP complex is separated from RBR, it initiates G1 to S

transition by activating the transcription of genes required for DNA duplication.

Furthermore, the E2F-like DEL transcription factors compete with E2F/DP for DNA binding

sites (Figure 6).


27

Figure 6. Molecular mechanism for cell cycle regulation: Four phases of cell cycle (G1, S, G2 and

M) are operated by successive activation and deactivation of cyclin dependent kinases (CDKs).

During the cell cycle these kinases bind with cyclins and get activated through phosphorylation by

CDK activating kinases (CDKD and CDKF) whereas KRPs inhibit the complexes. G1 to S transition is

controlled by CDKA-CYCD which phosphorylates the RBR proteins and releases the E2F

transcription factor, which activates S phase related genes. The G2-M transition is dependent on

CDKA/B and CYCA/B/D. The CDK complex is inactivated by phosphorylation through WEE1. The

exit from mitosis requires proteolytic degradation of CYCs which as mediated by Anaphase-

Promoting Complex/Cyclosome (APC/C) bind with CCS52 and CDC20. Phytohormones like auxin,

cytokinin, gibberellins (GA), brassinosteroids, abscisic acid (ABA) and methyl jasmonate (MeJA)

impact cell cycle regulation at different points (pointed and T shaped arrows indicate positive and

negative regulation and the question mark indicates unknown regulation, respectively).

Arabidopsis has three typical E2Fs (E2Fa, E2Fb, E2Fc), two dimerization proteins (DPa and

DPb) and three atypical E2Fs (E2F/DEL2, E2FE/DEL1, E2Ff/DEL3) (Mariconti et al., 2002).

E2Fa and E2Fb stimulate entry into and progression of the S-phase and overexpression of


28

these transcription factors leads to an enlarged phenotype due to enhanced cell

proliferation (De Veylder et al., 2002; Sozzani et al., 2006). Auxin positively regulates E2Fb

protein levels (Magyar et al., 2005). Additionally, the AXR1 transcript level was found to be

high in an E2Fb overexpression line (Sozzani et al., 2006). On the other hand, E2Fc is a

negative regulator of the S-phase where a decreased level leads to leaves and cotyledons

with more but smaller cells (del Pozo et al., 2006). Auxin affects the E2Fc protein level in

Arabidopsis. Mutation in the AXR1 gene leads to impaired modification of the CUL1 protein,

a structural component of the E3-SCF complex, with the Ub-related protein RUB, and shows

increased E2Fc protein levels (del Pozo et al., 2002). Atypical E2Fs/DELs are

transcriptional regulators for endoploidization, which act independently of DPs and RBR. It

is still unclear if they compete with typical E2Fs for binding sites or actively repress gene

transcription (Berckmans and De Veylder, 2009; Vlieghe et al., 2005).

Activated E2Fs in Arabidopsis target the expression of genes involved in DNA repair and

chromatin dynamics such as CDC6, CDT1, MCM3, ORC1 and ORC3, RNR, PCNA. However,

they also influence the expression of genes responsible for G2-M transition like CDKB1,

MYB and APC/C (Boudolf et al., 2004b; de Jager et al., 2001; Lammens et al., 2008; Naouar

et al., 2009; Ramirez-Parra et al., 2003; Vandepoele et al., 2005). Replication origin sites are

silenced in the G1 phase where CDC6 and CDT1 together with ORC allow the loading of

MCM to the replication origins; hence promoting the complex for activation of the S phase.

Later, the DBF-CDC7 complex phosphorylates ORC which then moves and exposes the

replication initiation site for the replisome complex, allowing replication to start (Blow and

Dutta, 2005; Francis, 2007). The plant hormone ABA negatively regulates the expression of

the CDT1a gene (Castellano Mdel et al., 2004). Methyl jasmonate (MeJA) was also reported

to affect initiation of DNA replication by inhibiting the pre-replication complex (Noir et al.,

2013) (Figure 6).

The Kip related proteins (KRPs) are direct inhibitors of CDK activity (ICKs). ICK1 inhibits

the CDKA/CYCD complex in response to negative stimuli like abscisic acid (ABA) (Van

Leene et al., 2011; Wang et al., 1998). Kinematic analysis showed that the overexpression


29

of KRP genes inhibits cell division rate, resulting in serrated leaves of reduced size with

fewer but enlarged cells (De Veylder et al., 2001; Kang et al., 2007). Beemster et al. (2006)

could simulate the effect on cell numbers using a computational model. Mutation of a single

KRP gene doesn’t have any effect on leaf growth, while downregulation of multiple KRP

genes increases final leaf area and cell proliferation (Cheng et al., 2013). The mechanism

behind this enhanced leaf growth is yet to be explained. Auxin and cytokinin activate CDKA

and CYCD, while KRP4 transcription is downregulated (Cho et al., 2010). It has been

reported that auxin signaling is translated into modified KRP expression through PRZ1-

mediated chromatin remodeling (Anzola et al., 2010). The mutual antagonistic effect of

CDKA;1 and KRPs was highlighted in a model of the G1/S transition control in pollen (Zhao

et al., 2012). The plant-specific F-box protein F-BOX LIKE 17 (FBL-17) is central in the

proposed regulatory network, in particular by mediating the degradation of KRP1,3,4,6,7

(Kim et al., 2008). The plant-specific SIM/SMR family also inhibits CDK activity in a number

of specific tissues, for instance the repression of the mitotic cycle in trichomes (Walker et

al., 2000). Gibberellin (GA) is proposed to promote mitotic cycles by lowering expression of

both KRP and SIM. CKIs act in a DELLA-dependent manner (Achard et al., 2009) and

enhance expression of E2Fe/DEL1 (Claeys et al., 2012).

After DNA duplication, cells enter the G2 phase to prepare them for division through

mitosis. CDKA and CDKB as well as CYCA, CYCB and CYCD are involved in this process. The

plant-specific B-type CDKs are subdivided into two groups: CDKB1 (with CDKB1;1 and

CDKB1;2) and CDKB2 (with CDKB2;1 and CDKB2;2). CDKB1 accumulates from late S to M

phase while CDKB2 is specifically expressed from G2 to M phase (Menges et al., 2005).

Overexpression of a dominant negative CDKB1;1 causes early exit from the M phase, which

increases the ploidy level in the leaf (Boudolf et al., 2004b). It has been reported that

CDKB1;1 forms a functional complex with CYCA2;3 to trigger mitosis in Arabidopsis

(Boudolf et al., 2009). Inhibition of CDKB2;1 and CDKB2;2 via the expression of an amiRNA

leads to a dwarf phenotype with an abnormal shoot apical meristem (Andersen et al.,

2008). Jasmonates (JAs) cause G2 arrest in tobacco (Nicotiana tabacum) Bright Yellow-2

cell cultures by reducing CYCB1;1 and CDKB (Swiatek et al., 2004). Similarly, inhibition of


30

mitotic phase genes by methyl JA causes G2 arrest in Arabidopsis cell cultures (Pauwels et

al., 2008).

An additional level of regulation of CDKA/CYCD complex activity involves inactivation

through phosphorylation by the WEE1 protein kinase. Overexpression of WEE1 inhibits

plant growth by arresting cell division (De Schutter et al., 2007). However, in plants WEE1

is probably not a core cell cycle regulator, but rather a DNA damage checkpoint kinase

(Dissmeyer et al., 2009).

Dissmeyer et al. (2009) have proposed and implemented alternative G2 phase modules in

the form of mathematical models starting from an existing generic model. The primitive

unicellular algae, Ostreococcus tauri, contain a bona fide CDC25, which antagonises WEE1

phosphorilation (Inze and De Veylder, 2006). In Arabidopsis a small CDC25 like

phosphatase can counteract the role of WEE1 kinase in vitro (Landrieu et al., 2004), but this

CDC25-like protein has arsenate reductase activity and is most likely not involved in cell

cycle regulation (Dissmeyer et al., 2010). The Arabidopsis genome therefore lacks a

functional copy of the CDC25 gene, which means that generic cell cycle models (Novak and

Tyson, 1993) need to be adapted to reflect the situation in plants.

Similar to the G1 phase, the CDK/CYC complex can be activated in G2 by a CDK-activating

kinase pathway, involving CDKF and CDKD coupled with CYCH. The activated CDK/CYC

complex promotes MYB repeat (MYB3R) transcription factors to bind with M phase Specific

Activators (MAS) elements at the promoter region of the target genes. Afterwards, MYB3R

phosphorylation activates the expression of M phase specific genes such as KNOLLE, CDC20,

CYCA and CYCB and NACK1 (Berckmans and De Veylder, 2009) (Figure 6).

There are two E3 ubiquitin ligase complexes involved in cell cycle control, SKPL-CULLIN-F-

BOX-PROTEIN (SCF) and ANAPHASE-PROMOTING COMPLEX/CYCLOSOME (APC/C), which

mark targets for degradation by the 26S proteasome. In analogy to the SCF complex playing

an important role in G1 to S phase by degrading cell cycle inhibitors (KRPs) (Fulop et al.,


31

2005; Hershko, 2005; Ren et al., 2008) the APC/C is essential for the G2 to M transition. The

exit from the M phase is regulated by the degradation of cyclins through ubiquitination by

the APC/C in association with the activators CCS52 (CELL CYCLE SWITCH 52) and CDC20

(Fulop et al., 2005; Marrocco et al., 2010; Sullivan and Morgan, 2007).

Overexpression of APC10 promotes the cell division rate by degradation of CYCB1;1 which

causes enlarged leaves (Eloy et al., 2011). Mutation of HOBBIT, a CDC27 subunit of the APC,

in the SAM leads to accumulation of high levels of the auxin response inhibitor

AXR3/IAA17, indicating that its activity would be involved in targeting AUX/IAA proteins

for degradation (Blilou et al., 2002). CCS52 is an important regulator for controlling exit of

mitosis. There are two classes of CCS52 in Arabidopsis thaliana, CCS52A (CCS52A1 and

CCS52A2) and CCS52B (Fulop et al., 2005). A-type CCS52 activators are typically expressed

from late M to late S-G2 and regulate the onset of endoreduplication in leaves (Fulop et al.,

2005; Lammens et al., 2008). CCS52B, like the APC/C activator CDC20, peaks from early G2

to M phase exit (Fulop et al., 2005; Kevei et al., 2011). Induced expression of CCS52B affects

branching in trichomes where CCS52BOE line forms four to five branches, while the wild

type has only three branches (Engler et al., 2012). However, more study is needed in

particular to understand role of CCS52B in leaf development. It has been suggested that

complementary phase-dependent expression of A and B-type CCS52 activators enable a

fine-tuned APC/C regulation during the cell cycle (Tarayre et al., 2004). Expression of the

negative regulator of CCS52A1 activity, ULTRAVIOLET-B-INSENSITIVE 4 (UVI4) peaks at

the G1-to-S transition (Heyman et al., 2011) and determines cell number and size of leaves,

likely through stabilisation of CYCA2;3 required for mitotic cell divisions (Boudolf et al.,

2009; Heyman et al., 2011; Imai et al., 2006). Its homolog UVI-Like/OMISSION OF SECOND

DIVISION 1 (OSD1) influences meiosis and does not directly impact leaf size. However, it is

expressed during the mitotic cell cycle peaking at the G2-to-M transition, possibly

preventing endomitosis (=incomplete mitosis) (Heyman and De Veylder, 2012). Besides

the mechanism of the inhibitory action of the UVI4 and OSD1 regulators, not much is

known about the specific targets of the APC/C (Heyman and De Veylder, 2012). Apart from

a recent study pointing to cytokinin upregulating CCS52A1 in the Arabidopsis root


32

(Takahashi et al., 2013), not much is known about the role of hormone signaling on APC/C

regulation. However, in stress-conditions GA likely modulates APC/C activity through

DELLA dependent downregulation of the UVI4 and DEL1 negative regulators (Claeys et al.,

2012).

Despite of the high level of conservation of the core cell cycle machinery (Harashima et al.,

2013), many plant-specific features exist. Plants are characterized for instance by a

remarkably broad cyclin family with many species-specific isoforms (at least 49 in

Arabidopsis, cf. Sablowski and Dornelas, 2013). The involvement of different orthologous of

many core cell cycle genes goes together with a functional diversity which manifests itself

in gene expression differences between species, developmental and environmental

conditions. Indeed, Beemster et al. (2005) showed by means of a microarray study that the

expression profile of roughly half of all cell cycle genes differed between roots and leaf

primordia. de Almeida Engler et al. (2009) found generally high expression of core cell

cycle genes in leaf primordia, in the lamina of young leaves and in vascular tissue of

expanding leaves. A number of cases of developmental stage-specific expression are

described in the relevant sections throughout this review. However, for many others the

functional significance has yet to be clarified.

Endoreduplication

Generally cells go through a regular cell cycle with the S phase (DNA duplication) followed

by the M phase (mitosis). Endoreduplication, endoreplication, endoploidization or, in short,

the endocycle is the process whereby DNA replicates repeatedly without alternating

divisions through mitosis, causing a high ploidy level in the cell.

To establish endoreduplication, the CDK activity essentially has to be kept low enough and

several ways have been proposed to achieve this (Berckmans and De Veylder, 2009; De

Veylder et al., 2011). For instance, CYCD3;1 which is specifically expressed in proliferating

tissues, reduces endoploidization (Dewitte et al., 2003). CDKB1 activity is also essential for

the G2 to M transition (Beemster et al., 2005). Overexpression of a dominant negative


33

CDKB1;1 interferes with cell cycle progression causing G2 arrest (Boudolf et al., 2004a).

CDKB1;1 forms an active complex with CYCA2;3 to suppress endoreplication in the leaf

(Boudolf et al., 2009). Loss of CYCA2;3 function increases ploidy in mature leaves (Imai et

al., 2006). The ILP1 (INCREASE LEVELS OF PLOIDY) gene, which encodes a protein

homologous to the C terminal region of mammalian GC binding factor, is proposed to be

involved in transcriptional repression of A2-type cyclins (Yoshizumi et al., 2006).

Expression of B-type cyclins, on the other hand, was repressed by decreased

phosphorylation of three-repeat MYB proteins (MYB3Rs) (De Veylder et al., 2011; Ito et al.,

2001). The E3 ubiquitin ligase complex, APC/C coupled with CCS52 influences endocycle

onset by controlling proteolytic degradation of G2-M specific cyclins like CYCB1;1 and

CYCB1;2 (Kasili et al., 2010) as well as CYCA2;3 (Boudolf et al., 2009) (Figure 7). CCS52A1

and CCS52A2 knockout plants have reduced DNA ploidy levels in leaves (Kasili et al., 2010;

Lammens et al., 2008). The previously mentioned plant-specific CCS52A1 inhibitor UVI4 is

likely involved in securing the G2-to-M transition and therefore preventing endocycle onset

(Heyman and De Veylder, 2012). Cells with increased ploidy levels in osd1 cotyledons and

the developmentally severely compromised uvi4 osd1 suggest some functional redundancy

between UVI4 and its homolog OSD1 (Cromer et al., 2012; Iwata et al., 2011). Mutation in

SAMBA, a plant specific subunit of the APC complex which probably activates A2-type

cyclin degradation, induces enhanced endoreplication in Arabidopsis leaves (Eloy et al.,

2012). Other factors such as the DP/E2F like transcription factor E2Fe/DEL1 are involved

in controlling APC/C activity. Downregulation of DEL1 triggers the expression of the

CCS52A2 gene, forcing cells to enter endoreduplication (Lammens et al., 2008).


34

Figure 7. Regulation of endoreduplication: CDKA/B and CYC activity is inhibited by cell cycle

inhibitors KRPs/SIM/SMRs that induce endoploidization. Cyclin A is inhibited by the ILP1 proteins

whereas downregulation of MYB3R causes decreased CYCB and ultimately induces

endoploidization. Proteolytic degradation of G2-M cyclins by the APC/C complex causes endocycle

onset. Other factors like, UVI4 and DEL1 suppress the endocycle by inhibiting the APC/C complex.

Plant hormones like auxin and jasmonic acid suppress the endocycle whereas gibberellins (GA),

abscisic acid (ABA) and ethylene stimulate it by regulating expression and activity of different

components (pointed and T shaped arrows indicate positive and negative regulation and the

question mark shows the unknown regulation, respectively).

The plant specific cell cycle inhibitor SIAMESE (SIM) gene that encodes for a member of the

SIAMESE RELATED (SMR) family also plays a role in endoreduplication (Churchman et al.,

2006; Walker et al., 2000). A mutation in SIM causes repressed endoreplication leading

instead to mitotic divisions in leaf trichomes. SIM interacts with CDKA;1 and D type CYCs

(Churchman et al., 2006), and it was suggested that inhibition of CDKA:CYCD3 complexes

might be the mechanism responsible for its role in endoreduplication onset (De Veylder et

al., 2011). Indeed, CYCD3;1 overexpression inhibits endoreduplication in Arabidopsis

leaves (Dewitte et al., 2003), whereas a cycd3 triple mutant displays premature onset of

endoreduplication in young leaves (Dewitte et al., 2007). Other SIM family members, such

as SMR1/LGO, might also promote polyploidization (Roeder et al., 2010). In fact, SMR1 and


35

SMR2 interact with CDKB1;1 and its interactor CYCB2;4 associates with SMR11 (Van Leene

et al., 2010).

Contrary to the emerging insights into endoreduplication onset, it is only poorly

understood how the endocycle is sustained. It has been envisaged that the cell cycle

inhibitor KRP controls CDKA activity by inhibiting the CDKA/CYCD complex to maintain the

CDK oscillations needed for DNA replication in the endocycle. KRPs were reported to

regulate mitosis and endoreplication in a dose dependent manner where low

concentrations promote the endocycle while high levels cause cell cycle arrest (Verkest et

al., 2005b). On the one hand, overexpression of KRP2/KRP5 in mitotically active cells

inhibits cell division and enhances endoreplication (Jegu et al., 2013; Verkest et al., 2005a)

while on the other hand its overexpression in postmitotic cells inhibits endocycle in

Arabidopsis leaves (Schnittger et al., 2003). This implicates that KRPs are an important

candidate for the regulation of rate and duration of endoreduplication in expanding leaf

cells.

Arabidopsis leaves, cells enter into the endoreduplication process as a consequence of

decreasing auxin concentrations. It has been observed that the mutants in auxin signaling,

biosynthesis and transport show a rapid transition from mitotis to endocycle causing

increased ploidy level in cotyledons (Ishida et al., 2010) but the detail of this mechanism is

still not known. Ethylene and gibberellins are hypothesized to positively affect

endoreduplication (Gendreau et al., 1999; Perazza et al., 1999; Swain et al., 2002). JAs were

shown to inhibit cell proliferation as well as endoploidization in a COI1 (encoding an F-box

protein which is a part of the SCF complex) dependent manner in Arabidopsis leaves (Noir

et al., 2013). It also negatively regulates the expression of key determinants of DNA

replication like CDC6A (Noir et al., 2013).

Despite of our increasing knowledge on the molecular mechanism of endoreduplication, its

actual function remains ambiguous with proposed roles in promoting cell expansion, stress

resistance or DNA damage protection (De Veylder et al., 2011). In any case, modulating


36

CDK-CYC activity levels in various ways remains a central principle. This pertains to the

ubiquitin dependent degradation of KRPs or the mechanism by which plant specific cell

cycle inhibitors (SIM/SMR) as well as developmental and environmental signals influence

the endocycle. Roodbarkelari et al. (2010) have modelled the endocycle onset in

Arabidopsis trichomes with KRP and the CULLIN4 ubiquitin ligase controlling G1/S and SIM

and APC/C controlling G2/M transitions. Computational approaches to predict tissue

distributions of cell ploidy combined with in vivo ploidy maps (Boudolf et al., 2004b) would

provide powerful insights to better understand its regulation and relationship to cell

expansion.

Regulation of transition between cell division and expansion

Leaf development involves two major phases. The first phase is dominated by proliferative

activity and the second phase by cell expansion (Figure 8). There is a correlation between

cell division activity and organ growth, so the timing of cell division has a large influence on

the final leaf size (Gonzalez et al., 2012; Korner et al., 1989; Meyerowitz, 1997). As cell

division ceases the cell continues expanding. This transition from division to expansion is

manifested as a cell cycle arrest front which remains fixed at some position for a particular

time period and then moves rapidly towards the base of the leaf blade (Andriankaja et al.,

2012). Several regulators appear to control the transition from proliferation to expansion.

Auxin plays an important role in the transition phase. It induces the expression of ARGOS

(AUXIN-REGULATED GENE INVOLVED IN ORGAN SIZE) gene, encoding for an ER localized

protein of unknown function (Hu et al., 2003). Overexpression and downregulation of

ARGOS increases and decreases leaf size, respectively. It regulates the action of a DNA-

binding protein ANT (AINTEGUMENTA) and of CYCD3;1 (Hu et al., 2003) (Figure 8). Loss of

function of ANT blocks the increase in leaf growth in ARGOS overexpressing plants. The

Arabidopsis ORS1 (ORGAN SIZE RELATED1) shares a conserved domain with ARGOS and

ARGOS LIKE (ARL), and positively regulates cell division and expansion in the leaf (Feng et

al., 2011; Hu et al., 2003). Like the ANT family proteins, the GRF (GROWTH REGULATING

FACTOR) and TCP (TEOSINTE BRANCHED/ CYCLOIDEA/PCF) transcription factors are


37

essential regulators of leaf growth (Figure 8). The Arabidopsis GRF family comprises nine

members. Overexpression of AtGRF1 and AtGRF2 results in larger leaves whereas the

grf1/2/3 triple mutant reduces leaf size, both as a result of alterations in cell size (Kim et

al., 2003). Overexpression of GRF5 increased cell number with prolonged growth, whereas

the grf5-1 mutant shows narrow leaves with reduced cell numbers. GIF1 (GRF-

INTERACTING FACTOR1), also known as ANGUSTIFOLIA3 (AN3) interacts with GRF5

(Horiguchi et al., 2005). GIF1 overexpression increases leaf size with leaves having more

cells, whereas its absence reduces cell proliferation (Lee et al., 2009).

miR396 negatively regulates six members of Arabidopsis Growth Regulating Factor (GRF)

together with GIF1 (Liu et al., 2009) (Figure 8). Interestingly, overexpression of miR396 in

a mutant deficient for GRF1 reduces shoot apical meristem size (Rodriguez et al., 2010).

The miR396 targeted GRFs are also essential for leaf polarity (Wang et al., 2011). The TCP

family of transcription factors regulates the expression of miR396 and miR319 (Palatnik et

al., 2003; Rodriguez et al., 2010). A point mutation in the miR319 target site of TCP4

induces miR396 which in turn decreases GRF expression and results in smaller leaves

(Figure 8). Similarly, overexpression of TPC4 decreases leaf size (Rodriguez et al., 2010).

Transcription factors from the TCP family such as CINCINNATA (CIN) of Antirrhinum,

LANCEOLATE (LA) of tomato and CINCINNATA (CIN)-TCPs of Arabidopsis thaliana control

cell cycle arrest (Nath et al., 2003; Ori et al., 2007; Palatnik et al., 2003). In Arabidopsis,

upregulation of miR319 in the jaw-D mutant reduces the expression of TCP2, TCP3, TCP4,

TCP10 and TCP24 producing large and wrinkled leaves (Palatnik et al., 2003).

Downregulation of single, double and triple TPC genes resulted in proportional increase in

leaf size and crinkliness (Schommer et al., 2008).


38

Figure 8. Regulation of the transition between proliferation and cell expansion: The

transition between division and expansion is shown by a dashed line which separates these two

growth processes according to their regulators. ARGOS promotes cell division via DNA binding

protein ANT and CYCD3 which is regulated by auxin. TCP and GIF/GRF transcription factors

promote division and are negatively regulated by miRNAs. Other factors like KLU and SWP also

promote proliferation. Some factors like ORS1 have a positive influence on division as well as

expansion. Cell expansion is directly controlled by the TOR pathway and ARL. Whereas, other

regulators like BB, MED25 and DA1 control the timing of proliferation. Abscisic acid promotes

transition at least in part by regulating DA1 whereas brassinosteroids with unknown molecular

mechanism (pointed and T shaped arrows indicate positive and negative regulation of the

particular process and the question marks show unknown mechanism, respectively).

In addition to these transcription factors, other genes are also essential to promote the

transition from division to expansion. The putative ubiquitin binding protein DA1 and the

E3 ubiquitin ligase BIG BROTHER (BB) also known as ENHANCER OF DA1-1 (EOD1)

controls organ size by restricting the duration of cell proliferation (Figure 8). In the da1-1

mutant, the production of a dominant negative protein negatively affects both DA1 and the


39

DA1-related (DAR) protein and the overexpression of DA1 results in large leaves with

increased cell numbers. Abscisic acid (ABA) induces the expression of DA1, whereas the

da1-1 mutant was less sensitive to ABA, implicating a role for ABA in determining the final

leaf size through the control of mitotic exit (Li et al., 2008). Mediator complex subunit 25

(MED25 also known as PFT1), functions together with DA1 in controlling leaf growth by

restricting cell proliferation (Figure 8). Overexpression of MED25 causes smaller leaves

with reduced cell numbers and cell sizes, whereas a loss of function mutant enhances organ

size with increased duration of cell proliferation and expansion (Xu and Li, 2011). Loss of

function mutation of the RING- finger protein encoding BIG BROTHER (BB) leads to

enlarged leaves and small changes in expression levels substantially alter organ size

suggesting it controls cell division and leaf size in a dose dependent manner (Disch et al.,

2006). The KLUH (KLU)/CYP78A5 gene, encoding for a cytochrome P450, required for

generating a mobile growth signal distinct from the classical phytohormones, is also an

essential regulator for leaf size control. Overexpression of KLU induces enlarged leaves

having more cells whereas in the klu mutant premature arrest of cell proliferation causes

smaller leaves (Anastasiou et al., 2007; Stransfeld et al., 2010). The SWP gene encodes a

protein with similarities to subunits of the Mediator transcriptional regulatory complex of

RNA polymerase II. It also plays a role in defining the period of cell proliferation. In the swp

mutant leaf size was reduced due to less cells, which was partially compensated by an

increase in final cell size (Autran et al., 2002) (Figure 8).

Like auxin, sugar signaling controls leaf growth possibly via the ARGOS pathway (Hu et al.,

2003; Wang and Ruan, 2013). BR also regulates leaf growth by controlling cell division and

expansion. The BR deficient mutant constitutive photomorphogenesis and dwarfism (cpd)

produces smaller leaves with fewer cells of reduced size (Zhiponova et al., 2013), however

the molecular mechanism controlling this process is yet to be clarified. The progressive

general cell proliferation arrest front of epidermal and mesophyll cells is followed by a

second cell cycle arrest front for dispersed meristematic cells (DMCs) that is controlled by

the putative transcription factors PPD1 (PEAPOD1) and PPD2 (White, 2006).


40

The transition to the expansion phase is essentially dependent on the regulators of cell

cycle arrest. Many factors have been implicated in the regulation of the cell division arrest

front. An important question is how the spatiotemporal dynamics of the arrest front could

be explained. Coordination through one or more gradients of (non-cell autonomous)

growth regulators appears to be the most likely mechanism. However, Efroni et al. (2008)

hypothesized a mechanism for organ differentiation through an internal self-advancing

sequential maturation program, where rate and time of advancement is regulated by a cell-

autonomous developmental clock (timed) program. CIN-TCPs would play a governing role

in this mechanism for the leaf. Sufficient details for building simulation models of the

transition phase still appear to be lacking in Arabidopsis. However, in the

monocotyledonous maize leaf a clearer picture is arising, where a peak in the activity of GA

is instrumental in regulating the spatial location of the transition (Nelissen et al., 2012).

Possibly models that will be developed for this monocotyledonous system can be adapted

to better understand the same process in the Arabidopsis leaf.

Turgor driven cell growth

Cell expansion is an essential step in determining final leaf size that is governed by

different mechanisms in each stage of cellular development. Expansion in meristematic

cells is determined by both increases in cytoplasmic and nuclear volume whereas in

differentiated tissues it is mainly determined by turgor-driven vacuolar enlargement that

allows the accumulation of water and solutes (Sablowski and Dornelas, 2013; Wolf et al.,

2012). Turgor driven cell expansion is the result of multiple steps like cell wall relaxation

to accommodate water uptake, wall extension by turgor pressure, dehydration/cell wall

stiffening and the accumulation of cell wall components (Cosgrove, 2005; Wolf et al., 2012)

(Figure 9).


41

Figure 9. Regulation of the cell expansion process with unknown molecular mechanism: Cell

expansion is the result of vacuolar enlargement as well as of turgor driven cell wall yielding. The

vacuole expands while taking up water and solutes whereas turgor driven cell wall yielding is the

result of multiple steps, including hydration and cell wall loosening, cell wall extension by turgor

pressure, dehydration/cell wall stiffening by release of apoplastic reactive oxygen species, cross-

linking and dehydration and lastly synthesis and accumulation of cell wall components. Cell wall

loosening is controlled by expansin (EXP) proteins and the xyloglucan endohydrolase (XEH) and

xyloglucan endotransglucosylase (XET) activites of xyloglucan endotransglucosylase/hydrolases

(XTHs). Auxin and brassinosteroid (BR) enhance activity of P-type plasma membrane proton

ATPase (AHA) (pointed and T shaped arrows indicate positive and negative regulation and the

question mark shows the unknown regulation, respectively).

In the plant cell wall cellulose microfibrils are associated through hemicellulose tethers to

form the cellulose-hemicellulose network, which is embedded in a pectin matrix. Primarily,

auxin or brassinolide induce activity of P-type plasma membrane proton ATPases (AHA)

that causes acidification of the apoplast and in turn activates hydration and cell wall

loosening by expansin (EXP) proteins, xyloglucanendotransglucosylase/hydrolases (XTHs),

xyloglucan endohydrolase (XEH) and xyloglucan endotransglucosylase (XET) (Caesar et al.,

2011; Rose et al., 2002; Wolf et al., 2012; Yokoyama and Nishitani, 2001). Dyson et al.

http://en.wikipedia.org/wiki/Microfibril


42

(2012) developed a model of hemicellulose dynamics in an expanding cell wall, showing

how the action of XTH and expansin family enzymes determine yield and extensibility of

the wall as encapsulated by the classical Lockhart equation (Lockhart, 1965). The

mechanism controlling cell wall swelling/hydration is yet to be clarified. Antisense and

sense constructs of the Arabidopsis EXP10 gene produce smaller leaves with altered

morphology and larger leaves having bigger cells, respectively (Cho and Cosgrove, 2000).

Wall hydration allows cell wall extension through structural alterations. Cell wall

relaxation stretches the plasma membrane which promotes opening of Ca2+ channels. The

resulting increase in cytoplasmic calcium affects growth by inhibiting P-ATPases that cause

alkalization of the apoplast and inhibition of expansin activity. It also activates NADPH-

oxidase which promotes secretion of superoxide into the cell wall, which is further

converted into hydrogen peroxide. These reactive oxygen species promote cross linking of

cell wall components, which causes cell wall dehydration and strengthening. At the end,

wall thickness is reinstated by biosynthesis of membrane lipids, cell wall components and

proteins, and appropriate channelization of these materials to their final cellular

destination (Wolf et al., 2012).

Auxin does not always promote cell expansion as its concentration has also been observed

to fall during leaf expansion (Braun et al., 2008), suggesting a more complicated dose-

response relation. The yucca and sur mutant of Arabidopsis have elevated auxin levels and

smaller leaves (Boerjan et al., 1995; Zhao et al., 2001). Mutation in EXIGUA (EXI) genes,

which encode for different subunits of the cellulose synthase complex required for

secondary cell wall biosynthesis, produces small leaves having defects in cell expansion

(Rubio-Dı´az et al., 2012). Growth anisotropy, the existence of directions with distinct

growth properties is determined by the orientation of the stiff cellulose microfibrils, which

in turn is controlled by the orientation of cortical microtubule (CMT) arrays guiding

cellulose synthase (Paredez et al., 2006). Uyttewaal et al. (2012) showed by experimental

and modeling approaches that the microtubule severing protein katanin mediates the

response of cells to mechanical stress in the Arabidopsis SAM. The alignment between PIN1

polarity and microtubule orientation in the SAM indicates a tight biophysical coupling


43

between morphogenesis and auxin transport as further corroborated by mathematical

modeling (Heisler et al., 2010).

Cell ploidy level is strongly correlated with mature cell size in many plant species

(Sugimoto-Shirasu and Roberts, 2003). Alteration in genes specific for G2-M transition

affects the onset of endocycle with earlier onset typically leading to enhanced ploidy. A

notable exception is downregulation of Arabidopsis REGULATORY PARTICLE AAA-ATPASE

(RPT2a), which encodes a subunit of the 26S proteasome that causes enlarged plant organs

having less but bigger cells. DNA content was higher in some organs but not in all which

suggests that the increase in organ size was not the result of endoploidization (Kurepa et

al., 2009). Another exception is KRP2 overexpression in Arabidopsis, which does not alter

timing of cell cycle exit, but induces fewer and enlarged cells in combination with lower

endoploidy levels (De Veylder et al., 2001). A recent study of different Arabidopsis mutant

and transgenic lines with altered cell sizes showed strong differences in the effect of a same

doubling of nuclear ploidy levels, by tetraploidization, on mature cell size (Tsukaya,

2013a). This indicates that genetic factors strongly affect and complicate the general

relationship between endoploidy and size, by thus far unknown mechanisms.

Cell differentiation

In the process of leaf development, cells have the ability to differentiate into distinct cell

types such as guard cells, vascular tissue cells, and trichomes, enabling them to perform

diverse specialized functions. All these cell types develop from undifferentiated

proliferating cells in the young primordium under the control of regulatory pathways that

are increasingly being elucidated.

a) Guard cell formation

In Arabidopsis, guard cell development is initiated by an asymmetric cell division of a

protodermal cell. The two daughter cells obtain different identities; the larger one

maintains protodermal cell identity, whereas the smaller one becomes a meristemoid


44

mother cell (MMC). The MMC divides asymmetrically to produce a larger stomatal lineage

ground cell (SLGC) and smaller meristemoid. Subsequently these SLGCs give rise to new

meristemoids by asymmetric division. The meristemoid can differentiate into a guard

mother cell (GMC), which divides symmetrically to form a pair of guard cell precursors,

which further differentiate into guard cells (Vaten and Bergmann, 2012). Two closely

related two-MYB-repeat transcription factors, FOUR LIPS (FLP) and MYB88 restrict this

final symmetric division to one (Lai et al., 2005). Interestingly, termination of the final

division happens through transcriptional repression of the core cell cycle genes CYCA2;3

and CDKB1;1 (Vanneste et al., 2011; Xie et al., 2010). Transition of individual cell into the

stomatal lineage is regulated by three helix-loop-helix (bHLH) transcription factors:

SPEECHLESS (SPCH), MUTE and FAMA (MacAlister et al., 2007; Ohashi-Ito and Bergmann,

2006; Pillitteri et al., 2007) (Figure 10).

The initial asymmetric division when protodermal cells enter the stomatal lineage is

controlled by SPCH. Overexpression of SPCH initiates extra asymmetric cell divisions while

no stomatal lineage was found in the spch mutant. MUTE is essential to transform a

meristemoid into a guard mother cell. Loss of function mutation of MUTE leads to the

production of stomatal precursors but no stomata, whereas its overexpression converts the

whole epidermis into stomata (MacAlister et al., 2007; Pillitteri et al., 2007). Lastly, FAMA

is required for the conversion of guard mother cells into guard cells. The GMC divides

rapidly in fama mutants, but the daughter cells do not differentiate, producing a row of

parallel cells (Ohashi-Ito and Bergmann, 2006). A second group of bHLH proteins are

INDUCER OF CBF EXPRESSION1/SCREAM (ICE1/SCRM) and SCRM2, which associate with

SPCH, MUTE and FAMA to activate sequential stomatal fate transition (Figure 10). Gain of

function scrm-D causes conversion of epidermal into stomatal cell identity and loss of SCRM

and SCRM2 resembles spch, mute and fama mutant (Kanaoka et al., 2008).


45

Figure 10. The control of stomatal development: Stomatal fate is determined by three

transcription factors, SPEECHLESS (SPCH), MUTE and FAMA. Specification of stomatal lineage

where conversion of a protodermal cell into a meristemoid mother cell (MMC) is regulated by

SPCH, MUTE controls the transition from meristemoid to guard mother cell (GMC) and FAMA is

essential to make functional guard cells from GMC. The MAPK signaling cascade including the MAPK

kinase YODA, MPKK4/5/7/9 and MAPKs (MPK3/6), EPIDERMAL PATTERNING FACTORs(EPF1 and

EPF2) perceived by TMM and the ER family inhibit stomatal identity in non-stomatal cells.

Brassinosteroids negatively regulate SPCH as well MAPKs simultaneously (pointed and T shaped

arrows indicate positive and negative regulation, respectively).

Intracellular signaling pathway analysis revealed that stomatal patterning is regulated by

interaction among three leucine-rich repeat receptor kinases (LRR-RLKs): ERECTA (ER),

ERECTA-LIKE1 (ERL1) and ERL2 (Shpak et al., 2005), peptides of the EPIDERMAL

PATTERNING FACOR-LIKE (EPFL) family (Hara et al., 2009) and the LRR-receptor-like

protein, TOO MANY MOUTHS (TMM) (Nadeau and Sack, 2002) (Figure 10a). EPF1 and

EPF2 expressed in GMC and MMC respectively (Peterson et al., 2010) control the number of

guard and non-guard cells. Loss of function mutants of either EPF1 or EPF2 produces more

stomata, whereas overexpression inhibits stomatal development (Hara et al., 2009). In


46

contrast, another member of the EPF family EPFL9/STOMAGEN is a positive intercellular

signaling factor involved in stomatal development (Sugano et al., 2010).

Members of the ER family also work as negative regulators with their downregulation

causing over-proliferation of stomata (Shpak et al., 2005). TMM affects stomatal spacing

and density and its loss of function mutant tmm forms clusters of stomata in leaves

(Nadeau and Sack, 2002). These intracellular signals in turn activate a mitogen-activated

protein kinase (MAPK) signaling cascade including the MAPK kinase YODA, MPKK4/5/7/9

and MAPKs (MPK3/6) to inhibit stomatal development in neighboring cells (Bergmann et

al., 2004; Lampard et al., 2009) (Figure 10). MAPK mediated phosphorylation negatively

regulates SPCH activity (Lampard et al., 2008), whereas the target in a later stage of

stomatal development is unknown. A recent study adds to the complexity of this network

since the brassinosteroid (BR) pathway phosphorylates YODA (Kim et al., 2012) and SPCH

(Gudesblat et al., 2012) (Figure 10). Thus, it is essential to understand the regulation of

MAPK pathway in later stages of the stomatal development and shed light on the complex

interaction between YODA and SPCH with BR. It is an interesting question how the

stomatal lineage is established and which regulators cause the initiation of SPCH

expression. In relation to that, a polarity-switching model for individual lineage behavior

was able to predict the location of the polarity determinant BASL (BREAKING OF

ASYMMETRY IN THE STOMATAL LINEAGE) over multiple divisions leading to stereotypical

spatial patterns of stomata lineages (Robinson et al., 2011). Sugar signaling is also involved

as an early signal, as sucrose, glucose and fructose all induce ectopic stomatal formation by

inducing stomatal lineage markers in non-stomatal lineage cells (Akita et al., 2013).

b) Vascular differentiation

At the time of leaf initiation, high local concentrations of auxin induce provascular identity

leading to the differentiation of midvein and lateral veins preceded by enhanced expression

of early markers for vascularization e.g. ATHB8 (Arabidopsis homeobox transcription

factor) (Bayer et al., 2009; Scarpella et al., 2004; Scarpella et al., 2006). A Dual Polarization


47

model proposed by Bayer et al. (2009) explains PIN1 protein localization at the time of leaf

initiation and midvein formation. Generally, vasculature development begins with the

formation of pre-procambium cells, which later differentiate into procambium cells under

control of an increased auxin flow (Kang and Soh, 2001; Scarpella et al., 2006). Xylem and

phloem cells are produced by the vascular meristem with xylem produced on the dorsal

(adaxial) side and phloem produced on the ventral (abaxial) side of the procambium. The

radial patterning of the vascular bundle is the result of an antagonistic relation between

Class III HD-ZIP (Class III Homeodomain Leucine Zipper) in the xylem domain and KANADI

(KAN) transcription factors in phloem precursor cells (Jung and Park, 2007) (Figure 11).

Of all five members of the HD-ZIP III family, PHV, PHB and REV are expressed in

vasculature, apical and floral meristems, and the adaxial domain of lateral organs (Emery et

al., 2003; McConnell et al., 2001) whereas ATHB8 and ATHB15 are exclusively expressed in

vascular tissue (Baima et al., 2001; Ohashi-Ito and Fukuda, 2003) and these factors are

negatively regulated by microRNA 165/166 (Emery et al., 2003). HD ZIP-III transcription

factors are regulated by two members of GARS family of transcription factors, SHR (SHORT

ROOT) and SCR (SCARECROW) which activate the genes encoding miR165/166

(Miyashima et al., 2013). Recently, it has been reported that the synchronous expression of

SHR and ATHB8 is important for the transition to the pre-procambial cell state that

precedes vein formation in leaf (Gardiner et al., 2011). The phb-6 phv-5 rev-9 loss of

function mutant produces abaxialized radial cotyledons in which phloem surrounds xylem

(Emery et al., 2003). The quintuple mutant rev-6 phb-13 phv-11 cna-2 athb8-11/athb8-12

has a severely compromised vascular phenotype similar to the phb phv rev triple mutant

(Prigge et al., 2005). Loss of ATHB8 and ATHB15 has no evident phenotypic effects, though

vascular development is slightly perturbed in athb15.


48

Figure 11. Regulation of vascular development: Central regulators for vascular development

involves the REV/PHB/PHV/CAN/ATHB8 genes which are members of HD-ZIP III family and KAN

(KANADI). These regulators act antagonistically to maintain xylem and phloem, respectively.

Transcription factors, SHR (SHORT ROOT) and SCR (SCARECROW) activate miR165/166, which

further inhibits HD-ZIP III. Auxin plays an essential role in regulating vascular formation through

PIN1 transporter by early markers like ATHB8. The BRASSINOSTEROID INSENSITIVE 1 (BRI1)

family, BRI1-LIKE (BRLs) inhibits phloem formation while inducing xylem formation. Expression of

VND6/7 affects the formation of proto/metaxylem (pointed and T shaped arrows indicate positive

and negative regulation, respectively).

The KANADI family that belongs to the GARP (Golden2, Arabidopsis RESPONSE

REGULATOR [ARR] and Chlamydomonas regulatory protein of P starvation/acclimatization

response [Psr1]-type transcription factors, is also essential for vasculature development.

The kan1 kan2 kan3 kan4 quadruple mutant makes abnormal vascular bundles where

xylem is surrounded by phloem (Emery et al., 2003; Kerstetter et al., 2001). The

transcription factor encoding genes ALTERED /PHLOEM DEVELOPMENT (APL; which

encodes an MYB coiled-coil transcription factor), VASCULAR-RELATED NACDOMAIN6

(VND6) and VND7 have a direct effect on xylem identity (Bonke et al., 2003; Kubo et al.,

2005). Next to the molecular mechanism regulating vascular development that has been

extensively investigated (Scarpella et al., 2006), knowledge of the regulation of these

processes by spatial signals such as growth hormones in order to explain the establishment

of their spatial distribution in simulation models is also emerging. Various mathematical


49

models were constructed to explore the role of auxin in vasculature development (De Vos

et al., 2012; Scarpella et al., 2006). However, a model proposed by Cano-Delgado et al.

(2004) highlights the role of brassinosteroids in vascular patterning in Arabidopsis. BRs is

perceived by BRI1, a membrane localized LRR-RL kinase which increase xylem and

reduced phloem differentiation. The loss of function of members of BRASSINOSTEROID

INSENSITIVE 1 (BRI1) family, BRI1-LIKE1 (BRL1) and BRI1-LIKE3 (BRL3) produces a

phenotype of reduced xylem and increased phloem (Cano-Delgado et al., 2004). A

mathematical model by Ibanes et al. (2009) shows that BR interacts with auxin for spatial

regulation of vascular bundles in shoot inflorescence.

c) Trichome development

During leaf development specific epidermal cells convert into leaf hairs or trichomes.

Trichomes generally go through three stages for their developmental- cell fate

determination, specification and morphogenesis (Hulskamp et al., 1994). Gene products

related to trichome formation can be subdivided into positive and negative regulators. The

R2R3 MYB transcription factor GLABRA1 (GL1), the bHLH factor GLABRA3 (GL3) and the

WD40- repeat factor TRANSPARENT TESTA GLABRA1 (TTG1) are positive regulators for

trichome formation (Figure 12). The Null mutant gl1-1 is not fully glabrous; a few

trichomes develop at the edges of the late rosette leaf (Kirik et al., 2005; Oppenheimer et

al., 1991). The gl3 mutant shows the same phenotype as gl1-1 whereas overexpression of

GL3 overcomes the trichome defect of ttg1 (Zhang et al., 2003). GL1 and TTG1 bind with

GL3, forming a MYB/bHLH/WD-repeat complex that activates the expression of its

downstream activators GL2 and TTG2, causing trichome differentiation (Grebe, 2012; Yang

and Ye, 2013; Zhao et al., 2008).

CAPRICE (CPC), TRIPTYCHON (TRY), ENHANCER OF TRY AND CPCs (ETC1, ETC2 and ETC3)

and TRICHOMELESS1 (TCL1) are negative regulators, encoding for R3 MYB proteins

(Tominaga et al., 2008) (Figure 12). A loss of function mutant of tcl1-1 induces trichome

formation and overexpression repressed trichome formation completely in Arabidopsis


50

(Wang et al., 2007). The triple mutant etc2 try cpc produces trichome at the edges of the

leaves. All these small MYB proteins replace GL1 in the MYB/bHLH/WD-repeat complex,

rendering it inactive so that the cell remains in the undifferentiated state (Kirik et al.,

2004).

Figure 12. Regulation of trichome differentiation: Transcription factors GLABRA1 (GL1),

GLABRA3 (GL3) and TRANSPARENT TESTA GLABRA1 (TTG1) forming the MYB/bHLH/WD-repeat

complex activates trichome development whereas CAPRICE (CPC), TRIPTYCHON (TRY),

ENHANCER OF TRY AND CPCs (ETC1, ETC2 and ETC3) and TRICHOMELESS1 (TCL1) inhibit the

process. The MYB/bHLH/WD-repeat complex causes the activation of GL2, TTG2 and SIM to induce

trichome differentiation. Trichome production is enhanced by gibberellins and jasmonic acid, while

salicylic acid inhibit it (pointed and T shaped arrows indicate positive and negative regulation,

respectively).

Generally, trichome cells go through four endoreduplication cycles for their development,

reaching an average DNA content of 32C, whereas other epidermal cells continue to divide

(Schnittger and Hulskamp, 2002). It has been observed that the cell cycle related genes like

SIAMASE (SIM), TRIPTYCHON (TRY), SlCycB2 and genes involved in the endoreduplication

process also regulate trichome formation. A sim mutant was found to have altered ploidy

levels affecting trichome development (Pesch and Hulskamp, 2011; Schnittger et al., 1999;

Walker et al., 2000). SIM is indeed directly targeted by the trichome initiation factors GL1

and GL3 (Morohashi and Grotewold, 2009). Plant hormones also regulate trichome


51

formation with GA and jasmonic acid enhancing trichome number and density while

salicylic acid reducing trichome number (Traw and Bergelson, 2003). Still, more studies are

needed to explore the role of phytohormone signaling pathways in trichome formation.

Two main theoretical models have been proposed to explain trichome patterning in

Arabidopsis leaves: an activator-inhibitor model and an activator-depletion model. In the

activator-inhibitor model, the activator (trimer complex of WD40, bHLH and MYB factors)

triggers its own inhibitor (R3MYB) which moves into the neighbouring cell and impedes

activation of the complex whereas, the activator-depletion model explains GL3 dependent

depletion of TTG1 in non trichome cells (Pesch and Hulskamp, 2009). Computational

modeling of the trichome pattern was used by Bouyer et al. (2008) to evaluate these

conceptual models indicating that both models may act in concert.

A System’s Perspective on Leaf Growth

In Systems Biology the aim is to acquire a mechanistic understanding of biological

processes. In most cases the detailed knowledge is formulated in mathematical models that

can simulate the behavior of the system and predict the effect of environmental and genetic

perturbations. Such predictions can then be experimentally tested and the results used to

improve the models further. This way models and experiments reinforce each other

leading to increased understanding of the system (Kitano, 2002).

Here we adopt the view that cells are the units that direct development by integrating local

signals into developmental decisions. Therefore, to build a mechanistic model for leaf

growth we need to be able to model a single cell and its progeny as it progresses from the

stem cell niche into the various positions in the mature leaf. The outcome of the integrated

behavior of all cells ultimately forming the leaf is an organ of realistic size and morphology.

This is currently still a very ambitious goal, but as a first step we addressed here the

question what the current state of knowledge is with regards to regulatory networks that

operate in cells as they progress in their individual developmental pathway.


52

During their developmental journey plant cells or rather their cell lineages are exposed to

diverse biochemical and biophysical conditions, despite being tied into a symplastic mesh-

work. Whereas, their final fate can be very different, ending up as a light harvesting

mesophyll cell versus an epidermal hair cell for instance, many similarities exist in the

events along their paths starting from the stem cell niche of the shoot apical meristem. We

have associated the different processes described above in separate sections with separate

regulatory networks. However, by comparing the corresponding network diagrams, it

readily becomes clear that many regulators and relations are shared; indicating that

considering them as isolated systems is a radical assumption.

All presented networks are subject to intense investigation and some are far from the

finished article, yet from a structural or topological perspective there are some recurring

themes or motifs that emerge. A first case is the negative feedback loop which is a typical

control structure that works like a thermostat: one factor stimulates a second factor which

switches the first one off above a certain threshold. Not surprisingly this motif is active in

the SAM where the WUS-CLV interaction ensures that sufficient stem cells are maintained

for indeterminate growth, at the same time avoiding over-proliferation. A second case we

have encountered is the CDK-APC/C interaction of the cell cycle. Here, the CDK-CYC activity

required for cell proliferation eventually turns on the degradation machinery that

inactivates CDK-CYC. Rather than providing spatial bounds the latter mechanism confers

temporal control on cell proliferation. A somewhat related type of periodicity is a result of

the auxin-PIN interaction crucial to phyllotactic patterning but likely also for determining

leaf venation and serration (Bilsborough et al., 2011). By polarizing PINs towards auxin

maxima, auxin levels are depleted in the surroundings. Another recurring motif is that of

mutual negative feedback inhibition which can lead to switch like (bistable) behavior. An

example is the proposed role of CDKA-KRP in the G1/S module of the cell cycle (Zhao et al.,

2012). Such a motif can also provide a strong basis to support two spatially distinct and

stable developmental domains. The antagonistic relation between ARP family and KNOX

family transcription factors for instance appears to operate as a mechanism that enables

primordium outgrowth while keeping the surrounding regions of the SAM undifferentiated.


53

We have encountered other cases where such a duality appears to be crucial:

determination of ab/adaxial leaf polarity on the one hand and vascular differentiation on

the other hand are both governed by the antagonistic relation between HD-ZIPIII and

KANADI family transcription factors. Importantly, here to exert such spatial inhibitory

effects additional mobile signals are in principle required, since the before mentioned TFs

as far as we know are immobile. Various small RNAs are prime candidates for such a role

(Braybrook and Kuhlemeier, 2010). In fact, many superimposed interactions with other

factors are typically present to further increase robustness to deleterious perturbations or

in contrast to increase the response to important developmental or environmental cues.

As we have seen how well the described regulatory networks are understood varies

considerably. Despite many plant-specific features and intricacies, the universal role and

conserved character of the cell cycle has helped in uncovering its regulation to a

considerable extent. Nevertheless, the precise functioning of KRPs and ubiquitin mediated

degradation in cell cycle transitions remains to be elucidated. For the regulation of the

transition between division and expansion for instance the coherency in the corresponding

network diagram is weaker indicating that our knowledge is still more scattered and

circumstantial. This lack of conceptual understanding is reflected in the absence of

published computational models for this process and similarly for others. Our

understanding of the regulation of cell growth is also relatively limited, in particular its

relation to cell division (Sablowski and Dornelas, 2013). Whereas, the core machinery is

relatively well understood, little is known about the way that primary growth determinants

such as water or nutrient availability are translated into cell growth differences. The role of

the TOR pathway in the regulation of growth and division, crucial in other eukaryotes, is

only starting to emerge for plants (Xiong et al., 2013).

Because of the symplastic nature of plant tissue and the lack of a central nervous system,

organ growth is more dependent on mobile growth signals that produce local gradients,

such as phytohormones, mobile proteins and miRNAs. Since evolution tends to take a

parsimonious approach it is not surprising that several growth signals are shared by


54

different processes (and organisms as well). As illustrated above (see Figure 1), auxin has

indeed been implicated in many developmental stages. If cytokinins are involved then they

typically act antagonistically with auxin and gibberellins (cf. primordium initiation). BRs at

the one hand positively regulate many growth processes, while on the other hand they

negatively regulate guard cell development. Some of the stress induced hormones such as

ABA and ethylene modulate cellular processes for example division, endoreplication and

the transition phase. Other growth hormones like JA and salicylic acid exert a negative

control on the endocycle and on leaf hair development respectively. These phytohormones

have complex interactions where one affects other’s synthesis, transport and signaling

cascades.

Obviously a generalization of the role of specific hormones would imply over-simplification

given the complexity of the regulatory interactions involved. Vernoux et al. (2011)

demonstrated indeed that the control of gene expression by auxin not only depends on its

distribution but also the expression patterns of the signaling network which consists of

over 50 potentially interacting transcriptional activators and repressors. This study further

highlights the importance of an integrative strategy which mathematical modeling

supported by detailed expression maps, live imaging of biosensors, and high-throughput

(interactome) data analysis. Given the crucial and complex role of non-cell-autonomous

signals such as phytohormones the development of sensitive (fluorescent) biosensors to

monitor their spatial and temporal distribution is an important trend (Brunoud et al., 2012;

Shani et al., 2013; Wells et al., 2013).

Other experimental data becoming invaluable for developing improved mathematical

models of leaf growth are quantitative growth data ranging from kinematic output

(Nelissen et al., 2013) to cellular-resolution digital data extracted form confocal images

(Kierzkowski et al., 2012). As repeatedly indicated above, multiple connections exist

between the discussed developmental stages, suggesting that an important challenge will

be to construct computational models that can reproduce these stages in a spontaneous

way. This will likely require a more advanced geometrical representation than a flat plane


55

or a simple sphere or cylinder. Developing coupled dynamical models of different tissues or

organs interacting through an interface might provide a useful first step. However,

eventually fully integrated three-dimensional models will be developed to grasp the

complex cross-talk between various internal and external signals. Next to biological insight,

increased computing power, for instance through improved parallelization algorithms, will

likely become the limiting factor in that process. Ultimately, a mechanistic model for leaf

development should integrate the regulatory networks that control developmental

decisions and processes of cells as they migrate in space and time from the shoot apical

meristem (SAM) to their final position in the leaf. Besides spatially and temporally highly

resolved experimental techniques combined with advanced top down data-extraction

techniques an important aspect will still remain to apply Ockham’s razor in a sensible way.

Choosing a minimal set of variables to produce the desired behavior will present a

challenge given the number of factors that are known to be involved or that are still to be

discovered. As we have attempted to demonstrate, in a number of cases it is already clear

which are the central regulators of the respective regulatory networks and some are

indeed central to existing computational models. Furthermore, the non-cell autonomous

signals and their gradients will inevitably be part of those future leaf developmental

models and connect them to the rest of the plant and even the environment.

Acknowledgements

This work was supported by a concerted research activity (GOA) research grant, ‘A Systems

Biology Approach of Leaf Morphogenesis’ from the research council of the University of

Antwerp and an Interuniversity Attraction Poles (IUAP) from the Belgian Federal Science

Policy Office (BELSPO). Dirk De Vos was funded by a return grant and grant IAP7/29 from

BELSPO and Shweta Kalve by a training grant from the Department of Science and

Education of the Flemish Government.


56

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Chapter 2

Three-dimensional patterns of cell division and

expansion throughout the development of

Arabidopsis thaliana leaves

Shweta Kalve1, Joanna Fotschki2, Tom Beeckman3,4, Kris

Vissenberg1 and Gerrit T.S. Beemster1*

1Department of Biology, University of Antwerp, Belgium

2Department of Food Sciences, IAR & FR, Polish Academy of Sciences, Olsztyn,

Poland

3Department of Plant Systems Biology, VIB, Gent, Belgium

4Department of Plant Biotechnology and Bioinformatics, Ghent University,

Gent, Belgium


This chapter is published as a research paper in Journal of Experimental

Botany, 2014 (doi:10.1093/jxb/eru358)

Contribution of S.K.- Performed most experiments, supervised J.F. and wrote the

manuscript

Three-dimensional leaf growth analysis

91

Abstract

Variations in size and shape of multicellular organs depend on the spatio-temporal

regulation of cell division and expansion. Here, cell division and expansion rates were

quantified relative to the three spatial axes in the first leaf pair of Arabidopsis thaliana. The

results show striking differences in expansion rates: the expansion rate in the petiole is

higher than the leaf blade; expansion rates in the lateral direction are higher than

longitudinal rates between 5 and 10 days after stratification, but become equal at later

stages of leaf blade development; and anticlinal expansion co-occurs with, but is an order of

magnitude slower than periclinal expansion. Anticlinal expansion rates also differed greatly

between tissues: the highest rates occurred in the spongy mesophyll and the lowest in the

epidermis. Cell division rates were higher and continued for longer in the epidermis

compared with the palisade mesophyll causing a larger increase of palisade than epidermal

cell area over the course of leaf development. The cellular dynamics underlying the effect of

shading on petiole length and leaf thickness were then investigated. Low light reduced leaf

expansion rates, which was partly compensated by increased duration of the growth phase.

Inversely, shading enhanced expansion rates in the petiole, so that the blade to petiole ratio

was reduced by 50%. Low light reduced leaf thickness by inhibiting anticlinal cell

expansion rates. This effect on cell expansion was preceded by an effect on cell division,

leading to one less layer of palisade cells. The two effects could be uncoupled by shifting

plants to contrasting light conditions immediately after germination. This extended

kinematic analysis maps the spatial and temporal heterogeneity of cell division and

expansion, providing a framework for further research to understand the molecular

regulatory mechanisms involved.


92

Introduction

Leaf morphology provides us an interesting conundrum: on the one hand it is genetically so

tightly defined that it serves as a basis for taxonomic discrimination and on the other hand

its dimensions are highly plastic and readily affected by environmental conditions.

Leaf growth is a dynamic process, where the transition from a small primordium to a

mature, fully grown leaf is regulated by two key processes: cell division and expansion

(Beemster et al., 2005; Breuninger and Lenhard, 2010; Gonzalez et al., 2012; Kalve et al.,

2014). Therefore, a thorough study of cell division and expansion is necessary to

understand leaf growth regulatory mechanisms. Kinematic analyses of cell division and

expansion in leaves are increasingly being used to understand the cellular basis of leaf size

differences (Nelissen et al., 2013; Silk and Erickson, 1979). It is well documented that leaf

growth is affected by different environmental constrains that affect the global rates of cell

division and expansion (Granier and Tardieu, 2009; Skirycz et al., 2011). Mutants

specifically altered in leaf shape and size, especially in the model species Arabidopsis

thaliana, strongly suggest that expansion and division in different orientations are to some

degree independently regulated and that they may have different temporal dynamics

(Horiguchi et al., 2006; Tsuge et al., 1996; Tsukaya, 2008). It is, however, rarely studied

how the rates of these growth processes vary relative to the three spatial dimensions,

length, width and thickness and in function of time during the growth of an organ to

determine the morphology of the mature leaf.

A second issue is that individual tissues display different cell division activities (Donnelly et

al., 1999) and this may extend to cell expansion. In analogy to the situation in the root tip

(Swarup et al., 2005; Ubeda-Tomás et al., 2009), tissue-specific regulation of growth

processes may be an important aspect of leaf growth regulation. Indeed, it was

demonstrated that the response of leaf growth to brassinosteroids resides in the epidermis

and is translated by a non-cell autonomous signal to the inner layers (Savaldi-Goldstein et

al., 2007). An elegant study of Nicotiana chimera showed that the genotype of the

epidermal layer determines the rate and extent of cell division in mesophyll and leaf size


93

(Marcotrigiano, 2010). On the other hand a detailed anatomical study of Arabidopsis

thaliana leaf development highlighted the increase in mesophyll volume as the most

prominent process (Pyke et al., 1991). Moreover, environmental cues like low light and

water deficiency have been shown to affect leaf thickness specifically through effects on the

cell volume in mesophyll cell layers (Wuyts et al., 2012). The effect of different light

intensities on leaf development showed that high light stimulates leaf thickness by

increasing the number of mesophyll tissue layers (James and Bell, 2000; Wuyts et al., 2012;

Yano and Terashima, 2004). Hence, it appears that different layers play a role in

determining specific aspects of leaf morphology in response to environmental and

physiological signals. Besides the interaction between layers, it is also still a question how

most of the environmentally and genetically induced morphological differences are

established during leaf development. Therefore, determining the spatial distribution of

growth and division rates in different tissue layers is a way to advance our understanding

of leaf growth regulation.

The objective of this study is therefore to quantify cell division and expansion rates in three

dimensions throughout the development of the Arabidopsis thaliana leaf. Specifically, the

following questions are addressed: 1. Are expansion rates synchronized in lateral

(increasing leaf width), longitudinal (increasing leaf length) and anticlinal (increasing leaf

thickness) directions at the whole leaf level? 2. Are anticlinal expansion rates synchronized

between tissue layers? 3. Are division rates synchronized between cell layers at the whole

leaf level? 4. What is the effect of shading on cell division and expansion rates causing

differences in leaf morphology?

The analysis provides a first spatio-temporal map of cell division and expansion rates in all

three directions for the first leaf pair of Arabidopsis thaliana under optimal conditions. The

study of the effect of shading demonstrates how a single environmental factor affects cell

division and expansion at different developmental stages and independently of one

another.


94

Results

Leaf morphology is defined by three axes: (a) the lateral axis which defines leaf width; (b)

the longitudinal axis connecting top (distal) and bottom (proximal) parts of the leaf; along

this axis a distinction between the blade and petiole appears during development; and (c)

the transversal or dorso-ventral axis that defines leaf thickness from the upper (adaxial) to

lower (abaxial) surface and along which cells are organized in distinct layers of different

cell types (Figure 1). To quantify the leaf growth process in relation to these three axes, we

determined cell division and expansion rates in the first leaf pair of Arabidopsis thaliana

from germination at day 5 till maturity at 25 days after stratification (DAS).

Figure 1. Anatomical and morphological characteristics of the mature Arabidopsis thaliana

leaf: (A) its three main axes (lateral, longitudinal and transversal; Scale Bar=5mm); (B) and (C)

cross sections at 5 DAS and 25 DAS respectively; (D-G) different cell layers (Scale Bar=100 µm): (D)

adaxial epidermis; (E) palisade mesophyll; (F) spongy mesophyll; and (G) abaxial epidermis.


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Whole-leaf expansion

Directly after emergence at 5 DAS, there is no distinction between blade and petiole. At 8

DAS the petiole is formed, contributing 27% of the total leaf length (Figure 2A). Both leaf

blade and petiole grow exponentially until 18 DAS, when they reach their mature size

(Figure 2A). Interestingly, petiole elongation rates were higher than those of the blade

between day 12 and 18 (Figure 2B), so that in the mature leaf the petiole contributes 39%

of the total length.

Figure 2. Leaf growth in three dimensions: (A) Petiole, leaf blade and total leaf length; (B)

Comparative length increase in the petiole and the leaf blade; (C) Measurement of leaf blade width,

length and thickness; (D) Expansion rate of leaf blade width, length and thickness; (E) Ratio

between leaf blade length and width. Symbols in A, C and E represent averages ± SE (n = 5-15; Error

bars smaller than the symbols are not shown), symbols in B and D are derivatives of 5 point fits on

population averages in A and C, respectively.


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In young primordia, at 5 DAS, the width of a leaf is less than 50% of its length (Figure 2C,

E). Like length, leaf width also increased at exponential rates, but the lateral expansion

rates were higher than longitudinal rates until 10 DAS (Figure 2D), so that the

length/width ratio of the blade gradually declines from 2 to 1, meaning that length and

width become roughly equal (Figure 2E). After that the leaf continues to expand at low

rates that are balanced in lateral and longitudinal directions until the leaf attains its final

size around day 20 (Figure 2D, E).

Expansion rates in the anticlinal direction (i.e. increasing thickness) were an order of

magnitude lower than areal expansion rates, explaining the flattened morphology of the

leaf. Interestingly, anticlinal expansion occurred during the same time frame as areal

expansion, but with different dynamics. Maximal areal rates were occurring at the earliest

time point while highest anticlinal expansion occurred between 7 and 12 DAS, when areal

expansion rates were rapidly declining (Figure 2D).

Cell type-specific anticlinal expansion

The contribution of different tissue layers to anticlinal growth was next examined. At the

first observation on 5 DAS, the mesophyll contributed 76% of the total thickness of the leaf

blade (Figure 3A). Although anticlinal expansion occurred throughout leaf development in

all tissues, the rates were higher in the mesophyll than in the epidermis (Figure 3B), so that

in the mature leaf the mesophyll contributed 81% of the total leaf thickness (Figure 3A).

Within the mesophyll, the palisade cells contributed 53% and the spongy mesophyll 23% of

total leaf thickness in the youngest stages (Figure 3A). Anticlinal expansion rates of the

spongy mesophyll tissue were consistently roughly double those of the palisade mesophyll

tissue throughout development (Figure 3B). Consequently, in the mature leaf, both layers

almost contributed equally (44 and 37%, for palisade and spongy mesophyll respectively)

to the total leaf thickness (Figure 3A).


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Figure 3. Tissue specific anticlinal growth: (A) Thickness of each cell layer during leaf

development; (B) Anticlinal expansion rate of each cell layer. Symbols in A represent averages ± SE

(n = 4-8; Error bars smaller than the symbols are not shown), symbols in B are derivatives of 5

point fits on population averages in A.

Taken together, the results show that, although the period of cell expansion is similar in all

tissues and directions, the periclinal expansion rates are by definition equal between all

tissue layers since they do not slide relative to one another. In contrast, the expansion in

anticlinal and periclinal orientation differs by an order of magnitude. Moreover, the

anticlinal expansion rates vary strongly between adjacent cell layers and within each cell

type.

Anticlinal cell division and periclinal expansion rates

To investigate potential differences in anticlinal cell division rates, that increase the

number of cells per layer, it was decided to compare palisade mesophyll tissues and abaxial

epidermal cells. These two layers were chosen because they were most homogeneous, due

to the lack of trichomes which are present in the adaxial epidermis and due to less

intercellular air spaces which are substantial in the spongy mesophyll and complicate the

calculations. Both the abaxial epidermis and palisade mesophyll are therefore easy to

study. First the surface area of the first leaf pair was measured to calculate leaf expansion

rates, because relative rates of changes in cell size depend on the balance between cell

growth (measured as the evolution of leaf area) and cell division rate (that partitions this

growing area; Green, 1976). Then, individual areas of epidermis and palisade cells were


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determined by quantitative image analysis on periclinal optical sections of the leaf, and cell

numbers were calculated by dividing the total leaf area by the average cell area of each

individual layer. From 7 till 9 DAS, there was a four-fold increase in leaf area (Figure 4A). At

this stage the palisade cell area was significantly smaller than the epidermal cell area

(Figure 4C, I), resulting in a slightly higher number of cells in the palisade layer than in the

epidermis (Figure 4D). From day 13 onwards this situation was reversed (Figure 4C, D),

indicating that the relative rate of size increase was higher in the palisade than in the

epidermal cells (Figure 4E), so that in the mature leaf the palisade cell area was 1.5 fold

larger than that of the average epidermal cell (Figure 4C, I). Because average rates of cell

expansion (Figure 4B) are equal in both layers, different size evolution rates must be due to

differences in the division rates in both layers. Indeed, cell division rates in palisade cells

declined much faster and divisions stopped around day 13 (when rates became 0), which is

about two days earlier than in the epidermal layer (Figure 4F). This extended division

period can be related to meristemoid activity driving guard cell development in the

epidermal cell layer as the number of guard cells increased more rapidly than the number

of pavement cells during this period (Figure 4H). Consequently, the stomatal index, the

ratio of guard cells and total number of epidermal cells of the abaxial epidermis, increased

rapidly from 7 till 15 DAS, exactly the period where division rates in the epidermis exceed

those of the mesophyll (Figure 4G). In conclusion, these results show that division rates

and the timing of exit from cell division differ between these two cell layers.


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Figure 4. Cell division and expansion in the paradermal plane: (A) Leaf blade area; (B) Areal

expansion rate; (C) Cell area in abaxial epidermis and palisade parenchyma; (D) Epidermal and

palisade cell number; (E) Relative change in rates of cell area in the abaxial epidermis and palisade

parenchyma; (F) Cell division rate of epidermal and palisade cells; (G) Stomatal Index; (H) Number

of epidermal and pavement cells; (I) Images of abaxial epidermis and palisade tissues on 7 and 25

DAS (Scale Bar=100 µm). Symbols in A, C, D, G and H represent averages ± SE (n = 3-5; Error bars

smaller than the symbols are not shown), symbols in B, E and F are derivatives of 5 point fits on

population averages in A, C and D, respectively.


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Effect of light on leaf growth

After quantifying differences in anticlinal division rates, differences in periclinal division

activity that increases the number of cell layers were addressed. For this, it was decided to

study the well-documented effect of light intensity on leaf thickness, mediated by

differences in the number of palisade cell layers (Dengler, 1980; Kim et al., 2005; Wuyts et

al., 2012; Yano and Terashima, 2004). Specifically, the aim was to address the question

whether variations in cell division, expansion or a combination lead to the observed

differences in cell layers and leaf thickness. To this end, plants were grown under high

(120-130 µmol s-1m-2 PAR) and low (10-20 µmol s-1m-2 PAR) light intensities.

Light intensity not only affected thickness, but also had a profound effect on leaf area.

Under low light, leaves were significantly smaller throughout their development; leaf area

increased at a lower rate and the final leaf surface area was decreased by 30% (p = 0.000;

Figure 5A). Indeed, the expansion rate during the early stages of leaf development was

about 1/3 of those of high light plants, which was partly compensated by an increase in the

duration of the expansion process (Figure 5B). The evolution of the leaf length/width ratio

of low light plants reflected this slower development as it followed the same pattern as in

high light, i.e. starting close to 2 in young primordia and declining to 1 at 13 DAS, which is 4

days later than the high light leaves (Figure 5E). An expected phenotype of the low light

leaves was the increase in the length of the petiole, which reached to 6.4 mm on 30 DAS,

whereas in high light plants it was only 3.7 mm (p = 0). Interestingly, this increased petiole

length was obtained despite the petiole being formed later than in high light leaves (Figure

5C). However, the petiole in low light is initiated at a greater length (Figure 5C) and in

contrast to the blade grows at a much faster rate than at high light (Figure 5D). As a

consequence, the ratio between blade and petiole length was 2-fold smaller in low light

leaves compared to high light (Figure 5F; p = 0.000). These results indicate a specific

stimulation of low light on the initiation and expansion of the petiole.


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Figure 5. The effect of shading on leaf development: (A) Leaf area under high and low light

intensities (10-20 and 120-130 µmols-1m-2 PAR); (B) Expansion rate of leaf surface area; (C) Leaf

blade and petiole length; (D) Elongation rates of petiole and leaf blade. (E) Ratio between leaf blade

length and width; (F) Ratio between leaf blade and petiole length. Symbols in A, C, E and F

represent averages ± SE (n = 3-15; Error bars smaller than the symbols are not shown), symbols in

B and D are derivatives of 5 point fits on population averages in A and C, respectively. Low/L and

High/H denote low and high light treatment, respectively.

As expected, the thickness of mature leaves was 45% reduced by low light (p = 0.000;

Figure 6A). Detailed analysis of the thickness over time showed that at 5 DAS there was

already a small, but significant reduction in leaf thickness in low light compared to high

light (Figure 6A and 7). This difference progressively increased during further

development. Curiously, in contrast to areal expansion rates (Figure 5B), the timing of


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anticlinal expansion was very similar between high and low light. The main difference in

leaf thickness appears to be generated between 6 and 15 DAS (Figure 6A), when anticlinal

expansion rates of low light leaves are only half of those of high light plants (Figure 6B).

Figure 6. Anticlinal leaf growth under high and low light intensities: (A) Total thickness of leaf;

(B) Anticlinal expansion rates; (C) Thickness of cell layers at 25DAS; (D) Number of cell layers in

the leaf. Symbols in A, C and D represent averages ± SE (n = 3-8; Error bars smaller than the

symbols are not shown), symbols in B are derivatives of 5 point fits on population averages in A.

Low and High denote low and high light treatment, respectively.

Quantification of individual cell layers indicated that all cell layers contributed to some

extend to this reduced thickness, but the decrease was largest in the palisade (49%; p = 0)

and spongy mesophyll (48%; p = 0.008) compared to the adaxial (22%; p = 0.018) and

abaxial (27%; p = 0.003) epidermis (Figure 6C). Consistent with earlier reports (Dengler,

1980; Kim et al., 2005), the decrease in thickness was associated with a decrease of one

layer of palisade cells (Figure 6D, 7). By determining the number of cell layers throughout

the development of the leaf, the aim was to determine the timing of periclinal divisions to

identify the difference in the division patterns that decreases the palisade with one layer in

the low light conditions. Surprisingly, it was found that the final number of layers was

already established at 5 DAS, when our kinematic analysis started in both light conditions.


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Therefore, the differences in the number of cell layers between high and low light were

already established before this time point, i.e. immediately after germination (Figure 6D,

7).

Figure 7. Cross-sections of leaves grown under high (left) and low (right) light intensities from 5

till 25 DAS (UE=Upper Epidermis, M=Mesophyll, PM=Palisade Mesophyll, SM=Spongy Mesophyll

and LE=Lower Epidermis).

These results indicate that the division forming the additional cell layer in high light grown

leaves precedes the analysis conducted here and must occur during, or immediately after

germination, whereas the expansion that generates differences in leaf thickness occur at a

later stage (Figure 6A, B). This suggests that the effect of light on the periclinal cell

divisions that determine the number of cell layers and on expansion that determines leaf

thickness are clearly separated in time. This led to the hypothesis that these effects can be

uncoupled by changing the light conditions shortly after germination.


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To test this possibility, plants were germinated and grown in low and high light until 3 DAS

and half of them were transferred to the opposite conditions (low to high and high to low

light, respectively) till 18 DAS. As predicted, it was found that leaves germinated under low,

but grown in high light had only six cell layers, whereas leaves germinated under high light

and grown in low light had seven layers of cells (p = 0.06; Figure 8A, B). Nevertheless, light

conditions during germination had only a very small effect on thickness at maturity, which

was almost completely dependent on light conditions during the growth period at a later

stage (Figure 8A, C).

Figure 8. Effect of intensity on leaf anatomy: (A) Cross sections of leaf grown under low and high

light intensities for 3 DAS and then transferred to the contrasting conditions until 18 DAS

(UE=Upper Epidermis, PM= Palisade Mesophyll, SM= Spongy Mesophyll and LE= Lower Epidermis)

(Scale Bar=100 µm); (B) Number of layers and (C) thickness of the leaf grown under low and high

light intensities for 3 DAS and then transferred subsequently in high and low light together with

plants grown under high and low light continuously. Bars in B and C represent averages ± SE (n = 4-

5).


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Discussion

Leaf development is a multi-dimensional process, where temporal variation in the spatial

distribution of growth and division rates determines shape and size. To determine

quantitatively how cell division and cell expansion contribute to differences in leaf area in

response to environment and genetic differences, kinematic analyses have been developed

(Nelissen et al., 2013). For leaves of eudicot plants, such as Arabidopsis thaliana, these

methods typically involve measurements of the growth of the leaf as a whole, assuming a

large degree of homogeneity. For determination of cell division, the focus is usually on the

abaxial epidermis as a cell layer representative for the whole of the leaf. This approach

provides a good insight into the developmental progression of the leaf as a whole, given the

strong correlation between kinematic and transcriptome data obtained from whole leaf

samples (Beemster et al., 2005).

Nevertheless, detailed qualitative studies of cell division (Andriankaja et al., 2012; Donnelly

et al., 1999), cell expansion (Kuchen et al., 2012; Walter et al., 2002; Wiese et al., 2007) and

cellular development (Pyke et al., 1991) in the leaves of Arabidopsis thaliana showed large

differences across the leaf and between tissue layers. In order to obtain a more quantitative

insight into spatio-temporal variations in cell division and expansion we have adapted the

kinematic approach here to determine cell division and expansion rates in function of the

major axes of leaf development. The results obtained illustrate the high degree of

heterogeneity across the developing leaf.

Differences in growth rates across the developing leaf

Generally, leaf morphology is divided into leaf blade and petiole. Consistent with the

present findings, other studies also showed that leaf petioles become significantly shorter

under white or strong light, while the length and width of leaf blades were less affected

(Tsukaya et al., 2002; Kozuka et al., 2005). Similar to the present observations, Donnelly et

al. (1999) observed the late emergence and higher elongation rates of the petiole compared

to the leaf blade.


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Furthermore, the present results showed that the longitudinal growth outpaced lateral

expansion in early stages of development of the leaf primordium, resulting in an oblong

shape. During subsequent development, the blade of the first leaf pair became round due to

expansion rates in lateral direction outpacing those in longitudinal direction. Ultimately,

during the final stages of leaf development, expansion rates became roughly similar in the

longitudinal and lateral direction, indicating isodiametric surface expansion of the whole

leaf blade.

The differential dynamics of longitudinal and lateral growth relate to genetic findings

indicating that expansion in both directions is regulated by separate regulatory pathways.

Longitudinal expansion is positively governed by ROT3 or ROT4 (ROTUNDIFOLIA), whereas

ANGUSTIFOLIA (AN) regulates lateral expansion (Narita et al., 2004; Tsuge et al., 1996;

Tsukaya, 2006). Hence, an elliptical shape of the leaf was observed in the early stages of its

development, which became more spherical because of the higher expansion rate in leaf

width. The gene expression data of Beemster et al. (2005) show that the expression of the

AN gene is highest at 9 DAS when lateral growth outpaces longitudinal growth, and AN

expression decreases till the maturity. In contrast, ROT3 expression increases from

proliferation till maturity. The opposite expression patterns of ROT3 and AN thus reflect

the relative increase in longitudinal expansion around 15 DAS where lateral and

longitudinal leaf growth become equal. Therefore, it can be predicted that the change in

growth rates in lateral and longitudinal directions is regulated by the crosstalk between

ROT3 and AN.

The present study showed that the rates of leaf blade expansion in the dorso-ventral

direction are an order of magnitude lower than in longitudinal and lateral directions, which

illustrates that in 3D leaf growth is highly anisotropic. Superimposed on this anisotropy is

the effect of environmental conditions on anticlinal cell expansion, where several studies in

different plant species demonstrated strong effects on leaf thickness by light intensity and

water deficiency (Dengler, 1980; Kim et al., 2005; Wuyts et al., 2012; Yano and Terashima,

2004). To our knowledge this study provides a first quantitative 3D analysis of cell

expansion in the Arabidopsis thaliana leaf and the results clearly illustrate the magnitude of


107

spatio-temporal variations that contribute to the final leaf shape. The results indicate that

individual cells differentially regulate the expansion of their walls depending on their

orientation. To address the question how this is achieved is a cell biological challenge due

to the 3D aspect that is not easily accessed by approaches using microscopy. Nevertheless,

the present data provide a framework in which such studies can be performed, providing

information of timing and the location at which differences are occurring.

Cell layer-specific contributions to leaf thickness

Leaf growth in the anticlinal direction is determined by growth of the individual cell layers.

The present analysis of tissue layers shows that anticlinal expansion rates differ strongly

between cell types, with mesophyll tissues having distinctly higher expansion rates than

epidermal cells. These results are consistent with observations that epidermal cells grew

substantially in area while there is little increase in cell height in Helianthus annuus

(Dengler, 1980). A developmental study of Arabidopsis thaliana leaves demonstrated the

role of mesophyll tissues in determining leaf thickness (Pyke et al., 1991). The

developmental importance of the mesophyll in determining leaf thickness in Arabidopsis

thaliana was demonstrated by Wuyts et al. (2012) who correlated the resulting decrease in

leaf thickness with a reduced proportion of mesophyll tissues. This shows that differential

growth in the mesophyll tissue is the primary determinant of anticlinal leaf growth. The

present results provide the dynamics of cell division and expansion that are at the basis of

the observed differences in number of cell layers and thickness of the leaf.

Under the standard conditions used here, the leaf lamina of Arabidopsis thaliana forms

seven layers of cells, which comprised two epidermal layers (adaxial and abaxial), two

layers of palisade and three layers of spongy mesophyll, which was similar to other studies

(Dengler, 1980; Wuyts et al., 2012). A developmental study of the Arabidopsis thaliana leaf

by Pyke et al. (1991) indicates that the increase in leaf thickness is associated with the

degree of elongation of the palisade tissue. The present observation illustrates that the

palisade mesophyll tissues contribute more to leaf thickness than spongy mesophyll tissues

in the early days of leaf development and that this difference was partially overcome by a


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higher anticlinal expansion rate in the spongy mesophyll. This shows that palisade

mesophyll tissues establish and differentiate earlier than spongy mesophyll tissues. Despite

having knowledge about the role of different cell layers in anticlinal growth, the reason for

the pronounced difference between cell expansion in anticlinal and in periclinal direction is

not clear. In roots and stems anisotropy of cell expansion is determined by the orientation

of cellulose microfibrils (Baskin, 2005; Baskin et al., 1999; Roudier et al., 2005). To our

knowledge this aspect has not yet been addressed in the context of the more complex

morphology of the eudicot leaf. The present detailed analysis of the time evolution of

expansion in different cell layers during the development of the leaf of Arabidopsis thaliana

can provide a basis for such studies.

Anticlinal cell division and size evolution differ between cell layers

The cellular measurements conducted in this study show that different cell layers have a

distinct growth evolution in response to leaf development. Changes in leaf growth have

mostly been evaluated by measuring cellular changes in the epidermal and/or mesophyll

cell layers (Andriankaja et al., 2012; Beemster et al., 2005; Donnelly et al., 1999; Granier

and Tardieu, 1998; Wuyts et al., 2010) and different mutants have been used to explain the

molecular basis of the observed growth differences (Cheng et al., 2013; De Veylder et al.,

2001; Horiguchi et al., 2006). However, spatial and temporal differences in the rates of cell

division and expansion processes between these cell layers have not been analyzed so far.

According to Green (1976) relative rates of cell size changes are determined by the balance

between relative surface extension and cell division rate. Thus, when cell growth and

division are perfectly balanced, the leaf area will increase, but the average cell size will be

constant. Because expansion rates are the same for all layers, the author concluded that

differences in cell size evolution must therefore be due to differences in cell division rates

between the layers. In this study, variations in cell division rates between palisade and

epidermal cells that cause differences in cell size evolution between these layers have been

quantified. Specifically, lower rates of cell division were found in palisade cells than in

epidermal cells, so that cell size increase is faster in palisade than in epidermal cells. It is


109

interesting that those two layers, which drive organ growth, have significant differences in

proliferation rate. This raises the question what the factors are that regulate tissue-specific

division rates and if there is communication between the different layers to appropriately

coordinate these rates, and thereby relative cell sizes and numbers in each tissue.

L1 layer-specific expression of two cyclin-dependent kinase (CDK) inhibitor genes, KRP1

and KRP4 by the AtML1 promoter inhibited cell division and reduced overall leaf size

(Bemis and Torii, 2007). Surprisingly, the number of cells in the sub-epidermal layer was

unchanged as compared to wild type. However, these cells were significantly smaller with

distorted organization. This clearly suggests that the L1 layer does not control the cell

division of inner layers. In contrast to this result, studies of sectoral chimeras in Nicotiana

demonstrated that the cell division rate of mesophyll cells is inhibited by reduced cell

division of the epidermis, resulting in smaller leaf sections with normal sized cells

(Marcotrigiano, 2010). This result suggests that that the epidermis communicates with

inner layers to stimulate or inhibit their growth.

HOBBIT (HBT) is a CDC27 homolog, which encodes a subunit of the Anaphase Promoting

Complex or Cyclosome (APC/C), is a candidate for involvement in this communication.

Postembryonic excision of a single complementing HBT gene copy in hbt mutant rescued

the mutant phenotype, demonstrating that the removal of HBT reduced cell division, which

was accompanied by increased cell expansion in all the layers of Arabidopsis thaliana

leaves. Interestingly, in L1-derived sectors (representing excised HBT); cell division could

be rescued by the presence of wild type HBT in the cells from the underlying layers. In

contrast, no rescue was found in sectors spanning all three layers; suggesting a role of non-

cell autonomous signal in controlling cell division between layers (Serralbo et al., 2006).

Additionally, AN3/GIF1, a transcriptional co-activator also mediates inter cell layer

signaling to balance cell proliferation in epidermis and mesophyll cells in leaves. Mutation

in AN3 reduces epidermal and sub-epidermal cell number, resulting in smaller leaves, and

recent studies have placed AN3 as a central component in the regulation of the transition

from cell proliferation to differentiation (Kawade et al., 2013; Vercruyssen et al., 2014).


110

Savaldi-Goldstein et al. (2007) studied inter cell communication during cell expansion by

using the L1-specific promoter AtML1 to trigger the expression of the brassinosteroid

receptor (BRI1) or a brassinosteroid biosynthetic enzyme CPD in the background of their

corresponding mutants (bri1 and cpd). The cells of epidermal and sub-epidermal layers in

these lines were rescued to wild type size, demonstrating that upon brassinosteroid

perception non-autonomous growth signals are sent from the epidermis to inner layers. It

will be interesting to determine the exact nature of the signaling molecules involved as well

as the potential role of other hormones by which different layers communicate to regulate

cell division and expansion.

Low light differentially affects leaf growth in three dimensions

The study of leaf growth under control conditions revealed large differences in rates of cell

division and expansion in virtually all dimensions tested. Low light intensity added another

level of complexity, which generally inhibits cell division and expansion throughout the

leaf, with the notable exception of petiole expansion rates, which are stimulated (Figure

5D).

Many previous studies in various plant species have shown that darkness or low light

reduced final leaf area, leaf thickness and epidermal cell number (Cookson and Granier,

2006; Dengler, 1980; Kim et al., 2005; Wuyts et al., 2012; Yano and Terashima, 2004). The

present study showed that shading reduced leaf surface area through decreased leaf

expansion rate, which is partly compensated by an increased duration of expansion. A

similar effect on leaf expansion was seen after UV-B treatment in Arabidopsis thaliana

(Hectors et al., 2010).

The enhancement of petiole length in combination with decreased leaf blade length by

shading of Arabidopsis thaliana plants is consistent with earlier reports (Tsukaya et al.,

2002). The present results demonstrate that these increased petiole lengths are primarily

related to enhanced petiole elongation rates, whereas the reduced size of the leaf blade is

due to a parallel inhibition of cell expansion in the blade. This contrasting response is


111

consistent with studies of photoreceptor mutants showing that PHYB and CRY1 promote

leaf blade expansion and inhibition of petiole elongation in red light and blue light,

respectively. Moreover, sucrose appears to promote leaf blade and petiole growth in the

dark, whereas it inhibits them in the light (Kozuka et al., 2005). Therefore, the contrasting

effect of light on leaf blade and petiole under low light is likely to be controlled by the

interaction of sugars and photoreceptors.

The results show that the well-documented effect of low light on leaf thickness was

associated with a reduction in thickness of all cell layers. However, the best-documented

effect of low light is the inhibition of the number of palisade cell layers (Dengler, 1980; Kim

et al., 2005; Wuyts et al., 2012; Yano and Terashima, 2001). Indeed, a one-layer reduction

in palisade cells was observed under low light compared with high light. Surprisingly, it

was found that this difference was already established prior to leaf emergence (Figure 6D),

whereas the differences in anticlinal cell expansion only occurred between 5 and 15 DAS

(Figure 6E). By moving plants from high to low and from low to high light conditions at 3

DAS, when seeds are germinating and start to unfold their cotyledons, the effects of the

light intensity on division and expansion were almost completely uncoupled. The

relationship between cell division and expansion is complex and compensation in size

occurs in response to inhibition of cell division (Beemster et al., 2003; Horiguchi and

Tsukaya, 2011). Here, it is shown that in addition to areal growth, compensation can also

occur in the anticlinal orientation.

Light can be perceived by seedlings prior to germination as can be seen from effects on

seed germination, where darkness significantly reduces the germination percentage (Qu et

al., 2008). Different phytochromes are involved to control seed germination and shade

avoidance responses in plants where phytochrome B is expressed from seedling till mature

plant stages (Chen et al., 2004; Somers and Quail, 1995). Consequently, it is conceivable

that the effect on periclinal divisions in the non-emerged primordium is mediated by

internal signals induced in response to light perception in the seed coat, the unfolded

cotyledons or the radicle, which can sense the low light before the primordium of the first

leaf pair is exposed to it. The present study shows the importance of the early stages of leaf


112

development, which is consistent with mathematical models that link early primordial

morphology to final leaf shape to through spatial regulation of the growth distribution

(Kuchen et al., 2012).

Implications of kinematic analysis

One of the reasons for performing kinematic analyses on the (abaxial) epidermal layer,

despite of its more complex composition of cell types (pavement cells, meristemoids and

guard cells) compared to the palisade mesophyll layer is the absence of potential periclinal

divisions in the latter tissue (De Veylder et al., 2001). Such divisions would lead to an

underestimation of cell division activity when the analysis is solely based on paradermal

(optical) sections of the leaf. However, the present study shows that such divisions are

restricted to a time window that precedes that of kinematic analyses and therefore

validates kinematic studies based on palisade cells.

Conclusion

Leaf growth is a multidimensional process, which involves well-defined cellular

arrangement of cell types in lateral, longitudinal and dorso-ventral directions. To our

knowledge this is the first quantitative kinematic study of the spatiotemporal dynamics of

cell division and expansion rates along the three different axes, which adds an extra

dimension to our knowledge of leaf development. This study opens up new possibilities for

further research, which can explain a number of interesting questions such as when exactly

division at early stage establishes the number of mesophyll cell layers and which are the

factors involved in regulating this process. Another area of research is to determine the

mechanisms that establish the variation between leaf expansion in anticlinal and areal

directions. Moreover, the study forms a framework for further in-depth studies of the

cellular and molecular basis to explain the observed differences in cell division and

expansion rates across the eudicot leaf.


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Material and Methods

Plant material and growth conditions

Arabidopsis thaliana wild type Col-0 seeds were sterilized in 70% ethanol for 1 minute and

5% bleach for 10 minutes followed by rinsing with water and sown on half-strength MS

(Murashige and Skoog, 1962) medium (Duchefa, The Netherlands) supplemented with 1%

sucrose in 150x25 mm round petri dishes (Falcon® tissue culture dishes). After sowing, the

plates were placed at 4°C for 2 days to synchronize germination. After stratification, the

plates were transferred to a growth chamber with an air temperature of 22°C and shelves

cooled to 19°C. Two different light intensities (10-20 and 120-130 µmol s-1m-2 PAR) were

applied in a 16 h day and 8 h night regime.

Leaf growth analysis

Growth analysis was performed on the first leaf pair. Leaves were fixed and cleared with

70% ethanol for 24 h and subsequently in 100% lactic acid, which was also used as a

mounting agent. Leaf images were obtained with a binocular microscope (Nikon SMZ1000)

fitted with a digital camera (Zeiss AxioCam Cc1) from 5 to 25 days after stratification

(DAS). For each day leaf surface area, blade length, blade width and petiole length of 5-15

leaves were measured using ImageJ (http://rsbweb.nih.gov/ij/). Logarithmic values of the

means of leaf area, leaf blade length, blade width and petiole length were used and locally

fitted with a 5-point quadratic function (Erickson, 1976) of which the first derivative was

used to determine the relative expansion rates.

Transverse sectioning

From 5 to 25 DAS, 4 to 8 leaves were fixed under a vacuum in a solution of 5% acetic acid,

5% formaldehyde and 50% ethanol for an hour. Fixed leaves were rinsed with phosphate

buffer, pH 7.2 and dehydrated by sequential 4 h incubations in 30%, 50%, 70%, 80%, 90%,

95% and 1 h incubation in 98%, 99% and twice in 100% ethanol. The dehydrated seedlings

http://rsbweb.nih.gov/ij/


114

were incubated at room temperature in 30%, 50%, 70% (v/v) Technovit 7100 resin with

ethanol and in 100% resin for 15 h. These incubated leaves were embedded in resin with

hardener and allowed to harden for 24 h at room temperature. Cross sections of middle

part of the leaf were cut (2 μm thick) with a rotary microtome (Leica Reichert-Jung 2040),

stained with 0.05% (w/v) solution of toluidine blue for 10 min and rinsed with distilled

water for 1 min. Slides with the sections were dried at 40˚C and mounted using DePeX as

mounting agent. Pictures of the sections were taken with a bright field microscope (Zeiss

Axio Scope A1 at 20x magnification) fitted with a digital camera (Zeiss AxioCam Cm1). The

number of cell layers was counted and total leaf thickness and the thickness of each cell

layer were measured with ImageJ. The logarithmic values of average leaf thickness and the

thickness of each cell layer per day were used and locally fitted using a 5 point quadratic

function of which the first derivative was used to determine the relative expansion rate.

Cellular measurements

We performed a kinematic analysis of the abaxial epidermal cells using 3-5 average leaves

for each time point from 7 to 25 DAS as described by Nelissen et al. (2013). Leaves of early

days, i.e. 7-10 DAS, were stained with propidium iodide followed by the protocol of Wuyts

et al. (2010) and cell images were obtained with a Nikon C1 confocal microscope mounted

on a Nikon Eclipse E600. Leaf samples of later time points were cleared with 70% ethanol

and subsequently stored and mounted in 100% lactic acid on object slides for microscopy.

Epidermal and palisade cells located between 25 to 75% of the leaf blade from tip to base

were imaged using DIC optics on a Zeiss Axio Scope A1 at 20x and 40x magnification fitted

with a digital camera (Zeiss AxioCam Cm1). The outlines of imaged epidermal and palisade

cells were hand drawn on an LCD tablet (Wacom drawing pad) connected to an iMac

computer running ImageJ. Cell analysis of drawn cells was done with an automated image

analysis software that discriminates guard cells from pavement cells based on the presence

of the stomatal pore, measures the area of all cells and counts the number of cells

(Andriankaja et al., 2012). From these data we calculated the average cell area, estimated

the number of cells per leaf by dividing leaf blade area by average cell area and determined

the stomatal index as the fraction of guard cells relative to all epidermal cells (pavement +


115

guard cells). We calculated rates of cell division and cell area increase as the relative rate of

increase in cell number and cell size in each layer over time, respectively. For this, the

logarithmic values of means of cell size and cell number were locally fitted with a 5 point

quadratic function of which the first derivative was used as the relative growth and

division rates, respectively.

Statistical analysis

Standard error was calculated from different replicates on each time point for leaf area, cell

area, cell number, stomatal index, thickness and cell layer. Statistical analysis to compare

light effects was conducted using SPSS 16.0 statistical software and significant differences

between the means of parameters were determined by t test (p value < 0.01). Because the

calculation of expansion and division rates are based on a single fit on the population

averages of 5 successive points, a single value is obtained for each time point, this

precludes further statistical analysis.

Acknowledgments




Policy Office (BELSPO). Shweta Kalve was funded by a training grant from the Department

of Science and Education of the Flemish Government. Joanna Fotschki was co-financed by

European Social Fund, Polish Government and Podlasie Voivodeship. The authors

acknowledge the financial support of the Research Foundation-Flanders (FWO-

Vlaanderen)


116

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Chapter 3

Crosstalk between Auxin Signaling and Osmotic

Stress Response in the Regulation of Leaf Growth

of Arabidopsis thaliana

Shweta Kalve1, Marios Nektarios Markakis1, Céline

Helsmoortel2, Frederik Coppens4, Geert Vandeweyer2,3, Kris

Laukens3, Manou Sommen2, Stephan Naulaers3, Kris

Vissenberg1, Els Prinsen1 and Gerrit T.S. Beemster1*


2Department of Medical Genetics, University of Antwerp, Antwerp, Belgium

3Biomedical Informatics Research Center Antwerp (Biomina), Department of

Mathematics and Computer Science, University of Antwerp, Belgium

4Department of Plant Systems Biology, VIB, Gent, Belgium


This chapter is to be submitted to The Plant Cell

Contribution of S.K.- Performed most experiments and wrote the manuscript

Crosstalk between auxin signaling and osmotic stress

125

Abstract

To understand the role of auxin in the response of leaf growth to water stress, we studied

the development of the first leaf pair of Arabidopsis thaliana seedlings growing in vitro,

using mannitol as an osmoticum and external application of NAA (α-Naphthalene acetic

acid) to change the auxin homeostasis. We observed that 25 mM mannitol reduced leaf size

by 25%, whereas 0.1 µM NAA increased it by 37%. Interestingly, leaves grown in

combination of NAA and mannitol were 30% smaller than untreated controls, showing that

exogenous supply of NAA increased the sensitivity to osmotic stress. Kinematic analysis

revealed that the decrease in leaf size induced by osmotic stress was mostly due to reduced

cell division rates. In contrast, increasing concentrations of NAA up to 0.4 µM increased

mature cell size by up to 40%, whereas cell numbers were maximal at 0.04 µM. DR5::GUS

analysis demonstrates that both NAA and mannitol enhanced the transcriptional response

to auxin. However, auxin measurements showed that NAA and mannitol had no significant

effect on the concentrations of endogenous free IAA, but additively reduced the levels of

conjugated IAA in the dividing cells. Transcriptome analysis of proliferating leaves by

mRNA sequencing demonstrated that 301 out of the 654 genes differentially expressed in

response to exogenous NAA were also affected by mannitol, confirming that auxin is an

integral part of the stress signal in young leaves. More detailed analysis showed that NAA

transcriptionally inhibits the expression of auxin biosynthesis genes, whereas osmotic

stress stimulates them. However, both stimuli induce auxin deconjugation and degradation

genes, explaining the reduced levels of conjugates. At the same time both treatments

increase auxin sensitivity by stimulating the expression of TIR1 and several ARFs, while

downregulating Aux/IAA genes, explaining the enhanced transcriptional response

demonstrated by the DR5 activity. Stimulation of cell division and expansion by NAA and

inhibition of the same processes by mannitol could be associated with specific subsets of

regulatory genes being regulated in response to both factors. In conclusion, our results

demonstrate that there is a crosstalk between auxin signaling and osmotic stress in the

regulation of leaf growth.


126

Introduction

Growth and development of plants are strongly affected by biotic and abiotic stresses, and

endogenous regulators, including phytohormones, mediate the response to these factors.

Among abiotic stresses, drought is one of the most prevalent factors, reducing crop

productivity worldwide (Ding et al., 2011; Vile et al., 2012). Hence, understanding plant

responses to drought is essential to improve crop yield in water deficit areas. In the last

decades significant progress has been made in unraveling the molecular mechanisms that

control the reaction of plants to drought (reviewed by Yamaguchi-Shinozaki and Shinozaki,

2006). Many genes were found to respond at the transcriptional level to drought

treatments (Huang et al., 2008). Most physiological studies on the effect of drought have

been conducted on mature tissue, and molecular analyses have typically been based on

whole shoot samples, consisting mainly of mature tissue. Consequently, knowledge on the

molecular mechanisms underlying plant growth responses to drought, which occur in the

plant’s growth zones that make up only a small part of the entire plant, is still very limited.

Leaf growth is driven by spatiotemporal regulation of two simultaneous processes; cell

division and expansion, which determine final leaf shape and size (Gonzalez et al., 2012;

Kalve et al., 2014). As roots are the sites where the plant perceives drought, the inhibition

of leaf growth is likely to be influenced by hormonal signaling from root to leaf (Peleg and

Blumwald, 2011). Therefore, it is important to understand how plant hormones control leaf

growth processes under stress conditions.

Proliferating and mature leaves have discrete responses to abiotic stresses, so the

mechanism affecting these tissues is different (Skirycz and Inze, 2010). Under osmotic

stress, ethylene and GAs (gibberellins) regulate cell proliferation in Arabidopsis leaves

(Achard et al., 2006; Claeys et al., 2012; Skirycz et al., 2011a; Skirycz et al., 2010), whereas

ABA is primarily associated with the response of mature tissues where it promotes

stomatal closure to reduce water loss by transpiration (Wilkinson and Davies, 2010).

Auxin regulates many plant growth and developmental processes including apical

dominance, cell growth, adventitious rooting, fruit and seed development (Leyser, 2010;


127

Perrot-Rechenmann, 2010; Sauer et al., 2013), vascular differentiation, leaf expansion,

shoot elongation, organogenesis (Reinhardt et al., 2000; Vanneste and Friml, 2009), root

gravitropism (Band et al., 2012), phyllotactic patterning and root hair formation

(Benjamins and Scheres, 2008; Krupinski and Jonsson, 2010). Curiously, its role in leaf

growth responses to water stress is still poorly understood.

Nevertheless there are several indications that auxin is involved in the response to

drought. Transcriptome studies in Arabidopsis thaliana showed that among 2000 drought

responsive genes, 95 genes were commonly regulated by drought and auxin (Huang et al.,

2008; Nemhauser et al., 2006). Moreover, some studies have shown the involvement of

auxin in water stress tolerance where overexpression of UGT74E2 in Arabidopsis (Tognetti

et al., 2010) and PIN3 in rice (Zhang et al., 2012) increased plant survival rates under

drought. Recently, Kim et al. (2013) found that the overexpression of YUCCA6, a member of

the YUCCA family of flavin monooxygenases in potato enhanced resistance to water stress

by reducing water loss. However, the leaves of overexpression lines showed a high auxin

phenotype i.e. narrow downward-curled leaves, and the tuber yield in transgenic plants

was also reduced. Similarly, an enhanced level of endogenous auxin in the activation-

tagged mutant yuc7-1D in Arabidopsis thaliana enhanced drought tolerance while the

leaves were narrow and curled (Lee et al., 2012). This illustrates that survival and growth

are two independent stress response parameters, as was pointed out by Skirycz et al.

(2011b), where to our knowledge the role of auxin in the growth response to osmotic

stress is not studied in detail so far.

To investigate the role of auxin in the leaf growth response to osmotic stress, we conducted

a set of experiments under relatively mild stress in order to avoid desiccation and dying of

plants, allowing to observe clear growth responses. To this end, we designed an

experimental setup where we grew Arabidopsis thaliana plants in vitro and induced

drought stress by adding mannitol as an osmoticum to the medium (Skirycz et al., 2010). At

the same time we altered the auxin status of the plants by adding auxin to the medium

(Ribnicky et al., 1996). This setup allowed us to perform (1) a detailed kinematic growth

analyses, (2) measurements of auxin concentrations in the developing leaves, (3) a


128

genome-wide transcriptome analysis by mRNA sequencing, and (4) DR5::GUS expression

studies to gain an integrated insight in the molecular and cellular response to osmotic

stress and altered auxin homeostasis. The results provide the first evidence for a crosstalk

mechanism between auxin metabolism and osmotic stress response in the growing tissues

of Arabidopsis thaliana.

Results

Crosstalk between osmotic stress response induced by mannitol and NAA

For analyzing leaf growth regulation in response to drought stress we first established

stress conditions that significantly inhibit growth, but do not lead to wilting or plant death.

Based on such a treatment it is possible to either ameliorate or exacerbate the effect of the

stress by additional perturbations. Therefore, we first determined the dose-response of

shoot and leaf growth to different mannitol concentrations used to vary the water

potentials in the medium. For this Arabidopsis thaliana seedlings were germinated and

grown in vitro on medium supplemented with concentrations of mannitol between 0 and

100 mM for 22 DAS (days after stratification) when the first leaf pair has reached maturity

(Beemster et al., 2005). By measuring the projected leaf area, we found that increasing

mannitol concentrations progressively reduce rosette area, reaching an approximate 80%

reduction at 100 mM (Supplemental Figure 1A). The effect of mannitol on the mature leaf

blade area of the first leaf pair closely reflected the response of the rosette area

(Supplemental Figure 1B). Moreover, the response was comparable between three

ecotypes (Supplemental Figures 1A and B), indicating that the effect is relatively

independent of the global genetic background.


129

Figure 1. The interaction of auxin and osmotic stress in the regulation of rosette growth in

Arabidopsis thaliana: (A) & (B) Images of rosette and leaf of Col-0 plants grown for 22 DAS in

Control, 25 mM Mannitol, 0.1 µM NAA, 0.1 µM NAA+25 mM mannitol; (C) Leaf series from seedlings

at 20 DAS (n=3-5); (D) Blade area of the first leaf pair of plants grown on medium supplemented

with different concentration of NAA under control and 25 mM mannitol treatment for 26 DAS; (E)

The reduction of leaf blade area in response to increasing concentrations of NAA in the medium; (F)

The number of epidermal cells; (G) Average area of abaxial epidermal cells in mature leaves grown

Control 25mM Mannitol 0.1µM NAA 25mM Mannitol

+0.1µM NAA

(B)

(A)

C1 C2 L1 L2 L3 L4 L5 L6 L7 L8

0

10

20

30

40

Lea

f b

lad

e are

a

(mm

2)

Leaf

Control

Mannitol

NAA

NAA+M

(C)

0

10

20

30

40ControlMannitol

(D)

Lea

f b

lad

e are

a

(m

m2)

-40

-20

0(E) %

Red

uctio

n

0

10000

20000

30000

0.01 0.1 1

(F)

0

Concentration of NAA (µM)

Cel

l n

um

ber

400

800

1200

1600

0.01 0.1 1

Concentration of NAA (µM)

(G)

0

Cell a

rea (µ

m2)


130

on increasing concentrations of NAA in presence or absence of 25 mM mannitol. Symbols denote

averages and error bars represent standard error (n=20-80 for leaf area and 3 for cellular analysis).

To study the effect of increasing auxin levels in the leaf, we added the synthetic auxin NAA

(α-Naphthalene acetic acid) to the growth medium. Low concentrations of NAA increased

leaf area to a maximum of approximately 37% at 0.1 μM NAA, whereas concentrations

above 0.1 μM had a negative effect (Figure 1D), and 1 μM completely inhibited the growth

of the leaves. These results show that whereas mannitol inhibits leaf growth, low

concentrations of NAA can increase it. This led to the question whether NAA addition could

overcome the effect of the low water potential of the medium.

To investigate this, we studied the interaction of auxin and osmotic stress on leaf growth by

determining the effect of 25 mM mannitol (because it gives a clear, but relatively mild

response), with different concentrations of NAA. Surprisingly, in addition to reducing leaf

size in absence of NAA, mannitol almost completely inhibited the stimulating effect of low

doses of NAA and increased the effect of supra-optimal doses (Figure 1D). As a

consequence, under increasing concentrations of NAA, the growth inhibitory effect of

mannitol progressively increased, roughly doubling the reduction in leaf size at a

concentration of 0.1 μM (Figure 1E). Thus by adding concentrations of up to 0.1 μM NAA,

we stimulate leaf growth on control medium, but at the same time increase the sensitivity

to low water potentials. This response was reproducible in three different ecotypes

(Supplemental Figure 1C and D) and occurred at the whole rosette scale (Figure 1A) and

individual leaf level (Figure 1B). More detailed analysis of the impact of the treatments on

the individual leaf positions showed that mannitol alone had little or no effect on the

number of leaves in the rosette but reduced their sizes at all positions. In contrast, 0.1 μM

NAA increased both their number and size, whereas in combination with mannitol it

reduced both number and size at all positions (Figure 1C).


131

Cellular basis of the leaf growth response to NAA and mannitol

Leaf area is determined by the number of cells produced by cell division and their size,

established by cell expansion (Gonzalez et al., 2012). To investigate the cellular basis of the

crosstalk between auxin and water stress, we measured the number of cells and their size

in mature leaves grown on different concentrations of NAA in presence or absence of 25

mM mannitol. Interestingly, both processes showed a different response. The cell number

responded in a similar fashion as the whole leaf area: NAA increased the number of cells up

to the concentration of 0.1 μM NAA, while higher concentrations reduced it. Mannitol

reduced cell number and prevented the increase in cell number at low auxin

concentrations (Figure 1F). In contrast, cell size increased progressively with increasing

NAA concentrations up to 0.4 μM (Figure 1G). Curiously, mannitol had no effect on cell size

in the presence of growth stimulating concentrations of NAA, but reduced cell size in

absence of NAA as well as in combination with the supra-optimal NAA concentration of 0.4

μM (Figure 1G). These results show that repressed cell division and expansion is

responsible for the growth inhibition by mannitol, whereas auxin differentially affects cell

division and cell expansion depending on its concentration. Moreover, the increased

sensitivity to mannitol in the presence of NAA can be attributed to enhanced sensitivity of

cell division.

Kinematic analysis of leaf growth

To study the effect of mannitol and auxin on cell division and expansion during leaf growth

in more detail, we performed a kinematic analysis (De Veylder et al., 2001). To this end, we

focused on leaves 1 and 2 of plants grown on control medium and medium supplemented

with 25 mM mannitol, 0.1 µM NAA, or the combination of the two. Leaves were harvested

daily from 8 to 29 days after stratification, allowing for measurements of leaf blade area,

size of abaxial epidermal cells, number of these cells per leaf, stomatal index and the rates

of division and expansion. Leaf blade area increased exponentially until around 13 DAS,

after which the expansion rate started to decrease gradually until maturity, which was

reached about 25 DAS in all the treatments (Figure 2A). The growth reduction due to


132

osmotic stress in comparison to the control was clearly observed from 11 DAS onwards,

whereas increased growth induced by NAA was observed from around 15 DAS (Figure 2A).

The combined treatment of NAA and mannitol reduced leaf size from the beginning of the

observations. This reduction was partially compensated by faster growth towards the end

of the growth period around 20 DAS (Figure 2A). Consistent with the reduced

developmental rate of the shoot as a whole (Figure 1C), this pattern suggests that the

development of leaves in this treatment was delayed. The calculated relative rates of leaf

expansion (RLER), a measure for average cell growth rates across the blade, indicate that

growth inhibition in mannitol treated leaves occurred between 9 and 12 DAS (Figure 2B).

The growth stimulation of NAA around 15 DAS was barely visible, illustrating that a very

small change in growth rate over a number of days can lead to significant effects on whole

leaf size. Similar to the effect of mannitol alone, the combination of NAA and mannitol

reduced the RLER until 12 DAS. However, the effect was stronger, demonstrating the

increased sensitivity to drought in the presence of NAA during this period. The increased

duration of leaf expansion in response to the combination of NAA and mannitol was

conspicuous around 20 DAS (Figure 2B).

At the cellular level, mature cell size was increased by 0.1 µM NAA and reduced by 25 mM

mannitol, whereas mannitol had no effect on cell size in the presence of NAA (Figures 1G

and 2E). The increased cell size in NAA treated leaves is not present in very young leaves,

but developed from around 16 DAS. Cells in mannitol grown leaves were also initially of

similar size as the control leaves, but started to grow slower from around 15 DAS. The cell

area of leaves treated with NAA and mannitol was smaller than control leaves from the

beginning of the observations, reflecting the developmental delay of the leaves, but due to

prolonged expansion they reach a mature size that is identical to that of the controls

(Figure 2E).

0.1 µM NAA caused an increase in the number of cells in mature leaves by 12% (p = 0.029;

Figures 1F and 2C), which can be attributed to a small increase in division rates between 8

and 9 DAS upon NAA treatment (Figure 2D). 25 mM mannitol reduced the number of cells

in mature leaves by 14% (p = 0.005; Figures 1F and 2C), which was related to an inhibition


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of cell division rates between 8 and 12 DAS by 5% (p = 0.000; Figure 2D). In contrast, the

strong reduction (35%) in the number of cells in mature leaves in response to the

combination of 0.1 µM NAA and 25 mM mannitol (p = 0.000; Figures 1F and 2C), was

already established at 8 DAS and further increased by a 9% reduction in cell division rates

between 8 and 12 DAS (p = 0.000). In contrast to cell expansion, there was no

compensation by increased duration of the cell division phase in these leaves (Figure 2B).

Figure 2. Kinematic analysis of the growth response to mannitol and NAA: (A) The evolution of

leaf blade area in function of time after sowing; (B) Relative leaf expansion rate (RLER); (C) The

number of epidermal cells on the abaxial side of the leaf; (D) Cell division rate (CDR); (E) Epidermal

cell area; (F) Stomatal index. Insets show the same data on a linear scale to show absolute

differences. Symbols denote averages and error bars represent the standard error (n = 8-10 for leaf

area and 3-5 for cellular analysis).

Even though the first stomata appeared concomitantly in control and NAA treated leaves,

the fraction of stomata was higher in the NAA treated leaves from around 12 DAS, resulting

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in an increase of 4% at maturity (p = 0.388; Figure 2F). Similarly, mannitol inhibited the

increase of the stomatal index from around 11 DAS, resulting in 11% reduction compared

to the controls (p = 0.032; Figure 2F). Stomatal appearance was severely delayed in the

combined treatment with NAA and mannitol, where first stomata emerged on 12 DAS. In

this treatment, the stomatal index was decreased (by more than 90%) in the early stages of

leaf development; this difference was reduced to 15% at maturity (p = 0.007; Figure 2F).

The results of kinematic analysis show that mannitol reduces leaf size by inhibiting both

cell division and cell expansion, whereas NAA has the opposite effect. NAA can overcome

the effect of mannitol on cell size by prolonging cell expansion, but it increases the

inhibition of cell division.

DR5::GUS expression

Having established that there is a crosstalk between osmotic stress; induced by mannitol

and externally applied NAA, we decided to study the effect of both treatments and their

combination on auxin signaling. To investigate this we first studied the effect of these

treatments on the inducibility of the auxin-signaling reporter DR5::β-glucuronidase (GUS)

(Ulmasov et al., 1997). To this end DR5::GUS plants were grown in vitro in the presence and

absence of 25 mM mannitol, 0.1 µM NAA, and a combination of mannitol and NAA and

harvested at 8 and 10 DAS, when the leaves are actively proliferating and most affected by

the treatments (Figure 2B). GUS activity at this stage was markedly higher in the

proliferating leaf 1 and 2 than in the nearly full grown cotyledons (Figure 3). As expected,

the activity of GUS was increased in response to NAA, suggesting that the externally applied

NAA is transported to the young leaves and induces the auxin response machinery.

Consistent with the hypothesized crosstalk between osmotic stress and auxin response,

mannitol induced an increased DR5::GUS activity compared to untreated controls (Figure

3). The highest activity occurred in the combination of NAA and mannitol, suggesting that

the effect of both treatments on the auxin response pathway is additive (Figure 3).


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Figure 3. DR5::GUS expression in proliferating leaves in response to mannitol and NAA:

Blue staining indicates activity of auxin response in 8- and 10-day-old plants grown under Control, 0.1

μM NAA, 25 mM mannitol, 0.1 μM NAA+25 mM mannitol containing medium. Scale bar =1 mm.

Endogenous IAA concentrations

The endogenous concentration of IAA in a plant is the result of a strict fine-tuning of the

homeostasis. It is therefore not uncommon that endogenous concentrations are altered

after exogenous feeding. To determine if the increased activity of DR5 in response to

osmotic stress and externally applied NAA was due to increased auxin levels, we measured

endogenous auxin concentrations in the developing leaves. Leaf 1 and 2 were harvested

from 10 DAS, when they were proliferating, until 22 DAS, when they became mature

(Figure 2B). In accordance with the DR5::GUS staining that was primarily found in

proliferating young leaves (Figure 3), the concentrations of free (active) and conjugated

IAA were highest during the earliest stages of leaf development, and gradually decreased

until maturity. Surprisingly, none of the treatments had a significant effect on

concentrations of free IAA, although the combination of NAA and mannitol had a somewhat

decreasing effect at 10 and 12 DAS and a slight induction at 16 and 18 DAS, reflecting the

delayed development induced by this treatment (Figure 4A). In contrast, the levels of

conjugated IAA were strongly affected by all treatments. Externally supplemented NAA

reduced the level by 26% on 10 DAS (p = 0.227), whereas at a later stage (at 20 DAS) it was

reduced by around 50%. Mannitol decreased the amount of conjugated IAA by 46% (p =


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0.028) on 10 DAS while the reduction was gradually decreased to 3-9% at maturity (Figure

4B). Interestingly, the combination of NAA and mannitol reduced the concentration of

conjugated IAA to 80% (p = 0.002) on 10 DAS and 50% (p = 0.028) on 12 DAS, whereas

from 14 DAS onwards the reduction was around 15-25% (Figure 4B). These results show

that in contrast to increased DR5::GUS activity, free IAA levels are maintained at an almost

constant level, whereas the pool of conjugated IAA is depleted by NAA, mannitol and their

combination. These results demonstrate that both NAA and mannitol affect auxin

homeostasis. The apparent contradiction between DR5 activity and IAA levels indicates

that these treatments either affect downstream signaling by other active auxin molecules,

or that they affect the sensitivity to free IAA.

Figure 4. The effect of NAA and mannitol on levels of IAA throughout the leaf development:

Leaves 1 and 2 were dissected from plants grown on control medium and medium supplemented

with 25 mM mannitol, 0.1 μM NAA, 0.1 μM NAA+25 mM mannitol from 10 till 22DAS

(A) Amount of free IAA; (B) Amount of conjugated IAA. Symbols represent averages and error bars

represent the standard error (n=4-6).

Transcriptome analysis

To further understand the nature of the crosstalk between auxin and osmotic stress on the

regulation of auxin homeostasis and on downstream signaling that leads to the observed

growth response, we performed a genome wide transcriptome analysis by means of mRNA

sequencing. For this, we extracted mRNA from the first leaf pair of plants grown on

medium containing 25 mM mannitol, 0.1 µM NAA and the combination of NAA and

mannitol at 10 DAS. This time point was chosen because it is the earliest moment which is

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feasible to dissect proliferating leaves and the treatments exert their main effect during this

phase (Figure 2B).

After mapping the reads, normalizing the data between samples and statistical analysis, a

total of 2292 genes were differentially expressed in response to at least one treatment

(FDR corrected- p < 0.05 and log2 fold change > 0.5). When plants were exposed to 0.1 µM

NAA the expression levels of 654 genes were significantly affected. In plants treated with

25 mM of mannitol 922 differentially expressed genes were found. Consistent with the

additive effect on DR5::GUS activity (Figure 3) and on the levels of conjugated IAA (Figure

4B), the combination of mannitol and NAA resulted in a more than twofold increase in the

number of differentially expressed genes, i.e. to 2181 (Figure 5A, Supplemental Table S1).

The overlap between the NAA and mannitol treatments confirms the hypothesis that there

is a crosstalk between their respective response pathways. Around half (301 out of 654) of

the genes that were differentially expressed in response to the auxin treatment, were also

affected by the osmotic stress induced by mannitol (Figure 5A, Supplemental Table S1).

Almost 90% of the genes that were differentially expressed in the NAA and mannitol

treated leaves were also affected by the combined treatment, whereas only few genes (50

out of 654 and 49 out of 922 genes for NAA and mannitol, respectively) were specific for

NAA or mannitol treatment. Together with the large number of genes affected by the

combination of the treatments this clearly indicates that auxin and osmotic stress have a

synergistic effect on gene expression.

To analyze the nature of the changes induced by the treatments in more detail, we first

performed a support tree analysis on the samples based on the expression values of the

significantly expressed genes (FDR corrected- p < 0.05 and log2 fold change > 0.5). The

resulting support tree demonstrated the reproducibility of the treatments as the samples

for all treatments grouped together. The large overlap between the effects of mannitol and

NAA were reflected by these two treatments being more similar to each other than to the

control, whereas due to their synergistic effect, the amplification of the transcriptional

response makes the combination treatment more different from the controls than both

single treatments (Figure 5B).


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Figure 5. Transcriptome analysis of the effect of osmotic stress and NAA on proliferating

leaves: Leaves 1 and 2 were dissected from plants grown on control medium and medium

supplemented with 25 mM mannitol, 0.1 μM NAA, 0.1 μM NAA+25 mM mannitol at 10 DAS and

subjected to next generation sequencing of mRNA.

(A) Overlap between genes induced by mannitol, NAA and NAA+mannitol. Values indicated in Venn

diagram represent the number of genes induced by each treatment compared to the controls.

Numbers accompanied by up and down arrows show up and downregulation of genes, respectively.

Transcripts were considered differentially expressed if the log2 of fold change > 0.5 and FDR-

corrected p value < 0.05 (C=Control, M-Mannitol, N=NAA, NM=NAA+Mannitol).

(B) Support tree analysis (Graur and Li, 2000) of the expression data of 2292 genes with a

significant differential expression, comparing individual samples of all the treatments. The level of


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support for each branch of the tree is 90-100%, which indicates the confidence for each branch. The

treatments are indicated below the tree and numbers represent the replicates for each treatment.

(C) Clustering of gene expression profiles by QT-Clust analysis (Heyer et al., 1999) of the expression

profile of 2292 significantly modulated genes (Pearson correlation measure; cluster diameter=0.5,

minimum cluster size= 25). Data are expressed as normalized expression values. Clusters elucidate

the major patterns of the gene dataset of four treatments. Treatments are shown in colored bars

and cluster number and size are indicated.

We next investigated the major expression profiles at the gene level induced by the three

treatments by means of a Quality Threshold (QT) Clustering (Heyer et al., 1999) of all 2292

differentially expressed genes. This resulted in 6 clusters, each containing 26 or more

genes that shared the similar pattern and one cluster (Cluster 7) comprising the remaining

34 genes (Figure 5C). All these clusters share some remarkable characteristics with regards

to the effect of the treatments:

1. NAA, mannitol and their combination affect the expression of all differentially

expressed genes in the same direction.

2. Clusters 1, 4 and 5 represent genes that are more sensitive to the osmotic stress,

whereas clusters 2, 3 and 6 encompass genes that are most sensitive to the auxin

treatment.

3. The effect of the combined treatment is stronger (Clusters 1, 2, 3, 4 and 5, Cluster 6

being an exception) than the individual treatments.

Gene enrichment

To better understand the link between transcriptional changes and the observed growth

phenotypes, we next wanted to know which biological processes are regulated by auxin,

osmotic stress and their combination in proliferating leaves. For this we performed a gene

enrichment analysis using PageMan on the genes that were up or downregulated by each of

the treatments. The results of this analysis have some striking features (Figure 6):

1. Over and underrepresentation were opposite among up and downregulated genes for

most categories.


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2. Reflecting the amplitude of the effect on the number of differentially expressed genes

(Figure 5A) and gene expression profile (Figure 5C), the combination treatment

induced the largest number of over or under represented classes among both the up

and downregulated genes.

3. Minor changes were observed in NAA treated samples which include

overrepresentation among downregulated genes of transcripts related to major and

minor carbohydrate metabolism, cell wall degradation and modification, cellulose

synthesis, aliphatic and indole glucosinolate synthesis. Moreover, genes related to the

metabolism of auxin and brassinosteroid metabolism were overrepresented in up and

downregulated genes.

4. Biological pathways that were overrepresented among genes upregulated by mannitol

and the combination of NAA and mannitol treatments include glycolysis, mitochondrial

electron transport, hemicellulose and pectin synthesis, tryptophan and indole

glucosinolate synthesis, receptor and MAP kinase signaling and ethylene metabolism.

Pathways that were overrepresented among downregulated genes include

photosynthesis machinery, minor carbohydrate metabolism, cellulose synthesis, cell

wall proteins, cell wall degradation and modification, aliphatic glucosinolates and the

metabolism of auxin, brassinosteroids, ethylene and gibberellins.


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Figure 6. PageMan overrepresentation analysis of the effect of 25 mM mannitol, 0.1 μM NAA and its

combination on proliferating leaves. Significantly enriched or depleted functional groups among

differentially expressed genes are represented in blue or red, respectively. The extend and direction

of induced changes are color-coded by heat-map.


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Auxin biosynthesis pathway

Indole-3-acetic acid (IAA) is the primary active auxin molecule in most plants and its levels

result from the balance between local synthesis, degradation, (de-) conjugation and net

transport. To understand the molecular basis of the crosstalk between externally applied

NAA and osmotic stress, we studied the transcriptional changes of genes related to auxin

homeostasis and signaling in more detail.

IAA is synthesized by two independent auxin biosynthesis pathways, the tryptophan (Trp)-

dependent and Trp-independent pathway. Although neither of these pathways is

completely characterized, many players have been identified (Figure 7A; Korasick et al.,

2013; Mano and Nemoto, 2012). The Trp-independent pathway diverges from the L-Trp

biosynthetic pathway at the level of indole and/or indole-3-glycerol phosphate (Ouyang et

al., 2000). In spite of having biochemical evidence, little is known about the metabolic

intermediates and genes involved in the Trp-independent pathway (Ostin et al., 1999).

Different Trp-dependent auxin biosynthesis pathways have been proposed, which includes

three major pathways in plants: 1. the indole-3-acetaldoxime (IAOx) pathway, 2. the indole-

3-acetamide (IAM) pathway and 3. the indole-3-pyruvic acid (IPA) pathway (Figure 7A). To

study the influence of NAA and osmotic stress on auxin production, we created a map of the

auxin biosynthesis pathway, allowing it to display the effect of NAA, mannitol and their

combination on the expression patterns of genes involved in biosynthesis. The tryptophan

biosynthesis transcripts, TSA and TSB, were significantly upregulated by mannitol, more so

by the NAA+mannitol treatment, whereas no change occurred in response to NAA. The

IAOx pathway is largely restricted to the brassicaceae family (Sugawara et al., 2009) and

converts L-Tryptophan into active IAA via Indole-3-actetaldoximine, either directly or via

Indole Glucosinolates to Indole-3-acetonitrille. The transcripts for the enzymes in this

pathway largely show the same response, a significant upregulation in response to

mannitol that was amplified by the combination with NAA. NAA alone, in contrast,

appeared to downregulate this pathway, but not all the changes were significant.

Consistently, upregulation of the glucosinolate synthesis in response to mannitol and

mannitol in combination with NAA was also detected in the overrepresentation analysis


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(Figure 6). Genes related to the IAM pathway were not significantly changed in any of the

treatments.

Figure 7 (A). The effect of NAA and mannitol on the expression of genes encoding the auxin

metabolism and response mechanism:

Auxin biosynthesis pathway: Heat-map representation of genes involved in auxin biosynthesis.

Red and blue shows down and upregulated genes, respectively under different treatments

(C=Control, M-Mannitol, N=NAA, NM=NAA+Mannitol). Data are expressed as the log2 of fold change

and asterisks indicate significance (t test, p < 0.05). Pathways for which enzymes have been

identified are shown in solid arrows, the pathways that have not been identified are in dashed

arrows and ‘?’ indicates an unknown pathway. Absence of heat-map for certain genes denotes the

absence of significant differences.


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The expression of TAA1, the gene responsible for the first step in the IPA pathway, was

significantly increased by both NAA and the combination of NAA and mannitol. The second

step in this pathway is mediated by the family of YUCCA genes, of which three were found

to be significantly changed. The expression changes of these three genes were quite

different; YUC2 was upregulated in response to NAA and YUC5 was downregulated in

response to the combination of NAA and mannitol, whereas YUC8 was upregulated in NAA

and mannitol treatment.

Another pathway from IPA to IAA was suggested to run via indole-3-acetaldehyde (IAAld)

by ARABIDOPSIS ALDEHYDE OXIDASE1 (AAO1) (Mashiguchi et al., 2011; Sekimoto et al.,

1998; Woodward and Bartel, 2005). Our results showed significant upregulation of AAO1

by mannitol alone and in combination with NAA, whereas no change occurred in response

to NAA (Figure 7A).

Overall this pathway analysis shows a pronounced difference in the effect of NAA and

osmotic stress. Osmotic stress upregulates almost all IAA biosynthetic pathways; whereas

NAA inhibits the IAN pathway while activating the IPA pathway, so that the net effect is not

clear. It is interesting to note that the effect of NAA generally enhances the effect of

mannitol even in the case that the single treatments have opposite effects.

Auxin conjugation and degradation

The active free IAA is only a small fraction of the total auxin pool in the plant, as most IAA is

present in the form of a multitude of conjugates, which was confirmed by our studies

(Figure 4A and B). The conversion between the two forms is regulated by enzymatic

reactions and many of the genes encoding the related enzymes have been identified. Auxin

conjugates play a major role in storage, transport and compartmentalization and can

provide free IAA upon hydrolysis or β-oxidation (Cohen and Bandurski, 1982). We

summarized current knowledge regarding auxin conjugation in a pathway map (Figure

7B). IAA conjugation occurs in three ways: amide-linked to amino acids, ester-linked to


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sugars, and amide-linked to peptides and proteins (Ludwig-Muller, 2011; Woodward and

Bartel, 2005).

Figure 7 (B). The auxin conjugation pathway: Heat-map representation of genes involved in

auxin conjugation. Red and blue shows down and upregulated genes, respectively under different

treatments (C=Control, M-Mannitol, N=NAA, NM=NAA+Mannitol). Data are expressed as the log2 of

fold change and asterisks indicate significance (t test, p < 0.05). Pathways for which enzymes have

been identified are shown in solid arrows and the pathways that have not been identified are in

dashed arrows. Absence of heat-map for genes denotes the absence of significant differences.

Group II of the GRETCHEN HAGEN3 (GH3) family of acyl amido synthetases plays an

important role in conjugating IAA to amino acids (Westfall et al., 2010). Curiously, two of

its isozymes respond in opposite ways to NAA, mannitol and their combination, so it is

unclear what the net effect would be. Inversely, various enzymes such as ILR1, ILR1-LIKE1

(ILL1), ILL2, ILL3, ILL5, and IAR3 hydrolyze amino acid conjugates back to free IAA. Three


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of the genes encoding these enzymes were significantly changed in our studies. IAR3 and

ILL2, which convert IAA-alanine into free IAA (Bitto et al., 2009; Korasick et al., 2013) are

upregulated by mannitol, NAA and to a larger extend by their combination, providing an

explanation for the reduced pool of conjugated auxin (Figure 4B). No significant change

was found in ILR1, an amidohydrolase that releases active IAA from IAA-leucine (Bartel

and Fink, 1995). Whereas, the expression of ILR2 that is essential to modulate metal

transport and auxin conjugate metabolism (Magidin et al., 2003), was downregulated in all

treatments. Other amino acid conjugates, IAA-aspartate and glutamate form intermediates

in the IAA degradation pathway and IAA-tryptophan is important for inhibition of auxin

action (Korasick et al., 2013; Ludwig-Muller, 2011). GH3.5 is the only transcript for these

reactions that was significantly changed in our transcriptome data, being upregulated by

NAA (albeit not significantly) and osmotic stress and more so by the combination,

suggesting increased rates of IAA degradation.

IAA-sugar conjugates are responsible for auxin storage and IAA inactivation. UGT84B1 and

UGT74D1 convert IAA into IAA-sugar conjugate while UGT74D1 inactivates IAA by its

oxidization to 2-oxindole-3-acetic acid (OxIAA) (Tanaka et al., 2014). Finally, IAA can also

be conjugated to its methyl ester form by IAMT1 in Arabidopsis thaliana (Qin et al., 2005).

Curiously, none of these genes were significantly changed in our transcriptome data in any

of the treatments.

In addition to IAA-amino acid and sugar conjugates, IAA-peptide conjugates have also been

identified but the enzymes that form and hydrolyse IAA-peptides is still under investigation

(Ludwig-Muller, 2011; Seidel et al., 2006).

Indole-3-butyric acid (IBA) is a second auxin molecule in plants that may have auxin

activity by itself (Ludwig-Muller, 2000), or by conversion into free IAA upon β-oxidation by

peroxisomal enzymes like IBR1, IBR3, IBR10 and ECH2 (Strader et al., 2010; Strader et al.,

2011). Out of all these genes only IBR3 was significantly altered in our studies. The levels of

IBR3 were upregulated by all three treatments, albeit not significantly by NAA, and most

strongly by the combination of NAA and mannitol, suggesting an increase conversion


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towards IAA. IBA also gets converted to an alanine conjugate by GH3 and deconjugated by

wheat hydrolase TaIAR3 (Campanella et al., 2004). The TaIAR3 protein has high specificity

for the hydrolysis of indole-3-butyric acid conjugates with alanine, unlike its orthologue

Arabidopsis IAR3, which has affinity for IAA-alanine. UGT74D1 and UGT74E2 encoding UDP

glucosyltransferase activity, convert IBA to the inactive IBA-glucose conjugate (Jin et al.,

2013; Ross et al., 2001). UGT74E2 was upregulated by all treatments, but only significantly

in response to osmotic stress in the presence of NAA.

In conclusion, the expression of genes related to auxin conjugation indicates that NAA,

mannitol and the combination of NAA and mannitol stimulate both auxin deconjugation

and degradation, which can be reconciled with the depletion of conjugated IAA and

relatively stable free IAA contents (Figure 4).

Auxin transport

The spatial distribution of auxin across tissues and presumably between organs is directed

by the activity of auxin influx and efflux transporters (Petrasek and Friml, 2009;

Zazimalova et al., 2010) (Figure 7C). The expression of the auxin influx carrier AUX1

(Swarup et al., 2001) was enhanced only in the NAA treatment. The expression of two

members of the LAX family (LIKE AUX1) LAX2 and LAX3, (Peret et al., 2012; Swarup et al.,

2008), was slightly, but not significantly upregulated by NAA and mannitol. Curiously, the

combination of the two treatments significantly downregulated LAX2, while the expression

of LAX3 was induced. On the other hand, expression of auxin efflux protein PIN7 (PIN-

FORMED) (Friml et al., 2003) was enhanced only under osmotic stress whereas NAA and

the combination of both had no significant effect. Curiously, the expression of the other

seven PIN genes (Krecek et al., 2009) was not altered significantly by any of the treatments

(Figure 7C). The expression of AXR4 that encodes for a protein that is essential for the polar

trafficking of auxin influx protein AUX1 to the plasma membrane (Dharmasiri et al., 2006),

increased under mannitol and in combination of NAA and mannitol, whereas a small, but

no significant change in the same direction was found after NAA treatment.


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Taken together, these results suggest that NAA and osmotic stress enhance both auxin in-

and efflux.

Figure 7 (C). The auxin transport and signaling pathway: Heat-map representation of genes

involved in auxin signaling. Red and blue shows down and upregulated genes, respectively under

different treatments (C=Control, M-Mannitol, N=NAA, NM=NAA+Mannitol). Data are expressed as

the log2 of fold change and asterisks indicate significance (t test, p < 0.05). Absence of heat-map for

genes denotes the absence of significant differences.

Auxin signaling

Over the last decades, auxin perception and gene regulation has been extensively

characterized. We incorporated this knowledge into the pathway map of auxin signaling

(Figure 7C). The SCFTIR1 ubiquitin ligase complex is the central regulator of auxin signaling,

which mediates the proteolytic degradation of the Aux/IAA family of transcriptional

regulators (Chapman and Estelle, 2009; Hayashi, 2012). In the presence of low auxin,

Aux/IAA (AUXIN/INDOLE-3-ACETIC ACID) proteins form dimers with ARF (AUXIN

RESPONSE FACTOR) transcription factors, inhibiting the transcriptional activation of


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auxin-responsive genes. At high concentrations, auxin binds to Aux/IAA, which stimulates

ubiquitination by the SCFTIR1 complex targeting it for degradation by the 26S proteasome,

which in turn releases ARF transcription factors, leading to the transcriptional activation of

auxin responsive genes (Woodward and Bartel, 2005). Our transcriptome analysis showed

that the expression of TIR1 was upregulated by NAA, mannitol and their combination. With

the exception of IAA 20, 26 and 29, most IAA genes were downregulated by the three

treatments, which should lower the level of these transcriptional inhibitors and stimulate

ARF activity. In addition, the expressions of significantly affected ARFs, ARF4, ARF6 and

ARF18 were increased in response to NAA, whereas ARF6 was significantly upregulated by

the osmotic stress and NAA and mannitol combination.

Taken together, these results show that both NAA and osmotic stress stimulate auxin-

regulated gene expression at multiple levels, which is consistent with the increased

DR5::GUS activity and the strong overlap between the differentially expressed genes

(Figures 3 and 5A).

Cell cycle regulation

To understand the molecular basis for the changes in cell division, we analyzed the

expression of known cell cycle genes (de Almeida Engler et al., 2009; de Jager et al., 2009;

Vandepoele et al., 2002). Consistent with altered cell division rates playing a crucial role in

the growth response, 18 out of 93 cell cycle genes were significantly affected by at least one

of the treatments (Supplemental Table S2). Despite having opposite effects on cell division,

but similar to the overall gene expression patterns (Figure 5C), NAA, mannitol and their

combination affected the expression of nearly all cell cycle genes in the same direction.

Therefore the net effect on cell division rates must be related to the relative strength of the

effects exerted by these treatments on the various classes of regulators. A notable

exception to this general picture is several B and a D-type cyclins, which are upregulated by

NAA and mannitol, but downregulated by their combination (Supplemental Table S2). This

may explain the strong inhibition of cell division rates by the latter treatment.


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To get a global picture of how altered cell cycle gene expression relates to the opposite

effects of NAA and mannitol on cell division rates, the number of significantly affected

genes in each class is most instructive:

- The expression of the growth promoting CDK activating cyclin CYCA2;1 (Vanneste et al.,

2011) was strongly reduced by mannitol (and the combination treatment), but was little

affected by NAA.

- The expression of growth promoting CYCB (Doerner et al., 1996) and CYCD family

members (Cockcroft et al., 2000) was more upregulated by NAA than by mannitol.

- The expression of genes CDC27B and CCS52B encoding components of the anaphase

promoting complex (APC) (Blilou et al., 2002; Tarayre et al., 2004) was enhanced under

NAA treatment, whereas no significant change in mannitol and combination of NAA and

mannitol was found.

- ORC2 and MCM5 genes act downstream of CDK and its interactors in the control of DNA

duplication (de Jager et al., 2009). Consistent with the inhibited cell division activity they

were downregulated in mannitol and in the combination treatment.

- E2Fc, a regulator for the balance between cell division and endoreplication (del Pozo et

al., 2006) was upregulated by all treatments, but most strongly in the NAA treatment,

predicting an increased endoreduplication. To test this possibility, we performed

flowcytometry on mature leaves. In complete agreement with the prediction, we found that

NAA, mannitol and the combination of the two enhanced endoreduplication, with NAA

alone exerting the strongest effect (Figure 8).

- CDK-activating kinases CDKD and CDKF were upregulated by all treatments. This is

opposite to what is expected in treatments that inhibit cell division rate and may therefore

represent a compensation mechanism. Inversely, the expression of cell cycle inhibitors

KRP2 and KRP4 (De Veylder et al., 2001) were also upregulated to similar extends in all

treatments, which would induce a counteracting effect.


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Figure 8. Ploidy distribution measurement of the effect of osmotic stress and NAA on mature

leaves after 25 DAS: Percentage of 2C, 4C, 8C, 16C and 32C nuclei. Error bars represent SE (n=4).

Regulation of cell expansion

The samples for transcriptome analysis were harvested on 10 DAS when RLER was

inhibited by mannitol and the combination of NAA and mannitol, while little or no effect

was exerted by NAA alone (Figure 2B). The expression of genes related to cell expansion

was mostly affected in the same direction by NAA, mannitol and their combination, so that

differential responses to these treatments may be due to relative effects.

The majority of genes related to the synthesis of structural cell wall components, cellulose

and hemicellulose, as well as structural cell wall proteins were downregulated in all

treatments, with higher numbers and fold changes in response to mannitol alone or in

combination with NAA, than in response to NAA (Supplemental Table S3), reflecting the

inhibition of cell growth by the mannitol treatments. In contrast, cell wall precursor

synthesis genes showed both up and downregulation.

A notable exception to the general pattern were the hydroxyproline-rich rich glycoproteins

(HRGPs) that were nearly all upregulated by mannitol alone and in combination with NAA,

but downregulated by NAA alone, implicating them as a possible factor for the differential

effect of the treatments.

Cell wall modifying enzyme families showed a complex picture (Supplemental Table S3):

Control Mannitol NAA NAA+M0

20

40

60

80

100

% o

f n

ucl

ei 2C

4C

8C

16C

32C


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- Transcripts encoding cell wall degrading enzymes were overall downregulated by all

three treatments, although specific genes showed the opposite effect. Among the cell

wall modifying enzymes both up and downregulation is also observed, but several

(including EXLB3, ATXTH18, ATXTH19, ATEXPA16) in contrast to the global picture,

show opposite effects in response to NAA and mannitol.

- Interestingly, two genes related to pectin synthesis were highly upregulated in

response to mannitol alone or in combination with NAA, while pectin esterases were

also primarily upregulated, with some specific genes showing the opposite in response

to NAA (AT3G09405 and AT4G02330).

Overall these results indicate global changes in cell wall synthesis and the regulation of its

extensibility, which broadly correlate with the observed differences in cell growth rates.

Regulation of redox metabolism

Drought induces production of reactive oxygen species (ROS) which lead to oxidative

damage and cell death in plants (reviewed by Miller et al., 2010). Moreover, ROS

homeostasis during stress greatly depends on the balance between the production of ROS

and ROS scavenging enzymes which creates a baseline from which ROS spears function as a

signal in different cellular processes (Mittler et al., 2004). Therefore, ROS are important

signaling molecules that regulate growth and development under drought stress. To

investigate the involvement of auxin in altering redox metabolism under osmotic stress, we

studied the expression of transcripts related to major antioxidant enzymes. Few significant

genes were observed in mannitol and NAA treatment which were majorly up and

downregulated, respectively (Supplemental Table S4). Interestingly, we found that most of

the important genes belong to superoxide dismutase (SOD), ascorbate peroxidase (APX),

glutathione peroxidase (GPX), ascorbate oxidase (AO), glutathione-S-transferase (GST) and

peroxidase (POX) family were significantly upregulated under combination treatment of

NAA and mannitol (Supplemental Table S4). Our results clearly suggest that auxin has an

influence on redox status under osmotic stress.


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Discussion

Auxin plays a central role in plant growth and development under standard growth

conditions (Benjamins and Scheres, 2008; Sauer et al., 2013). Based on the observed

correlation between auxin and drought induced gene-expression (Huang et al., 2008), we

hypothesized that auxin may also play an important role in the regulation of the growth

response to osmotic stress. Therefore, we performed a detailed study of the interaction

between auxin signaling and osmotic stress in growing Arabidopsis leaves. Our results

prove that there is clearly a crosstalk between the response to osmotic stress

(experimentally induced by adding mannitol) and altering auxin homeostasis (by applying

NAA to the growth medium).

The dose-response experiments in combination with DR5::GUS expression studies and a

genome wide transcriptome analysis provide the physiological basis for the nature of this

crosstalk. Consistent with earlier findings (Collett et al., 2000; Polak et al., 2011) we show

that a modest increase of auxin levels increases plant growth, but that supra-optimal levels

will inhibit it. Osmotic stress increases sensitivity to auxin, stimulating the auxin signaling

cascade as evidenced by the high overlap between auxin and osmotic stress induced genes.

This means that leaves grown under osmotic stress behave as if they have supra-optimal

auxin levels. Increasing the auxin levels even further, by adding NAA to the medium, will

therefore increase the effect of the osmotic stress. Thus, the dose of 0.1 µM NAA studied

here in detail, by itself increased auxin levels to optimal for stimulating leaf growth,

whereas in combination with 25 mM of mannitol it pushes plants further into the supra-

optimal region of the response curve, making their growth effectively hypersensitive to

drought.

This crosstalk between auxin and drought may be more general as it was demonstrated

recently that the exogenous addition of auxin increases the sensitivity of seed germination

to salinity stress (Park et al., 2011).

Two recent studies demonstrated that overexpressing YUCCA genes improved drought

tolerance of Arabidopsis and potato plants, measured as plant survival rates (Kim et al.,


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2013; Lee et al., 2012). In both studies the enhanced expression of auxin biosynthesis genes

increased drought tolerance, but reduced plant growth. The increased drought tolerance

was related to the induction of specific drought response genes in mature tissues (Lee et al.,

2012). In our study, we also found the upregulation of the well-known stress induced

secondary metabolites, indole glucosinolates in proliferating leaves (Figure 6), which has

been reported to play a role in osmotic adjustments under water stress (del Carmen

Martínez-Ballesta et al., 2013; Lopez-Berenguer et al., 2008; Schreiner et al., 2009).

Additionally, our study shows that there is a crosstalk between auxin and ROS under

osmotic stress that ultimately affects leaf growth. We found that the expression of

antioxidant enzymes increased under osmotic stress and was more enhanced in the

presence of NAA under stress. Consistently, previous study showed that auxin modulates

ROS homeostasis by inducing ROS detoxification enzymes, glutathione S-transferases (GSH)

and quinone reductases (Laskowaski et al., 2002). Moreover, many studies suggested that

mutual interaction between auxin and ROS under environmental stresses affect plant

growth (reviewed by Tognetti et al., 2012). This indicates that the elevation of antioxidant

capacity, which protects the plant from oxidative damage and thereby enhances drought

tolerance (de Campos et al., 2011; Kim et al., 2013; Nakabayashi et al., 2014), maybe under

auxin control and it can explains the improved survival in plants with an elevated auxin

production (Kim et al., 2013; Lee et al., 2012).

The cellular basis of the growth response to auxin and osmotic stress

Auxin controls growth by regulating the cellular growth processes (reviewed by Perrot-

Rechenmann, 2010). Indeed, we found that exogenous supply of NAA affected cell division

and expansion in a concentration dependent manner. Interestingly, our data show that

both processes have a distinct response profile, with cell expansion being stimulated up to

concentrations of 0.4 μM, whereas cell division shows an optimum at a 10-fold lower

concentration (Figure 1F and G). In contrast, our data confirm earlier findings (Skirycz et

al., 2010; 2011a) that osmotic stress reduced leaf growth by reducing cell number and size.

Moreover, the reduced stomatal index in response to mannitol showed the effect on

meristemoid activity allowing for morphological adjustment to reduce water loss (Skirycz


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et al., 2010). Remarkably, NAA by itself or in combination with mannitol did not affect the

stomatal index, suggesting that meristemoid activity under osmotic stress is under control

of an auxin independent regulatory pathway.

Osmotic stress affects auxin homeostasis and signaling

Based on the auxin response curves of leaf size in presence or absence of mannitol we

hypothesized a role for auxin signaling upstream of the growth response in dividing and

expanding leaf cells. The increased activity of the DR5::GUS response marker (Figure 3) and

the large overlap between genome-wide expression changes induced by NAA and mannitol

(Figure 5), demonstrate that a large part of the drought signaling is mediated by the auxin

signal.

Our measurements of IAA levels, however, complicate the interpretation. In contrast to

what could be expected, the concentrations of free IAA are not upregulated, but unaffected

or possibly even downregulated by the combination of mannitol and NAA. Moreover, the

levels of conjugated IAA, constituting the bulk of the auxin pool, are downregulated by both

NAA and mannitol in an additive way (Figure 4). This implies that 1. there is a major effect

of both treatments on auxin homeostasis and 2. the increased auxin response is not directly

related to levels of IAA. Detailed analysis of auxin metabolism and response mediators

provided us with an explanation for this conundrum.

Our data show that osmotic stress upregulates almost the entire IAA biosynthetic pathway.

However, both auxin deconjugation and degradation are also upregulated, which can be

reconciled with the depletion of conjugated IAA and relatively stable free IAA contents. The

effect of NAA on IAA synthesis is less clear, but it also stimulates the deconjugation and

degradation. Together this means that although auxin homeostasis is significantly affected

the net effects of osmotic stress and NAA on free active IAA are small, implying that the

increased response may be related to increased sensitivity to the auxin levels or increased

signaling. Indeed, we found that all three treatments increased the level of the TIR1

receptor and reduced the expression of the majority of Aux/IAA inhibitors of Auxin

Responsive transcription Factors (ARF), three of which were upregulated. Together, these


156

changes should comprise a strong increase in auxin sensitivity, consistent with increased

gene expression.

Many aspects of this global picture can be corroborated with earlier findings:

- Similar to our observations Ribnicky et al. (1996) found that exogenous supply of auxin

has limited effects on the endogenous IAA concentration.

- We found an upregulation of the biosynthesis of the precursor for IAA biosynthesis,

tryptophan (Tzin and Galili, 2010; Zhao, 2012) in response to osmotic stress (Figure 7A),

which corresponds with its enhanced production under various stresses (Nikiforova et al.,

2003; Zhao et al., 1998). Mild osmotic stress increased auxin biosynthesis mainly via IAOx,

the specific pathway for brassicaceae (Sugawara et al., 2009) through the NIT2 and AAO1

pathway (Woodward and Bartel, 2005). Expression of NIT2 was also reported to increase

under salt stress in Arabidopsis thaliana (Fang and Yang, 2002).

- It has also been shown before that stresses induce auxin deconjugation (Kinoshita et al.,

2012; Ludwig-Muller, 2011). Park et al. (2007) showed that overproduction of

WES1/GH3.5, a stress inducible IAA-Asp conjugating enzyme, caused growth reduction and

altered leaf shape whereas it enhanced stress tolerance.

- Finally, a global analysis of stress responsive genes showed that the expression of TIR

increased under drought and osmotic stress (Kilian et al., 2007).

Thus it appears that fractions of the response mechanism we have deciphered here are

supported by previous findings. Some of these responses demonstrate their functional

significance in terms of increased tolerance to drought and related stresses.

We think that the main reason for obtaining such a clear picture of the role for auxin

signaling in our analysis is that we focused specifically on very young, proliferating tissues

where this mechanism has it’s role. Sampling of whole plants, even at the seedling stage,

probably biases the analysis to the mature tissues that form the bulk of the material and

where entirely different responses predominate, which has been shown in previous studies

(Fujita et al., 2007; Kant et al., 2007; Papdi et al., 2008).


157

Growth regulation

Our kinematic analysis shows that a decrease in cell division and expansion causes leaf

growth reduction under osmotic stress and in the combination of NAA and mannitol,

whereas NAA alone enhances cell cycle activity (Figure 2). The contrasting effect of the

treatments on this process requires differential effects. Indeed, the main explanation for

the enhanced cell division activity in response to NAA is the upregulation of B and D type

cyclins and members of the Anaphase Promoting Complex (APC), whereas the main effect

of mannitol appears to be a downregulation of CYCA2;1.

A reduced level of A-type cyclins has been observed earlier in response to different stresses

(Kakumanu et al., 2012; Kitsios and Doonan, 2011) and it has been demonstrated that

reducing their expression inhibits cell division during Arabidopsis leaf growth (Vanneste et

al., 2011).

KRP2 and KRP4 are reported to inhibit cell division and ultimately to decrease leaf growth

(Bemis and Torii, 2007; De Veylder et al., 2001). Consistent with the studies we also

observed increased expression of KRP2 and KRP4 and reduced proliferation under osmotic

stress in the presence and absence of NAA. Earlier, auxin was reported to decrease the

expression of KRP4 in Arabidopsis (Cho et al., 2010; Sanz et al., 2011). In contrast, we found

increased expressions of KRP2 and KRP4 in response to NAA. From our dose-response

experiments we can hypothesize that the effect of auxin on KRP expression is dose

dependent, where low concentrations inhibit its expression and higher concentrations

promote it.

Recently, auxin was found to stimulate degradation of the F-box protein SKP2A through the

ubiquitin proteasome system (Jurado et al., 2010). Moreover, the majority of cell cycle

regulators are controlled by ubiquitin dependent proteolysis by SCF or APC (Teixeira and

Reed, 2013). In accordance with the upregulation of CDC27B and CCS52B in response to

NAA, this suggests that the APC complex is connected with auxin signaling (Del Pozo and

Manzano, 2014). It has been demonstrated that its upregulation can stimulate cell division

and leaf growth in Arabidopsis (Eloy et al., 2011; 2012).


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Next to the effects on cell division, our kinematic analysis shows that osmotic stress

reduced cell size by reducing cell expansion rates. As typically turgor is not affected by

relatively mild drought stress, changes in cell wall synthesis and the production of essential

cell wall loosening proteins such as expansins (Cosgrove, 2000) and xyloglucan

endotransglucosylase/hydrolases (XTHs; Van Sandt et al., 2007) are important for the

observed alterations in cell expansion (Li et al., 2014; Wolf et al., 2012). Consistently we

found major changes in the expression of these genes in our transcriptome analysis

(Supplemental Table S3). Similarly, reduced cellulose content was observed also in tobacco

cell cultures under osmotic stress, which ultimately decreased cell expansion (Iraki et al.,

1989). The structural proteins extensins are extracellular basic hydroxyproline (Hyp)-rich

structural glycoproteins (HRGPs) (Lamport et al., 2011), they are important for the

crosslinking of cell wall components, cell wall dehydration and strengthening (Wolf et al.,

2012), and their expression was enhanced under osmotic stress in our dataset. This is

consistent with earlier findings that various biotic and abiotic stresses promote extensin

crosslinking (Merkouropoulos and Shirsat, 2003; Tseng et al., 2013; Zagorchev et al., 2014).

Pectins form a major fraction of the primary cell wall in plants and they help to determine

cell wall stiffening under stress and reduced growth (Willats et al., 2001; Zagorchev et al.,

2014). We also found an increased pectin biosynthesis while pectin esterases are

downregulated (Bray, 2004) under osmotic stress.

Taken together, the reduced cell expansion under osmotic stress can be attributed to

inhibited cell wall synthesis, altered composition, as well as altered expression of cell wall

loosening proteins, that all impact the extensibility of the wall and thus cell expansion.

In conclusion, our findings clearly indicate that auxin signaling plays a central role in the

growth response to drought. The plant response to drought is intricate and complex and

often overly simplified. It is well established that in different parts of the plant, drought

exerts even completely opposite responses. One well-known example of this is the

stimulation of root growth, whereas at the same time shoot growth is inhibited (Lee et al.,

2012). It is also more than likely that the response of growing tissues is entirely different

from mature tissues, which are the subject of the majority of published studies to date. Our

study yields important new insights on the drought response in young growing leaves. If


159

indeed the nature of the response of different parts and developmental stages of the plant

is different, it is important to precisely understand communalities and specific aspects of

each. This will allow us to develop specific combinations of genotypes that result in

increased tolerance to drought, in absence of negative side effects such as diminished

growth. Translating such knowledge to crops will then provide a valuable tool to increase

productivity and/or to maintain it in light of increased frequency of drought spells,

predicted for many regions of the world in the context of global climate changes (Cazale et

al., 2009).



Arabidopsis wild type Col-0, Ler-0 and WS-0 seeds were sterilized in 70% ethanol for 1

minute and 5% bleach for 10 minutes, followed by rinsing with water for 3-5 times. The

seeds were sown on half-strength (Murashige and Skoog, 1962) medium (Duchefa

Biochemie) supplemented with 1% sucrose and 0.8% plant agar (Duchefa Biochemie). To

study osmotic stress 25, 50 or 100 mM mannitol was added to the media. The response to

externally applied auxin was analyzed by addition of NAA (α-Naphthalene acetic acid) in

0.01% DMSO (Dimethyl sulphoxide) at final concentrations of 0.01, 0.02, 0.04, 0.06, 0.1, 0.4,

0.8 and 1 µM. An equivalent volume of DMSO was added to control medium to exclude

effects of the solvent. 28 seeds were sown in 150x25 mm round petri dishes (Falcon®

tissue culture dishes, VWR). After stratification at 4°C for 2 days, plates were transferred to

a growth chamber with an air temperature of 22°C and shelves cooled to 19°C to avoid

condensation against the lid and a 16h day [80-90 µmols-1m-2 s-1 photosynthetically active

radiation (PAR), supplied by fluorescent tubes (cool white, LUMILUX, Germany)] and 8 h

night regime.

Rosette and leaf growth analysis

Images of rosettes were taken with a digital camera at 22 DAS and the area was measured

using ImageJ v 1.48 (http://rsbweb.nih.gov/ij/). Leaf growth analysis was performed on



160

the first leaf pair. For this purpose, leaves were harvested from 8 to 29 DAS, after which

they were fixed and cleared with 70% ethanol for 24hrs and subsequently in 100% lactic

acid, which was also used as a mounting agent for subsequent microscopic observations.

Whole leaf dark field images were obtained with a binocular microscope (Nikon SMZ1000)

fitted with a digital camera (Zeiss [AxioCam Cc1]). For kinematic analysis, the surface area

of 8-20 leaves was measured using ImageJ. We calculated cell expansion rates as the

relative rate of increase in leaf area over time. For this, the logarithmic values of the mean

of cell numbers were locally fitted with a 5 point quadratic function (Erickson, 1976), using

the first derivative as the relative leaf expansion rate.


To determine the effect of auxin and mannitol on cell division and expansion, we

performed a kinematic analysis of the abaxial epidermal cells of 3-5 average leaves from 8

to 29 DAS as described in more detail by Nelissen et al. (2013). Young leaves, i.e. 8-10 DAS,

were stained with propidium iodide according to the protocol of Wuyts et al. (2010) and

cell images were obtained with a Nikon C1 confocal microscope using a Nikon Eclipse E600.

Samples of older leaves were cleared with 70% ethanol and subsequently stored and

mounted in 100% lactic acid on object slides for microscopy, whereby abaxial epidermis

cells were imaged using DIC optics on a Zeiss Axio Scope A1 at 20x and 40x magnification

fitted with a digital camera (Zeiss, AxioCam Cm1). The outlines of the cells were hand

drawn on an LCD tablet (Wacom drawing pad) connected to an iMac computer running

ImageJ. Morphometric analysis of the drawn cells was performed with automated image

analysis software that measures total area of the drawn cells and counts the number of

pavement and guard cells (Andriankaja et al., 2012). From these data we calculated average

cell area and estimated the number of cells per leaf by dividing leaf blade area by cell area.

Stomatal index was calculated as the percentage of stomata in the total number of

epidermal cells. We calculated cell division rates as the relative rate of increase in cell

number over time. For this, the logarithmic values of the mean of cell numbers were locally

fitted with a 5 point quadratic function (Erickson, 1976), using the first derivative as the

division rate. An average cell division rate over the period between 8 and 12 DAS was


161

determined by calculating the increase in number of cells per hour during this period.

Number of cells and stomatal index of 22, 25 and 29 DAS were used to calculate the average

number of cells and stomatal index of the mature leaves.

Auxin measurements

15 to 300 leaves were harvested every second day from 10 to 22 DAS. The analyses were

repeated six times in independent experiments and from multiple plates within each

experiment. Samples of all treatments were harvested at the same time of the day, between

9 and 13 h, to avoid variation related to diurnal patterns. Because of their small size, leaves

on 10 and 11 DAS were dissected under a binocular microscope with microscissors

(Student Vannas Spring Scissors, Fine Science Tools) whereas at later stage leaves were

easily visible, therefore dissected without the microscope. Dissected leaves were collected

in tubes, cooled with liquid nitrogen and stored at -80˚C. Before analysis, the samples were

ground and homogenized using a MagNALyser (Roche) with 2mm glass beads.

IAA and IAA conjugates were extracted overnight in 80% methanol. An internal standard

(200 pmol [13C6-phenyl]- IAA (Cambridge Isotope Laboratory Inc., Andover, MA, USA))

was added for recovery and quantification purpose. Pigments were removed by binding in

80% MeOH on a reversed phase C18 cartridge (500 mg, BondElut Varian, Middelburg, the

Netherlands). One-third of the effluent was subjected to alkaline hydrolysis at 100°C

(Bialek and Cohen, 1989) to analyze IAA conjugates. The remaining fraction was used for

the separation and purification of free IAA. Samples were diluted to 50% MeOH and

transferred to a DEAE cartridge (DEAE-Sephadex A-25, GE Healthcare, Uppsala, Sweden,

500mg, formiate conditions) and C18 cartridge (500mg, BondElut Varian, Middelburg, the

Netherlands) as described by Prinsen et al. (2000). Prior to analysis, all samples were

methylated (Schlenk and Gellerman, 1960). An ACQUITY UPLC System combined with an

ACQUITY TQD mass spectrometer (Waters, Milford, MA, USA) for quantification. Samples

were injected on a VanGuard pre-column (BEH C18, 1.7 µm, 2.1 x 5 mm; Waters, Milford,

MA, USA) coupled to a reversed-phase column (BEH C18, 1.7 µm, 2.1 x 50 mm; Waters,

Milford, MA, USA). After 2 min equilibration at 10:90 A:B (with A: methanol and B: 1mM


162

ammonium acetate), samples were eluted from the column by changing solvent

composition to 90:10 A:B in a 2 min linear gradient, using a constant flow-rate of 300 µl

min-1 and a column temperature of 30°C. ESI(+)-MRM mode was used for quantification

based on specific diagnostic transitions for IAA and 13C6-IAA (190>130 and 196>136

respectively). Chromatograms obtained were processed using QuanLynx v4.1 (Waters,

Milford, MA, USA). Concentrations were calculated using the principle of isotope dilution.

GUS staining

To determine the spatio-temporal patterns of auxin activity, Arabidopsis thaliana Col-0

plants harboring the DR5::GUS reporter were grown in vitro and whole plantlets were

harvested on 8 and 10 DAS, when the first pair of leaves was still actively proliferating. The

samples were incubated in 100% acetone for 10 minutes at room temperature. Acetone

was replaced with GUS assay buffer (Phosphate buffer [pH-7], 0.1% Triton X-100, 0.5 mM

K4[Fe(CN)6].3H20, 0.5 mM K3[Fe(CN)6]) and placed under vacuum for 10 minutes. This

buffer was replaced by a GUS assay buffer supplemented with 958 µM X-gluc in 1% DMF

(Dimethyl sulfoxide) and vacuum infiltrated for 10 minutes. Samples were incubated

overnight at 37°C, after which the reaction was stopped by replacing the X-gluc GUS assay

buffer with fixative (4% Glutareldehyde and 10.8% Formaldehyde) for overnight

incubation at 4°C. After fixation the samples were cleared overnight with absolute ethanol

and transferred to 100% lactic acid. For microscopy, plantlets were mounted in lactic acid

on an object slide and covered with a coverslip. Photographs of the samples were obtained

on a binocular microscope (Nikon SMZ1000) fitted with a digital camera (Zeiss AxioCam

Cc1) using bright field illumination.


To study the effect of osmotic stress and auxin on the transcriptome of proliferating cells,

plants were grown on control medium, medium supplemented with 0.1 μM NAA, 25 mM

mannitol, and 0.1 μM NAA + 25 mM mannitol, respectively. For each of these treatments,

primordia of leaves 1 and 2 were dissected under a binocular at 10 DAS, frozen in liquid

nitrogen and stored at -80°C. Before analysis, the samples were ground and homogenized


163

using a MagNALyser (Roche) with 2 mm glass beads. Total RNA of three replicates, each

containing 100 to 250 leaves was isolated using Trizol Reagent (Life Technologies). The

quantity and integrity of the RNA was measured spectrophotometrically on a QIAxcel

system (Qiagen). Library preparation was done using the TruSeq® Stranded mRNA sample

preparation 96 rcx kit (Illumina™) following the low sample protocol according to the

Illumina™ guidelines. Briefly, approximately 2.5 µg of total RNA was purified using RNA

purification beads targeting the poly-A tail of the mRNA and subsequently the mRNA was

fragmented by means of the enzymes provided in the kit. After the cDNA synthesis

adenylation of 3’ ends and ligation of the adaptors were performed. Adaptors were ligated

in 12-plex formation, allowing the pooling of 12 or more samples after the PCR enrichment

of the library. Subsequently, the library was quantified using PicoGreen® dye (Life

Technologies™). A combination of 18 samples (from which 12 were used for this

experiment) was pooled to run in the same lane on the flowcel on the sequencer. In order

to accurately quantify the concentration in nM of our pools, the Kapa SYBR® FAST

universal qPCR kit (KAPA Biosystems ™) for Illunima™ sequencing was used to quantify the

number of the amplifiable molecules in the pools and the Bioanalyzer® (Agilent

Technologies™) to determine the average fragment size of our pool. Sequencing was done

on an Illumina HiSeq 1500 used in the rapid mode together with the TruSeq® Rapid SBS

Kit for 50 cycles.

Transcriptome data analysis

Transcriptome data analysis was performed using CLC Genomics Workbench v.6

(http://www.clcbio.com/blog/clc-genomics-workbench-7-0/) with the Arabidopsis

thaliana (Col-0 TAIR10) sequence database (http://www.arabidopsis.org/) as reference

genome. After the trimming of adaptors from the sequences, they were mapped against the

reference genome. The expression values were calculated based on “reads per kilobase of

exon model per million mapped reads” (RPKM) values (Mortazavi et al., 2008). RNAseq

data was grouped accordingly and two group comparisons (unpaired) were performed.

The expression values were normalized by scaling to an arbitrarily chosen reference

sample. Moderated t statistics for pairwise contrasts were calculated using the Baggerley’s

http://www.clcbio.com/blog/clc-genomics-workbench-7-0/


164

test (Baggerly et al., 2003). Statistical analysis for the effect of mannitol and NAA

treatments was conducted by a two-way ANOVA on the MeV software (Multi Experiment

Viewer 4.9.0). The obtained p values were corrected for multiple testing for each contrast

separately by means of false discovery rate (FDR; Benjamini and Hochberg, 1995) using

only genes for which expression was detected in all three replicates of at least one

treatment. A FDR < 0.05 and log2 fold change > 0.5 was used as a cutoff. Raw RNA

sequencing data have been deposited with NCBI’s Gene Expression Omnibus (GEO

accession no. GSE60870, http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60870).

Expression profiles for differentially expressed genes were visualized and clustered using

Quality Threshold clustering on MeV.

For all significant genes according to ANOVA and FDR, the corrected p values for the pair-

wise contrasts were used for Venn diagram construction, overrepresentation analyses by

PageMan (Usadel et al., 2006) and to study individual pathways where significantly

induced or repressed genes with known functions were classified into groups based on

gene ontology (GO) information obtained from the TAIR Database

(http://www.arabidopsis.org/) and plotted in newly constructed regulatory pathway maps

using MapMan 3.5.0 (Thimm et al., 2004).


Statistical analysis of the rosette and leaf area measurements of mannitol, NAA and

NAA+mannitol treatments was performed by one-way ANOVA using SPSS 16.0 statistical

software and significant differences between the means of the treatments were determined

using the LSD test (p < 0.05). Statistical analyses for auxin measurements and kinematic

data were conducted by t tests in Microsoft Excel. To study the interaction effect of NAA

and mannitol on leaf growth in the combined treatments, a two-way ANOVA was

performed using the LSD test (p < 0.05).

http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60870


165

Supplemental Data

All supplemental data is listed below. Supplemental figure can be found at the end of the

chapter and supplemental tables are available upon request.

Supplemental Figure 1. The interacting effect of mannitol and NAA on leaf growth in

different Arabidopsis ecotypes.

Supplemental Table S1. All the genes for which expression was detected in all three

replicates of at least one treatment.

Supplemental Table S2. Significantly affected cell cycle genes.

Supplemental Table S3. Significant genes related to cell wall.

Supplemental Table S4. List of significantly expressed genes that encode for key

antioxidant enzymes under mannitol (M), NAA (N) and NAA+mannitol (NM).

Acknowledgements

We thank Sevgi Oden for the help in IAA measurements. We also thank Dr. Malgorzata A.

Domagalska, Gaurav Zinta and Hamada Abdelgawad for useful discussions related to

experiments and manuscript writing. This work was supported by a concerted research

activity (GOA) research grant, ‘A Systems Biology Approach of Leaf Morphogenesis’ from

the research council of the University of Antwerp and an Interuniversity Attraction Poles

(IUAP: MARS IUAP VII/29) from the Belgian Federal Science Policy Office (BELSPO).

Shweta Kalve was funded by a training grant from the Department of Science and

Education of the Flemish Government.

https://pure.york.ac.uk/portal/en/researchers/malgorzata-anna-domagalska(e7e32df0-179c-4d4f-8c5a-89899cc7bc3e).html



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Supplemental Figure 1. The interacting effect of mannitol and NAA on leaf growth in

different Arabidopsis ecotypes: (A) Rosette area of Arabidopsis Col-0, Ler-0 and WS-0 ecotypes

grown on different concentrations of mannitol for 22 DAS; (B) Leaf area measurement; (C) Rosette

area of plants grown under Control, 25mM Mannitol, 0.1µM NAA), NAA+mannitol for 22 DAS

(n=20-60); (D) Leaf area measurement after 22 DAS (n=30-80). Experiment was repeated twice for

Control, 25mM Mannitol, 0.1µM NAA and NAA+mannitol (p<0.05). In NAA+Mannitol treatment,

NAA*Mannitol interaction p value = 0. Error bars represent standard error.

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sett

e a

rea

(mm

2)

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M25

M50

M100L

eaf b

lad

e area

(mm

2)

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M25

M50

M100

0

10

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50

100

150

200

250(D)(C)

(B)

d

dd

cc

c

bbb

aa

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sett

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rea

(mm

2)

Control

Mannitol

NAA

NAA+Ma

(A)

Col Ler WS

ddd c c

c

a

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f bla

de a

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(mm

2)

Control

Mannitol

NAA

NAA+M

0

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Chapter 4

Downregulation of KRPs promotes cell division

and endoreduplication in the leaves of Arabidopsis

thaliana

Shweta Kalve1, Dirk De Vos1,2, Markakis Marios Nektarios1,

Malgorzata A. Domagalska1, Joanna Stelmaszewska3, Lieven De

Veylder4, Arp Schnittger5 and Gerrit T.S. Beemster1*


2Department of Mathematics and Computer Science, University of Antwerp,

Antwerp, Belgium

3Department of Reproduction and Gynecological Endocrinology Medical

University of Bialystok, Bialystok, Poland

4Department of Plant Systems Biology, VIB, 9052 Ghent, Belgium

5Department of Developmental Biology, University of Hamburg, Germany


This chapter is an early draft for a publication

Contribution of S.K.- Performed most experiments, supervised J.S. and wrote the

manuscript


Multiple downregulation of KRPs

185

Abstract

Like in other eukaryotes, the plant cell cycle is tightly regulated by CDKs (cyclin-dependent

kinases), and their activity is negatively regulated by low molecular weight proteins known

as Kip-related proteins (KRPs). Seven KRPs have been reported in Arabidopsis and this

redundancy makes that mutation of one of them has no or very limited effect on plant

growth and development. This study focuses on the effect of downregulation of multiple

KRPs in parallel, particularly KRP4, KRP6 and KRP7 on Arabidopsis leaf growth. We used

single, double and triple T-DNA insertion mutants for the study. Our results demonstrate

that the loss of activity of single KRP genes does not affect leaf development except for

KRP4 which leads to growth reduction. Simultaneous reduction of the activity of two or

three KRPs enhances leaf growth, with the triple mutant having the most effect on mature

leaf size. Kinematic analysis showed, as expected, that increased cell proliferation was

responsible for the enlarged leaves of double and triple mutants. However, in combination

with the increased cell number, smaller cells were found in all the mutants. Remarkably,

we found that the increased leaf size was largely established prior to the time frame in

which we performed kinematic analysis, suggesting that the bigger leaves were already

determined in the seed. Indeed, we found that the triple mutant has significantly larger

seeds that contain larger embryos. Moreover, when similarly sized seeds are selected from

the size range found in mutant and wild type, the difference of mature leaf size of the

seedlings was absent. By means of mRNA sequencing we investigated the molecular

changes in proliferating and expanding leaves. The result showed an upregulation of genes

involved in DNA replication. Subsequently, flow-cytometry revealed that the inhibition of

multiple KRPs enhanced not only proliferation, but also endoreduplication. Hence, we

conclude that the downregulation of multiple KRPs promotes leaf growth by increasing cell

proliferation during seed development and DNA replication in growing leaves.


186

Introduction

The cell cycle is one of the most studied fundamental processes in multicellular organisms.

Like in all other organisms, the plant cell cycle progresses through four different phases:

G1, S, G2 and M. The transitions between G1 to S and G2 to M are tightly controlled by

phosphorylation of CDK (cyclin-dependent kinase)/CYC (cyclin) complexes, which initiates

the onset of DNA duplication and mitosis, respectively (Dewitte and Murray, 2003; Inze and

De Veylder, 2006). The KRPs (Kip related proteins) or ICKs (interactors/inhibitors of

cyclin-dependent kinase) are an important class of cell cycle inhibitors that regulate the

cell cycle progression by controlling CDK activity (De Veylder et al., 2007; Verkest et al.,

2005b; Wang et al., 2006). Plant KRPs share a limited homology with mammalian p27Kip1

proteins (Wang et al., 1997) and have been identified in many plant species, including

Arabidopsis (De Veylder et al., 2001; Lui et al., 2000; Zhou et al., 2002), tobacco (Jasinski et

al., 2002; 2003), tomato (Bisbis et al., 2006), alfalfa (Pettko-Szandtner et al., 2006), maize

(Coelho et al., 2005) and rice (Barroco et al., 2006; Yang et al., 2011).

All plant KRPs share a conserved C-terminally located 31-amino-acid CDK-binding domain

(De Veylder et al., 2001; Torres Acosta et al., 2011). Removal of this domain in KRP1 leads

to loss of CDK binding and inhibition activity (Zhou et al., 2003). Arabidopsis has seven KRP

genes which are divided into two groups according to their exon-intron organization, one

with three and another with four exons (Torres Acosta et al., 2011). These seven KRP genes

have distinct expression patterns in plants (De Veylder et al., 2001; Menges et al., 2005;

Ormenese et al., 2004; Wang et al., 2006).

Domain studies have elucidated that all the KRPs have a CDK/CYC binding site to interact

with A-type CDKs and D-type cyclins, while none of them were found to interact with B-

type cyclins (De Veylder et al., 2001; Van Leene et al., 2010; Wang et al., 1998; Zhou et al.,

2002). Moreover, in maize endosperm KRP1 and KRP2 inhibit CYCA1;3-associated CDK

activity (Coelho et al., 2005). Some reports suggest the interaction of KRPs with CDKB as

well (Nakai et al., 2006; Pettko-Szandtner et al., 2006). In addition to the CDK/CYC binding

site, KRPs contain several other functional domains and motifs, including a nuclear


187

localization domain, a CDK phosphorylation site, a protein degradation domain (PEST) and

a coiled-coil domain (Torres Acosta et al., 2011). Consistently, all Arabidopsis KRPs have

been shown to localize in the nucleus (Bird et al., 2007). Furthermore, CDK

phosphorylation sites were reported in KRP3, KRP4, KRP6 and KRP7 but the experimental

verification of the functionality of these phosphorylation sites is needed. PEST domains,

which are involved in protein degradation (Rogers et al., 1986) are present in Arabidopsis

KRP2, KRP4, KRP5 and KRP6 (De Veylder et al., 2001; Torres Acosta et al., 2011). Several

studies postulated that the level of KRPs are regulated by a 26S proteasome mediated

degradation pathway (Gusti et al., 2009; Jun et al., 2013; Kim et al., 2008; Lai et al., 2009;

Liu et al., 2008; Ren et al., 2008). In addition to other motifs, a coiled-coil domain was

suggested to be present in KRP1 which is important for mediating protein-protein

interaction (De Veylder et al., 2001; Torres Acosta et al., 2011).

In the last decades several overexpression studies of KRPs have been reported. Arabidopsis

plants overexpressing different KRPs have altered plant morphology and exhibit a

reduction in cell number and increased cell size, resulting in small, serrated leaves (Bemis

and Torii, 2007; De Veylder et al., 2001; Jasinski et al., 2002; Jun et al., 2013; Wang et al.,

2000; Zhou et al., 2002). In contrast, the constitutive expression of KRP5 had no effect on

organ size, but resulted in serrated leaves (Jegu et al., 2013). Several studies have also

reported that overexpression of KRP genes repressed endoreduplication (De Veylder et al.,

2001; Jasinski et al., 2002; Schnittger et al., 2003; Zhou et al., 2002) while few KRPs

triggered the endocycle transition (Jegu et al., 2013; Jun et al., 2013; Verkest et al., 2005a;

Weinl et al., 2005). In spite of detailed knowledge regarding the effects of KRP

overexpression, only few studies presented the consequences of downregulation, as KRP

genes are highly redundant and may compensate the reduced expression of other KRP gene

in the family. Silencing of six KRP genes led to dedifferentiation and hyperproliferation

(Anzola et al., 2010). On the contrary, downregulation of five KRPs was recently shown to

enhance plant growth and to upregulate the E2F pathway (Cheng et al., 2013).

Furthermore, a mutation in KRP2 increased lateral roots in Arabidopsis thaliana (Sanz et al.,

2011). Although, the effect of KRP inhibition on plant growth has been shown, it’s effect on

the regulation of cell division and endoreplication processes is currently not well


188

understood.

In the present work, we studied single, double and triple T-DNA Knock-Out mutants of

Arabidopsis KRP4, KRP6 and KRP7 genes whereby KRP4 belongs to one class and KRP6 and

KRP7 to another class of phylogeny (Torres Acosta et al., 2011). We describe the effect of

downregulation of these KRP genes on leaf growth. Our results clearly show enhanced leaf

growth in lines accumulating multiple mutations as a result of an increased cell number.

Interestingly, detailed growth analysis revealed that the growth difference in the triple

mutant was already established during embryonic development. Moreover, enhanced

ploidy in higher order mutant was observed which shows that a lower dose of KRPs

stimulate endoreduplication.

Results

Identification of the T-DNA insertion mutants

To study the role of Arabidopsis KRPs in leaf development, we used KRP4/ICK7, KRP6/ICK4

and KRP7/ICK5 as they belong to two different classes of phylogeny and are different in

their exon-intron organization (Torres Acosta et al., 2011). We used single, double and

triple mutants for KRP4, KRP6 and KRP7 as earlier studies showed that the combination of

their mutations led to the strongest phenotypes (Schnittger, Unpublished). We confirmed

the homozygocity, insertion of T-DNA and the expression of respective genes. To identify T-

DNA tags in krp4 (SAIL_248_B06) (Zhao et al., 2012), krp6-1 (SAIL_548_B03) (Gusti et al.,

2009; Zhao et al., 2012) and krp7-1 (GK_841D12) (Cheng et al., 2013; Zhao et al., 2012),

PCR was performed with a specific primer set using genomic DNA extracted from the

leaves of each line (Figure 1A, Supplemental Table S2). Similarly, the presence of insertion

was confirmed for double and triple mutants of respective genes (Figure 1B). RT-PCR

(Reverse Transcription PCR) was also performed to check the expression of KRP4, KRP6

and KRP7 in the rosette of the triple mutant at 1.04 stage, when four rosette leaves are

bigger than 1 mm in length (Boyes et al., 2001). Amplification of cDNA with primer pairs

revealed the absence of full-length transcripts of all the genes in the mutants (Figure 1C,


189

Supplemental Table S3). For clarity we further used following nomenclature where krp4,

krp6 and krp7 denoted as single mutants, krp4/6, krp4/7 and krp6/7 as double mutants and

krp4/6/7 as triple mutant.

Figure 1. Genotyping and gene expression analysis: (A) T-DNA PCR verifying the genotype of

the single mutants & (B) double and triple mutants. A gene-specific primer pair was used to check

the presence of a wild type (WT), undisrupted allele of the gene (Lane 1). Separate PCR reaction

using a T-DNA-specific primer and a gene-specific primer was used to test for the presence of a T-

DNA insertion in the gene of interest (Lane 2); (C) RT-PCR analysis of wild-type and krp4/6/7 to

detect the full length transcript of KRP4, KRP6 and KRP7.

Differential expression of seven Arabidopsis KRPs during leaf development

In present study we focused on the role of KRPs in leaf development, therefore we

performed an experiment to study the differential expression of all the KRPs during

different growth stages of the Arabidopsis leaf by quantitative real-time PCR. PCR was

performed by specific probes for each KRP and expression levels were normalized against

KRP4

KRP6

KRP7

WT Mutant1 21 2

(A)

KRP6

KRP4

KRP7

WT krp4/6 krp4/7 krp6/7 krp4/6/71 2 1 2 1 2 1 2 1 2(B)

krp4/6/7

UBQ10

KRP4

KRP6

KRP7

WT(C)


190

ACT 8 as the reference gene. Our results showed that KRP1, KRP2, KRP4 and KRP6 express

ubiquitously in all stages of leaf development. Remarkably, KRP1 had the highest

expression level throughout leaf development compared to other KRPs with a gradual

increase till 17 DAS and then a slight decrease at later stages of leaf growth. Moreover,

KRP2, KRP4 and KRP6 were most equally expressed in all the stages of leaf development

from 9 till 29 DAS (Figure 2). The expression of KRP5 was highest in proliferating tissues

from 9 till 13 DAS, decreased in expanding cells between 13 and 22 DAS and again

increased at mature stage from 24 to 29 DAS. Similarly, the highest expression of KRP7 was

detected on 9 and 24 DAS, whereas the expression was lower from 15 till 20 DAS (Figure

2). Interestingly, KRP3 was highly expressed in proliferating tissues on 9 DAS, while its

expression gradually decreased until 13 DAS and was not detected on later days of leaf

development. Our results showed that all seven KRPs have different expression patterns

during leaf development. It can be concluded from transcription profiling of different KRPs

that they might play distinct role in leaf development.

Figure 2. Differential expression profiling of Arabidopsis KRP genes in different stages of leaf

developmental determined by real-time PCR. The averages and standard error of relative

expression are based on three biological replicates.

9 11 13 15 17 20 22 24 26 290

1

2345678

RQ

DAS

KRP1

KRP2

KRP3

KRP4

KRP5

KRP6

KRP7


191

Inhibition of KRPs causes enhanced leaf growth by increasing cell number

To study the effect of KRP4, KRP6 and KRP7 downregulation on leaf growth, we measured

leaf blade area and epidermal cell area of first leaf pair at 26 DAS in single (krp4, krp6,

krp7), double (krp4/6, krp4/7, krp6/7) and triple (krp4/6/7) mutants. We found no

significant changes in leaf blade area of krp6 and krp7, whereas krp4 was smaller than the

wild type. Downregulation of multiple KRPs led to significantly enlarged leaves. Among

double mutants krp4/6 and krp6/7 had around 10-15% larger leaves whereas krp4/7

showed the increase of 23% in leaf area compared to Col-0. However, the triple mutant

krp4/6/7 had the most pronounced leaf growth resulting in an increase of 33% in leaf

blade area (Figure 3A; Supplemental Figure 1A).

Figure 3. Growth analysis of mutants: Change in (A) leaf area; (B) Cell size; (C) Cell number; (D)

Stomatal index of the single (krp4, krp6, krp7), double (krp4/6, krp4/7, krp6/7) and triple mutant

(krp4/6/7) relative to the wild type (Col-0). For leaf area measurements 20-100 leaves whereas for

cellular measurements 3-9 leaves were used. Error bars represent standard error. An asterisk

indicates a significant difference at *P<0.05, **P<0.01 and ***P<0.001.

Col

krp4

krp6

krp7

krp4/

6

krp4/

7

krp6/

7

krp4/

6/7

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4 ***

******

***

***

R

ela

tiv

e

Lea

f a

rea

(A)

Col

krp4

krp6

krp7

krp4/

6

krp4/

7

krp6/

7

krp4/

6/7

0.0

0.5

1.0

1.5

2.0(C)

******

***

R

ela

tiv

e

Cel

l n

um

ber

Col

krp4

krp6

krp7

krp4/

6

krp4/

7

krp6/

7

krp4/

6/7

0.0

0.2

0.4

0.6

0.8

1.0

1.2(B)

********

R

ela

tiv

e

Cel

l si

ze

Col

krp4

krp6

krp7

krp4/

6

krp4/

7

krp6/

7

krp4/

6/7

0.0

0.2

0.4

0.6

0.8

1.0

1.2(D) * *****

R

ela

tiv

e

Sto

ma

tal

Ind

ex


192

Increased leaf growth can be the consequence of increased cell size or cell number.

Therefore, to analyze the cause of increased leaf area we measured abaxial cell size and

calculated cell number as the ratio of leaf and cell area’s in all the mutants. In addition to an

absence of an effect on leaf size, no significant change in the cell number and size was

observed in krp6 and krp7. The reduced leaf size of krp4 was the result of smaller cells,

while no change in cell number was found. In the double mutants we observed a consistent

increase in cell number coupled with a proportional reduction in cell size. Around 43, 45

and 35% more cells but 22, 19 and 12% smaller cells in comparison to control was the

result of downregulation of KRPs in krp4/6, krp4/7 and krp6/7, respectively. A large

increase of 77% in number of cells compared to wild type resulted in bigger leaves in the

krp4/6/7 mutant while 25% reduction in cell size partly compensated for the increased cell

number (Figure 3B, C; Supplemental Figure 1B, C). Increased cell number and smaller size

could be due to effects on all cells or on a shift in the proportions of (large) pavement cells

and (small) guard cells. The stomatal index, which depicts the number of guard cells as a

fraction of total number of cells, showed only a small but significant increase in krp4,

krp4/7 and krp6/7 compared to control (Figure 3D; Supplemental Figure 1D). Therefore

this cannot explain the general tendency across all lines towards more and smaller cells. In

conclusion, cellular measurements showed that an overall increased cell number

contributed to the enhanced leaf growth after the downregulation of multiple KRPs. This

enhanced cell number is partly compensated for by a smaller average cell size.

Kinematic analysis shows no difference in cell division rates between Col-0

and the krp4/6/7 mutant

Study of single, double and triple mutants suggested that the triple mutant krp4/6/7 has

most prominent changes in leaf growth (Figure 3A). Therefore, to gain insight into the

effect of downregulation of KRP4, KRP6 and KRP7 on leaf development and cell cycle

duration, a kinematic analysis was performed on the first leaf pair of Arabidopsis in vitro

grown plants. For this analysis, leaves of wild type and krp4/6/7 mutant were harvested

daily from 6 till 26 DAS and leaf area measurement was performed by quantitative image

analysis. Cellular measurements were performed on abaxial epidermis where cell number,


193

cell size, the number of guard cells and the rates of cell division were calculated. From 6 till

12 DAS, the leaf area increased exponentially in both Col and krp4/6/7 (Figure 4A).

Interestingly, leaf area on 6 DAS was already significantly increased in the triple mutant in

comparison to the wild type (p = 0.046). Initially on 6 and 7 DAS leaf growth rates were

higher in the triple mutant. From 8 DAS, leaf expansion rates were similar in krp4/6/7 and

Col, both gradually decreased until the maturity at about 22 DAS (Figure 4B). Cellular

measurements demonstrated that the increase in cell number contributed to an enhanced

area of mature krp4/6/7 leaves. Remarkably, the mutant had around 2-fold more cells than

Col from the beginning at 6 DAS. From 6 till 12 DAS cell number increased exponentially in

the wild type and the mutant until the final number was reached about 10835+685 and

21964+1296, respectively (Figure 4C). Cell division rates decreased in krp4/6/7 and Col

from 6 till 13 DAS. Cell division rate showed only minor differences between the wild type

and mutant during leaf development (Figure 4D). However, when calculating the rate of

change in cell numbers over the interval between 6 and 10 DAS we found a small (4%) but

significant increase (p = 0.019) in krp4/6/7 compared to the wild type.

The average cell size depends on the balance between division and expansion rates (Green,

1976). Our results showed an exponential increase in cell size in Col and the mutant from 6

till 12 DAS. In contrast to cell number, average epidermal cell size was reduced in the

mutant, which indicates that the mutation triggers negative cell size compensation (Figure

4E). From 6 till 8 DAS very few stomata were present and no significant difference in

stomatal index was observed. From 9 till 15 DAS the stomatal index was lower in the triple

mutant, while after 15 DAS it increased to slightly higher values than in the wild type

(Figure 4F). This pattern suggests a slight delay in the developmental progression of the

mutant leaves, which, curiously, is not evident from the other cellular parameters. Overall,

kinematic analysis revealed that the increased cell proliferation was responsible for the

enhanced leaf growth in the krp4/6/7 mutant.


194

Figure 4. Kinematic analysis of leaf growth of first leaf pair of Col-0 and krp4/6/7 plants: (A)

Leaf blade area; (B) Relative leaf expansion rate (RLER); (C) Epidermal cell number on the abaxial

side of the leaf; (D) Cell division rate (CDR); (E) Epidermal cell area; (F) Stomatal index. Insets show

the same data on a linear scale to show absolute differences. 8-22 leaves were used to measure leaf

area and cellular analysis was done on 3-6 leaves. Error bars represent standard error.

Increased leaf size in the krp4/6/7 mutant is the result of enlarged seed

and embryo size

To understand when the earliest differences in the development of the mutant arise, we

analyzed seed and embryo size for Col and krp4/6/7. Remarkably, we found a 25 %

(p=0.000) increase in seed size and (Figure 5A and C) and a 19 % (p=0.000) increase in

embryo size (Figure 5B and D) in the krp4/6/7 mutant compared to wild type, respectively.

These results suggest that the increased leaf size is a consequence of an increased seed size

in the triple mutant.


195

Figure 5. Seed and embryo size of the krp4/6/7 mutant: (A) Seed and (B) Embryo image of Col-0

and the krp4/6/7 mutant; (C) Seed size (n=400-500); (D) Embryo size measured as projected area

(n=30-40). Error bars represent standard error. An asterisk indicates a significant difference at

***P<0.001.

We decided to investigate in more detail the contribution of seed size in the leaf phenotype

of the mutant. Therefore measured the size of 418 and 453 seeds in the wild type and the

triple mutant and grouped the seeds according to their sizes. Distribution analysis revealed

a clear shift in the seed size of the krp4/6/7 mutant, where the median seed size was 100

and 130µm2 in Col and krp4/6/7, respectively (Figure 6A). Furthermore, to study the effect

of seed size on leaf growth, wild-type seeds having a size of 80, 100, 120 and 140µm2 while

mutant seeds having a size of 90, 110, 130 and 150µm2 were grown in vitro. In another

experiment, plants of Col and krp4/6/7 mutant having similar seed size of 120µm2 and

median seed size of 100 (Col) and 130 (krp4/6/7) µm2 were grown. Interestingly, our

results demonstrated the effect of different seed size on leaf growth of the wild type and

the mutant. Leaf area of wild type and mutant gradually increased with an increase in seed

size (Figure 6B). Moreover, Col and krp4/6/7 plants grown from the same seed size had the

same leaf area. While, the leaf area of the plants grown from median seed size had a

Col krp4/6/70

50

100

150 ***

See

d s

ize

(µm

2)

(C)

Col krp4/6/70

50

100

150

200

***

Em

bry

o s

ize

(µm

2)

(D)

(A) Col krp4/6/7 Col krp4/6/7(B)


196

significant (p = 0.000) increase of 12.5% in the krp4/6/7 mutant compared to Col (Figure

6B). Our results clearly demonstrate that downregulation of KRP4, KRP6 and KRP7 results

in increased embryo size, which later leads to enhanced leaf growth.

Figure 6. Effect of seed size on leaf growth of Col and krp4/6/7: (A) Seed size distribution of

Col-0 and krp4/6/7 mutant where dotted oval represents the median size of each line; (B) Leaf area

measurement of wild type and krp4/6/7 mutant lines having seed size of 80, 100, 120, 130 and 140

µm2 [C=Col-0 (black bars) and k=krp4/6/7 mutant (grey bars)]. All three experiments were carried

out on different petriplates (n=15-35 for each experiments). An asterisk indicates a significant

difference at ***P<0.001.

Transcriptome analysis of krp4/6/7 reveals upregulation of genes related

to cell cycle and DNA replication in leaves

To understand the molecular mechanism responsible for cellular changes, we performed

transcript profiling comparing proliferating and expanding leaves of the krp4/6/7 and wild

type at 9 and 15 DAS, respectively. Overall 417 genes were differentially expressed (FDR

corrected- p value < 0.05 and log2 fold change > 0.75) between triple mutant and the wild

type. Statistical analysis showed 232 and 76 upregulated and 91 and 26 downregulated

transcripts at 9 and 15 DAS, respectively (Figure 7A; Supplemental Table S4). To identify

the major biological functions modulated by silencing multiple KRPs, we performed an

overrepresentation analysis of all significantly up and downregulated genes using the

Cytoscape plugin BiNGO (Maere et al., 2005). Overall the overrepresented categories were

consistent with enhanced cell cycle activity at both 9 and 15 DAS. The majority of

40 80 120 160 200 2400

10

20

30

40

50

60

70

80

See

d s

ize

dis

trib

uti

on

Seed size (µm2)

Col

krp4/6/7

(A)

C80

C10

0

C12

0

C14

0k90

k110k13

0k15

0

C12

0k12

0

C10

0k13

00

10

20

30

40

50

***

Lea

f a

rea

(m

m2

)

Seed size (µm2)

(B)


197

overrepresented classes were related to DNA synthesis, repair and replication (Figure 7B;

Supplemental Figure 3, 4 and Table S5, S6). Inversely, transcripts related to negative

regulation of cell cycle were clearly downregulated at 9 DAS (Figure 7C; Supplemental

Figure 5 and Table S7).

Figure 7A. Functional analysis of genes: Overlap between genes expressed on 9 and 15 DAS in

krp4/6/7 mutant. Values indicated in Venn diagram represents the number of genes expressed on

respective day. Numbers represented by up and down arrow shows up and downregulation of genes,

respectively. Transcripts were considered differentially expressed if log2 of fold change > 0.75 and FDR-

corrected p value < 0.05

As gene-enrichment analysis demonstrated that downregulation of multiple KRPs affected the

DNA replication machinery and obviously the cell cycle, we decided to analyze the expression of

previously reported key genes related to these processes (de Almeida Engler et al., 2009; de

Jager et al., 2009; Vandepoele et al., 2002). Remarkably, most of the positive regulators were up

while negative regulators were downregulated. Among significant genes of the cell cycle 3 types

of CDKs were upregulated at 9 and 15 DAS. A family of CYCA and CYCB genes were significantly

upregulated whereas in CYCD family CYCD2;1 and CYCD3;2 were down and CYCD4;2 was

upregulated (Table 1). As observed in the gene-enrichment analysis, genes related to DNA

synthesis were generally upregulated on 9 and 15 DAS (Table 1, Figure 7B). However, the

8

94

315

9 DAS

15 DAS

323

232

91

krp4/6/7

vs Col

102

76

26

krp4/6/7

vs Col


198

expression of DEL3 and RBR was also enhanced. Expression of KRP4, KRP6 and KRP7, targeted

genes of the triple mutant, were decreased. Few reads in KRP7 was found in RNAseq (Table 1;

Supplemental Figure 6) but the absence of a full length transcript by RT-PCR confirmed the

downregulation of KRP7 in GK_841D12 (Figure 1C). Previous studies have also reported the

absence of KRP7 transcript in krp7-1 (GK_841D12) (Cheng et al., 2013; Zhao et al., 2012).

Interestingly, expression of other KRPs was significantly increased on 9 DAS. Furthermore,

transcripts related to CCS52B and WEE1 were increased on 9 and 15 DAS, respectively (Table

1). In conclusion, our transcriptome profiling suggests that downregulation of KRP4, KRP6 and

KRP7 enhances the expression of other genes related to the cell cycle and DNA replication not

only in proliferating cells at 9 DAS, but also in expanding cells at 15 DAS.


199

Figure 7B. Gene enrichment analysis of differentially expressed genes: Overrepresentation

study of upregulated genes expressed on 9 and 15 DAS in krp4/6/7 mutant (FDR corrected- p <

0.05 and log2 fold change > 0.75).

9 DAS

15 DAS


200

Figure 7C. Overrepresented function and processes in 91 downregulated genes on 9 DAS in the

krp4/6/7 mutant. Transcripts were considered differentially expressed if log2 of fold change > 0.75

and FDR- corrected p value < 0.05


201

Table-1 List of significantly expressed cell cycle genes on 9 and 15 DAS. Expression changes are

presented as log2 and significance (p value < 0.05) is shown in boldface.

Locus Annotation Log2 9 DAS Log2 15 DAS

CDKs

AT3G48750 CDKA;1 -0.18624 0.294058

AT3G54180 CDKB1;1 0.526928 0.502636

AT1G76540 CDKB2;1 0.344388 0.861914

AT1G67580 CDKG;2 0.117975 0.293572

Cyclins

AT1G44110 CYCA1;1 0.359816 1.358478

AT1G77390 CYCA1;2 -0.31914 2.613179

AT5G11300 CYCA2;2 0.657137 -1.22365

AT1G15570 CYCA2;3 0.211788 0.097428

AT5G43080 CYCA3;1 1.204948 1.000994

AT1G47210 CYCA3;2 0.553703 0.877546

AT1G47230 CYCA3;4 0.28166 -0.6161

AT4G37490 CYCB1;1 0.459292 0.484514

AT3G11520 CYCB1;3 0.435928 -0.19291

AT4G35620 CYCB2;2 0.355935 -1.22396

AT1G76310 CYCB2;4 0.682363 1.483733

AT2G22490 CYCD2;1 -0.12491 -0.31074

AT5G67260 CYCD3;2 -0.04476 -0.368

AT5G10440 CYCD4;2 0.917886 0.304156

Kip related proteins

AT2G23430 KRP1/ ICK1 0.449765 -0.16582

AT3G50630 KRP2/ ICK2 0.29135 0.400997

AT2G32710 KRP4/ ICK7 -1.13579 -2.59394

AT3G24810 KRP5 /ICK3 1.276318 0.46618

AT3G19150 KRP6/ ICK4 -1.99013 -3.79553

AT1G49620 KRP7 / ICK5 0.800682 1.92563

DNA Synthesis

AT3G01330 DEL3/E2Ff/ E2L2 0.406168 0.883819

AT2G37560 ORC2 1.157494 1.165096

AT5G16690 ORC3 1.34255 1.330334

AT2G01120 ORC4 0.479437 0.306458

AT1G26840 ORC6 0.504699 1.017525

AT2G29680 CDC6 0.601401 0.633626

AT2G31270 CDT1a 0.780425 0.526552

AT3G54710 CDT1b 0.279236 -0.74908

At5g46280 MCM3 0.963692 -0.00331

At2g16440 MCM4 1.077427 0.746697

At2g07690 MCM5 1.009651 -0.00703


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Downregulation of KRP genes stimulates endoreplication

The upregulation of cell cycle regulatory genes in expanding cells suggested a potential

effect of the kpr4/6/7 mutation on endoreduplication. Endoreduplication is the process

where DNA replication occurs without the subsequent completion of mitosis and occurs

during cell expansion (Beemster et al., 2005). To confirm this hypothesis, we measured

endoreplication in single, double and triple mutants by flow-cytometry. The ploidy level

was measured in the first leaf pair of all the mutants harvested at 26 DAS, when the leaves

are fully mature. While we found no difference in endoreduplication index in krp4, krp6

and krp7 single mutants compared to wild type, enhanced EI was observed in the krp4/6,

krp4/7 and krp6/7 double mutants. The krp4/6/7 triple mutant had a 13% higher ploidy in

comparison to wild type (Figure 8A; Supplemental Figure 2).

At4g02060 Prolifera protein (PRL)/MCM7 1.051764 1.064518

At5g67100 DNA polymerase alpha catalytic

subunit/ICU2 0.891267 1.322839

At1g67630 DNA polymerase alpha subunit B/

POLA2 1.146654 0.648343

At1g07370 PCNA1 0.896384 0.717024

At2g29570 PCNA2 0.624496 0.909116

At2g21790 Ribonucleoside-diphosphate reductase small chain/ RNR1 0.680507 0.840374

At3g27060 Ribonucleoside-diphosphate reductase small chain/TSO2 0.732396 0.320548

At1g67320 DNA primase large subunit 0.996682 0.613327

At5g41880 DNA primase small subunit/POLA3/4 0.980469 0.548148

At5g08020 Replication protein 1.434072 1.869596

At5g61000 Replication protein 0.283254 1.068813

At3g46940 Deoxyuridine 50 triphosphate

nucleotidohydrolase 0.951191 0.76586

At5g18620 DNA-dependent ATPase/ CHR17 0.650014 0.422302

Cell cycle regulators

AT1G02970 WEE1 1.102572 1.221062

AT3G12280 RBR1 0.705309 0.231523

Proteasome

AT5G13840 CCS52B/FZR3 0.130241 0.079696


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Figure 8. Ploidy distribution measurement of Col and krp4/6/7: (A) Relative endoreplication

index (EI) of first leaf pair of Col-0, single, double and triple mutant after 26 DAS when they are

fully grown; (B) Endoreduplication index of Col-0 and krp4/6/7 mutant; (C)-(F) Percentage of 2C,

4C, 8C and 16C nuclei in wild type and triple mutant. Endoreduplication index represents the

average number of endocycles undergone by a typical nucleus (EI = 0*2C+1*4C+2*8C+3*16C).

Error bars represent SE (n=3). An asterisk indicates a significant difference at *P<0.05 and

***P<0.001.

To study the effect of downregulation of KRP4, KRP6 and KRP7 on endoreplication in detail,

we measured the ploidy level during leaf development alternatively from 9 till 26 DAS in

the krp4/6/7 mutant. Our results showed no difference in DNA level in fully proliferating

leaves at 9 DAS, indicating that the effects of the mutation affect G1/S and G2/M transition

equally. Moreover from D11 onwards the data show advanced onset and faster rates of

20

30

40

50

60

70

% o

f n

ucl

ei

Col

krp4/6/7

2C

(C)

8 12 16 20 24 280

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DAS

8C

(E)

8 12 16 20 24 280

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(D)

Col

krp4

krp6

krp7

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7

krp6/

7

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6/7

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*

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8 12 16 20 24 280.3

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En

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krp4/6/7

(B)


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endoreduplication in the krp4/6/7 mutant compared to Col both contribute to the

increased ploidy levels observed in mature leaves (Figure 8B-F).

To answer whether simple rate amplification can explain the observed ploidy dynamics, we

constructed an elementary mathematical model describing the dynamical changes in the

respective ploidy fractions in order to quantitatively compare the kinetics of the endocycle

of Col and the krp4/6/7 mutant. Except for the 2C to 4C conversion all other processes

were described by irreversible mass-action kinetics with the rates proportional to the

substrate fractions (details in Methods section and Supplemental Text 1). By fitting the Col

and the triple mutant time dependent ploidy data with the model we obtained reliable

estimates of the first order rate constants for the various conversions except for the 16C to

32C conversion (Supplemental Text 1, Supplemental Figure 7A-J). The rate constants

(Indexed according to the reaction step with ‘1’ indicating the 2C to 4C, ‘2’ the 4C to 8C, ‘3’

the 8C to 16C, and the ‘f’ or ‘r’ referring to forward or reverse steps) for the triple mutant

(k1f=0.48 d-1, k1r=0.25 d-1, k2=0.10 d-1, k3=0.024 d-1) and Col (k1f=0.24 d-1, k1r=0.11 d-1,

k2=0.076 d-1, k3=0.0092 d-1) indicate an overall doubling of all conversion rate constants. A

direct comparison of the two resulting model versions demonstrates faster decrease of the

2C and 4C fractions combined with faster and stronger build-up of the 8C and 16C fractions

in the mutant (Figure 9A-D). Due to the complexity of the cell cycle machinery it is often

difficult to predict the effect of perturbations on both mitotic cycles and endocycles. We

therefore implemented a published mathematical model of the cell cycle in Arabidopsis

trichomes (Roodbarkelari et al., 2010). Simulating this model in a parameter regime that

produces endocycles showed indeed that a relatively small decrease of 20% in CKI levels

(Figures 10; details in Methods and Supplemental Text 1) results in faster oscillations in

accordance with the increased efficiency of the endocycle found for the krp4/6/7 mutant.

Our results therefore clearly show that decreased levels of KRPs promote

endoreduplication in leaves and inversely that KRP expression limits endoreduplication in

wild type plants.


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Figure 9. (A-D) Model predictions of dynamical ploidy fractions for WT and krp4/6/7. Blue and

red line represents WT and krp4/6/7, respectively.

Figure 10. Trichome cell cycle model with WT and lower CKI level.

Discussion

In plants, functional analysis of individual KRP genes is difficult because of the presence of

seven members in the family, which are likely to have redundant functions, compensating

the loss of each single gene. Differential expression studies of the KRP gene family

demonstrated the expression of various KRPs in different tissues as well as the existence of

all the KRPs in a single tissue (De Veylder et al., 2001; Ormenese et al., 2004). Similarly, we

observed differential expression patterns of all the KRPs during leaf development

suggesting a differential role of individual KRPs in the regulation of leaf growth. The

(A) (B)

(C) (D)


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presence of multiple CDK inhibitors in leaves can be predicted to regulate the activity of

various CDKs in different developmental stages.

To obtain more insight for the role of individual KRP, downregulation of an individual gene

is important. However, due to the functional redundancy of the KRP gene family

phenotypes are typically not observed in mutants of individual family members. Therefore,

most of the studies were based on over/mild/miss-expression of KRP genes (De Veylder et

al., 2001; Jegu et al., 2013; Jun et al., 2013; Schnittger et al., 2003; Verkest et al., 2005a).

These studies showed that the enhanced expression of KRPs negatively affect leaf growth

by inhibiting cell division. Therefore, to explore the function of KRP4, KRP6 and KRP7 genes

in leaf growth and development, we used a downregulation approach and studied single,

double and triple T-DNA insertion mutants for respective genes. Our result showed no

major changes in single mutants while concurrent silencing of two or three genes

accelerates leaf growth. This could be the reason of the functional similarity of KRPs in

plants (Torres Acosta et al., 2011). Similarly, a recent study has also demonstrated that

downregulation of multiple KRP genes increased plant growth (Cheng et al., 2013).

One of the important finding of our results is that the increased leaf size in the krp4/6/7

triple mutant was influenced by enhanced embryonic development which suggests that the

mutation in KRPs affects early development which ultimately results in enhanced organ

growth. Seed size is an important parameter for improving crop yield and the plants having

large seeds were reported to enhance plant growth and development and were competent

to survive under different environmental stress conditions (Harper et al., 1970; Kaydan

and Yagmur, 2008; Khurana and Singh, 2000). Moreover, previous studies in monocots

have shown a role of KRPs in seed development. Overexpression of KRP1 was reported to

reduce seed filling and affects the production of endosperm cells in rice (Barroco et al.,

2006). Moreover, KRP1 and KRP2 were found to inhibit CDK activity in maize endosperm

(Coelho et al., 2005). Our study opens a new field of research which can demonstrate the

role of KRPs in embryonic development as the specific role of KRPs in seed development is

not well defined.


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Furthermore, our study in leaves focusing in proliferating and expanding tissues however,

provides a clear insight into how cell cycle activity is affected and how this translates into

organ size differences. Kinematic analysis showed that the increased leaf growth was the

result of increased proliferation in double and triple mutants. Consistent with the growth

analysis, the transcriptome study also showed upregulation of cell cycle related genes.

KRPs were reported to interact with CDKA and/or CYCD, demonstrates that the key target

of KRPs is CDKA-CYCD complexes (Van Leene et al., 2010, Wang et al., 2006). Indeed,

downregulation of three KRPs showed enhanced expression of CDKA and CYCD4 in the

triple mutant. Curiously, the expression of other CYCDs such as CYCD2 and CYCD3 were

decreased. Recent study showed that KRP5 and CYCD3 has antagonistic activity (Jegu et al.,

2013) which was also reflected in our results as the expression of KRP5 was induced after

the inhibition of KRP4, KRP6 and KRP7. Remarkably, we also observed the increased

expression of the CYCA and CYCB family. It has been shown before that KRP1 and KRP2

repress CYCA-CDK activity in maize (Coelho et al., 2005) whereas the interaction with

CYCB was not observed. Increased expression of CDKB after the inhibition of three KRP

genes in the krp4/6/7 mutant suggests transcriptional interaction between CDKB and KRP.

In vitro pull-down assay has also indicated that KRP interacts with CYCD2/CDKB in

Arabidopsis (Nakai et al., 2006). Increased expression of CDKB1 and CDKB2 reveals that

downregulation of KRPs promote G2-M transition and therefore increase proliferation.

Remarkably, the downregulation of KRP4, KRP6 and KRP7 increased the expression of

KRP1, KRP2 and KRP5 in the triple mutant suggesting a functional compensation in the KRP

gene family. This could be the reason that the downregulation phenotype of KRP genes in

triple mutant was not as strong as the phenotype of the KRP overexpression lines (De

Veylder et al., 2001; Jun et al., 2013; Verkest et al., 2005a). Analogous to our results Cheng

et al. (2013) also demonstrated enhanced expression of different CDKs and cyclin genes in

the ick1/2/5/6/7 quintuple mutant.

Our results also showed the upregulation of the retinoblastoma-related (RBR) protein, a

transcriptional repressor for E2F/DP complex in the triple mutant. Increased expression of

RBR can be the result of high CDK activity as the phosphorylation of RBR by CDKs releases

RBR from E2F/DP and activates the expression of S phase genes (Boniotti and Gutierrez,


208

2001; Nakagami et al., 2002). Enhanced RBR expression in the triple mutant could activate

the E2F pathway. We also observed the enhanced expression of DEL3, a member of atypical

E2F family that encodes DP-E2F-Like Protein (Lammens et al., 2009). A previous study has

shown that DEL3 controls cell expansion by repressing cell wall biosynthesis genes in roots

and hypocotyls of Arabidopsis (Ramirez-Parra et al., 2004). Therefore, it is tempting to

suggest that the smaller cells of triple mutant are the result of increased expression of DEL3

which in turn inhibit cell expansion. Consistent with the observation of enhanced

expression of RBR and DEL, our results also showed increased expression of E2F target

genes such as MCM3, ICU2, POLA, TSO1, HTA6, KLP2 and ORC1 (de Jager et al., 2009)

(Supplemental Tables S5 and 6), suggests that the downregulation of KRPs upregulate E2F

pathway. We also found the upregulation of G2-M specific negative regulator of cell cycle

such as WEE1. DNA damage conditions were seen to induce the expression of WEE1 which

is putatively involved in the inhibitory phosphorylation of CDKs (De Schutter et al., 2007).

Our transcriptome results clearly showed the enhancement of DNA synthesis and repair

machinery in the triple mutant which can be correlated with the increased expression of

WEE1.

In addition to a stimulation of proliferation, the triple mutant also showed upregulation of

endoreplication (reviewed by De Veylder et al., 2011; Massonnet et al., 2011), which

suggests that together with G1-S, G2-M transition is also upregulated by inhibition of KRPs.

This is consistent with the study which showed that KRP2 suppress both cell cycle and

endocycle (De Veylder et al., 2001). Moreover, endocycle is regulated separately in

developmental window (Jacqmard et al., 1999) which could be the cause of an enhanced

endoreduplication in krp4/6/7. Secondly, CYCD3s have been reported to restrain endocycle

(Dewitte et al., 2007) and a recent study showed that KRP5 promote endoreduplication by

inhibiting CYCD3;1 (Jegu et al., 2013). Similarly, our transcript profiling showed enhanced

expression of KRP5 and downregulation of CYCD3;2 in krp4/6/7, which can also be

predicted as a cause of enhanced endoreplication. Additionally, mathematical simulation of

the cell cycle also provides a theoretical mechanism explaining a twofold rate-enhancement

in endoreplication by inhibition of KRPs.


209

Previous studies have shown that endoreduplication is positively correlated with cell size

where changes in ploidy levels affect cell size in leaves (del Pozo et al., 2006; Tojo et al.,

2009; Verkest et al., 2005a). In contrast, our study showed negative covariation between

endoreduplication and cell size where increased endoreplication was accompanied by

decreased cell area.

According to Green (1976) relative rate change of cell size is determined by the balance

between the relative surface extension and cell division rates. Therefore, it can be

predicted that the smaller cell size of krp4/6/7 is the result of increased cell proliferation

while constant leaf surface expansion. Moreover, previous studies have postulated that

reduced cell number cause increased cell size in leaves of plants overexpressing KRPs (De

Veylder et al., 2001; Verkest et al., 2005a) and this phenomenon was called as

compensation (Beemster et al., 2003; Ferjani et al., 2010; Horiguchi and Tsukaya, 2011;

Tsukaya, 2002). Our results showed enhanced cell proliferation and reduced cell size in the

leaves of krp4/6/7 mutant which seems to be opposite of the prototypic compensation.

Similarly, the more and smaller cells (msc) mutants have increased cell number and smaller

cells in leaves (Usami et al., 2009). This suggests that the increase in cell number can

negatively influence cell size during leaf development.



The Arabidopsis T-DNA insertion lines for KRP/ICK genes used in this study were krp4

(At2g32710, SAIL_248_B06), krp6-1 (At3g19150, SAIL_548_B03) and krp7-1 (At1g49620,

GK_841D12). Double and triple mutants of these T-DNA insertion lines were created by

crosses. The SAIL and GABI-Kat lines are in Col-0 background. Mutant and wild type seeds

were sterilized in 70% ethanol for 1 minute and 5% bleach for 10 minutes followed by

rinsing with water and sown on half-strength MS (Murashige and Skoog, 1962) medium

(Duchefa, The Netherlands) supplemented with 1% sucrose and 0.8% plant agar (Duchefa


210

Biochemie) in 150x25 mm round petri dishes (Falcon® tissue culture dishes, VWR). After

stratification at 4°C for 2 days plates were transferred to a growth chamber with an air

temperature of 22°C and shelves cooled to 19°C under a 16 h day [80-90 µmols-1m-2 s-1

photosynthetically active radiation (PAR), supplemented by fluorescent tubes (cool white,

brand)] and 8 h night regime.

Genotyping and gene expression analysis

Genomic DNA of T-DNA insertion lines and Col-0 was isolated from rosette leaves for

genotyping analysis by PCR. Total RNA of whole rosette at 1.04 stage (Boyes et al., 2001)

was extracted using Trizol Reagent (Life Technologies) followed by the purification with

RNeasy mini kit (Quiagen) and the quantity of RNA was measured with a nanodrop ND

1000 (Thermo Scientific). For RT-PCR, first-strand cDNA was synthesized from 2 µg of total

RNA according to “Maxima® First Strand cDNA Synthesis Kit” (Fermentas,

Cambridgeshire). The primer pairs for genotyping and RT-PCR are listed in supplemental

table S1 and S2, respectively. Primers for RT-PCR were designed using the AmplifX primer

designing tool.

Leaf growth analysis




fitted with a digital camera (Zeiss [AxioCam Cc1]). For phenotyping of mutants, leaf images

were taken on 26 DAS (days after stratification) whereas for the kinematic analysis images

were taken from 6 to 26 DAS. For each day leaf surface area of 10-25 leaves were measured

using ImageJ (http://rsbweb.nih.gov/ij/). Logarithmic values of means of leaf surface area

were used for locally fitting a 5 point quadratic function (Erickson, 1976) of which the first

derivative was used to determine the relative expansion rate.



211


We performed a kinematic analysis (De Veylder et al., 2001) of the abaxial epidermal cells

of 3-6 average leaves from 6 to 26 DAS as described by Nelissen et al. (2013). Leaves of

early days, i.e. 6-10 DAS, were stained with propidium iodide following the protocol of

Wuyts et al. (2010) and cell images were obtained with a Nikon C1 confocal microscope

using a Nikon Eclipse E600. Leaf samples of later days were cleared with 70% ethanol and

subsequently stored and mounted in 100% lactic acid on object slides for microscopy.

Abaxial epidermal cells located on top, middle and bottom part of the leaf were imaged

using DIC optics on a Zeiss Axio Scope A1 at 20x magnification fitted with a digital camera

(Zeiss [AxioCam Cm1]). The outlines of imaged epidermal cells were hand drawn on an LCD

tablet (Wacom drawing pad) connected to an iMac computer running ImageJ. Cell analysis

of drawn cells was done with automated image analysis software that measures the total

area of drawn cells and that counts the number of cells (Andriankaja et al., 2012). From

these data we calculated average cell area, estimated the number of cells per leaf by

dividing leaf blade area by cell area and stomatal index was calculated as the percentage of

stomata across all epidermal cells. We calculated cell division rates as the relative rate of

increase in cell number over time. For this, the logarithmic values of mean of cell number

were locally fitted with a 5 point quadratic function of which the first derivative was used

as the division rate.

Flow cytometric analysis

First leaf pair of wild type and mutant was harvested, frozen in liquid nitrogen, and kept at

-80°C until analysis. For flow cytometry analysis, nuclei were extracted by chopping 3 to 30

leaves with a razor blade in 200 μl of Cystain UV Precise P Nuclei extraction buffer (Partec),

supplemented with 800 μl of staining buffer. The mix was filtered through a 50 μm filter

and read through the Cyflow MB flow cytometer (Partec). The nuclei were analyzed with

the CyFlow flow cytometer and the FloMax software (Partec).


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Embryo and seed size measurements

Seeds of Col-0 and the krp4/6/7 mutant were stratified in darkness at 4°C for 4 days, and

then sown in potting mix (Tref EGO substrates, Moerdijk, The Netherlands, 5×5 cm pots),

filled with a mixture (1:1, v/v) of a loamy soil and organic compost at a humidity of 0.30 g

water/g dry soil. Pots were transferred to a controlled growth chamber with an air

temperature of 21/18°C and 50-55% humidity under a 16 h day (90-100 µmols-1m-2 s-1

PAR) and 8 h night regime. Siliques were harvested at stage 10 (Bowman, 1994) and the

seeds were dissected under the binocular to isolate embryos. Embryos were treated for 1 h

in Hoyer’s solution according to Ohto et al. (2005). The images of around 30-40 embryos

were obtained with DIC microscope and their areas were measured by ImageJ

(http://rsbweb.nih.gov/ij/).

Around 500 dried seeds from four different plants of wild type and mutant grown next to

each other were used to study seed size. Seed images were taken with a digital camera and

their areas were also measured by ImageJ. To study the effect of seed size on leaf growth in

mutant and wild type, seed size distribution of 400-450 seeds were analyzed. Seeds were

grouped according to their sizes and the median seed size was calculated for both wild type

and mutant.

Quantitative RT-PCR analysis

RNA was extracted from approximately 5 to 200 leaves using the Trizol Reagent (see above

for details). Real time PCR was performed using TaqMan® Universal Master Mix II with

UNG (Life Technologies). Multiplex PCR was performed with ACT 8 (Probe id

At02270958_gH) as an endogenous control and TaqMan® probes for all the KRP genes as

specified in supplemental table S1. Three technical and 4 to 5 biological repeats were

performed. The results were analyzed with the StepOne-Plus™ Real-Time Software.



213


Total RNA of the first leaf pair was isolated on 9 and 15 DAS using Trizol Reagent (Life

Technologies) and the quantity and integrity of the RNA was measured

spectrophotometrically on QIAxcel system (Qiagen). Library preparation was done using

the TruSeq® Stranded mRNA sample preparation 96 rcx kit (Illumina™) following the low

sample protocol according to Illumina™ guidelines. Briefly, approximately 2.5 µg of total

RNA was purified using RNA purification beads targeting the poly-A tail of the mRNA and

subsequently was fragmented by means of the enzymes provided in the kit. After the cDNA

synthesis adenylation of 3’ ends and ligation of the adaptors were employed. Adaptors

were ligated in 12-plex formations, allowing the pooling of 12 samples after the PCR

enrichment of the library. Subsequently, the library was quantified using PicoGreen® dye

(Life Technologies™). Thereafter 12 samples were pooled at equal concentrations to create

the eight pools. In order to accurately quantify the concentration in nM of our pools, the

Kapa SYBR® FAST universal qPCR kit (KAPA Biosystems ™) for Illunima™ sequencing was

used to quantify the number of the amplifiable molecules in the pools and the

Bioanalyzer® (Agilent Technologies™) to determine the average fragment size of our pools.

These both allowed optimizing the flow cell clustering and proceed with the run.

Data analysis

A preliminary analysis was performed by means CLC Genomics Workbench v.6 using

Arabidopsis thaliana (Col-0 TAIR10) sequence database (http://www.arabidopsis.org/) as

reference genome. The RNA-Seq analysis was carried out for sequence reads obtained from

mutant harvested at 9 and 15 DAS. Throughout the analysis with CLC default settings were

used. Briefly, after the trimming of the sequences they were mapped against the reference

genome with the default settings. The expression values were calculated based on “reads

per kilobase of exon model per million mapped reads” (RPKM) values (Mortazavi et al.,

2008). RNA-seq data was grouped accordingly and two group comparisons (unpaired)

were performed. The expression values were normalized by scaling to corresponding

controls and for comparisons of interest, moderated t statistics were calculated using the


214

Baggerley’s test and p values were corrected for multiple testing for each contrast

separately (Baggerly et al., 2003). Genes for which no counts were detected in all three

replicates for at least one of the genotype/time combinations, were discarded as not

detectable above the background. False discovery rate (FDR) corrected p-value < 0.05 and

log2 of fold change > 0.75 was used as a cutoff (Benjamini and Hochberg, 1995).

All significantly induced or repressed genes with known functions were classified into

groups based on gene ontology (GO) information obtained from the TAIR Database

(http://www.arabidopsis.org/) and overrepresented functions and gene enrichment

studies were carried out by Cytoscape using the BiNGO plugin (Maere et al., 2005).


Standard error was calculated from different replicates on each time point for leaf area, cell

area, cell number and stomatal index. Statistical analysis of leaf area, cell number, cell size

enoreduplication index, leaf series, seed and embryo size was conducted by t test on excel.

Model construction and analysis

An elementary model was defined to describe dynamical changes in ploidy fractions and

was subsequently implemented with Mathematica (www.wolfram.com/mathematica/).

The model represents the leaf as a single compartment with fractions of 2C, 4C, 8C, 16C,

and 32C nuclei as the state variables. Simple mass-action kinetic equations were assigned

to the various conversions with only the 2C 4C as a reversible process. The

corresponding ordinary differential equations were solved using the NDSolve function.

Parameter estimates were obtained through fitting of the experimentally obtained ploidy

data using the NMinimize function with default search algorithms and according to the

procedure in De Vos et al., 2011, with the 9 DAS data points as fixed initial fractions.

For the Arabidopsis trichome cell cycle model the published parameter set was used (cf.

Supporting Information in Roodbarkelari et al., 2010), with two changes. First the

parameter kssim (SIM synthesis rate) was set ten times higher to induce an endocyclic


215

regime (SPF and not MPF oscillating). To simulate a decrease in KRP levels the CKIT

production rate k11 was reduced by ten percent to 0.18. A stronger reduction leads to a

more pronounced effect eventually leading to the disappearance of the endocycle

oscillations when reducing by 50 %.

Supplemental Data

All supplemental data is listed below. Supplemental figures can be found at the end of the

chapter or available upon request. Supplemental text is also found at the end of the chapter

and tables are available upon request.

Supplemental Figure 1. Growth analysis of mutants.

Supplemental Figure 2. Ploidy distribution measurement.

Supplemental Figure 3. BiNGO analysis of the genes upregulated on 9 DAS.

Supplemental Figure 4. BiNGO analysis of the genes upregulated on 15 DAS.

Supplemental Figure 5. BiNGO analysis of the genes downregulated on 9 DAS.

Supplemental Figure 6. The position of T-DNA insertion at in krp7-1 (GK_841D12) and

RNAseq mapping of KRP7 gene in Col-0 and krp4/6/7.

Supplemental Figure 7. Model for time dependent ploidy level.

Supplemental Table S1. Probes used to perform qPCR of seven Arabidopsis KRP.

Supplemental Table S2. Primers for genotyping of SAIL and GABI-Kat lines.

Supplemental Table S3. Primers for RT-PCR.

Supplemental Table S4. Differentially expressed genes in krp4/6/7 compared to Col-0 on 9

and 15 DAS.

Supplemental Table S5. Overrepresentation analysis of upregulated genes on 9 DAS in

krp4/6/7 compared to Col-0.

Supplemental Table S6. Overrepresentation analysis of upregulated genes on 15 DAS in


Supplemental Table S7. Overrepresentation analysis of downregulated genes on 9 DAS in



216

Supplemental Text 1. The text describes the reactions involved which represent the

mechanical basis. This in accordance with the fact that doubling the DNA content to 4C

level can be reverted by cell division but not any longer at higher ploidy levels.

Acknowledgments

We thank Sevgi Oden for the help in drawing cells for kinematic analysis. This work was

supported by a concerted research activity (GOA) research grant, ‘A Systems Biology

Approach of Leaf Morphogenesis’ from the research council of the University of Antwerp

and an Interuniversity Attraction Poles (IUAP) from the Belgian Federal Science Policy

Office (BELSPO). Dirk De Vos was funded by a return grant from BELSPO and Shweta Kalve

by a training grant from the Department of Science and Education of the Flemish

Government.

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227

Supplemental Figure 1. Growth analysis of mutants: (A) leaf area; (B) Cell size; (C) Cell number;

(D) Stomatal index of the wild type (Col-0) and the single (krp4, krp6, krp7), double (krp4/6, krp4/7,

krp6/7) and triple mutant (krp4/6/7). For leaf area measurements 20-100 leaves whereas for

cellular measurements 3-9 leaves were used. Error bars represent standard error. An asterisk

indicates a significant difference at *P<0.05, **P<0.01 and ***P<0.001.

Supplemental Figure 2. Ploidy distribution

measurement: Endoreduplication index of first

leaf pair of Col-0, single, double and triple mutant

after 26 DAS when they are fully grown.

Endoreduplication index represents the average

number of endocycles undergone by a typical

nucleus (EI = 0*2C+1*4C+2*8C +3*16C). Error bars

represent standard error (n=3). An asterisk

indicates a significant difference at *P<0.05 and

**P<0.01. **P<0.01.

Col

krp4Col

krp6Col

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krp4/

6Col

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7Col

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6/7

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228

(A)

(B)

Supplemental Figure 6. (A) Four exons of KRP7 gene and the position of T-DNA insertion at third

exon in krp7-1 (GK_841D12); (B) RNAseq mapping of KRP7 gene in Col-0 and krp4/6/7 where short

red lines represents the sequence reads of exons.

KRP7_At1g49620

GK_841D12


229

Supplemental Figure 7. Model for time dependent ploidy level: (A-E) WT ploidy data (circles)

fitted to simple model (lines) and (F-J) krp4/6/7 ploidy data fitted.

Supplemental Text 1.

The following system of ordinary differential equations was used to simulate the dynamical

changes in the fractions of 2C, 4C, 8C, 16C, and 32C nuclei. The latter are represented by the

state variables )(2 tCX , )(4 tCX , )(8 tCX , )(16 tCX and )(32 tCX . Basic first order rate

expressions were used to describe the respective conversions, with reversible steps only

for the 2C to 4C reaction:

(A)

(B)

(C)

(D)

(E)

(F)

(G)

(H)

(I)

(J)


230

)(16)(32

)(16)(8)(16

)(8)(4)(8

)(4)(4)(2)(4

)(4)(2)(2

4

43

32

211

11

tCXkdt

tCdX

tCXktCXkdt

tCdX

tCXktCXkdt

tCdX

tCXktCXktCXkdt

tCdX

tCXktCXkdt

tCdX

rf

rf

The equations were numerically integrated with the NDSolve function of Mathematica 7,

using the 9 day ploidy fractions as initial conditions. The NMinimize function was used with

the sum of the squared differences between experimental and predicted fractions as the

objective function to be minimized (final sum of the squares for the final WT fit: 0.054, for

the triple mutant: 0.070). Parameter constraints were set to (0.0001, 1) intervals to speed

up calculations.

Chapter 5

Mild overexpression of CDKB2;2 accelerates plant

growth in Arabidopsis thaliana

Shweta Kalve1, Markakis Marios Nektarios1, Arp Schnittger2 and

Gerrit T.S. Beemster1*


2Department of Developmental Biology, University of Hamburg, Germany


This chapter is an early draft for a publication

Contribution of S.K.- Performed most experiments and wrote the manuscript

Effect of mild overexpression of CDKB2;2

233

Abstract

Cyclin-dependent kinases (CDKs) are major regulators of the eukaryotic cell cycle. Here, we

focused on the role of a B2-type plant specific cyclin-dependent kinase on leaf growth. We

have used the CDKA;1 promoter for moderate overexpression of CDKB2;2 in Arabidopsis

thaliana. Our results clearly demonstrate that the enhanced expression of CDKB2;2

promotes leaf growth and development. Kinematic analysis revealed that increased cell

proliferation was entirely responsible for enhanced leaf growth as CDKB2;2 was not found

to affect the cell size in leaves. Additionally, increased 2C DNA content in leaves also

suggests that overproduction of CDKB2;2 increases the mitotic cycle while reducing the

endocycle. Improved growth was not only restricted to leaves, it was also observed that the

whole shoot and root growth was also accelerated in response to enhanced CDKB2;2

expression. Interestingly, we found that the enhanced leaf growth in PROCDKA;1:CDKB2;2 was

influenced by increased seed and embryo size which shows that the stimulation of CDKB2;2

promotes embryo development which results in larger organs. In addition, moderate

induction of CDKB2;2 resulted in enhanced cytokinin signaling. Thus, our results show that

CDKB2;2 promotes embryonic development in a hormone-dependent manner, which

further translates into enhanced plant growth.


234

Introduction Organ growth in multicellular organisms is tightly controlled by two overlapping

processes: cell division and expansion (Gonzalez et al., 2012). Cell division usually occurs

as a part of unidirectional and well-regulated process called cell cycle. The cell cycle is an

ordered set of events that drives the increase of cell number. The four distinct phases

recognized in cell cycle are G1 (Gap 1 Phase), S (Synthesis Phase), G2 (Gap 2 Phase) and M

(Mitosis Phase) where G1 and G2 are checkpoints for entry into the next phase, DNA

replication occurs in S phase whereas in M phase cell divides into two daughter cells

through mitosis (Dewitte and Murray, 2003; Inze and De Veylder, 2006; Inze et al., 1999).

The plant cell cycle is controlled by the activity of complexes formed of CDKs (cyclin

dependent kinases) catalytic subunit and CYCs (cyclins) regulatory subunit. Plant CDKs are

classified in eight classes namely CDKA to CDKG and CDK-Like kinases- CKLs where CDKA

and CDKB are two largest classes among all the CDKs and important for cell cycle

regulation (Boruc et al., 2010; Inze and De Veylder, 2006; Menges et al., 2005; Tank and

Thaker, 2011).

In Arabidopsis, A-type CDK is encoded by a single copy gene (CDKA;1) which is a functional

homolog of yeast Cdc2/Cdc28p and mammalian Cdk1/Cdk2/Cdk3 proteins that contains

the conserved PSTAIRE motif essential for cyclin binding. CDKA is expressed constitutively

throughout the cell cycle and plays a crucial role at both transitions from G1 to S and G2 to

M (Hemerly et al., 1995; Nowack et al., 2012). CDKBs are plant specific and shown to play

pivotal role in mitotic phase. They are classified into two subtypes: CDKB1 (CDKB1;1 and

CDKB1;2) and CDKB2 (CDKB2;1 and CDKB2;2). The PSTAIRE cyclin-binding motif in CDKA

is replaced with PPTALRE or P(S/P)TTLRE in CDKB1 and CDKB2, respectively (Boudolf et

al., 2001; Vandepoele et al., 2002). The expression of CDKB1 is found from late S to the M

phase while CDKB2 is more restricted from G2 to M phase (Menges et al., 2005; Porceddu et

al., 2001)

In last decades, CDKA has been studied extensively whereas much less is known about

CDKB in cell cycle progression. Arabidopsis plants overexpressing a dominant negative


235

allele of CDKB1;1 had leaves with fewer but larger cells which also had a higher

endoreduplication (Boudolf et al., 2004b). Additionally, these lines showed defects in

meristemoid division (Boudolf et al., 2004a). Similarly, stomatal abnormalities were also

seen in the cdkb1;1 cdkb1;2 double mutant (Xie et al., 2010). The role of CDKB2 in meristem

organization and proper cell cycle progression has been explained in Arabidopsis thaliana.

Silencing both CDKB2 using artificial microRNA caused dwarf plants with an abnormal

shoot apical meristem. Moreover, improper cellular organization and morphology was

observed in the CDKB2 overexpression and knockdown line (Andersen et al., 2008).

Recently, it was described that the role of CDKB2 differs between Arabidopsis and rice in

response to DNA damage where DNA damage in rice neither reduce the expression of

Orysa;CDKB2;1 nor promote endoreplication (Endo et al., 2012).

In the present study, we investigated the function of CDKB2 in Arabidopsis thaliana by

means a mildly overexpressed line of CDKB2;2 with a CDKA;1 promoter. Our results

showed that the enhanced expression of CDKB2;2 accelerates plant growth and increases

organ size. Moreover, we found that the larger leaf size of the overexpression line was the

result of increased cell proliferation. Interestingly, our work demonstrates that the bigger

leaves were at least partly a consequence of larger seeds and embryos.

Results

Mild overexpression of CDKB2;2 enhances plant growth

As previous studies have demonstrated that CDKB2 is essential for proper development of

the shoot apical meristem (SAM) where silencing of CDKB2;1 and CDKB2;2 through

amiRNA cause abnormal development of SAM and overall shoot growth reduction

(Andersen et al., 2008). Curiously, overexpression of two CDKB2s under the control of 35S

promoter also showed phenotype similar to amiRNA lines (Andersen et al., 2008) which

could be the effect of gene silencing. Therefore, we used mild overexpression of CDKB2;2

with a CDKA;1 promoter to study the effect of overproduction of CDKB2 on plant growth.


236

Interestingly, contrary to 35S:CDKB2;2 (Andersen et al., 2008), the mild overexpression line

PROCDKA;1:CDKB2;2 led to enhanced plant growth (Figure 1A and 1B).

Figure 1. Growth analysis of the mild overexpression line: (A) Image of rosette of Col-0 and

PROCDKA;1:CDKB2;2 plants grown for 22 DAS; (B) Image of leaf series after 26 DAS; (C) Rosette area

(n=30-40); (D) Leaf blade area (n=35-40); (E) Leaf blade length; (F) Leaf blade width; (G) Root

length from 3 to 12 DAS (n=14); (H) Root elongation rate. Error bars represent standard error. An

asterisk in panels C-F indicates a significant difference at ***P<0.001.

Col CDKB2;20

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DAS

Col

CDKB2;2

(H)

Col

ProCDKA;1:

CDKB2;2

3 6 9 120

10

20

30

40

50

60 (G)

Ro

ot

len

gth

(m

m)

DAS

Col

CDKB2;2


237

In the first step to study in more detail the effect of mild overexpression of CDKB2;2 on

plant growth, we measured the rosette size of in vitro grown Arabidopsis PROCDKA;1:CDKB2;2

and Col-0 after 22 DAS. We found an increase of 23% in rosette area (p = 0.000; Figure 1C).

The effect of the mild overexpression (OE) on the mature leaf blade area of the first leaf

pair after 26 DAS closely reflected the response of the rosette area, as the leaf area

increased by 22% (p = 0.000; Figure 1D). An increase of the total leaf area can be due to the

change in the length and/or the width of the leaf. Therefore, to examine the effect of

CDKB2;2 on leaf size, we measured leaf length and width of the first leaf pair. Results

demonstrated that the final increase in leaf size was the result of a significant increase in

leaf length as well as width (Figure 1E and 1F). As there was significant increase in aerial

part of the PROCDKA;1:CDKB2;2 line, we studied the effect on root growth as well.

Remarkably, similar to the shoot, enhanced root growth was also observed in mild OE line.

Root elongation rate was up to 48% higher in mild OE line at the beginning of root growth

where PROCDKA;1:CDKB2;2 grew at the rate of 134 mm/h. Root growth in mild OE line

exponentially increase till 8 DAS and declined gradually after 9 DAS. As the result of high

elongation rate, root length was increased by 8% in the PROCDKA;1:CDKB2;2 line compared to

wild type after 12 DAS (Figure 1G and 1H).

In conclusion, macroscopic growth analysis showed that the mild overexpression of

CDKB2;2 promotes plant growth.

Enhanced leaf growth of PROCDKA;1:CDKB2;2 is mainly due to an increase in

cell number

To study the effect of overexpression of CDKB2;2 on cell division and expansion during leaf

growth in more detail, we performed a kinematic analysis (De Veylder et al., 2001). To this

end, leaves 1 and 2 were harvested daily from 6 to 26 days after stratification, allowing for

measurements of leaf blade area, size of abaxial epidermal cells, number of cells per leaf,

stomatal index and the rates of division and expansion. Leaf area increased exponentially

till 12 DAS. Interestingly, there was a significant increase (p = 0.000) in leaf area in

PROCDKA;1:CDKB2;2 from the beginning of the observations i.e. on 6 DAS in comparison to


238

wild type (Figure 2A). Leaf expansion rates were lower in the OE line than in the wild type

plans throughout development (Figure 2B), so that the initial difference in leaf blade area

on D6 (127%) decreased to 36% in mature leaves on 26 DAS.

Figure 2. Kinematic analysis of leaf growth of the first leaf pair of Col-0 and

PROCDKA;1:CDKB2;2 plants: (A) Leaf blade area; (B) Relative leaf expansion rate (RLER); (C)

Epidermal cell number on the abaxial side of the leaf; (D) Cell division rate (CDR); (E) Epidermal

cell area; (F) Stomatal index. Insets show the same data on a linear scale to show absolute

differences. 8-22 leaves were used to measure leaf area and cellular analysis was done on 3-6

leaves. Error bars represent standard error.


239

Cellular measurements showed that there was no difference in cell area between wild type

and OE line (Figure 2E), which shows that the increase in leaf area was entirely due to

increased cell numbers. Remarkably, the OE line had around 2-fold (p = 0.003) more cells

than Col-0 from the beginning at 6 DAS. From 6 till 12 DAS cell number increased

exponentially in both wild type and mutant until the final number was reached about

10835+685 and 20598+1988, respectively (Figures 2C). In analogy to the cell expansion

rates, cell division rates tended to be higher in Col-0 (Figure 2D). Indeed there is a

significant increase of the average cell division rates calculated over the interval between 6

and 10 DAS by 10% (p = 0.000). In addition, the timing of the transition from division to

expansion was advanced by one day in the OE line (Figure 2D). As a consequence of the

lower division rates and the shorter duration of proliferation the initial difference in cell

number (86% at D6) declined to 40% at maturity.

CDKB2 OE also affected the development of stomata. From 6 till 19 DAS there was no

significant difference in stomatal index between wild type and OE line, but from 20 DAS

there was a clear increase (Figure 2F), suggesting that stomatal development continued

longer in the OE line. Overall, kinematic analysis revealed that the increased cell

proliferation prior to D6 was responsible for the increase leaf size in PROCDKA;1:CDKB2;2.

We next performed flow-cytometry analysis to assess the effect of the overexpression of

CDKB2 on endoreduplication. Ploidy analysis revealed reduction of endoreduplication in

leaves of OE line where the fraction of cells with a DNA content of 2C and 4C increased,

which suggests that enhanced expression of CDKB2;2 inhibits endoreplication (Figure 3A

and 3B).


240

Figure 3. Ploidy distribution measurement in Col and PROCDKA;1:CDKB2;2: (A)

Endoreplication index of first leaf pair of Col-0 and PROCDKA;1:CDKB2;2 after 26 DAS when they are

fully grown; (B) Percentage of 2C, 4C, 8C and 16C nuclei. Endoreduplication index represents the

average number of endocycles undergone by a typical nucleus (EI = 0*2C+1*4C+2*8C+3*16C).

Error bars represent SE (n=3).

CDKB2;2 overexpression line makes larger seeds and embryos

The difference in leaf area between OE line and wild type was observed from the beginning

of our leaf growth observations (Figure 2A), which suggested that the difference was

established prior to the leaf development. Therefore, we analyzed seed and embryo size to

investigate if the variation at early stage of development between wild type and OE line

could already be determined during seed development on the mother plant. Indeed, we

found 11% increase in seed (p = 0.000) (Figure 4A and B) and embryo size (p = 0.008)

(Figure 4C and D) in OE line compared to wild type, respectively.

We have established a strong correlation between seed and embryo size with the size of

leaves formed after germination (Previous Chapter). Therefore we conclude that mild

overexpression of CDKB2;2 increases embryo size, which after germination leads to a

seedling that produces larger primordia that grow out into larger leaves.

Col CDKB2;20

20

40

60

80

100

Col CDKB2;2

%

2C

4C

8C

16C

(B)

Col CDKB2;20.0

0.4

0.8

1.2

1.6

Col

En

do

red

up

lica

tio

n

Ind

ex

(A)

CDKB2;2


241

Figure 4. Analysis of seed and embryo size: (A) Seed image of Col-0 and PROCDKA;1:CDKB2;2; (B)

Seed size (n=400-500); (C) Embryo image; (D) Embryo size (n=30-40). Error bars represent

standard error. An asterisk indicates a significant difference at **P<0.01 and ***P<0.001.


To further understand the molecular mechanism responsible for cellular changes, we

studied transcript profiling in proliferating and expanding leaves at 9 and 15 DAS,

respectively. After mapping the reads, normalizing the data between samples and

statistical analysis, a total of 231 genes were differentially expressed in PROCDKA;1:CDKB2;2

(FDR corrected- p value < 0.05 and log2 fold change > 0.75). Statistical analysis showed 90

and 43 upregulated and 38 and 63 downregulated transcripts at 9 and 15 DAS, respectively

(Figure 5A).

ProCDKA;1:CDKB2;2Col(A)

(C)Col CDKB2;2

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Col

***

Rel

ati

ve

See

d s

ize

(B)

CDKB2;2

Col CDKB2;20.0

0.2

0.4

0.6

0.8

1.0

1.2

Col CDKB2;2

**

R

ela

tiv

e

Em

bry

o s

ize

(D)


242

Figure 5A. Functional analysis of genes: Overlap

between genes expressed on 9 and 15 DAS in

PROCDKA;1:CDKB2;2. Values indicated in the Venn diagram

represents the number of genes expressed on the

respective day. Numbers represented by up and down

arrow shows up and downregulation of genes,

respectively. Transcripts were considered differentially

expressed if log2 of fold change > 0.75 and FDR-

corrected p value < 0.05.

To better understand the link between transcriptional changes and the observed growth

phenotypes, we addressed the question what are the biological processes that are

regulated by mild overexpression of CDKB2;2. For this we performed a gene enrichment

analysis using PageMan on the genes that were up or downregulated. Few genes related to

cell wall, cell cycle, transport, RNA regulation and cytokinin and ethylene metabolism were

changed which were distributed among up and downregulated genes on 9 and 15 DAS

(Figure 5A). As kinematic analysis revealed that there were only small changes in cell

division and expansion rates between wild type and PROCDKA;1:CDKB2;2, which was also

reflected in transcriptome analysis where only few genes related to cell division and cell

wall were altered. The significant increase in the expression of CDKB2;2 clarifies the

upregulation of the gene in both developmental stages in PROCDKA;1:CDKB2;2. Inhibition of

cell cycle inhibitor KRP7 (De Veylder et al., 2001) and B-type cell cyclin CYCB3;1 (Menges

et al., 2005) was found on 15 DAS. Genes related to cell wall degradation and modification

were both up and downregulated (Supplemental Table S2). Transcripts encoding for

arabinogalactan protein, AGP1 was up while AGP14 was downregulated on 15 DAS. Pectin

biosynthesis gene XGD1 and pectin esterases were upregulated on both days (Wolf et al.,

2012). Cytokinin biosynthesis gene IPT3 (Takei et al., 2004) and the cytokinin degradation

related gene CKX4 (Nishiyama et al., 2011) were upregulated on 9 DAS. Moreover, A-type

response regulators, ARR5 and ARR16, act as a negative regulator for cytokinin signaling

(Ren et al., 2009; To et al., 2004) were upregulated on 9 and 15 DAS, respectively

(Supplemental Table S2). Expression of ethylene biosynthesis gene ACS11 (Tsuchisaka and

9 DAS

15 DAS

3

103

125

128

90

38

106

43

63


243

Theologis, 2004) was enhanced on 15 DAS while the gene encoding for the transcription

factor ERF-104 was decreased on 9 DAS (Supplemental Table S2).

These minor changes in transcriptome data are consistent with the small effects observed

by the kinematic and flow-cytometry data and reinforce the conclusion that the main

effects of CDKB2;2 overexpression occur at embryonic stage (Figure 4), which is further

translated in enhanced organ growth.


244

Figure 5B. Functional analysis with MapMan categories and the PageMan overrepresentation tool.

Significantly enriched or depleted functional groups are represented in blue or red, respectively

and treatments are mentioned on top.


245

Discussion

CDKB is the only plant specific CDK family. It has been reported that silencing of the

CDKB2s as well as overexpression by 35S promoter caused abnormal SAM formation and

reduced plant growth (Andersen et al., 2008). We hypothesize that more modest

upregulation may be less detrimental for plant development. Indeed, we show that a mild

overexpression of CDKB2;2 in fact enhances plant growth. Moreover, role of CDKB2 in leaf

growth has not been explored in detail. One study showed that overexpressing a dominant

negative CDKB1;1 reduced the number of cells while increasing the cell size as well

endoreplication (Boudolf et al., 2004b). Here, we show that in addition to CDKB1, CDKB2

affects leaf growth as our study demonstrate that a mild stimulation of CDKB2;2 increases

leaf growth. Interestingly and in contrast to Boudolf et al. (2004b) no change in cell size

was observed. So, the enhanced leaf growth was only influenced by increased cell

proliferation.

One of the main findings of our research was that increased CDKB2 expression stimulates

seedling growth through enhanced embryonic development. The data on leaf development

are consistent with the idea that a larger seedling would have a larger SAM allowing for a

larger number of cells to be recruited in the primordium, which influence the later stage of

leaf development. In support of this hypothesis, previous studies have shown that the

number of cells in leaf primordium affects the final leaf size. Mutation in SWP, encodes for

RNA polymerase II transcription mediator, reduced leaf size by decreasing cell size. It was

found that the reduction in cell number was established at an early stage of primordium

initiation (Autran et al., 2002). Moreover, according to the AtGenExpress developmental

dataset, CDKB2s are highly expressed during the development of seeds and shoot apical

meristem (Schmid et al., 2003). Additionally, manipulation in CDKB2 expression was also

seen to inhibit growth of the shoot apical meristem (Andersen et al., 2008). This suggests

that the CDKB2 plays an important role in the seed development and organ initiation stage

in plants.


246

Another important finding of moderate upregulation of CDKB2;2 was the decreased

endoreplication, which suggests that a decreased activity of CDKB2;2 is necessary for the

initiation of endoreplication. Consistently, downregulation of CDKB2 was found to have

higher DNA content (Andersen et al., 2008, Adachi et al., 2011). On the other hand opposite

to our results overexpression of CDKB2 was also found to increase endoreplication in

Arabidopsis (Andersen et al., 2008). Moreover, endoreplication is often associated with

differentiation processes (Breuer et al., 2010; De Veylder et al., 2011), and thus, the results

of the ploidy analysis are consistent with a delayed onset of cell differentiation in CDKB2;2-

overexpressing plants where upregulation of CDKB2;2 stimulates stomatal development by

extending the time frame during which the stomates are formed.

Cytokinin is essential for controlling cell division by modulating expression of D-type cyclin

(Riou-Khamlichi et al., 1999). Moreover, it controls initiation of shoot apical meristem, leaf

and root differentiation, chloroplast biogenesis, stress tolerance and inhibition of leaf

senescence (Haberer and Kieber, 2002; Riefler et al., 2006; Zwack and Rashotte, 2013). One

of the more prominent features in our transcriptome study was the upregulation of

cytokinin synthesis and feedback regulator (Supplemental Table S2), which suggest that

the mild overexpression of CDKB2;2 stimulate cytokinin production which enhances cell

division and ultimately increases leaf growth. Consistent with our results, Andersen et al.

(2008) has also found that the inhibition of CDKB2s downregulates cytokinin level in

Arabidopsis thaliana. In conclusion, our study clearly shows that CDKB2;2 is an important

regulator for embryonic development. It promotes cell division in leaves in a hormone-

dependent manner. Moreover, detailed cellular and molecular analysis at shoot apical

meristem can resolve the mechanism that causes enhanced leaf growth and can also

highlight other cell cycle regulators that promote the activity of CDKB2;2.


247



The Arabidopsis PROCDKA;1:CDKB2;2 line was used to study the role of CKDB2;2 in plant

growth. The overexpression line is in Col-0 background and was kindly provided by Arp

Schnittger (CNRS, France). Seeds from CDKB2;2 overexpression line and wild type were

sterilized in 70% ethanol for 1 minute and 5% bleach for 10 minutes followed by rinsing

with water and sown on half-strength MS (Murashige and Skoog, 1962) medium (Duchefa,

The Netherlands) supplemented with 1% sucrose and 0.8% plant agar (Duchefa

Biochemie) in 150x25 mm round petri dishes (Falcon® tissue culture dishes, VWR) for

shoot and 120x120x17 mm square petri dishes (Greiner Bio One) for root growth. After

stratification at 4°C for 2 days plates were transferred to a growth chamber with an air

temperature of 22°C and shelves cooled to 19°C under a 16 h day [80-90 µmols-1m-2 s-1

photosynthetically active radiation (PAR), supplemented by fluorescent tubes (cool white, ,

LUMILUX, Germany)] and 8 h night regime.

Leaf and root growth analysis




fitted with a digital camera (Zeiss [AxioCam Cc1]). For phenotyping of mutants, leaf images

were taken on 26 DAS (days after stratification) whereas for the kinematic analysis images

were taken from 6 to 26 DAS. For each day leaf surface area of 10-25 leaves were measured

using ImageJ 1.48v (http://rsbweb.nih.gov/ij/). Logarithmic values of means of leaf surface

area was used and locally fitted with a 5 point quadratic function (Erickson, 1976) of which

the first derivative was used to determine the relative expansion rate.



248

For the root growth, plants of Col-0 and PROCDKA;1:CDKB2;2 were grown on vertically

inclined petriplates for 12 DAS and root length was measured every day at the same time

and root length and elongation rate was measured using ImageJ.


We performed a kinematic analysis of the abaxial epidermal cells of 3-6 average leaves

from 6 to 26 DAS as described by Nelissen et al. (2013). Leaves of early days, i.e. 6-10 DAS,

were stained with propidium iodide followed by the protocol of Wuyts et al. (2010) and cell

images were obtained with a Nikon C1 confocal microscope using a Nikon Eclipse E600.

Leaf samples of later days were cleared with 70% ethanol and subsequently stored and

mounted in 100% lactic acid on object slides for microscopy. Epidermal cells located on

top, middle and bottom were imaged using DIC optics on a Zeiss Axio Scope A1 at 20x and

40x magnification fitted with a digital camera (Zeiss [AxioCam Cm1]). The outlines of

imaged epidermal cells were hand drawn on an LCD tablet (Wacom drawing pad)

connected to an iMac computer running ImageJ. Cell analysis of drawn cells was done with

automated image analysis software that measures the total area of drawn cells and that

counts the number of cells (Andriankaja et al., 2012). From these data we calculated

average cell area, estimated the number of cells per leaf by dividing leaf blade area by cell

area and stomatal index was calculated as the percentage of stomata across all epidermal

cells. We calculated cell division rates as the relative rate of increase in cell number over

time. For this, the logarithmic values of mean of cell number were locally fitted with 5 point

quadratic function of which the first derivative was used as the division rate.

Flow cytometric analysis

First leaf pair of wild type and OE (overexpression) line was harvested, frozen in liquid

nitrogen, and kept at -80°C until analysis. For flow cytometry analysis, nuclei were

extracted by chopping 3 to 5 leaves with a razor blade in 200 μl of Cystain UV Precise P

Nuclei extraction buffer (Partec), supplemented with 800 μl of staining buffer. The mix was

filtered through a 50 μm filter and read through the Cyflow MB flow cytometer (Partec).


249

The nuclei were analyzed with the CyFlow flow cytometer and the FloMax software

(Partec).

Embryo and seed size measurements

Seeds of Col-0 and PROCDKA;1:CDKB2;2 line were stratified in darkness at 4°C for 4 days, and

then sown in potting mix (Tref EGO substrates, Moerdijk, The Netherlands, 5×5 cm pots),

filled with a mixture (1:1, v/v) of a loamy soil and organic compost at a humidity of 0.30 g

water /g dry soil. Pots were transferred to a controlled growth chamber with an air

temperature of 21/18°C and 50-55% humidity under a 16 h day (90-100 µmols-1m-2 s-1

PAR) and 8 h night regime. Siliques were harvested at stage 10 (Bowman, 1994) and the

seeds were dissected under the binocular to isolate embryos. Embryos were treated for 1 h

in Hoyer’s solution according to Ohto et al. (2005). The images of around 30-40 embryos

were obtained with DIC microscope and their areas were measured by ImageJ.

Around 500 dried seeds from four different plants of wild type and mutant grown next to

each other were used to study seed size. Seed images were taken with digital camera and

their areas were also measured by ImageJ.


To study the effect of overexpression of CDKB2;2 on leaf growth, primordia of leaves 1 and

2 were dissected under a binocular at 9 and 15 DAS. Total RNA of three replicates each

containing around 50-250 leaves was isolated using Trizol Reagent (Life Technologies) and

the quantity and integrity of the RNA was measured spectrophotometrically on QIAxcel

system (Qiagen). Library preparation was done using the TruSeq® Stranded mRNA sample

preparation 96 rcx kit (Illumina™) following the low sample protocol according to

Illumina™ guidelines. Briefly, approximately 2.5 µg of total RNA was purified using RNA

purification beads targeting the poly-A tail of the mRNA and subsequently was fragmented

by means of the enzymes provided in the kit. After the cDNA synthesis adenylation of 3’

ends and ligation of the adaptors were employed. Adaptors were ligated in 12-plex


250

formations, allowing the pooling of 12 samples after the PCR enrichment of the library.

Subsequently, the library was quantified using PicoGreen® dye (Life Technologies™).

Thereafter 12 samples were pooled at equal concentrations to create the pool. In order to

accurately quantify the concentration in nM of our pools, the Kapa SYBR® FAST universal

qPCR kit (KAPA Biosystems ™) for Illunima™ sequencing was used to quantify the number

of the amplifiable molecules in the pools and the Bioanalyzer® (Agilent Technologies™) to

determine the average fragment size of our pools. In order to precede with the run the

HiSeq 1500 was used in the rapid mode together with the TruSeq® Rapid SBS Kit for 50

cycles, to sequencing the samples.

Data analysis

Transcriptome analysis ware performed by means of CLC Genomics Workbench v.6 using

Arabidopsis thaliana (Col-0 TAIR10) sequence database (http://www.arabidopsis.org/) as

reference genome. The RNA-Seq analysis was carried out for sequence reads obtained from

mutant harvested at 9 and 15 DAS. Briefly, after the trimming of adaptors from the

sequences, they were mapped against the reference genome. The expression values were

calculated based on “reads per kilobase of exon model per million mapped reads” (RPKM)

values (Mortazavi et al., 2008). RNA-seq data was grouped accordingly and two group

comparisons (unpaired) were performed. The expression values were normalized by

scaling to corresponding controls and for comparisons of interest, moderated t statistics

were calculated using the Baggerley’s test and p values were corrected for multiple testing

for each contrast separately (Baggerly et al., 2003). False discovery rate (FDR) corrected p

value < 0.05 was used as a cutoff (Benjamini and Hochberg, 1995). Gene enrichment

analysis of all differentially expressed genes was carried out by PageMan (Usadel et al.,

2006).


Standard error was calculated from different replicates on each time point for rosette area,

leaf area, leaf length, leaf width, root length, cell area, cell number and stomatal index.


251

Statistical analysis of rosette area, leaf area, leaf length, leaf width, seed and embryo size

was conducted by t test on excel.

Supplemental Data

The following materials are available upon request.

Supplemental Table S1. All the genes for which expression was detected in all three

replicates of at least one treatment.

Supplemental Table S2. Significant genes according to cutoff (FDR p value<0.05, log2 fold

change>0.75).

Acknowledgments




Policy Office (BELSPO). Shweta Kalve was funded by a training grant from the Department

of Science and Education of the Flemish Government.

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Regulation of cell proliferation in the stomatal lineage by the Arabidopsis MYB FOUR LIPS

via direct targeting of core cell cycle genes. Plant Cell 22, 2306-2321.

Zwack PJ, Rashotte AM. 2013. Cytokinin inhibition of leaf senescence. Plant Signal Behav

8, e24737.

Chapter 6

General Discussion and Future Perspectives

General discussion and future perspectives

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Why Leaf Growth is Important?

The world population is predicted to increase by 2 billion over the next 36 years, which

extrapolates to 9 billion people by 2050. FAO’s (The Food and Agriculture Organization of

the United Nations) evaluation also shows the requirement to increase food production by

60% by 2050. Moreover, rising consumption of meat, dairy products and bio-fuel will also

require more agricultural growth (Godfray et al., 2010; Tilman et al., 2011). On the other

hand, this expected rapid increase in global food demand is even more challenging in the

context of global climate changes such as an increase in temperature, salinity and drought

(Dai, 2010; Ding et al., 2011; Hawkins et al., 2013; Tester and Langridge, 2010). To improve

crop yield under rapidly changing climatic conditions next to ongoing conventional

breeding, plant biotechnology, which in principle enables faster crop improvement, could

provide solutions. Therefore, to augment crop yield through biotechnological interventions,

molecular understanding of plant growth regulation is crucial.

Leaf is a major part of the shoot and a basic photosynthetic unit of the plant, which

provides the energy driving most ecosystems on the planet and the production of food for

the human population. Moreover, the leaf has a tendency to adapt to environmental

changes by modifying its size and anatomy to maximize life span and propagation.

Therefore, it is essential to understand the mechanisms regulating leaf growth and

development. Leaf growth is defined by two successive processes i.e. cell division followed

by cell expansion. This suggests that to understand the leaf growth, exploration of these

two processes is crucial. Over these years, it is becoming clear that many aspects of these

processes are controlled by various phytohormones. Additionally, different environmental

factors influence cellular processes by altering the regulation of growth hormones, which

in turn impinges on the regulation of the basic growth regulatory processes, cell division

and cell expansion. Taken together, the leaf is a vital plant organ and its development is

controlled by multiple endogenous and exogenous factors.

Mostly, understanding leaf biology has been restricted by the contracted focus of individual

studies. Regardless of its scientific importance, resultant conclusion is not enough to

elaborate the multifaceted issues regarding leaf biology. Therefore, interdisciplinary


260

studies are essential to understand the complex system of leaf growth and development.

Hence, the goal of this thesis was to investigate leaf growth and development from a

systems perspective, and to understand how the environment affects leaf growth processes

through transcriptional networks and plant growth hormones.

Importance of Early Events in Leaf Development

Seed development is determined by the coordinated growth of the embryo, endosperm and

maternal tissues. Moreover, seed size is a crucial agronomic trait to improve crop yield and

large-seeded plants are also able to tolerate various stresses during seedling development

(Harper et al., 1970; Kaydan and Yagmur, 2008; Khurana and Singh, 2000). It has been

reported that the final leaf growth is influenced by the seed size (Howe and Richter, 1982;

Lima et al., 2005). Moreover, genes such as DA1 (Li et al., 2008) and FERONIA (FER) (Yu et

al., 2014) have also been found to control seed development therefore affecting organ size.

The role of the cell cycle inhibitor KRP1 has been reported in seed and leaf development

where overexpression of KRP1 reduced seed filling and leaf growth (Barroco et al., 2006).

In chapter 4 we clearly demonstrated that the inhibition of multiple KRPs enhances leaf

growth and induce cell proliferation, which was influenced by increased seed and embryo

size. A similar response was also observed in plants mildly overexpressing CDKB2;2

(Chapter 5). These results indicate that the cell cycle regulators, KRPs and CDKB influence

early stages of leaf development, which ultimately results in enhanced leaf growth.

Moreover, it can be predicted that the increase in cell proliferation in krp4/6/7 and

CDKB2;2 overexpression line is due to more cells in the leaf primordium at the time of

initiation (Chapter 4 and 5). However, further investigations are necessary to explore the

intrinsic signals generated by these cell cycle regulators to promote initial processes of leaf

development. Additionally, in chapter 2 we have explained that periclinal cell divisions that

determine leaf thickness in response to light intensity already occur prior to leaf

emergence. However, the molecular signals controlling these early stages of the leaf growth

process clearly need further investigation. To conclude, early developmental events have a

major impact on final leaf growth and should be explored in more details.


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Regulation of Leaf Development by Genetic Regulators and

Phytohormones

Leaf growth is a complex process where individual cells from a stem cell niche go through a

series of developmental events to reach their final destination as a part of a mature leaf

(Chapter 1). Out of these events cell division and expansion play an important role in

deciding the future of a cell (and its progeny), which ultimately reflect final shape and size

of the leaf. In chapter 2 we have demonstrated by 3D kinematic analysis that leaf growth is

an anisotropic process where cell division and expansion rates show large differences with

respect to directions and tissues, explaining plasticity in leaf shape and size.

The cell division cycle in plants is tightly regulated by the action of positive (e.g. CDKs and

CYCs) and negative regulators (e.g. KRPs, SIM and SMRs). In chapter 4 and 5 we have

explored the function of plant specific B type CDKs and KRPs. Our study demonstrates that

the inhibition of multiple members of the KRP family of negative regulators promotes cell

division, while it inhibits cell expansion, resulting in more, but smaller cells in the leaf. This

phenomenon of mutual adjustment, called compensation of cell number and size has been

observed in many mutants (Beemster et al., 2003; Horiguchi and Tsukaya, 2011; Tsukaya,

2002). On the other hand, mild overexpression of B2 type CDK also increases cell

proliferation but it does not affect mature cell size. Being cell cycle regulators it is obvious

that altering these genes will affect cell division, however their effects on cell expansion

raises new question whether these regulators also influence process of cell expansion.

These growth processes are also regulated by the complex network of phytohormones.

Auxin is a major growth regulator which is involved in various aspects of plant

development from seed development till senescence (Leyser, 2010; Sauer et al., 2013).

Auxin has been reported to promote cell proliferation by the induction of CDKA and

CYCD3;1, while it inhibits cell cycle inhibitors KRP (Cho et al., 2010; Perrot-Rechenmann,

2010). On the contrary, ARF2 (Auxin Response Factor 2) inhibits cell division by inhibiting

ANT and CYCD3;1 in Arabidopsis thaliana (Schruff et al., 2006). Additionally, auxin is also a

positive regulator of cell expansion, which lowers the extracellular pH, thereby enhancing

the activity of cell wall proteins, expansins (EXPs) and xyloglucanendotransglucosylase/


262

hydrolases (XTHs) that stimulate cell wall loosening (Perrot-Rechenmann, 2010). In

Chapter 3 we have elucidated the dual role of auxin as it promotes and inhibits cell division

and expansion in a concentration dependent manner. Moreover, cytokinin is also involved

in different processes of plant development (Haberer and Kieber, 2002). It promotes cell

division by increasing the level of CYCD (Riou-Khamlichi et al., 1999). The loss of function

mutant of CYCD3;1 was found to reduce cell number as well as cytokinin response (Dewitte

et al., 2007). Consistently, we found that CDKB2;2 promotes cell division and cytokinin

response (Chapter 5). Therefore, the role of phytohormones in leaf growth and

development is crucial, and our study suggests that these hormones decide the fate of plant

cell processes in a dose dependent manner.

A specific variant of the plant cell cycle, endoreduplication where DNA replicates

constantly without subsequent completion of mitosis, is also under control of the KRPs. It

has been reported that KRPs regulate cell cycle and endocycle in dose dependent manner

where low amounts repress the mitotic cycle while high level arrest cell division and

endoreduplication (Verkest et al., 2005). To understand the role of KRPs in the regulation

of endocycle, we used loss of function mutants. We clearly demonstrated that multiple

inhibition of KRPs increases endoreduplication (Chapter 4). Moreover, we also confirmed

the role of KRPs in endoreduplication by mathematical modeling which shows that the

downregulation of KRPs enhances endoreplication by two-fold. Simultaneous increase in

cell proliferation and endoreplication suggest that the cell cycle and endocycle are

regulated in different time frame of leaf development (Chapter 4). However, detailed

analysis is required to decipher the role of KRPs in controlling the endocycle.

Influence of Environmental Factors on Leaf Growth

Different environmental factors affect cell division and expansion and thereby affect leaf

growth. Water deficit is one of the most common limitations affecting leaf growth causing

alterations in leaf size and shape. It has been reported that osmotic stress influences

dividing and mature tissues by diverse mechanisms (Skirycz and Inze, 2010). The growth

hormone ethylene and GAs were reported to regulate cell proliferation in the leaves

whereas ABA was more associated with the response in mature tissues (Achard et al.,


263

2006; Claeys et al., 2012; Skirycz et al., 2011; Skirycz et al., 2010; Wilkinson and Davies,

2010).

In the present thesis, we uncovered the importance of the crosstalk between auxin

signaling and osmotic stress in proliferating leaves. We showed that altering auxin

homeostasis resulted in leaf growth reduction by inhibiting cell division and expansion

under osmotic stress (Chapter 3). Supra optimal levels of externally applied auxin enhance

the expression of KRPs, which inhibits CDK/CYC activity and therefore reduces cell

proliferation under stress (Chapter 4). Additionally, in our results upregulation of ethylene

metabolism under osmotic stress (Chapter 3, Figure 6) suggest that high auxin levels

promote ethylene biosynthesis (Hentrich et al., 2013; Swarup et al., 2007; Tsuchisaka and

Theologis, 2004; Zheng et al., 2013) that affects GA metabolism and stabilize the DELLA

proteins, which inhibit cell proliferation under osmotic stress (Achard et al., 2003; Dubois

et al., 2013). Therefore, it can be conceived that there is a crosstalk between auxin and

ethylene under osmotic stress to reduce leaf growth. However, targeted studies are

required to demonstrate their interaction in response to stress. Like cell division, cell

expansion was also reduced by osmotic stress (Chapter 3). The expression of expansion

related genes like EXPs and XTHs were affected in proliferating leaves under osmotic stress

in the presence and absence of exogenous auxin (Chapter 3). Furthermore, we also found

evidence for cell wall weakening through decreased expression of cellulose synthesis genes

under osmotic stress in combination with NAA, suggesting that a high auxin level is

inhibitory for cell expansion (Chapter 3). Taken together, it can be concluded that high

auxin concentration is inhibitory for leaf growth but the downstream mechanisms involved

needs to be further illustrated. Our transcriptome dataset provides a unique starting point

for such studies.

Light is another environmental factor that affects cellular processes during leaf

development (Chapter 2). Previous studies showed that under high light leaves are larger,

thicker and develop more palisade cells while under low light leaves are smaller, thinner

and have less developed palisades (Terashima et al., 2006). Our detailed three dimensional

analysis shows that these light dependent changes in leaf growth are regulated by specific


264

effects on cell division and expansion (Chapter 2). Moreover, we found that low light

increases petiole elongation rates, which results in increased petiole length while reduced

expansion rate inhibits final leaf size (Chapter 2). This differential growth response under

low light has been shown to be under control of various phytohormones including auxin,

ethylene and brassinosteroids (Kozuka et al., 2010; Millenaar et al., 2009; Vandenbussche

et al., 2003). In addition, a recent study showed that the shade induced petiole elongation

was the result of changes in microtubule dynamics and increased auxin biosynthesis which,

stimulates the expression of XTHs (Sasidharan et al., 2014). Furthermore, it will also be

interesting to explore how cell cycle regulators control the ratio of leaf blade and petiole

under low light.

In conclusion, this work gives an overview of the complex network of growth regulators

and environmental stimuli in leaf growth and development. We demonstrated that leaf

growth is not only regulated by cellular and molecular processes occurring during actual

leaf growth, but also affected by events prior to leaf emergence such as embryonic

development. Moreover, hormones play a key roles in growth regulation in a concentration

dependent manner under optimal as well as in stress conditions. This work provides

fundamental knowledge on the interaction between various growth regulators and

environmental factors, which can be further used to resolve agronomic difficulties. Overall,

we showed that growth regulation is a multidirectional process and studying only one

parameter does not provide a complete picture of the underlying mechanisms. Therefore,

taking all the controlling factors together will deepen our knowledge and will provide

significant information, which could be used for mathematical modeling to obtain a

mechanistic view on the growth regulating processes.


265

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CURRICULUM VITAE

Personal Name: Shweta Kalve

Current address: Platanenlaan 1, Wilrijk, Antwerp, Belgium-2610

Permanent address: J-101, Grevillea, Magarpatta City, Hadapsar

Pune, Maharashtra, India-411028

Email: [email protected]

Mobile: +32(0)489004133

Date of birth: September 11, 1983

Place of birth: Gwalior, India

Nationality: Indian

Marital status: married to Shrikrishna Kulkarni

Languages: English, Hindi, Marathi

Current Position Position: Pre-doctoral fellow

Research group: Laboratory for Molecular Plant Physiology and Biotechnology

Institute: University of Antwerp

Address: CGB building U 6th floor, 171 Groenenborgerlaan, B-2020 Antwerp, Belgium

Email: [email protected]

Tel: +32(0)32653826

Education 2010 - 2014: Ph.D. Student

Laboratory for Molecular Plant Physiology and Biotechnology, Department of Biology, University of Antwerp, Antwerp, Belgium under the supervision of Prof. dr. ir. Gerrit T.S. Beemster 2005 - 2007: Masters in Biotechnology

Obtained at the RTM Nagpur University, Nagpur, Maharashtra, India

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Master dissertation

“Analysis of protein profiles of bamboo treated with different concentration of salt and protoplast isolation from leaf tissue” performed in the research group of Environmental Biotechnology Division under the supervision of Dr. Bijaya K. Sarangi at National Environmental Engineering Research Institute (NEERI), Nagpur, Maharashtra, India

2002-2005: Bachelors in Biotechnology

Obtained at the RDVV University, Jabalpur, Madhya Pradesh, India

Experience Nov 2010 - Oct 2014: PhD fellow in University of Antwerp

Jan 2010 - Oct 2010: Flemish Research Fellow

Laboratory for Molecular Plant Physiology and Biotechnology, Department of Biology, University of Antwerp, Antwerp, Belgium under the supervision of Prof. dr. ir. Gerrit T.S. Beemster on “Drought response in Arabidopsis thaliana leaves”

2007 - 2009: Project Fellow

Environmental Biotechnology Division, National Environmental Engineering Research Institute (NEERI) on “Molecular characterization of Pteris, Veteveria, Bamboo and Mimosa plant species for arsenic and chromium stress for Phytoremediation” 2012 – 2013: Supervising Mehtap Cakiroglu with her bachelor thesis entitled “Role of

SMR2 in leaf development, an inhibitor of cell cycle regulation”.

2012 – 2013: Supervising Joanna Stelmaszewska with her master thesis entitled “Role of Kip-related proteins in leaf development”.

2011 – 2012: Supervising Joanna Dabk with her master thesis entitled “Effect of light

on leaf development - researches in vitro”. 2010 - 2011: Assist master practical courses on Plant Physiology

Awarded Grants/Awards Belgium Government Research Fellowship

January 2010- October 2010: Laboratory for Molecular Plant Physiology and Biotechnology, Department of Biology, University of Antwerp, Antwerp, Belgium under the supervision of Prof. dr. ir. Gerrit T.S. Beemster on “Drought response in Arabidopsis thaliana leaves”

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FWO Travel Grant

Travel grant to attend 23rd International Conference on Arabidopsis Research (ICAR) July 2012, Vienna, Austria

Irene Manton Poster Prize

Best poster award for the poster on “Three-dimensional analysis of cell division and expansion in leaves of Arabidopsis thaliana subjected to different light intensities”, Society of Experimental Biology (SEB), Valencia, Spain, July, 2013 219

Publications Shweta Kalve, Dirk De Vos, Gerrit T.S. Beemster, “Leaf development: a cellular

perspective”, Frontiers in Plant Science, 5(362), 2014.

Shweta Kalve, Joanna Fotschki, Tom Beeckman, Kris Vissenberg and Gerrit T.S. Beemster, “Three-Dimensional patterns of cell division and expansion throughout the development of Arabidopsis thaliana leaves”, Journal of Experimental Botany, 2014 (doi:10.1093/jxb/eru358).

Dirk De Vos*, Abdiravuf Dzhurakhalov*, Delphine Draelants*, Irissa Bogaerts*, Shweta Kalve*, Els Prinsen, Kris Vissenberg, Wim Vanroose, Jan Broeckhove and Gerrit T.S. Beemster, “Towards mechanistic models of plant organ growth”, Journal of Experimental Botany, 63(9), 3325–3337, 2012. (*: shared first author)

Shweta Kalve, Bijaya Ketan Sarangi, Ram Awatar Pandey and Tapan Chakrabarti, “Arsenic and chromium hyperaccumulation by an ecotype of Pteris vittata – prospective for phytoextraction from contaminated water and soil”, Current Science, 100(6), 2011.

Meetings Attended

Presenting speaker

Scientific meeting organized by the Belgian Plant Biotechnology Association (BPBA) on Plant Stress Biotechnology”, Leuven, Belgium on 3rd December 2010: Shweta Kalve, Els Prinsen, Kris Vissenberg, Gerrit T.S. Beemster, “Auxin plays a role in the response of leaf development to drought stress”.

Poster presentation Conference of Society of Experimental Biology (SEB), Valencia, Spain, 3rd-6th July, 2013:

Shweta Kalve, Joanna Dąbkowsk, Kris Vissenberg and Gerrit T.S. Beemster, “Three-

274

dimensional analysis of cell division and expansion in leaves of Arabidopsis thaliana subjected to different light intensities”.

23rd International Conference on Arabidopsis Research (ICAR), Vienna, Austria, 3rd-7th July 2012: Shweta Kalve, Els Prinsen, Kris Vissenberg and Gerrit T.S. Beemster, “Auxin plays a role in the growth response of Arabidopsis leaves to osmotic stress”.

International Conference on Toxic Exposure related Biomarker- Genomes and Health

related effects, Nagpur, India from 10-11th January 2008: Shweta Kalve, Bijaya K. Sarangi and Tapan Chakrabarti, “An assessment of plant biomarkers for strategic application in bioremediation of arsenic”.

International Congress on Bioprocesses in Food Industries (ICBF-2008) & 5th Convention of the Biotech Research Society of India (BRSI), Hyderabad, India from 6-8th December 2008: Shweta Kalve, Bijaya K. Sarangi, Ram A. Pandey, Asha A. Juwarkar and Tapan Chakrabarti, “Potentiality of Pteris vittata for Cr accumulation in plant biomass for phytoremediation of chromium”.

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ACKNOWLEDGEMENTS

At the end of my thesis, it is a pleasant task to express my thanks to all those who

contributed in many ways to the success of this study and made it an unforgettable

experience for me. First and foremost, I thank my supervisor Prof. dr. ir. Gerrit T.S.

Beemster, whose expertise, understanding, motivation, enthusiasm, and positive attitude

added considerably to my graduate experience. You have been a steady influence

throughout my PhD career. Despite of your busy schedule, you have always been there at

all times of need. Your wide knowledge and logical way of thinking have been a great value

for me. You are always helpful in directing, correcting and giving positive criticism for the

experiments and the writing. I doubt that I will ever be able to convey my appreciation

fully, but I owe you my eternal gratitude.

I would like to specially thank the members of my committee Prof. dr. Els Prinsen and Prof.

dr. Kris Vissenberg for your valuable time, interest, constructive criticism and insightful

comments. I am immensely indebted to your timely feedback and for keeping a check on

my yearly progress. I wish to extend my thanks to Prof. dr. Yves Guisez and Prof. dr. Han

Asard for scientific discussions and support during these years. My warmest thanks goes to

Prof. dr. Arp Schnittger and Prof. dr. Lieven De Veylder for taking time out from your busy

schedule to serve as external readers of my thesis. I would again like to thank Prof. dr. Arp

Schnittger for providing me the cell cycle related mutants and overexpression line which

helped me in exploring the role of cell cycle regulators in detail. I am also grateful to Prof.

dr. Tom Beeckman and Prof. dr. Lieven De Veylder for allowing me to use the facility in

their labs.

I would like to thank Dr. Stijn Dhondt for designing software for cell analysis which made

my PhD work easy. I am indebted to Dr. Domagalska Malgorzata Anna, for sharing her

genius with me, and for teaching me all the molecular techniques. I was fortunate to have a

chance to work with Dr. Dirk De Vos, whose wisdom and keen scientific insight greatly

benefited my work. My sincere thanks goes to Dr. Marios Nektarios Markakis for your

276

important contribution in my research work. Your help in RNA sequencing is highly

appreciated.

Furthermore, I acknowledge my fellow lab-mates and friends, Hamada AbdElgawad and

Viktoriya Avramova, for the stimulating discussions, for the calm weekends when we were

working together, and for all the fun we had in the last five years. I also would like to thank

my other lab mates Dr. Abdiravuf Dzhurakhalov, Dr. Evelyn Farfan, Bulelani Sizani and

Katrien Sprangers for the fun and support. I am grateful to Irissa Bogaerts, for being the

best colleague and friend I could wish for.

The technical assistant of Annette Geldmeyer and Sevgi Oden is highly appreciated. Thank

you very much for your kind help. A special thanks to Danny Huybrecht, Suzanne Pooters

and Sophie Nys for the friendly atmosphere and for countless much-needed coffee breaks.

Master students Bernhardt Vankerckhoven, Joanna Dabk, Joanna Stelmaszewska and

Mehtap Cakiroglu deserve great thanks for helping me in my experiments. I also owe my

sincere gratitude to all the members of PGO (Plant Growth and Development) group for

social and scientific discussions.

I would like to extend my special thanks to Gaurav Zinta, Kumud Saini, Aziz Hasan and

Nitin Gedam; you have been unwavering support in all my endeavours. I thank you all for

your friendship, love, and unyielding support. My sincere acknowledgement goes to Dr.

Amit Sinha, Dr. Nissy Nevil, Tanmay Nath, Dr. Sandeep Singh, Dr. Khushbu Kushwaha, Dr.

Hemant Dixit, Dipti Kulkarni, Dr. Ravi Kishor, Sai Ratna Manjari, Ajay Kumar, Bala

Narsimha, Nitin Pipralia and Neelava Das for providing me a warm home away from

home during these years and supporting me like a family during tough times.

Last but not least, my sincere thanks to my granny, my stepmother, mother- and father-in-

law, brothers- and sisters-in-law, uncles, aunts and cousins for their continuous support.

My most heartfelt thanks to my brother and friend Sushant Kalway for his support, love

and care.

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If I failed to include your name above, but you helped me in one way or another, my sincere

thanks goes out to you.

Shweta

A Systems Biology Approach to Understand Leaf Growth ...

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