Association genetics, geography and ecophysiology linkstomatal patterning in Populus trichocarpa with carbongain and disease resistance trade-offs

ATHENA D. MCKOWN,* ROBERT D. GUY,* LINDA QUAMME,* JAROSLAV KL �AP�ST �E,*†

JONATHAN LA MANTIA,* C. P . CONSTABEL,‡ YOUSRY A. EL-KASSABY,* RICHARD

C. HAMELIN,* MICHAEL ZIFKIN‡ and M. S . AZAM*

*Department of Forest and Conservation Sciences, Faculty of Forestry, Forest Sciences Centre, University of British Columbia,

2424 Main Mall, Vancouver, BC V6T 1Z4, Canada, †Department of Genetics and Physiology of Forest Trees, Faculty of

Forestry and Wood Sciences, Czech University of Life Sciences, Prague 165 21, Czech Republic, ‡Department of Biology, Centre

for Forest Biology, University of Victoria, Victoria, BC V8W 3N5, Canada

Abstract

Stomata are essential for diffusive entry of gases to support photosynthesis, but may

also expose internal leaf tissues to pathogens. To uncover trade-offs in range-wide

adaptation relating to stomata, we investigated the underlying genetics of stomatal

traits and linked variability in these traits with geoclimate, ecophysiology, condensed

foliar tannins and pathogen susceptibility in black cottonwood (Populus trichocarpa).Upper (adaxial) and lower (abaxial) leaf stomatal traits were measured from 454

accessions collected throughout much of the species range. We calculated broad-sense

heritability (H2) of stomatal traits and, using SNP data from a 34K Populus SNP array,

performed a genome-wide association studies (GWAS) to uncover genes underlying

stomatal trait variation. H2 values for stomatal traits were moderate (average H2 = 0.33).

GWAS identified genes associated primarily with adaxial stomata, including polarity

genes (PHABULOSA), stomatal development genes (BRASSINOSTEROID-INSENSITIVE 2)and disease/wound-response genes (GLUTAMATE-CYSTEINE LIGASE). Stomatal

traits correlated with latitude, gas exchange, condensed tannins and leaf rust

(Melampsora) infection. Latitudinal trends of greater adaxial stomata numbers and

guard cell pore size corresponded with higher stomatal conductance (gs) and

photosynthesis (Amax), faster shoot elongation, lower foliar tannins and greater

Melampsora susceptibility. This suggests an evolutionary trade-off related to differ-

ing selection pressures across the species range. In northern environments, more

adaxial stomata and larger pore sizes reflect selection for rapid carbon gain and

growth. By contrast, southern genotypes have fewer adaxial stomata, smaller pore

sizes and higher levels of condensed tannins, possibly linked to greater pressure

from natural leaf pathogens, which are less significant in northern ecosystems.

Keywords: adaxial–abaxial patterning, amphistomaty, evolutionary trade-offs, genome-wide

association studies, Melampsora, stomatal conductance, stomatal ratio

Received 4 June 2014; revision received 29 September 2014; accepted 12 October 2014

Introduction

Variation in traits arising within a species across its

distribution may indicate differing selection pressures

along environmental clines and functional dichotomies,

or trade-offs, relating to range-wide adaptation.Correspondence: Athena D. McKown, Fax: 604-822-8645;

E-mail: admckown@gmail.com

© 2014 John Wiley & Sons Ltd

Molecular Ecology (2014) doi: 10.1111/mec.12969

Untangling these requires the ability to link genetic and

phenotypic studies at the organism–environment

interface by identifying traits that respond to differing

clinal pressures (where selection at one end of the cline

should be inherently different than the other) and

uncovering the genetic basis for variability in these traits.

This is becoming feasible through advances in genomics,

harnessed in conjunction with ecological studies, and has

been applied to gene discovery in traits of evolutionary

and/or ecological interest (Ingvarsson & Street 2011) and

understanding mechanisms of adaptation (Savolainen

et al. 2013). For instance, genome-wide association

studies (GWAS) have determined that many ecologically

important traits have high genetic complexity underlying

phenotypic variability, which may act to facilitate species

adaptation either at the local level or across landscapes

(Savolainen et al. 2013).

In trees, the underlying genetics of numerous

ecologically important traits is emerging; however,

variability in many ecophysiological traits which may

be involved in local adaptation, such as leaf anatomy

and gas exchange properties, is less well understood on

a genetic basis. This includes stomata, which are porous

structures that act to balance internal leaf requirements

for gas exchange to support carbon gain with

limitations relating to water evapotranspiration and

desiccation (Sack et al. 2003; Franks & Beerling 2009).

Accordingly, variability in stomatal traits regulating gas

exchange and leaf conductivity can strongly influence

overall fitness through modifying photosynthetic rates

and plant growth. Gas exchange relating to stomatal

activity and the potential rate of diffusion is commonly

measured as stomatal conductance (gs) and is

fundamentally linked to the physical anatomy of the

leaf. Maximal gs is determined by individual guard cell

sizes (and corresponding aperture pore lengths),

spacing of guard cells and total density of stomata

across the leaf surface (Franks & Farquhar 2007; Franks

& Beerling 2009; Dow et al. 2014). These physical

parameters of stomata are coupled with functional

behaviour and responsiveness of guard cells to stimuli

and signalling (reviewed in Lawson & Blatt 2014), and

subsequently, gs can be modified by a number of means

and varies greatly between species (Franks & Beerling

2009; Merilo et al. 2014).

Stomata can occur on both the upper (adaxial) and

lower (abaxial) leaf surfaces (i.e. amphistomaty) or on

one surface alone, typically the abaxial surface (i.e.

hypostomaty). These distribution patterns are found

across numerous, divergent lineages and play a large

role in determining overall stomatal density and

maximum gs (Mott et al. 1982; Beerling & Kelly 1996).

The presence (and number) of stomata on adaxial leaf

surfaces varies by taxon, but can act to improve gas

exchange supporting development of thicker leaves

(such as a thicker adaxial palisade layer) or isobilateral

anatomy (i.e. adaxial and abaxial palisade layers).

Furthermore, stomatal responses on adaxial and abaxial

surfaces of the leaf are not necessarily linked and each

surface can independently respond to environmental

conditions, such as CO2 levels (Pearson et al. 1995;

Driscoll et al. 2006), humidity (Pallardy & Kozlowski

1979; Mott 2007), irradiance (Pallardy & Kozlowski

1979; Ceulemans et al. 1988) and different wavelengths

of light (Wang et al. 2008).

As gs has a fundamental effect on carbon gain and

overall plant growth rates, more restrictive environments

with higher desiccation potential and risk of xylem cavi-

tation due to drought or water stress often select for

lower stomatal densities and/or smaller stomata to bal-

ance water loss (Franks & Beerling 2009). Smaller sto-

mata are advantageous by facilitating higher gs for the

same total pore area (relating to a shorter diffusion path

length) and providing a more rapid stomatal response

(Franks & Farquhar 2007; Raven 2014). By comparison,

environments where high maximum leaf conductance is

advantageous may favour combinations of stomatal

traits, such as amphistomaty, density, pore size and/or

sensitivity, to increase gas exchange and corresponding

photosynthetic rates and/or productivity. Notably,

amphistomaty appears to be ecologically related to

exposure and is common among ‘open area habitat’

species, such as full sun, higher altitude and early

successional species (Mott et al. 1982; Beerling & Kelly

1996). Yet, while stomata are acting to balance the

external stresses of desiccation with internal stresses of

decreasing internal CO2 concentrations (Ci), stomata can

also provide a direct entry for disease (Zeng et al. 2010).

Although stomata are considered to be responsive to

pathogens (i.e. pathogen/microbe-triggered stomatal

closure), changing stomatal locations and/or increasing

stomatal densities (or sizes) in leaves might entail a

substantial risk of exposing internal leaf tissues to

pathogens simply by increasing the number of potential

infection sites. Consequently, natural selection should

balance maximal gs to drive photosynthesis and

transpiration while limiting opportunities for invasion

by pathogens. The ‘optimal’ combination of stomatal

characteristics to achieve both purposes is not necessar-

ily clear, and any trade-offs within a species may be

linked to the relative strength of pathogen selection

pressure within a particular environment.

To test how stomatal traits might vary across a

species reflecting geographical and environmental

distribution, we focused on Populus trichocarpa Torr. &

A. Gray, a widespread tree species in the western part

of North America. In general, P. trichocarpa follows a

cordilleran distribution and occurs in a number of mid-

© 2014 John Wiley & Sons Ltd

2 A. D. MCKOWN ET AL.

to low elevation habitats, many of which are relatively

open (Farrar 1995). Previous studies of P. trichocarpa

have linked clines in geography with differences in gs(Gornall & Guy 2007; McKown et al. 2014a). In addition,

a number of phenology, growth/biomass accumulation

and ecophysiology traits for this species follow

geography, particularly latitude (McKown et al. 2014a).

Latitude is a proxy for a combination of clines in photo-

period (day length) and temperature, both of which

strongly modify the growing season across the species

range. Among northern P. trichocarpa genotypes, gs is

consistently higher compared with mid- or southern

latitude genotypes and correlates with higher photosyn-

thetic rates, faster intrinsic growth and lower water use

efficiency (WUE) measured using both gas exchange

data and carbon isotope ratios (McKown et al. 2014a). A

corresponding trend has been observed in higher

stomatal densities and amphistomaty (i.e. increasing

adaxial to abaxial stomatal ratio) in ~23 P. trichocarpa

genotypes from five watersheds spanning a north–south

distribution (Gornall & Guy 2007; Pointeau & Guy

2014). Accordingly, it is possible that range-wide

variation in gs and photosynthesis observed in

P. trichocarpa accessions, in conjunction with differences

in carbon gain and growth, may be functionally driven

(or supported) by variations in stomatal densities and/

or amphistomaty.

Alongside this relationship between anatomy and

physiology, selection for traits influencing carbon gain,

including modifications to physical properties of leaf

stomata by changing stomatal patterning (i.e. density,

size and/or location), may increase the possibility of

pathogen attack (cf. Siwecki & Przybyl 1981; Dunlap &

Stettler 2001). For instance, increasing stomatal numbers

on the adaxial leaf surfaces in P. trichocarpa could

facilitate increased infection rates of pathogens that

enter through pores, such as the leaf rust pathogen

(Melampsora Castagne). In Populus, overall biomass

yields, productivity and juvenile tree survivorship rates

are strongly influenced by duration and severity of

pathogen infections, particularly of Melampsora

(Newcombe et al. 1994; Newcombe 1996; Major et al.

2010). While Melampsora is a naturally occurring

biotrophic pathogen of poplar trees, numerous studies

have underscored that Melampsora infection rates and

severity correlate with latitude and indicate a general

vulnerability and/or lack of resistance among mid- to

northern populations of P. trichocarpa compared with

southern populations (Xie et al. 2009, 2012; La Mantia

et al. 2013). Nevertheless, any functional relationship

between stomatal traits and the resistance observed in

southern populations vs. apparent maladaption in

northern populations of P. trichocarpa is largely

unstudied. Furthermore, potential links between

stomatal traits and ‘costly’ defence compounds (cf. Fag-

erstrom et al. 1987), such as flavonoids or proanthocy-

anidins (condensed tannins) in Populus (Miranda et al.

2007), are unknown.

In this study, we provide an in-depth examination of

the physical properties of stomata from P. trichocarpa

accessions collected throughout the northern two-thirds

of the species range with the goals of understanding

genes that affect stomatal anatomy (and overall plant

function) and related causes and functional

consequences of variation in this important anatomical

attribute. Among the 454 P. trichocarpa accessions used

in this study, 448 accessions were previously genotyped

for single nucleotide polymorphisms (SNPs) estimating

extensive allelic variation in 3.5K genes distributed

across the P. trichocarpa genome (Geraldes et al. 2013).

We estimated the broad-sense heritability (H2) of

stomatal traits and performed a genome-wide associa-

tion study (GWAS) to search for genes associated with

these traits. In addition, we integrated data from

stomatal traits with analysis of condensed foliar tannins

and previously published geographical and trait data

for the same accessions. We explored the following: (i)

What are the distributions of amphistomaty and other

stomatal traits across the range of P. trichocarpa? (ii)

What is the heritability of stomatal traits? (iii) Which

genes are associated with these stomatal traits using

GWAS? and (iv) What are the correlative relationships

between stomatal traits and geography, climate, eco-

physiology, growth, leaf traits, condensed tannins and

disease severity in P. trichocarpa? Using an integration

of numerous lines of evidence, we outline genetic and

functional connectivity and suggest potential evolutionary

trade-offs in P. trichocarpa that relate to stomatal trait

variation and invoke differing selection pressures across

the species range.

Materials and methods

Plant materials

An established collection of native cottonwood poplars

(Populus trichocarpa Torr. & A. Gray) from 130

populations spanning 44–60° N was used for stomatal

trait assessments (Fig. 1). Full details have been

previously published regarding the collection of wild

P. trichocarpa accessions (Xie et al. 2009) and planting

and maintenance of the common garden at Totem Field,

University of British Columbia (McKown et al. 2013,

2014a). All accessions used for assessment of stomatal

traits and condensed foliar tannins were grown in

clonal replication (i.e. multiple ramets). Clonal ramets

were cultivated from cuttings taken in 2008, with at

least four replicates of each accession, and planted

© 2014 John Wiley & Sons Ltd

ECOLOGICAL TRADE- OFFS AND AMPHISTOMATY 3

within a 1.5 9 1.5 m spacing in a random block design.

All accessions in the study were represented by trees of

similar age and condition.

Stomatal anatomy

Mature, neoformed leaves used for stomatal traits were

collected in early August 2010 from the sun-exposed,

upper canopy of all clonal replicates (n = 2000 from 454

genotypes). A number of trees (n = 447 from 222

genotypes) were resampled in early August 2011 for

stomatal trait repeatability. Full details regarding

stomatal data collection are available (Appendix S1,

Supporting information). Stomatal trait data were

collected using replica nail polish imprints (peels) of

both the abaxial and adaxial leaf surfaces (Table S1,

Supporting information). Peels were digitally imaged

using a Nikon Eclipse E600 microscope and a Nikon

DX10000 digital camera (Nikon Inc., USA). Three

randomly selected, nonoverlapping images

(7.0 9 10�2 mm2 each) were taken from each leaf

surface for measurements and assessed using ImageJ

(Rasband 2007) for numbers/sizes of adaxial and

abaxial stomata. These were used to calculate densities

(# per mm2) of total leaf, adaxial and abaxial stomata,

the ratio (AD:AB) of stomatal densities between both

surfaces, aperture pore lengths (lm) of adaxial and

abaxial stomata and the size ratio of pores between leaf

surfaces. The relative porosity of individual leaf

surfaces was calculated using the stomatal pore area

per leaf area index (SPI = stomatal density 9 pore

length2, unitless) (cf. Sack et al. 2003), as both pore

length and stomatal density correlate with the theoretical

maximum gs (Franks & Beerling 2009). Presence of

adaxial stomata was scored for each peel (0 = absent;

1 = present). Where adaxial stomata were observed,

these were binned giving a classification of general

adaxial stomatal numbers throughout the entire peel

(0 = absent; 1 = sparse, 1–2 stomata only; 2 = moderate,

~5–10 stomata; 3 = numerous, >10 stomata). The

distribution patterns of adaxial stomata (if present)

were also classed into three main pattern types (0 = few

Fig. 1 Distribution of Populus trichocarpa

(black cottonwood) accessions used for

analysis of stomatal traits and condensed

foliar tannins. Trees in this study were

collected from 130 provenances in 30

drainages (as illustrated by different

symbols) across the northern two-thirds

of the species’ range as it occurs west of

the Rocky Mountains and replanted in

the Totem Field common garden at

the University of British Columbia,

Vancouver, Canada. Map courtesy of

A. Geraldes.

© 2014 John Wiley & Sons Ltd

4 A. D. MCKOWN ET AL.

stomata; 1 = clusters of stomata along minor veins; and

2 = evenly distributed stomata).

Condensed leaf tannin assay

Condensed foliar tannins [lg tannin mg dry weight

(DW)�1] were assayed from upper canopy, exposed

leaves collected in early August 2010 and 2011. Leaves

were harvested prior to canopy senescence or Melampsora

infection, as there may be upregulation of condensed

tannins (proanthocyanidins) in Melampsora-infected

poplar leaves (Miranda et al. 2007). Full details regarding

condensed tannin methodology are available (Appendix

S1, Supporting information). Quantity of foliar tannins

was determined with a standard curve using a purified

P. tremula 9 P. tremuloides condensed tannin as a

standard (Table S2, Supporting information). Log

transformation was applied to tannin data to improve

normality and residual distribution for correlation

analyses.

Ecophysiology, growth, leaf traits and disease

Stomatal trait data were compared with detailed

information previously published on ecophysiology,

growth, leaf traits (McKown et al. 2013, 2014a) and

susceptibility/severity of infection by Melampsora for

each accession (La Mantia et al. 2013) (Table S2,

Supporting information). Briefly, gas exchange-based

traits were taken from sun-exposed, upper canopy

leaves on each tree in the common garden (comparable

to the leaf used for stomatal traits) and included

maximum photosynthetic rate (Amax; lmol CO2/m2/

s1), stomatal conductance (gs; mol H2O/m2/s) and

instantaneous WUE as determined by photosynthetic

rate over transpiration (WUE; lmol CO2/mmol H2O).

Leaf tissue samples from these same leaves were used

to determine C to N ratio (C:N; mg/mg), leaf N con-

tent per unit dry mass (Nmass; mg/mg), photosynthetic

N-use efficiency (NUE; lmol CO2/g N/s) and isotopic

composition (d13C) to calculate net discrimination

against 13CO2 as a longer-term inverse index of WUE

(Δleaf; &). Values of d13C indicating overall WUE

across multiple years were also analysed from 1 mg

samples of dried, ground wood (d13Cwood). Other

parameters measured included leaf shape (length:

width), seasonal chlorophyll content and leaf mass

per unit area (LMA; mg/mm2). Heights of all trees

were measured repeatedly to calculate intrinsic rates

of height growth or rate of terminal shoot elongation

(log cm/day) occurring before terminal bud set mark-

ing the end of growth. Disease susceptibility data

were described previously (La Mantia et al. 2013), and

all trees were scored for disease onset and severity of

Melampsora 9 columbiana infection. Both timing and

disease ratings were used to calculate a genotypic

score for area under the disease progress curve

(AUDPC; unitless). For comparisons with stomatal

trait data, we focused on AUDPC data from 2010 and

2011.

Geographical and climate variables

Latitude, longitude, elevation and associated climate

data (i.e. ‘geoclimate variables’) for all accessions have

been previously reported (McKown et al. 2014a) (Table

S2, Supporting information). We focused our analysis

on geography and growing season-related variables

including the number of frost-free days (FFD), mean

annual temperature (MAT; °C), mean warmest month

temperature (MWMT; °C), mean annual precipitation

(MAP; mm), mean summer precipitation from

May–September (MSP; mm), annual heat moisture

index [AHM; derived from (MAT+10)/(MAP/1000)]

and summer heat moisture index [SHM; derived from

(MWMT)/(MSP/1000)].

Correlation and regression analyses

Analyses were carried out using GraphPad Prism 6

(GraphPad Software, Inc., La Jolla, CA, USA). We

estimated the correlative relationships between clonal

mean stomatal trait values, geoclimate variables,

ecophysiology, growth measurements, condensed

tannins and disease susceptibility using Pearson’s

product-moment correlations (r). We also performed

simple linear regression analyses for trends between

the stomatal density ratio (AD:AB) and different

ecophysiology, leaf, growth and disease susceptibility

traits. Because sample sizes were large, we used a

stringent Bonferroni correction (a = 0.001) for multiple

correlations to highlight the strongest correlative

relationships within our data set.

SNP genotyping of accessions

Four hundred and forty-eight accessions were

genotyped using a 34K Populus Illumina Infinium� SNP

genotyping array designed for P. trichocarpa estimating

extensive allelic variation in genes distributed across

the genome. Full details of SNP selection and array

development are given in Geraldes et al. (2011, 2013),

and array data and results are described in McKown

et al. (2014b). Briefly, the chip included 34, 131 SNP

markers within 3543 genes and intergenic regions

(�2 kb up- or downstream from the longest transcript).

Following array genotyping, we excluded SNPs with

minor allele frequency <0.05 and call rate <0.9 resulting

© 2014 John Wiley & Sons Ltd

ECOLOGICAL TRADE- OFFS AND AMPHISTOMATY 5

in 29 355 SNPs representing 3518 genes. Each

significant SNP from the GWAS results was visually

inspected for quality, and the ‘Nisqually-1’ genome

sequence P. trichocarpa v2.2 SNP positions and gene

models described in Geraldes et al. (2013) were

translated into the latest Populus reference genome

assembly (v3.0) on Phytozome 9.1 (http://www.

phytozome.net/).

Genetic correlations

To assess a common genetic basis for independent

trait variation, we calculated pairwise genetic

correlations between stomatal traits. These correlations

are ‘broad-sense’ genetic correlations and are based on

clonal best linear unbiased predictions (BLUPs)

obtained from the linear mixed model results presented

in McKown et al. (2014a). Pearson’s product-moment

correlations were estimated as follows:

rGx;y¼ Covgxgyffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi

Vargx � Vargyp

where Covgxgy is the covariance between clonal BLUPs

of traits x and y, Vargx is variance in clonal BLUPs for

trait x, and Vargy is variance in clonal BLUPs for trait y.

As accession sampling sizes were large, we focused on

correlations where |rG| ≥ 0.3.

Broad-sense trait heritability

We estimated broad-sense heritability values (H2) of

stomatal and tannin trait data from all individual

ramets (i.e. clonal replication). Following methodology

for heritability calculations on the same group of

P. trichocarpa accessions (McKown et al. 2014a), we used

the fixed effect of population structure fitted by PC1 in

the linear mixed model implemented in ASReml

(Gilmour et al. 2002) to estimate H2 variance components

as follows:

y ¼ Xbþ Zuþ e

where y is a vector of measurements, b and u are

vectors of fixed (population) and random (genetic)

values, X and Z are incidence matrices assigning

fixed and random effects to each measurement in y,

and e is a vector of residuals (effect of ramets within

clone) following E�N 0; Ir2e

� �, where r2

e is residual

(environmental) variance and I is the identity matrix.

The vector of genotypic values follows VarðuÞ ¼ Ir2g ,

where r2g is total genetic variance containing both

additive and nonadditive genetic components. The

variance components estimated in the models defined

above were used to calculate H2 as follows:

bH2 ¼ br2gbr2

g þ br2e

The generalized mixed linear models were performed

for count phenotypes (general adaxial stomatal

numbers, adaxial stomata distribution patterns) or

binary phenotypes (adaxial stomata presence) using the

Poisson (Reid et al. 2011) or binomial family (Gilmour

et al. 2002). H2 for count phenotypes was estimated as

follows:

bH2 ¼ r2g

r2g þ u ln 1

ygþ 1

� �

where φ is an over/under-dispersion parameter and �ygis the geometric mean. H2 for binary phenotypes was

estimated as follows:

bH2 ¼ br2gbr2

g þ ur2e

where r2e is p2

3 (considering the logit link function, cf.

Gilmour et al. 2002).

Population structure and GWAS

We evaluated the effects of population structure among

our accessions on a trait-by-trait basis by comparing

log-likelihood values between models with the Bayesian

information criterion (BIC) (Yu et al. 2006; McKown

et al. 2014b). Full details regarding implementation of

population structure models to adequately reduce the

likelihood of false positives while avoiding overfitting

models (resulting in false negatives) in our test

population are previously described (Porth et al. 2013;

McKown et al. 2014b). Briefly, we compared structures

based on family relatedness using a kinship (K) model,

population structure using a principal component

analysis (P) model or a clustering matrix (Q) model,

combinations of structures (P + K, Q + K), and a

‘simple’ model (i.e. simple linear regression without

any additional correction) following McKown et al.

(2014b). R scripts for integrating population and kinship

structures are publicly available (Appendices S2–S4,

Supporting information).

The SNPs used in structure estimates were further fil-

tered for Hardy–Weinberg equilibrium and pairwise

linkage disequilibrium (LD) at r2 < 0.2, and from this

filtering, 8749 SNPs distributed throughout the genome

were used for model analyses. The K model was calcu-

lated following Loiselle et al. (1995). Using the P model

based on principal component analysis (Patterson et al.

2006), we determined that only the first principal

component (PC1) was significant within our population

using broken stick modelling. The clustering model-

© 2014 John Wiley & Sons Ltd

6 A. D. MCKOWN ET AL.

based inference (Q matrix) was performed using the

correlated allele frequency model (Marchini 2013) and

detected some subpopulation structure (K = 5), which

was subsequently used for the Q matrix. Among the

stomatal traits, BIC selected the simple, P or Q models

depending on the trait. Similar to other studies, the K

component was not considered the best fit for the data

structure (La Mantia et al. 2013; Porth et al. 2013;

McKown et al. 2014b).

Following methodologies in Porth et al. (2013) and

McKown et al. (2014b), we carried out the GWAS using

the GLM procedure implemented in TASSEL (Bradbury

et al. 2007):

y ¼ lþ Saþ Xbþ e

where y is the vector of measurements, l is the overall

population mean, S and X are index matrices assigning

fixed effects for both SNP genotype and population to

the measurements, respectively, a and b are vectors of

fixed effects for both SNP genotype and population,

respectively, and e is the residual effect. We used a

Bonferroni multiple testing correction and considered

SNP–trait associations significant where P < 1.7 9 10�6

(=0.05/29 355). Because this is a relatively stringent

cut-off, we also investigated trait associations where

P < 3.4 9 10�6 (=0.10/29 355). Finally, we calculated

composite pairwise LD between all trait-associated

SNPs based on genotype correlations (Weir et al. 2004)

and the total phenotypic variance of stomatal traits

(cumulative R2) accounted for by SNPs (Ingvarsson

et al. 2008).

Results

Stomatal trait variation, heritability and correlationbetween accessions

Leaf imprints indicated the majority of our P. trichocarpa

accessions (417/452 = 92%) have at least some adaxial

stomata. This result was also observed in preformed

(spring) leaf samples (data not shown). Despite the

presence of adaxial stomata, mean density among

clones was low (3.1/mm2) (Table 1). By contrast, mean

abaxial stomatal density was much higher (183.9/mm2),

and correspondingly, total stomatal densities were

largely driven by abaxial stomata. Mean stomatal

density ratios (AD:AB) were also generally low (0.02)

and ranged from 0 to 0.3. Overall, pore lengths of

adaxial stomata were smaller than abaxial stomata

reflecting an AD:AB pore ratio <1, and the resultant SPI

values of adaxial vs. abaxial surfaces showed a 16-fold

difference in surface porosity. These low numbers of

adaxial stomata were partly related to lower detection

due to a limited/dispersed presence among many

accessions and/or clustered distributions of adaxial

stomata above leaf minor veins as only a few accessions

had stomata evenly distributed across the adaxial leaf

surface (Fig. 2, Table S1, Supporting information).

Table 1 Clonal variation in stomatal traits and condensed foliar tannins among Populus trichocarpa accessions indicating mean trait

value (�standard deviation), trait range (minimum and maximum values), coefficient of correlation (r) for traits measured across

years using Pearson’s product-moment correlations and broad-sense heritability estimates (H2 � standard error)

Trait Genotypes (n) Mean value � SD Trait range (min–max) Years (r)† H2 � SE

Density (per mm2)

Total leaf 454 187 � 29 109.8–279.4 0.39*** 0.34 � 0.03

AD 454 3.1 � 6.7 0–44.2 0.53*** 0.39 � 0.02

AB 454 184 � 30 96.7–279.4 0.43*** 0.35 � 0.03

AD:AB 454 0.02 � 0.04 0–0.3 0.55*** 0.42 � 0.02

Pore length (lm)

AD 160 30.4 � 4 19.2–42.1 0.34 0.41 � 0.07

AB 454 34.4 � 3 26.8–44.8 0.13 0.35 � 0.03

AD:AB 160 0.9 � 0.1 0.55–1.2 0.54* 0.18 � 0.08

SPI

AD 160 0.014 � 0.01 0.0018–0.0421 0.44 0.16 � 0.06

AB 454 0.22 � 0.03 0.135–0.332 0.18* 0.34 � 0.03

Adaxial stomata

Presence 454 NA 0, 1 NA 0.39 � 0.03

Numbers 454 NA 0–3 NA 0.37 � 0.03

Distribution 454 NA 0–2 NA 0.09 � 0.04

Tannins (lg mg/DW) 454 32.67 � 32.2 2.61–178 0.96*** 0.59 � 0.02

AB, abaxial; AD, adaxial, SPI, stomatal pore index.

***P < 0.001, *P < 0.05.†n = 222 genotypes compared across 2010–2011.

© 2014 John Wiley & Sons Ltd

ECOLOGICAL TRADE- OFFS AND AMPHISTOMATY 7

Many stomatal traits measured in a subsample of

accessions in 2011 were significantly correlated across

years, particularly stomatal density, indicating

moderate to good repeatability in stomatal traits from

year to year (Table 1). This was supported by broad-

sense heritability estimates (H2) of stomatal traits,

which were moderate (average H2 = 0.33; Table 1, Table

S3, Supporting information). Adaxial stomatal traits

(density, pore length) had the highest H2 values

(range = 0.39–0.41), while abaxial stomatal traits were

somewhat lower. The AD:AB density ratio had a higher

H2 value (0.42) than the corresponding AD:AB pore

length ratio that had a much lower H2 value (0.18).

Some traits that were strongly correlated across years

also had higher H2 values (i.e. adaxial and abaxial

densities, AD:AB), but this was not the case for AD:AB

pore ratio. Binary and count traits for adaxial stomata

ranged in H2 values. Adaxial stomata presence had the

highest heritability (H2 = 0.39), while binned adaxial

stomatal numbers and distribution classes on the leaf

had lower H2 values.

Genetic correlations between all stomatal traits (to

assess trait variation independent from genetic linkage)

showed that total stomatal density largely reflected

abaxial stomatal density (Table 2). By comparison,

adaxial stomatal density was strongly driving the AD:

AB density ratio. Adaxial stomatal density was also

correlated with adaxial SPI values, but had little

relationship with adaxial pore length. Abaxial stomatal

density was not significantly correlated with the AD:AB

density ratio but showed strong relationships to abaxial

pore lengths and SPI values. Stomatal densities for both

leaf surfaces lacked a significant correlative relationship,

whereas pore lengths showed positive correlation. As a

result, SPI values calculated for both leaf surfaces (but

related primarily to density values) also lacked

significant correlation.

Gene discovery through GWAS

Association analysis between stomatal traits and 29K

SNPs uncovered 25 significant SNP markers at the

(a) (b) (c)

Fig. 2 Leaf epidermal imprints illustrating three patterns of adaxial stomatal distribution in Populus trichocarpa.

(a) Solitary, dispersed adaxial stomata (SLMD = 50.3°N, HAZH = 55.2°N). (b) Clusters of adaxial stomata, particularly along minor

veins (QBKR = 53°N, MEMA = 50.2°N). (c) Evenly distributed stomata (BULF = 54.6°N). All images captured at 100 9 using differ-

ential interference contrast light microscopy.

© 2014 John Wiley & Sons Ltd

8 A. D. MCKOWN ET AL.

lower Bonferroni multiple testing correction threshold

(a = 0.05; P < 1.7 9 10�6) annotated to 15 loci across

the genome (Table 3, Table S4, Supporting information).

Five additional associations were further detected just

above this threshold (a = 0.1; P < 3.4 9 10�6), two of

which were for SNPs previously associated with other

traits at the lower threshold, while the others added

three supplementary loci with potential phenotypic

effect (Table 3, traits in italics). Full SNP results and

information, location of SNPs, MAF, marker r2 and LD

values are available in Supporting Information (Tables

S4 and S5, Supporting information).

Trait-associated SNPs significant at the lower

threshold were associated with only four stomatal traits

(adaxial density, adaxial stomatal numbers, adaxial SPI,

AD:AB) (Table 3). At the higher cut-off, associations

were retrieved with two additional traits (adaxial

stomata presence and distribution). No SNP–trait

associations were detected for abaxial stomata or pore

length traits. Most significant SNP markers were located

in noncoding regions (22/28 = 79%), while six markers

were located in coding regions (nonsynonymous = 1,

synonymous = 5). On average, SNP markers explained

4.9% of trait variation, with individual SNPs explaining

between 3.8 and 11.9% of the phenotypic variation. Some

genes were retrieved with multiple SNP–trait associa-

tions, and in such cases, the SNPs were highly linked

(r2 = 0.6–1; Table S5, Supporting information). Both

adaxial stomatal density and AD:AB density ratio

retrieved the greatest numbers of genes, with overlap

where two genes were associated with both traits

(Table 3). These traits also had the highest cumulative

proportion of phenotypic variance (cumulative R2)

explained by significant SNPs (R2 = 0.24, 0.21). By

comparison, other traits retrieved far fewer genes and

had correspondingly lower cumulative R2 values

(R2 = 0.05–0.12).

The 18 genes identified by GWAS underlying

phenotypic variation in stomatal traits represented

diverse functionality (annotations based on the

Arabidopsis homologues; www.arabidopsis.org)

(Table 3). These included genes annotated as encoding

proteins for transcription factors, kinases, transporters,

pectinesterases, lyases and ligases. Among the genes

associated with stomatal traits in P. trichocarpa, many

showed substantial allelic effects on the associated

phenotype and are highlighted below providing the

Arabidopsis homologue annotation, location information

(i.e. chromosome/SNP/feature), allelic variation among

accessions and the underlying P. trichocarpa phenotypic

variability.

Some genes retrieved by GWAS have known effects

on leaf tissue patterning in Arabidopsis. One example

with specific involvement in stomatal patterning in

Arabidopsis, and associated with stomatal density in this

study, is BRASSINOSTEROID-INSENSITIVE 2 (BIN2).

The P. trichocarpa homologue, Potri.004G059000, had a

single trait-associated SNP (4_4744948; intergenic).

Accessions homozygous for the minor allele had 6-fold

higher adaxial stomatal densities compared with

homozygotes of the major allele, while heterozygous

accessions had 2-fold higher density than the major alle-

lic homozygotes (Fig. 3a). A second gene, PHABULOSA

(PHB), has effects on polarity patterning and specification

of the adaxial/abaxial axis in Arabidopsis and may be

involved in adaxial/abaxial tissue patterning in

P. trichocarpa. The homologue Potri.011G098300 was

associated with adaxial stomatal density with two

Table 2 Broad-sense genetic correlations (rG) among stomatal traits from Populus trichocarpa accessions based on clonal best linear

unbiased predictions (BLUPs)

Stomatal trait

Density (per mm2) Pore length (lm)

SPI

Total AD AB AD:AB AD AB AD:AB AD

Density

AD 0.13

AB 0.98* �0.07

AD:AB 0.04 0.97* �0.15

Pore length

AD �0.15 0.03 �0.15 0.13

AB �0.54* 0.08 �0.56* 0.13 0.30*

AD:AB 0.02 �0.08 0.04 �0.05 0.63* 0.13

SPI

AD 0.07 0.69* �0.07 0.69* 0.23* 0.12 0.04

AB 0.47* 0.003 0.48* �0.04 0.12 0.44* �0.06 0.05

AB = abaxial, AD = adaxial, SPI = stomatal pore index.

*Significant following Bonferroni multiple testing correction (a = 0.001).

© 2014 John Wiley & Sons Ltd

ECOLOGICAL TRADE- OFFS AND AMPHISTOMATY 9

significant SNP markers (11_11976401; synonymous/

11_11982117; intergenic), both in moderate pairwise LD

(r2 = 0.57; Table S5, Supporting information). The two

alleles had phenotypic change in the same direction

where accessions homozygous for the minor allele had

adaxial stomatal densities 9-fold higher than the major

allelic variants, and heterozygous accessions had 2-fold

higher density than the major allelic homozygotes

Table 3 Genes identified by GWAS with SNP markers associated with stomatal traits in Populus trichocarpa, functional annotations,

and potential significance or relationship to stomatal traits

Trait* Gene model† AT homologue Annotation† Potential significance

AD presence Potri.001G087300‡,§ AT1G64550 GCN3 (GENERAL CONTROL

NON-REPRESSIBLE 3)

ABC transporter, connection

with MAMP (microbe-associated

molecular patterns)-

induced stomatal closure

AD density Potri.001G339500 AT3G27400 Pectin lyase-like family protein Pectate lyase activity

AD:AB, AD

density

Potri.001G372400 AT4G37990 ELI3 (ELICITOR-ACTIVATED

GENE 3)

Aryl-alcohol dehydrogenase,

mRNA levels increase with

phytopathogenic bacteria

AD density Potri.003G126900 AT4G23100 GSH1 (GLUTAMATE-CYSTEINE

LIGASE)

Defence response to bacteria and

fungus, depletion of GSH in

guard cells enhances

ABA-induced stomatal closure

AD number Potri.004G010100‡ AT4G22010 SKS4 (SKU5 SIMILAR 4) Oxidoreductase activity

AD density Potri.004G059000 AT4G18710 BIN2 (BRASSINOSTEROID-

INSENSITIVE 2)

Glycogen synthase kinase 3/

shaggy-like kinase family

member, brassinosteroid

signalling pathway, regulates

stomatal development

AD distribution Potri.005G148000 AT1G43130 LCV2 (LIKE COV 2) Unknown

AD:AB, AD

density

Potri.007G139100 AT4G28390 AAC3 (ADP/ATP CARRIER 3) Mitochondrial ATP:ADP

antiporter protein, systemic

acquired resistance

AD density Potri.008G128800‡ AT1G71010 FAB1C (FORMS APLOID AND

BINUCLEATE CELLS 1C)

Phosphatidylinositol-4-phosphate

5-kinase family protein,

stomatal closure

AD density Potri.009G152800 AT5G17920 ATMS1 (METHIONINE

SYNTHESIS 1)

Methionine biosynthetic process,

stress response

AD:AB, AD

density

Potri.010G074300 AT3G23150 ETR2 (ETHYLENE RESPONSE 2) Protein serine/threonine kinase

activity, ethylene-mediated

signalling pathway

AD density Potri.011G098300 AT2G34710 PHB (PHABULOSA) Transcription factor, adaxial/

abaxial pattern specification,

polarity specification of

adaxial/abaxial axis

AD number Potri.012G014500‡,§ AT5G53370 PMEPCRF (PECTIN

METHYLESTERASE PCR

FRAGMENT F)

Pectinesterase activity, regulation

of plant-type hypersensitive

response, water transport

AD:AB Potri.014G004400 AT5G39390 Leucine-rich repeat protein

kinase family protein

Protein serine/threonine kinase

activity

AD:AB Potri.014G004500 AT2G22620 Rhamnogalacturonate lyase

family protein

Lyase activity

AD SPI Potri.014G127000§ AT2G47550 Pectinesterase family protein Regulated by brassinolide,

responsive, wound response

AD:AB Potri.018G139200§ Unknown Unknown protein Unknown

AD:AB Potri.T125700 AT5G64200 ATSC35; SC35-like splicing factor Unknown

AB, abaxial, AD, adaxial.

*Italicized traits are significant at P < 3.4 9 10�6 (a = 0.1/29 355). See Table S4 for full gene and SNP details.†Poplar gene models are annotated to v3.0 of the genome.‡SNP marker and/or gene retrieved in other GWAS studies (La Mantia et al. 2013; McKown et al. 2014b).§SNP marker retrieved by FST outlier studies relating to geography and/or climate (Geraldes et al. 2014).

© 2014 John Wiley & Sons Ltd

10 A. D. MCKOWN ET AL.

(Fig. 3b). Different combinations of both SNPs resulted

in seven genetic variants (haplotypes); however, no

combinations of double major and double minor allelic

individuals (i.e. CC/AA or TT/GG, respectively) were

found among our P. trichocarpa accessions.

Genes with other effects on pectin, stomatal

behaviour and signalling were retrieved by GWAS.

For instance, PECTIN METHYLESTERASE PCR

FRAGMENT F (PMEPCRF) is inferred to have pectines-

terase activity, regulate hypersensitive response and

affect water transport in Arabidopsis. The homologue in

P. trichocarpa, Potri.012G014500, was associated by a

single SNP (12_1425770; intergenic) with adaxial

stomatal number (based on the classification of general

adaxial stomatal numbers). The heterozygous form was

the most common allelic variant and had a similar

phenotypic effect to the minor allelic variant (values of

2 = moderate numbers, ~5–10 stomata observed)

(Fig. 3c). The major allelic variant had fewer adaxial

stomata (value of 1 = sparse numbers, 1–2 stomata only).

Another gene, FORMS APLOID AND BINUCLEATE

CELLS 1C (FAB1C), is believed to be involved with

stomatal closure in Arabidopsis and was associated with

adaxial density in P. trichocarpa. The homologue

Potri.008G128800 had a single trait-associated SNP

(8_8392536; intron). Among our P. trichocarpa

accessions, the minor allelic variant had 10-fold higher

adaxial stomatal density compared with the major

allelic variant but was uncommon (n = 2, MAF > 0.05;

Table S4, Supporting information) (Fig. 3d). Similar to

other SNPs retrieved by GWAS, heterozygous

accessions had 2-fold higher density compared with the

major allelic homozygotes.

Other genes identified by GWAS have connections to

disease response based on prior studies in Arabidopsis.

One gene related to defence response and stomatal

(a) (b)

(c) (d)

(e) (f)

Fig. 3 Allelic effects of significant SNPs

on the associated stomatal phenotype

(�standard error) in Populus trichocarpa.

Segregating bases and numbers of

accessions with each allelic variant are

indicated. (a) Potri.004G059000 (BIN2;

BRASSINOSTEROID-INSENSITIVE 2)

with SNP 04_4744948 associated with

adaxial stomatal density. (b)

Potri.011G098300 (PHB; PHABULOSA)

with SNP 11_11976401 associated with

adaxial stomatal density. (c)

Potri.012G014500 (PMEPCRF; PECTIN

METHYLESTERASE PCR FRAGMENT F)

with SNP 12_1425770 associated with

adaxial stomatal number. (d)

Potri.008G128800 (FAB1C; FORMS

APLOID AND BINUCLEATE CELLS 1C)

with SNP 08_8392536 associated with

adaxial stomatal density. (e)

Potri.003G126900 (GSH1; GLUTAMATE-

CYSTEINE LIGASE) with SNP

03_14770863 associated with adaxial

stomatal number. (f) Potri.001G372400

(ELI3; ELICITOR-ACTIVATED GENE 3)

with SNP 01_38672544 associated with

adaxial to abaxial stomatal density ratio

(AD:AB). Black bars = major allelic variant,

grey bars = heterozygous variant, white

bars = minor allelic variant. AB = abaxial,

AD = adaxial.

© 2014 John Wiley & Sons Ltd

ECOLOGICAL TRADE- OFFS AND AMPHISTOMATY 11

closure in Arabidopsis is GLUTAMATE-CYSTEINE

LIGASE (GSH1) and was implicated in adaxial

stomatal density in P. trichocarpa. The homologue

Potri.003G126900 had five SNPs (3_14763876; intergen-

ic/3_14764946; intron/3_14766296; intron/3_14768902;

intron/3_14770863; synonymous) in high LD (r2 = 0.99;

Table S5, Supporting information), and all alleles

showed phenotypic change in the same direction. The

minor allelic variant for all SNPs was uncommon (n = 1,

MAF > 0.05; Table S4, Supporting information) and had

17-fold higher adaxial stomatal density than the major

allelic variant, with heterozygous variants intermediate

in phenotype (Fig. 3e). A second gene identified by

GWAS, ELICITOR-ACTIVATED GENE 3 (ELI3),

responds to phytopathogenic bacteria in Arabidopsis. The

P. trichocarpa homologue Potri.001G372400 was associ-

ated with the AD:AB stomatal ratio (and adaxial stoma-

tal density at the higher threshold cut-off) by two

significant SNP markers (1_38671609; intergenic/

1_38672544; nonsynonymous). The SNPs are in high

pairwise LD (r2 = 0.74; Table S5, Supporting informa-

tion), and allelic effects of both SNPs on the associ-

Table 4 Coefficient of correlation (r) between stomatal traits from Populus trichocarpa accessions with geoclimate, ecophysiology,

condensed foliar tannins, growth and Melampsora disease susceptibility traits using Pearson’s product-moment correlations

Variable

Density (per mm2) Pore length (lm) SPI

AD AB† AD:AB AD AB AD:AB AD AB

Geoclimate‡

Latitude (°N)§ 0.50* �0.28* 0.51* 0.18 0.20* �0.07 0.48* �0.11

Elevation (m) 0.09 0.03 0.09 �0.05 0.03 �0.06 0.002 0.04

FFD (day) �0.32* 0.10 �0.31* �0.07 �0.09 0.09 �0.23* 0.02

MAT (°C) �0.39* 0.17 �0.39* �0.10 �0.13 0.10 �0.31* 0.06

MWMT (°C) �0.31* 0.18 �0.31* �0.07 �0.13 0.09 �0.22* 0.07

MAP (mm) �0.22* 0.07 �0.21* �0.08 �0.05 0.02 �0.12 0.04

MSP (mm) �0.05 �0.03 �0.05 �0.10 �0.001 �0.03 �0.05 �0.04

AHM 0.22* �0.05 0.19* �0.02 �0.04 �0.03 0.03 �0.10

SHM �0.07 0.05 �0.08 0.07 �0.03 0.08 �0.08 0.04

Ecophysiology‡

Amax (lmol CO2/m2/s) 0.32* �0.09 0.31* 0.03 �0.01 �0.03 0.29 �0.10

C:N (mg/mg) �0.10 0.05 �0.09 �0.12 �0.06 0.03 �0.07 �0.01

Chlsummer (CCI) 0.30* �0.14 0.28* 0.01 0.10 �0.03 0.22 �0.03

Δleaf (&) 0.28* �0.11 0.28* 0.03 0.08 0.01 0.27 �0.04

d13Cwood (&) �0.10 �0.09 �0.09 �0.01 0.13 �0.05 �0.22 0.04

gs (mol H2O/m2/s) 0.44* �0.12 0.42* 0.05 0.09 �0.002 0.37* �0.04

Leaf shape (length:width) 0.07 0.02 0.06 0.07 0.09 �0.01 0.13 0.13

LMAsummer (mg/mm2) 0.03 �0.01 0.04 0.03 0.12 �0.03 0.02 0.12

Nmass (mg/mg) 0.06 �0.01 0.05 0.07 0.04 �0.01 0.03 0.03

NUE (lmol CO2/g/s) 0.20* �0.14 0.19* 0.003 �0.06 0.02 0.20 �0.21*

WUE (lmol CO2/mmol H2O) �0.23* 0.07 �0.22* �0.01 �0.11 0.03 �0.18 �0.04

Foliar tannins

Tannins (lg mg/DW)¶ �0.26* 0.15 �0.25* �0.03 �0.08 0.05 �0.18 0.06

Growth‡

Shoot elongation (log cm/day) 0.42* �0.22* 0.43* 0.14 0.18* �0.06 0.28 �0.08

Disease**

AUDPC 2010 0.51* �0.26* 0.52* 0.21 0.20* 0.002 0.43* �0.09

AUDPC 2011 0.54* �0.20* 0.53* 0.16 0.14 �0.01 0.46* �0.09

AB, abaxial; AD, adaxial; AHM, annual heat moisture index; Amax, maximum photosynthetic rate; AUDPC, area under the disease

progress curve, C:N, carbon:nitrogen; Chl, chlorophyll content; D, net discrimination; d13C, stable carbon isotope ratio; FFD, number

of frost-free days; gs, stomatal conductance, LMA, leaf mass per unit area; MAP, mean annual precipitation; MAT, mean annual

temperature; MSP, mean summer precipitation; MWMT, mean warmest month temperature; NUE, photosynthetic nitrogen use

efficiency; SHM, summer heat moisture index; SPI, stomatal pore index; WUE, instantaneous water use efficiency.

*Significant following Bonferroni multiple testing correction (a = 0.001).†Total and abaxial stomatal densities are highly correlated (r = 0.97) and present similar information.‡Geoclimate, ecophysiology and growth data from McKown et al. (2014a).§Latitude and longitude covary and present similar information.¶Values are log-transformed for normality.

**Disease data from La Mantia et al. (2013).

© 2014 John Wiley & Sons Ltd

12 A. D. MCKOWN ET AL.

ated phenotype were similar. Heterozygous accessions

had the highest AD:AB stomatal ratios, which were

11-fold higher than minor homozygotes, while AD:AB

stomatal ratios of the major homozygotes were 8-fold

higher than minor homozygotes (Fig. 3f). Phenotypes

for adaxial stomatal densities in homozygotes and

heterozygous accessions followed the same pattern as

observed in AD:AB (data not shown).

Stomatal traits related to geoclimate, ecophysiology,growth and disease susceptibility

Stomatal traits in P. trichocarpa were most strongly

correlated with latitude among all geoclimate variables

(Table 4). Climate variables highly associated with

latitude (FFD, MAT and MWMT) also showed

significant but opposite relationships with stomatal

traits. By comparison, weaker or no correlations were

observed between stomatal traits and elevation,

precipitation or heat:moisture indices. The positive

clinal trends with latitude indicated both presence and

greater numbers of adaxial stomata, but not abaxial sto-

mata (Fig. 4). With an increasingly northern latitude of

origin, higher adaxial stomatal density was observed

(Fig. 4a) acting to shift AD:AB stomatal ratios (Fig. 4b).

By contrast, there was a general nonlinear trend of lar-

ger pore sizes in both adaxial and abaxial stomata

among northerly accessions (originating from loca-

tions > 55°N) (Fig. 4c). Adaxial and abaxial pore

lengths scaled linearly (Fig. 4c, inset), resulting in

equivalent AD:AB pore length ratios across the range

(not shown). The trend in adaxial SPI followed adaxial

stomatal density, whereas the abaxial SPI showed no

pattern across the range (Fig. 4d). Of note, the range-

wide differences in abaxial stomata density and pore

size appeared to shift around 55°N, and these combined

to result in maintaining a constant abaxial SPI across

the species range.

There were strong correlations between stomata,

carbon gain, water relations, growth and disease sever-

ity traits (Table 4, Fig. S1, Supporting information). The

strongest correlations were positive relationships

between these traits, adaxial density and AD:AB density

ratio. For instance, accessions with increased AD:AB

stomatal ratio (and adaxial density) showed higher

Amax, greater chlorophyll content, higher gs, faster

intrinsic stem elongation and height growth, and higher

susceptibility to Melampsora infection. These traits also

had negative relationships with intrinsic WUE and

condensed leaf tannins. By comparison, stomatal traits

were largely uncorrelated with nutrient-content traits,

stem-based carbon isotopes (d13Cwood) and leaf

structural traits. Notably, adaxial pore lengths were not

significantly correlated with any other trait, while

adaxial SPI values were significantly correlated with gsand disease severity. Abaxial stomatal density showed

only a few significant correlations and was negatively

correlated with intrinsic height growth and severity of

Melampsora infection. By comparison, abaxial pore

length showed positive relationships with these same

(a) (b)

(c) (d)

Fig. 4 Relationship of stomatal traits in

Populus trichocarpa with latitude. (a)

Adaxial (black circles) and abaxial (white

circles) stomatal densities (# per mm2).

NB, different scales applied to each leaf

surface. (b) Adaxial to abaxial stomatal

density ratio (AD:AB). (c) Adaxial (black

circles) and abaxial (white circles) guard

cell pore lengths (lm). Inset shows the

positive, allometric relationship of

adaxial and abaxial pore lengths. (d)

Adaxial (black circles) and abaxial (white

circles) stomatal pore index (SPI =stomatal density 9 pore length2,

unitless). NB, different scales applied to

each leaf surface. AB = abaxial,

AD = adaxial.

© 2014 John Wiley & Sons Ltd

ECOLOGICAL TRADE- OFFS AND AMPHISTOMATY 13

traits, while abaxial SPI was negatively correlated with

nitrogen use efficiency (NUE).

Alongside these findings, there was a strong negative

correlation between condensed leaf tannins and latitude

(r = �0.52, P < 0.001) and corresponding positive

correlation between Melampsora infection and latitude

(r = 0.73, P < 0.001). Genotypes with more adaxial

stomata had greater Melampsora infection rates and

lower inherent condensed foliar tannins. Individuals

with the GT and TT SNP variants of Potri.012G014500

(homologue of PMEPCRF), which is associated with

both adaxial stomata (Table 3) and Melampsora infection

(AUDPC 2011, La Mantia et al. 2013), also had more

adaxial stomata, higher incidences of disease and lower

condensed tannin levels compared with the major GG

allelic variant (Fig. 5).

Discussion

Stomatal patterning corresponds with latitude

The results from this study show a clear

correspondence in amphistomaty with latitudinal

geography in natural populations of P. trichocarpa

(Fig. 4). Greater numbers of adaxial stomata (increasing

the adaxial stomatal density and adaxial leaf porosity)

and related changes to the AD:AB stomatal ratio were

observed in more northern accessions compared

with southern accessions. Notably, fewer apparent

differences were observed in abaxial stomata traits

resulting in equivalent abaxial leaf porosity observed

across the range. Furthermore, shifting southern trees

northwards (i.e. planting accessions originating at 44°Nin a common garden at 49°N) did not result in these

southern genotypes developing amphistomaty.

Leaves of P. trichocarpa have often been described as

hypostomatous (Ceulemans 1990; Afas et al. 2007);

however, this may have been due to limited work using

northern genotypes of P. trichocarpa. Dunlap & Stettler

(2001) observed some adaxial stomata in populations of

P. trichocarpa from dry, interior environments of

Washington and suggested they might result from

introgression with nearby P. deltoides populations.

Among our accessions, however, introgression is

unlikely to have influenced stomatal patterning. There

is genetic evidence for limited introgression in northern

and interior locations of the species range where

P. trichocarpa and its sister species, P. balsamifera, can

hybridize (Geraldes et al. 2014). Genetic introgression

would be unlikely to result in amphistomaty, as

anatomical features of P. balsamifera have been

investigated across its range and the species is consid-

ered essentially hypostomatous (Soolanayakanahally

et al. 2009; Pointeau & Guy 2014). Among our

accessions, there were a few northern and interior

individuals with >20% admixture from P. balsamifera

(Geraldes et al. 2014) and these had numerous adaxial

stomata and high adaxial stomatal densities, in

accordance with their mostly P. trichocarpa heritage.

Underlying genetics of stomatal patterning

Stomatal distributions and patterning were relatively

consistent across years in P. trichocarpa reflecting the

moderate heritability of many stomatal traits (Table 1).

Traits correlating with latitude, particularly adaxial

stomatal traits and AD:AB stomatal ratio, had the

highest heritabilities (H2 = 0.39–0.42; Table 1). This is

consistent with other studies where traits, such as

adaxial and abaxial stomatal densities, and AD:AB

stomatal ratio have also been found to be relatively

stable and heritable from reciprocal plantings in

common garden studies of P. trichocarpa (Dunlap &

Stettler 2001) and in Populus species crosses (Ceulemans

1990). In this study, genetic associations using the 34K

SNP array were retrieved with variation in traits related

largely to adaxial stomata among our P. trichocarpa

accessions. These associations implicated genes

involved in stomatal development and behaviour,

polarity patterning and disease/wound response and

Fig. 5 Putative allelic effects of SNP 12_1425770 (upstream of

Potri.012G014500, homologue of PMEPCRF; PECTIN

METHYLESTERASE PCR FRAGMENT F) on the associated

phenotypes adaxial stomatal number (based on binned

classification of stomatal numbers, see Methods) and

Melampsora disease severity (AUDPC 2011) (�standard error).

The corresponding foliar condensed tannin content is included

to demonstrate that susceptible allelic variants (GT, TT) are

more amphistomatous (i.e. have more adaxial stomata) and

lower levels of condensed foliar tannins.

© 2014 John Wiley & Sons Ltd

14 A. D. MCKOWN ET AL.

may be significant within an ecological context for plant

functioning and survival.

The functional annotations of these genes in

Arabidopsis remain to be verified within P. trichocarpa;

however, some of the loci detected by GWAS have

precedent for involvement in stomata and are strong

candidates for understanding stomatal development

and/or function in Populus. For instance, BIN2 (a

Shaggy-like kinase) is regulated by brassinosteroids and

has a direct role in regulating SPEECHLESS (SPCH),

which triggers stomatal formation (Gudesblat et al.

2012; Kim et al. 2012). BIN2 also influences stomatal

spacing and bin2 mutants showed clustered stomata

(Khan et al. 2013). FAB1C (a phosphatidylinositol-3P 5-

kinase) is plant specific, related to rapid stomatal

response, and associated with water loss through vacu-

olar acidification of guard cells (Bak et al. 2013). The

impaired abscisic acid (ABA) response in fab1c mutants

resulted in delayed stomatal closure and accelerated

water loss relative to wild-type Arabidopsis, suggesting a

direct genetic link with WUE. While genes for WUE in

P. trichocarpa have not yet been identified using GWAS

(cf. McKown et al. 2014b), genes associated with stoma-

tal traits with putative effects on WUE might present

good candidates for future research relating to this trait.

Other loci detected implicate additional phenotypes

related to known gene functions. For instance, PHB

(encoding a member of the HD-Zip family) is well

recognized in plant development and polarity

patterning, and specification of the adaxial and abaxial

axis (McConnell et al. 2001); however, it has not been

implicated in development of stomata or stomatal

patterning in any species. In P. trichocarpa, the

homologue of PHB may have a role in specifying

stomatal development on the adaxial surface of the leaf.

Similarly, GSH1 (encoding the enzyme glutamate–

cysteine ligase) is important in the molecular

mechanisms underlying plant responses to stress and

infection by pathogens (Dubreuil-Maurizi et al. 2011;

Dubreuil-Maurizi & Poinssot 2012). GSH1 is also

involved in ABA-induced stomatal closure through

regulating glutathione content in guard cells (Okuma

et al. 2011). While GSH1 has not been linked directly

with stomatal development, the association between

GSH1 and stomatal patterning in P. trichocarpa might

represent a coselection of traits. Similarly, genes such as

ADP/ATP CARRIER 3 (AAC3), ELICITOR-ACTIVATED

GENE 3 (ELI3), GENERAL CONTROL NON-

REPRESSIBLE 3 (GCN3), METHIONINE SYNTHESIS 1

(ATMS1) and PMEPCRF have annotated effects on

pathogen/wound response in Arabidopsis and may

represent coordination of stomata traits and disease

response.

We compared our list of stomatal trait-associated

SNP markers and genes to those found in other studies

of our P. trichocarpa population. More than one-third of

loci (7/18 = 39%) uncovered through our association

analysis were also detected in other GWAS (at a = 0.05)

and FST outlier studies (Table 3). These included

overlaps of associations with phenology traits (McKown

et al. 2014b) and Melampsora infection (La Mantia et al.

2013), and FST outliers based on geography and climate

(Geraldes et al. 2014). For example, the SNP uncovered

for adaxial stomatal number in Potri.004G010100

(homologue of SKU5 SIMILAR 4) was also associated

with bud set phenology (McKown et al. 2014b). The

two SNPs located upstream of Potri.014G127000

(pectinesterase family protein) associated with adaxial

SPI and a SNP in Potri.018G139200 (unknown)

associated with AD:AB ratio were also retrieved

through geographical FST analysis (Geraldes et al. 2014).

In Potri.001G087300 (homologue of GCN3), the SNP

associated with the presence of adaxial stomatal was

also detected by phenology/biomass trait associations

(McKown et al. 2014b) and as a geographical FST outlier

(Geraldes et al. 2014). By comparison, Potri.008G128800

(homologue of FAB1C) was associated with both adaxial

stomatal density and Melampsora infection (La Mantia

et al. 2013), but the associations involved separate

intronic and exonic SNPs, respectively. Notably,

Potri.012G014500 (homologue of PMEPCRF) had the

same upstream SNP retrieved by associations with

adaxial stomatal number, numerous phenology traits

(McKown et al. 2014b), Melampsora infection (La Mantia

et al. 2013) and geography and climate FST outlier

studies (Geraldes et al. 2014). Two additional SNPs

within Potri.012G014500 (homologue of PMEPCRF)

were also associated with Melampsora infection (La

Mantia et al. 2013). In a separate study, Zhou et al.

(2014) also found an FST outlier SNP in the same region

upstream of Potri.012G014500 (homologue of

PMEPCRF), and the authors considered this to be a

likely promoter region for the gene (Zhou et al. 2014).

Finally, RNA sequencing of 192 P. trichocarpa accessions

using juvenile leaves (with replicates) determined that

all genes retrieved in our GWAS were expressed during

leaf development (Table S6, Supporting information),

and 11 of 18 genes were considered to be differentially

expressed among these accessions (C. Hefer and

S. Biswas, personal communication).

Physiological variation related to stomatal patterning

Correlation analyses between stomatal traits and a

number of previously published ecophysiological,

growth and disease parameters for P. trichocarpa

© 2014 John Wiley & Sons Ltd

ECOLOGICAL TRADE- OFFS AND AMPHISTOMATY 15

demonstrated that the potential functional effects of

changing stomatal patterning lie largely in amphistom-

aty (i.e. changing the numbers of adaxial stomata and

the related AD:AB stomatal ratio) (Table 4). By compar-

ison, modifying abaxial stomatal densities and/or

stomatal pore lengths appeared to have less effect on

the ecophysiological and disease traits included in our

study (based on the correlative relationships). Despite

the positive linear relationship between adaxial and

abaxial stomata pore lengths, adaxial stomata were con-

sistently smaller than abaxial stomata underscoring that

the physiological effects of modifications to stomatal

patterning are probably related to adaxial stomatal

numbers and not size.

Effects of amphistomaty through higher adaxial

stomatal density in P. trichocarpa had the greatest

influence on conductance (i.e. increased gs) that

supported higher photosynthetic rates (Amax) while

indicating lower WUE relative to carbon gain

(Table 4). Lower WUE among accessions with higher

adaxial stomatal density was confirmed by leaf-based

carbon isotope discrimination (Δleaf). A corresponding

trend in increased leaf chlorophyll content (but not C:

N or Nmass) was observed which, alongside increased

gas exchange, probably also acted to support higher

photosynthesis. As chlorophyll content is not function-

ally known to relate to stomatal density, this finding

may be indicative of coselection for leaf traits that

maximize rapid carbon gain in northern genotypes of

P. trichocarpa. By comparison, LMA, which is related

to leaf thickness and has been correlated with adaxial

stomatal density in P. trichocarpa (Afas et al. 2007),

showed no relationship to stomatal traits among our

accessions and suggests that changed stomatal densi-

ties and/or stomatal locations (i.e. amphistomaty)

may be uncoupled with thicker leaves (cf. Mott et al.

1982). Higher adaxial stomatal density in P. trichocarpa

was correlated with faster intrinsic terminal shoot

elongation among more northern genotypes,

supporting the hypothesis of selection for leaf traits

sustaining greater carbon gain and growth with

increasing latitude. However, faster growth rates also

correlated with lower condensed tannin content and

higher incidences of Melampsora infection, suggesting

differences in environmental selection pressures and/

or trait trade-offs across the range of P. trichocarpa.

All stomatal anatomical traits (measured from

individual leaves per ramet) showed some level of

plasticity across the P. trichocarpa accessions, yet trends

with geography and other phenotypic traits affecting

carbon gain and whole plant physiology were robust.

While this study highlights some clear relationships

between ecophysiological traits and the physical

parameters of leaf stomata (i.e. location, size, number),

differences in crown architecture, leaf production rates

and total leaf area must also influence whole plant

production (Ridge et al. 1986; Ceulemans 1990; Orlovi�c

et al. 1998; Afas et al. 2007), of which terminal bud set

phenology is a major determinant (Soolanayakanahally

et al. 2013). An additional component of this variability

includes stomatal behaviour, which was not part of this

study. The adaxial and abaxial leaf surfaces experience

differences in solar irradiance and turgor of the

surrounding epidermal cells (Mott 2007) and

accordingly respond differently depending on the

microclimate (Pallardy & Kozlowski 1979; Ceulemans

et al. 1988).

Evolutionary trade-offs invoked in range-wide selection

Along the latitudinal range of P. trichocarpa, clinal

trends suggest selection for amphistomaty and stomatal

patterning modifying adaxial stomatal density to

increase leaf gas exchange rates supporting greater

carbon gain and faster growth among northern

genotypes. A strong correlation between substantially

higher incidences of Melampsora infection and latitude

(r = 0.74, P < 0.001) is also evident in P. trichocarpa (La

Mantia et al. 2013). This occurs alongside the finding

that adaxial stomatal density (and pore length to a

lesser extent) among our P. trichocarpa accessions was

positively correlated with severity of Melampsora

infection (Table 4). Given that Melampsora invades via

stomata, the susceptibility may simply be linked to a

greater number of potential infection sites, particularly

on the adaxial surface. Dunlap & Stettler (2001) also

observed that P. trichocarpa clones with amphistomaty

(i.e. greater adaxial stomatal densities) were more

susceptible to M. occidentalis than hypostomatous

clones. In addition, P. trichocarpa keep stomata

physically open for long periods of time, both diurnally

and seasonally (Siwecki & Przybyl 1981; Ceulemans

et al. 1988; McKown et al. 2013). Siwecki & Przybyl

(1981) outlined this stomatal behaviour as largely

responsible for severity of Melampsora infection across

the genus Populus, although inspection of their data set

demonstrates that higher susceptibility was also

observed in P. trichocarpa genotypes with an increased

number of stomata (including adaxial stomata).

The strong negative correlation between condensed

leaf tannins and latitude indicates that northern

genotypes may invest more carbon into growth and less

carbon in secondary compounds, such as defence

compounds (at least prior to Melampsora infection cf.

Miranda et al. 2007). Although we do not suggest that

Potri.012G014500 (homologue of PMEPCRF, a pectin

methyltransferase) necessarily has any direct role in

determining tannin content, the correspondence

© 2014 John Wiley & Sons Ltd

16 A. D. MCKOWN ET AL.

between fewer adaxial stomata and lower Melampsora

infection (associated with this gene), and higher

condensed tannins (Fig. 5) may indicate a relationship

between hypostomaty and increased secondary

compounds in P. trichocarpa, prevalent in more

southerly genotypes. By contrast, if pathogen pressure

in the local environment is much lower, such as in

more northern latitudes or higher elevations (cf. Traw

& Bergelson 2010), this may have selected for reduced

condensed foliar tannin content and optimizing and

investing the carbon in enhanced growth rather than

secondary compounds for defence (Fagerstrom et al.

1987; Herms & Mattson 1992).

The GWAS results in this study indicate that there

may be some coselection of genes involved in pathogen

response along with increased adaxial stomata;

however, strong disease resistance among northern

P. trichocarpa accessions was not observed in common

garden studies at both higher and lower latitudes (54°Nand 49°N, respectively) (Xie et al. 2009, 2012; La Mantia

et al. 2013). Rather, these studies noted the inherent

susceptibility, high disease damage and mortality

occurring among northern P. trichocarpa accessions.

Thus, structural leaf traits, such as increased adaxial

stomata, that might result in greater potential for

pathogen attack and damage appear maladaptive. It is

possible that northern P. trichocarpa genotypes have

lower inherent resistance to diseases because pathogen

pressure in poleward environments is generally

considered to be low, probably relating to temperature

(Traw & Bergelson 2010), or alternatively, these

genotypes may have resistance developed to track a

suite of local pathogens from their original

environment. Another possibility is that the seasonal

timing when canopy diseases occur, such as late

summer Melampsora infection, may be correspondingly

curtailed in cooler, northern environments, thereby

limiting losses to disease among these P. trichocarpa

populations. For instance, timing of rust inoculum loads

in the Totem Field common garden generally occurred

in late summer and/or early fall (La Mantia et al. 2013).

In P. balsamifera, rust infection has also been noted to

occur late in the season and immediately prior to leaf

drop (R. Soolanayakanahally, personal communication).

Bud set generally marks a period of shifting leaf

physiology to increase gas diffusion through stomata

resulting in higher gs and photosynthetic rates in

P. trichocarpa (Ceulemans et al. 1988; McKown et al.

2013), while disease resistance signalling components

may become suppressed under short-day photoperiods

(Li et al. 2014). Melampsora infection would reduce the

ability of the tree to boost photosynthate production

during fall periods (i.e. ‘post-bud set period’ cf.

McKown et al. 2013) as expression levels of

photosynthetic genes become greatly reduced following

compatible poplar leaf rust infection interactions

(Miranda et al. 2007; Major et al. 2010).

It is possible that modified stomatal traits observed in

northern genotypes of P. trichocarpa may not actually

result in increased pathogen attack in native

environments. Nonetheless, as projected changes to

climate across western North America predict warmer

annual temperatures, extended growing seasons and a

corresponding shift of species northwards (cf. Wang

et al. 2012), this may include changing pathogen

distributions, emergence of virulent races of southern

pathogens and/or earlier onset in timing of diseases in

northern ecosystems. While response to pathogens

might be more equivalent during summer-free growth,

the inherent susceptibility among northern provenances

is more apparent later in the canopy cycle when

Melampsora infections occur. Thus, while southern

populations of P. trichocarpa appear to have evolved

mechanisms relating to disease reduction, northern

populations of P. trichocarpa may be inherently

maladapted for future pathogen distributions.

Conclusions

Current findings within this study suggest a functional

anatomical trade-off between amphistomaty (i.e.

stomata occurring on both upper/adaxial and lower/

abaxial leaf surfaces) supporting increased gas exchange

and higher carbon gain vs. hypostomaty (i.e. stomata

occurring only on the lower/abaxial leaf surface) limit-

ing the severity of pathogen attack. Although further

assessment with additional SNP markers is required to

fully understand the genetic architecture of stomatal

patterning, our GWAS suggests that the developmental

modifications resulting in amphistomaty through higher

adaxial stomatal density might relate to a small number

of genes. This implies that the genetic specifications of

stomata could change rapidly under strong selection

pressure. Stomata are relatively plastic over geological

time changing in size and/or density in different

species to meet current environmental needs (Franks &

Beerling 2009). In higher latitude environments, the

necessity for maximizing carbon gain and growth in a

limited summer season is probably substantial, while

the extended growing season experienced by lower

latitude genotypes can support investment in secondary

compounds and lower intrinsic rates of carbon gain

relating to lower overall stomatal density, fewer adaxial

stomata and smaller pore sizes. Within P. trichocarpa

(and possibly other tree species with a north–south

distribution), changing stomatal patterning underscores

a significant ecological trade-off to increase fitness

supported by greater carbon gain and faster growth

© 2014 John Wiley & Sons Ltd

ECOLOGICAL TRADE- OFFS AND AMPHISTOMATY 17

with the potentially high cost of increased disease

susceptibility.

Acknowledgements

This work was supported by the Genome Canada Large-Scale

Applied Research Project (Project 168BIO) funds to

RDG, CPC, YAE-K and RCH. We thank A. Geraldes and

R. Soolanayakanahally for helpful comments and discussion,

and S. Biswas and C. Hefer for developmental leaf

transcriptome data.

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A.D.M. and R.D.G. conceptualized this study and its

contents. A.D.M. oversaw data collection, performed

statistical analyses, interpreted the results and wrote the

manuscript. L.Q. was responsible for technical aspects

of tissue collection and stomatal assessment. J.K.

performed the heritability, genetic correlation and

association analyses. J.L.M. and R.C.H. provided insight

into the effects of Melampsora. C.P.C. and M.Z. were

responsible for analysis of condensed foliar tannins.

Y.A.E. provided insight into the association analyses.

M.S.A. scored Melampsora disease incidence at the

Totem Field common garden.

Data accessibility

All trait data and R scripts used in determining

population structure are publicly available as online

supplemental material. Geographical and trait data

from previous publications (La Mantia et al. 2013;

McKown et al. 2014a) are also included within the

Supporting Information. SNP data for all P. trichocarpa

accessions are hosted by New Phytologist in support of

McKown et al. 2014b (DOI: 10.1111/nph.12815).

Supporting information

Additional supporting information may be found in the online

version of this article.

Fig. S1 Relationships between ecophysiology, leaf traits,

growth, disease susceptibility, and the adaxial: abaxial stomatal

density ratio (AD:AB) in Populus trichocarpa.

Table S1 Stomatal trait data for P. trichocarpa accessions.

Table S2 Biogeographical data1, climate data2, condensed foliar

tannins, physiological3, growth3, leaf trait3, and disease data4

for P. trichocarpa accessions.

Table S3 Broad-sense heritability values (H2) for stomatal and

condensed foliar tannin traits measured in 448 genotyped

P. trichocarpa accessions determined using a simple model.

Table S4 Full details of SNP-trait associations using

genome-wide association studies (GWAS) in P. trichocarpa indi-

cating population structure correction model, associated P-val-

ues, significance (a), marker r2, closest Arabidopsis homolog

and putative gene function/annotation.

Table S5 Pairwise linkage disequilibrium (LD) r2 values

between all SNP markers significant at P < 3.4 9 10�6. Values

≥0.3 are highlighted in blue.

Table S6 Expression and transcript abundance of genes

retrieved by GWAS associated with stomatal traits from RNA

sequencing of developing leaves from 192 P. trichocarpa

accessions.1.

Appendix S1 Supplementary methods: Full details for method-

ology determining stomatal trait parameters and condensed

foliar tannins.

Appendix S2 R script for population structure correction in

GWAS.

Appendix S3 Kinship matrix for structure correction in GWAS.

Appendix S4 Stomatal trait file used for GWAS.

© 2014 John Wiley & Sons Ltd

20 A. D. MCKOWN ET AL.