Cytological, genetic and agronomic characterization of a ...

Cytological, genetic and agronomic characterization of a barley reciprocal translocation

Alba Farré Martinez

Cytological, genetic and agronomic characterization of a barley reciprocal

translocation


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Thesis committee Thesis supervisor Prof dr. F.A. van Eeuwijk Professor of Applied Statistics Wageningen University Thesis co-supervisors Prof dr. I. Romagosa Professor of Crop Science University of Lleida, Spain Dr.ir. J. Jansen Senior Research Scientist, Biometris Wageningen UR Other members

Prof. dr. J. Voltas, University of Lleida, Spain Dr. W.T.B. Thomas, The James Hutton Institute, Dundee, UK Prof. dr. R.G.F. Visser, Wageningen University Prof. dr. J.H.S.G.M. de Jong, Wageningen University This research was conducted under the auspices of the C.T. de Wit Graduate School of Production Ecology and Resource Conservation.

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Cytological, genetic and agronomic characterization of a barley reciprocal

translocation


Thesis submitted in fulfillment of the requirements for the degree of doctor

at Wageningen University by the authority of the Rector Magnificus

Prof. dr. M.J. Kropff, in the presence of the

Thesis Committee appointed by the Academic Board to be defended in public

on Wednesday 17 October 2012 at 4 p.m. in the Aula.

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Alba Farré Martinez Cytological, genetic and agronomic characterization of a barley reciprocal translocation, 130 pages.

PhD thesis Wageningen University, Wageningen, The Netherlands (2012) With references, with summaries in Dutch and English ISBN 978-94-6173-411-2

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“Als de casa”

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Contents

Chapter 1 General introduction …………………………………………………….5

Chapter 2 Linkage map construction involving a reciprocal translocation ……….15

Chapter 3 General characterization of a reciprocal translocation present in a widely

grown barley variety …………………………………………………...31

Chapter 4 Agronomic effects of a large reciprocal translocation present in a widely

grown Spanish barley variety …………………………………….…....49

Chapter 5 Construction of an integrated genetic linkage map of barley (Hordeum

vulgare L.) involving a parent carrying a reciprocal translocation .…...55

Chapter 6 QTL analysis in multiple interconnected barley doubled haploid

populations in the presence of a reciprocal translocation …………...…83

Chapter 7 General discussion ………………………………………….…….…..106

References ……………………………………………………………….………..….115

Summary

Samenvatting

Acknowledgements

Curriculum vitae

1

Chapter 1

General introduction

Today, cereals are still the basis of global agriculture by providing more than half the

human food consumption. Among the cereals, barley ranks fourth after maize (Zea

mays), wheat (Triticum ssp.) and rice (Oryza sativa) with the widest range of production

areas in the world (130-140 million tonnes in the recent years; Horsley et al. 2009). In

Spain, barley is the cereal with the largest cultivated area (2.8 million ha), 46% of the

total area used for growing cereals, with an annual production of 9 million tonnes which

corresponds with approximately 51% of the total cereal production (MARM; 2011).

Cultivated barley (Hordeum vulgare) is a diploid species (2n = 2x =14), with some

tetraploid and hexaploid wild relatives (Martin et al. 1999). It has been derived from the

wild progenitor Hordeum vulgare ssp spontaneum, which continues to grow in the

Middle East. Barley is one of the most widely adapted plant species grown in a wide

range of environments from near-arctic to semi-desert. Barley varieties have been

classified according to their morphology and agronomic adaptation. Morphological,

barley varieties can be divided according the number of kernel rows in the head: two-

row (only one spikelet at each node is fertile) and six-row (all three spikelets are fertile).

Considering agronomic adaptation, varieties can be classified into three types: winter,

spring and facultative. Winter barley varieties are tolerant to low temperature, sensitive

to daylenght and require vernalization. Spring barley varieties do not require

vernalization, and are typically insensitive to short day photoperiod. Facultative barley

varieties are tolerant to low temperatures, but do not require vernalization (Zitzewitz et

al. 2005).

Despites its large genome (approximately 5,100 Mb; Arumuganathan and Earle 1991;

Doležel et al. 1998) barley provides an excellent model for other Triticeae species

because it is a diploid self-pollinating species with a huge genetic variability. It has been

found that the large size of its genome is not due to the presence of a greater number of

genes in comparison with other species from the Triticeae tribe (family Poaceae), but to

the presence of highly repetitive DNA (80% of the genome), mostly retrotransposons (

Chapter 1

2

Bennetzen et al. 1998; Ramakrishna et al. 2002; Schulman et al. 2004). In fact, it has

been estimated that barley has around 32,000 genes, which is not very different from

rice (41,000 genes, Jung et al. 2008), Sorghum (34,500 genes, Paterson et al. 2009) or

Brachypodium (30,000 genes, The International Brachypodium Initiative 2010). The

genetic progress in barley has been focused on improving: yield and stability, resistance

against diseases and pests, malting quality and quality as animal feed. Barley is grown

for many purposes, but most barley is used as animal feed, human food and the

production of malt.

The barley variety ‘Albacete’

Conventional plant breeding have been successful in improving yield and yield stability

of some important crops under favourable conditions or to conditions which could be

made favourable by the use of fertilizers, irrigation, pesticides and fungicides. However,

current research is focused on raising yields under low-input conditions, which are more

self-sustaining and less harmful to the environment.

In the semiarid areas of Spain crop productivity is not only limited by drought, but also

by high temperatures at the end of the growth cycle. The increased use of ‘local’

germplasm could lead to the selection of varieties adapted to specific regional

conditions. So, the use of a barley variety like ‘Albacete’, with its proven adaptation to

semiarid conditions, can be an excellent option.

In Spain ‘Albacete’ was the most widely grown barley variety during the last decades

(up to 1 million ha/year), particularly in semiarid rain-fed areas. This variety was

obtained more than 50 years ago by Enrique Sánchez-Monge at the Estación

Experimental Aula Dei (Spanish Research Council) in Zaragoza, as an inbred line in a

local heterogeneous landrace population from the Albacete province. It is a six-row

facultative variety with a relatively long growth cycle but showing lodging at the end of

the cycle. Its yield, in optimal environmental conditions, is average compared to other

cultivars. However, its tolerance to cold and drought makes ‘Albacete’ the best choice

in years with low rainfall. For all these properties, it has been grown for decades,

particularly in drought-prone areas.

General Introduction

3

Lasa et al. (1987) investigated different barley populations under drought conditions in

Spain using ‘Albacete’ cultivar as a check. They found significant differences between

the populations and between the populations and ‘Albacete’ for all the traits (related to

crop development, growth and yield components). For most of the traits, the local

cultivar ‘Albacete’ gave the best results, with the exception of test weight and lodging.

‘Albacete’ was the latest in flowering, and had the shortest grain filling period. Later,

Arnau et al. (1997) studied the effect of water stress on plant water status and net

photosynthetic gas exchange in six barley genotypes differing in productivity and

drought tolerance. ‘Albacete’ showed the highest osmotic adjustment capacity, relative

water content and photosynthetic gas exchange. The high osmotic adjustment capacity

of ‘Albacete’ could explain its high yield under very dry conditions.

Intense breeding efforts to cross ‘Albacete’ with other varieties during the 1970s and

80s failed due to the sterility of the offspring, which gave ‘Albacete’ a poor reputation

as a parent in breeding programmes. Vazquez and Sanchez-Monge (1987) found the

cytological cause of this sterility by carrying out meiotic analyse of semi-sterile F1

hybrids involving ‘Albacete’. The presence at metaphase-anaphase I of five bivalents

and one quadrivalent, representing 75% of PMC (pollen mother cells) (Figure 1),

provided clear evidence of the existence of a reciprocal translocation. This high

percentage indicates that the interchanged segments must be of considerable length.

They also detected that the coorientation of the quadrivalent in the hybrids of ‘Albacete’

was mainly of the adjacent type (74%) and the average fertility of the translocation

heterozygotes was 54%. However, they did not identify the chromosomes involved. A

preliminary study has revealed that chromosomes 1H and 3H are involved in the

reciprocal translocation (Lacasa-Benito et al. 2005). ‘Albacete’ is the only known,

widely cultivated barley variety that carries a reciprocal translocation. Until now, it is

unknown whether the translocation is responsible for the drought tolerance and whether

it has some interesting phenotypic attributes that could be transferred to other barley

genotypes to develop specific germplasm adapted to stress.

Chapter 1

4

Figure 1. Meiotic metaphase of F1 hybrid involving ‘Albacete’ showing 5 II + 1 IV (adjacent

coorientation). (provided by L. Cistué)

Chromosome rearrangements

Chromosome rearrangements include deletions, duplications, inversions and

translocations have played an important role in plant evolution. Each of these events can

be caused by chromosome breakages which are followed by the reunion of broken ends

(Figure 2a) or crossing-over between repetitive DNA segments (Figure 2b). Sometimes

these breaks will occur within genes generally disrupting gene functions.

There are two general types of rearrangements, balanced and imbalanced. Imbalanced

rearrangements change the total amount of chromosomal material of the affected

chromosomes. The two simple classes of imbalanced rearrangements are deletions and

duplications. Some examples in human are the cri du chat (del (5p)) or Wolf-

Hirschhorn (del (18p); del (18q); del (4p)) syndromes. In contrast, balanced

rearrangements change the chromosomal gene order but do not change the total amount

of chromosomal material. The two simple classes of balanced rearrangements are

inversions and reciprocal translocations.


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Figure 2. Origins of chromosomal rearrangements: (a) by breakage and rejoining; (b) by crossing-

over between repetitive DNA

Reciprocal translocations are produced by an interchange of chromosome segments

between two non-homologous chromosomes. Rieger et al. (1968) classified the

reciprocal translocations into asymmetrical or symmetrical translocations depending on

the way the chromosome segments rejoin after a chromosomal breakage (Figure 3). In

an asymmetrical translocation, the segments carrying the centromeres are joined

together resulting in an acentric (without centromere) and a dicentric (with two

centromeres) chromosomes. Standard monocentric chromosomes are formed in

symmetrical translocations, which are often viable.

(a)

(b)

= break

= repetitive DNA segments

= rejoining

= crossover

Chapter 1

6

Figure 3. Possible products of a reciprocal translocation interchange

When a symmetrical reciprocal translocation occurs, two new chromosomal

arrangements appear, so the individuals can be: (i) homozygotes for the standard

arrangement (Figure 4a); (ii) homozygotes for the interchange (Figure 4b) and (iii)

heterozygotes for the interchange (Figure 4c). For both homozygotes the meiotic

behaviour is regular as they form bivalents. The complex meiosis for the structural

heterozygote is explained below.

Figure 4. Possible individuals resulting from the reciprocal translocation

Meiosis in heterozygotes having two translocated chromosomes and their normal

counterparts causes some important genetic and cytological effects. During meiotic

prophase I homologous chromosomes interact with each other through precise synapsis

and crossover recombination. In the case of a reciprocal translocation heterozygote,

saturated pairing gives rise to a quadrivalent (association of 4 chromosomes) involving

the two translocation chromosomes and their non-translocation counterparts instead of

two independent bivalents in the normal situation (Burnham 1962; Sybenga 1975).

Various configurations can be observed at diakinesis–metaphase I, depending on the

number and positions of the crossing overs: zig-zag shapes, rings and open forms of 2–4

chromosomes, as well as univalents. As shown in Figure 5, crossing overs may occur in

three types of chromosomal segments: the interchanged segment, the interstitial

segment (between translocation points and centromeres) and the non-interchanged

segments (chromosome arms distal to the centromeres).

a) b) c)

Symmetrical

Asymmetrical


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Figure 5. Pairing diagram of translocation heterozygote (1 and 2 are the normal chromosome

arrengement, 12 and 21 are the translocated chromosomes)

If no crossing over takes place in the interstitial segments, the viability of the resulting

gametes will depend upon the coorientation of the centromeres at metaphase I. These

could be: (i) alternate segregation (corresponding with a zig-zag configuration of the

quadrivalent) or (ii) adjacent segregation (corresponding with a ring configuration of the

quadrivalent). The latter type is further divided into two classes: Adjacent-2 and

Adjacent-1 segregations, according to the separation of homologous centromeres, and

whether they end up into the same Telophase I cell or not, respectively. Adjacent

segregation leads to gametes with a translocation and a non-translocation chromosome,

containing a duplicated and a deleted segment; this leads to non-viable gametes.

Alternate segregation occurs when the chromosomes on opposite sides of the

translocation cross segregate into the same pole. In these cases, four balanced gametes

are formed: 50% carry the normal chromosome arrangement, and 50% have the

translocated chromosomes. Hence, depending on the relative frequency of the

alternative orientation, individuals that are heterozygous for a translocation will produce

a certain proportion of non-viable gametes. This results in a reduction of fertility; it is

called semi-sterility.

If we assume that a crossover occurs in one interstitial segment followed by alternate or

adjacent-1 segregations, 50% of the gametes belong to the non-recombinant parental

type and the other 50%, recombinant, carry a segment deficiency and duplication and

are usually non-viable. The same crossover followed by adjancent-2 will produced non-

viable gametes. It is important to note that, in barley, the alternate segregation in the

interchange heterozygote is more frequent than the others types of separations, therefore

crossing over will further reduce genetic recombination of loci within the interstitial

segment because the chromatids carrying the crossover pass to the unbalanced gametes

(Burnham, 1964). Therefore the presence of a reciprocal translocation reduces

1 21

2 12

× × × ×

×

×

Chapter 1

8

recombination frequencies between the translocation breakpoints (TB) and the

centromere. If the TB is close to or in the centromere region, the reduction in

recombination that may take place will be due to the interference effects in the flanking

TB region.

Lacadena (1989) showed that more complex combinations of crossovers may lead to

balanced gametes carrying recombination within the interstitial segment. For instance, if

a single crossover occurs in both interstitial segments and in non-interchanged

chromosome arms distal to the centromeres, it may happen that with adjacent

segregation some gametes results in balanced recombinant chromatids. Following the

same reasoning, the alternate segregation could generate unbalanced gametes. Thus, the

possibility of crossing-over in the interstitial region can alter the viability of gametes

produced after an adjacent or alternate segregation.

Reciprocal translocations may occur spontaneously or in response to irradiation or

treatments with certain chemicals. The first report on a naturally occurring reciprocal

translocation was by Belling (1914) in the Florida velvet bean (Stizolobium

deeringianum), and Muller (1930) was first to report on X-ray-induced translocations in

Drosophila. In barley, few cases of spontaneous reciprocal translocations have been

described in cultivated barley, although they are induced frequently by mutagen

treatments. Konishi and Linde-Laursen (1988) conducted an exhaustive study which

showed that chromosomal rearrangements such as inversions and translocations rarely

occur spontaneously in barley. They investigated 1,240 cultivated barley lines and 120

wild barley lines to detect spontaneous reciprocal translocations. Of the 1,240 cultivated

barley lines, four Ethiopian landraces carrying a reciprocal translocation had the same

breakpoints at the centromere involving chromosomes 2H and 4H (2HS·4HS and

2HL·4HL), suggesting that the chromosomes involved in the rearrangement had a

common origin. Of the 120 wild barley genotypes, three carried translocations between

chromosomes 2H and 4H, 3H and 5H and 3H and 6H, respectively.

Translocations have been widely utilized in both applied and fundamental scientific

research for chromosome mapping, in particular for assigning linkage groups to

chromosomes, development of physical maps in plants (Kim et al. 1993; Sorokin et al.

1994; Marthe and Künzel 1994; Künzel et al. 2000), and to improve our understanding


9

of meiotic chromosome pairing behaviour (Rickards 1983). They have been reported in

a number of crop species, such as rye (Benito et al. 1994), soybean (Mahama and

Palmer 2003), Prunus (Jáuregui et al. 2001), Lens (Tadmor et al. 1987), pea (Kosterin et

al. 1999), wheat (Naranjo et al. 1987; Badaeva et al. 2007), Brassica napus (Osborn et

al. 2003) and other crops.

Methodological aspects

Some methodological problems arise when dealing with reciprocal translocations:

i. Map construction:

Specific methodology for linkage map construction in the presence of a

reciprocal translocation has to be developed in order to cope with the ‘pseudo-

linkage’ present between the chromosomes involved in the interchanges.

Durrant et al. (2006) introduced QuadMap, a software application, to analyze

linkage maps affected by translocations. Large intermarker distance variance

was proposed as an indication of the presence of a breakpoint. However, high

variances may also be caused by gross deficiencies in the data.

ii. Integrating linkage maps:

Integrating linkage maps of multiple populations requires powerful methods to

handle the huge number of missing data due to markers not segregating in all

populations. A widely used platform for the construction of genetic linkage

maps is provided by JoinMap®. However, the regression algorithm of

JoinMap® fails when it is required to integrate linkage maps involving large

numbers of markers. Besides that, the effect of the reciprocal translocation on

the construction of a linkage map must be taken into account.

iii. QTL analysis in multiple populations:

QTL methods have been developed for multi-trait and multi-environment but

few studies have been published using interconnected mapping populations in

cereals (i.e. Blanc et al. 2006, 2008; Cuesta-Marcos et al. 2008a; Liu et al.

2010). The model used for QTL analysis must involve a correction for the

Chapter 1

10

effect of the translocation as the reciprocal translocation is present in a part of

the populations. In populations involving the translocations we have to deal

with split linkage maps.

Scope of the thesis

The aim of the thesis is to develop an in depth understanding of the reciprocal

translocation present in the widely grown Spanish barley variety ‘Albacete’. To achieve

this objective different complementary approaches will be followed. First, a statistical-

genetic approach will be developed for the construction of a linkage maps in

populations obtained from reciprocal translocation heterozygotes using a double haploid

population (Chapter 2). Second, the reciprocal translocation present in ‘Albacete’ will

be characterized by a combination of cytological and molecular genetic approaches

(Chapter 3). Third, a large number of doubled haploid lines derived from four crosses

involving ‘Albacete’ as one of the parents will be used to phenotypically characterize

the effects of the reciprocal translocation on some interesting agronomic traits at two

locations in two growing seasons (Chapter 4). Fourth, once we know how to construct a

linkage map if one of the parents carries a reciprocal translocation, use will be made of

the statistical-genetic approach to construct an integrated genetic linkage map

combining five interconnected biparental doubled haploid populations involving four

barley varieties (‘Albacete’, ‘Barberousse’, ‘Plaisant’ and ‘Orria’) (Chapter 5). Fifth,

development of specific methodology for the simultaneous analysis of these

interconnected populations for QTL analysis in the presence of a reciprocal

translocation (Chapter 6).

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Chapter 2

Linkage map construction involving a reciprocal

translocation

A. Farré1,4 I. Lacasa Benito1 L. Cistué2 J.H. de Jong3 I. Romagosa1 J. Jansen4

Published in Theor Appl Genet (2011) 122:1029-1037

Abstract

This paper is concerned with a novel statistical-genetic approach for the construction of

linkage maps in populations obtained from reciprocal translocation heterozygotes of

barley (Hordeum vulgare L.). Using standard linkage analysis, translocations usually

lead to 'pseudo-linkage': the mixing up of markers from the chromosomes involved in

the translocation into a single linkage group. Close to the translocation breakpoints

recombination is severely suppressed and, as a consequence, ordering markers in those

regions is not feasible. The novel strategy presented in this paper is based on (1)

disentangling the "pseudo-linkage" using principal coordinate analysis, (2) separating

individuals into translocated types and normal types and (3) separating markers into

those close to and those more distant from the translocation breakpoints. The methods

make use of a consensus map of the species involved. The final product consists of

integrated linkage maps of the distal parts of the chromosomes involved in the

translocation.

Keywords Linkage maps Reciprocal translocation Translocation breakpoint

Barley Principal coordinate analysis Graphical genotypes

1Department of Plant Production and Forest Science, University of Lleida, Lleida, Spain; 2Estación Experimental de Aula Dei, CSIC, Zaragoza, Spain; 3Laboratory of Genetics, Wageningen University and Research Centre, Wageningen, the Netherlands; 4Biometris, Wageningen University and Research Centre, Wageningen, the Netherlands

Chapter 2

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Introduction

At present barley (Hordeum vulgare L.) is the fourth most important cereal crop, after

maize, wheat and rice. Barley is a diploid (2n = 14) self-pollinating species which can

be used as a model plant for other Triticeae species providing an excellent system for

genome mapping and map-based analyses (Costa et al. 2001). Well-established linkage

maps containing morphological, chromosomal, protein and molecular markers are

indispensable tools for genetic analysis and for analyzing DNA sequence variation

between the crops and its relative accessions and species. In barley, common molecular

marker technologies include restriction digest based RFLPs (Restriction Fragment

Length Polymorphisms; Graner et al. 1991; Heun et al. 1991; Kleinhofs et al. 1993),

and PCR-based markers like AFLPs (Amplified Fragment Length Polymorphism; Vos

et al. 1995), STS (Sequence Tagged Site; Olson et al. 1989), SSRs (Simple Sequence

Repeat; Liu et al. 1996; Ramsay et al. 2000; Pillen et al. 2000; Li et al. 2003), and

recently, DArT (Diversity Arrays Technology), a technique based on DNA

hybridization (Jaccoud et al. 2001; Wenzl et al. 2004). The more recent SNPs (Single

Nucleotide Polymorphisms) have become popular thanks to a high density within the

genome, easy development from sequence data and high reproducibility. Wenzl et al.

(2006) constructed a high-density linkage map which will be used as a reference for

future mapping work. The map was based on datasets from multiple populations,

comprising 2,935 loci (2,085 DArT, 850 SSR, RFLP and/or STS markers) and spans

1,161 cM. Recently, Varshney et al. (2007) produced a high-density linkage map, using

SSR marker data from six mapping populations. A total of 775 microsatellite loci from

688 primer pairs were used to cover 1,068 cM of the barley genome.

Major complications in the construction of genetic maps arose in populations containing

reciprocal translocation heterozygotes (Lehmensiek et al. 2005). Reciprocal

translocations involve the exchange of two terminal segments between two non-

homologous chromosomes. Due to reciprocal translocations recombination between loci

around the translocation breakpoints will be suppressed. Consequently, markers in these

regions become 'pseudolinked', i.e. linkage is detected between markers lying on

different chromosomes. Reciprocal translocations are induced spontaneously or

artificially by ionizing radiation, mutagens or by transposons and can be confirmed by

aberrant chromosome and banding morphology, by establishing quadrivalent formation

Linkage map construction involving a reciprocal translocation

13

in metaphase I complements, and semisterility of pollen in translocation heterozygotes,

and by linkage analysis (Jáuregui et al. 2001). Translocations are well-documented in

various crops, including rye (Alonso-Blanco et al. 1993; Benito et al. 1994; Catarino et

al. 2006), soybean (Mahama and Palmer. 2003), Prunus (Jáuregui et al. 2001), Lens

(Tadmor et al. 1987) and pea (Kosterin et al. 1999). Many bread wheat cultivars contain

the 1RS-1BL wheat-rye chromosome translocation, introduced to provide resistance to

pests and diseases (Mago et al. 2002; Sharma et al. 2009).

In barley, spontaneous reciprocal translocations were described by Konishi and Linde-

Laursen (1988) who investigated 1,240 barley landraces and varieties and 120 wild

barley lines, using test-cross and Giemsa chromosome banding analyses. Of the 1,240

landraces and varieties, four carried translocations involving chromosomes 2H and 4H

with breakpoints near or at the centromere. Of the 120 wild barley lines, three carried

translocations between chromosomes 2H and 4H, 3H and 5H and 3H and 6H,

respectively. 'Albacete' is a barley variety that it is known to have a reciprocal

chromosomal translocation. Recent results suggest that chromosomes 1H and 3H are

involved in this translocation (Lacasa-Benito et al. 2005).

The consensus map of barley (Wenzl et al. 2006) was used as a reference. Preliminary

linkage analysis of a doubled haploid population obtained from a cross between

'Albacete' and the non-translocation barley variety 'Barberousse' shows that linkage

groups 1H and 3H are indeed involved in the translocation. In order to detect

unexpected relationships between markers at those chromosomes we apply a principal

coordinate analysis which visualizes marker positions in a tridimensional graph. The

next step of our analysis is based on the cytogenetical theory that (1) during meioses

two types of viable gametes are produced: a "normal" type (with a balanced set of non-

translocation chromosomes) and a "translocated" type (with a balanced set of

translocated chromosomes), and (2) that around the translocation breakpoints

recombination is suppressed (Burnham, 1962; Sybenga, 1975). The crucial step consists

of dividing the doubled haploid population into two subpopulations according to the

origin of the alleles at the translocation breakpoints: 'Barberousse' alleles refer to the

"normal" type and 'Albacete' alleles refer to the "translocated" type. The position of the

translocation breakpoint is found by a graphical display of recombination frequencies

versus positions on the consensus map. At this stage we discuss the problem of extreme

Chapter 2

14

segregation distortion around the translocation breakpoints in the two subpopulations,

which is solved by removing markers around the translocation breakpoints with severe

segregation distortion. Linkage maps for the various chromosome arms are then

obtained for each of the subpopulations separately. The final step is integrating the

linkage maps of the corresponding arms of linkage groups 1H and 3H of the two

subpopulations.

Materials and methods

Plant material

Two six-row parental barley varieties, 'Albacete' and 'Barberousse', were crossed and

anther culture lines were produced from the F1 from which 231 spontaneous doubled

haploids were obtained at Estación Experimental de Aula Dei, Zaragoza, Spain. Seed

from each doubled haploid line was retained as a reference stock and used to grow the

plants for DNA extraction. More than 50 years ago, 'Albacete' was found by Enrique

Sánchez-Monge at the Estación Experimental Aula Dei, Spanish Research Council, as

an inbred line in a local heterogeneous landrace population from Albacete (province of

Spain). It is a six-row barley variety, drought tolerant with a stable grain yield. For these

properties, it has been grown for decades on up to 1 million ha/year, especially in

drought-prone areas. 'Barberousse' is a six-row winter barley variety released in France

in 1977. It was obtained from the cross [259 711/(Hatif de Grignon/Ares)]/Ager.

Although it is sensitive to drought, this variety is known for its good productivity and

easy adaptation.

DNA isolation

Genomic DNA of the DHs was extracted using two different protocols. For genomic

and EST-derived SSR markers, genomic DNA was extracted from 0.1 g of fresh leaf

tissue sprayed with liquid nitrogen according to the method of Doyle and Doyle (1990)

with some modifications. DNA was diluted in TE buffer pH8 and preserved for a long

period at a temperature of -20ºC. For DArT markers the genomic DNA was extracted

from fresh leaf tissue using the Qiagen DNeasy 96 Plant Kit.


15

Genotyping

Genotypic data were first produced for genomic and EST-derived SSR markers. We

refer to the Genomic SSRs markers using the prefix ("Bmac" or "Bmag") followed by

four digits and to the ESTs-derived SSR markers using the prefix ("scssr") followed by

five digits. Genomic and EST-derived SSR analyses were carried out using the

fluorescent fragment detection system on an ABI PRISM® 3100-Avant Genetic

Analyzer using Genescan software from Applied Biosystems. For this method, the

reverse primer was labeled with a fluorochrome at the 5’ end. For all amplifications the

PCR programs were used are published in the UK CropNet databases

(http://ukcrop.net/db.html).

Subsequently, a genome wide scan was carried out using the Diversity Arrays

Technology (DArT, http:\\www.diversityarrays.com). In a single assay, DArT uses

microarrays to detect DNA polymorphisms at several hundred genomic loci spread over

the entire genome. It is based on hybridising labelled genomic representations of

individual DNA samples on a micro-array, which contains a large number of DNA

fragments derived from the total genomic DNA of the species under consideration

(Wenzl et al. 2004). Polymorphisms were scored as presence (= 1) or absence (= 0) of

hybridization to individual array elements. The locus designations of Triticarte Pty. Ltd.

were used. DArT markers consisted of prefix (“bPb” or “CloneID”) followed by a

number corresponding to the particular clone in the genomic representation.

Linkage analysis

For the construction of linkage maps we used the maximum likelihood (ML) algorithm

in Jansen et al. (2001) which enables map construction in batch mode and the

implementation in JoinMap 4.0 (van Ooijen 2006) which enables the use of many

graphical tools. Linkage maps were drawn using MapChart 2.2 (Voorrips 2002).

Statistical techniques

Principal coordinate analysis (Chatfield and Collins 1980), a special form of

multidimensional scaling, was used to obtain a 3D representation of the markers on the

Chapter 2

16

linkage groups involved in the reciprocal translocation. The similarity between markers

was measured by the simple matching coefficient, which for a doubled haploid

population is equal to one minus the recombination frequency. Calculations were

carried with Genstat version 12 (Payne et al. 2009), using the directives FSIMILARITY

and PCO.

Results

Polymorphisms between parents

We applied the following liberal rules for excluding markers: (1) markers with an

unknown location on the consensus map (these were later included again when

constructing our final maps); (2) markers with an ambiguous chromosome assigment on

the consensus map; (3) markers with more than 5% missing data and (4) markers with

low quality readings (Q value less than 77). For linkage analysis, 30 polymorphic

genomic and EST-derived SSR markers and 309 polymorphic DArT were used. This

amounted to an average of 48 markers per chromosome, with an average interlocus

distance of 4.4 cM based the consensus linkage map. A few regions had gaps of over 10

cM. Chromosome 4H showed strikingly low levels of polymorphisms, which is in

agreement with the findings of Qi et al. (1996), Karakousis et al. (2003), Kleinhofs et al.

(1993) and Wenzl et al. (2006).

Preliminary linkage map construction

We obtained six main linkage groups involving 305 markers. Using a recombination

frequency threshold of 0.2, 34 markers could not be assigned to one of these linkage

groups. Five linkage groups could be related to linkage groups of the consensus map

(Wenzl et al. 2006): 2H (48 markers), 4H (20 markers), 5H (48 markers), 6H (49

markers) and 7H (58 markers). The remaining 82 markers had known positions on 1H

and 3H of the consensus map, of which 78 formed one linkage group. Four markers, on

the consensus map located at the very end of the long arm of linkage group 1H, were

found to be unlinked with the 78 markers of 1H and 3H. One marker showing a

consistently high nearest-neighbour stress (Van Ooijen 2006) was also excluded. Figure

1 displays one linkage map with the positions of the remaining 77 markers obtained by


17

the maximum likelihood algorithm. Many different linkage maps were obtained by

rerunning the maximum likelihood algorithm. This was a clear indication that it was not

possible to obtain a linear order of the markers in an unambiguous way.

Figure 1. Graphical representation of a linkage map obtained for markers of linkage groups 1H

and 3H according to the consensus map of Wenzl et al. (2006); markers of linkage

group 1H and 3H are displayed in blue and ochre, respectively.

A spatial representation of the positions of the markers was obtained using principal

coordinate analysis. Figure 2 shows a three-dimensional plot in which the points

represent the positions of the markers with regard to the first three principal axes; the

percentages variance explained by the first three axes were 27.2, 15.59 and 13.9,

respectively. The points have been joined by straight lines according to their position on

the consensus map of Wenzl et al. (2004). Markers of linkage group 1H and 3H have

been displayed in blue and ochre, respectively. Figure 2 shows that linkage groups 1H

Chapter 2

18

and 3H merge at one point (indicated by the circle) and that the short and long

chromosome arms divert from this point, and from each other, in three-dimensional

space. As a consequence, the translocation breakpoints lie within the circle.

Figure 2. Graphical representation of a principal coordinate analysis using the simple matching

coefficient for the markers of linkage groups 1H and 3H according to the consensus

map of Wenzl et al. (2006). The percentage variance explained by the first three

principal axes are 27.2, 15.5 and 13.9, respectively. The markers have been joined

according to their position on the consensus map of Wenzl et al. (2006). The black

circle encloses markers of linkage groups 1H and 3H that are close to the translocation

breakpoints; they are separated by a small number of recombinations.

Recombination around the translocation breakpoints

To study the recombination behaviour of markers around the translocation breakpoints

we focused on estimates of the recombination frequencies between the markers of 1H

and 3H, in which the allocation of markers to linkage groups as well as their positions


19

were based on the consensus map. In Figure 3, these recombination frequencies were

plotted against the corresponding positions on the consensus map. In Figure 3a, we

observed that markers close to the translocation breakpoints have recombination

frequencies close to zero. On linkage group 1H the translocation breakpoint was

situated at about 60 cM and on linkage group 3H at about 65 cM based on the consensus

map. The marker pair with the smallest recombination frequency consisted of HvM20

(1H) and Bmag0136 (3H) with a recombination frequency of 0.017 (4 recombinants out

of 231 DHs). Cross-sections of Figure 3a through the positions of markers Bmag0136

and HvM20 are shown in Figure 3b and 3c, respectively.

Figure 3. (a) Graphical representation of the recombination frequencies between markers of

linkage group 1H and linkage group 3H versus their position on the consensus map of

Wenzl et al. (2006). (b) Graphical representation of the recombination frequencies

between markers of linkage group 1H with marker Bmag0136 of linkage group 3H

versus their position on linkage group 1H of the consensus map of Wenzl et al. (2006).

(c) Graphical representation of the recombination frequencies between markers of

Position on 3H(cM)

Position on 1H(cM)

2040

6080

100

020

4060

80100

120140

160180120

0.5

0.4

0.3

0.2

0.1

0.0

Rec

ombi

nati

on f

requ

ency

Position on 3H(cM)

Position on 1H(cM)

2040

6080

100

020

4060

80100

120140

160180120

0.5

0.4

0.3

0.2

0.1

0.0

Rec

ombi

nati

on f

requ

ency

Chapter 2

20

linkage group 3H with marker HvM20 of linkage group 1H versus their position on

linkage group 3H on the consensus map of Wenzl et al. (2006).

Cytogenetical theory suggests that the DH1 population should be split into two

subpopulations: (1) a subpopulation containing individuals in which the alleles close to

the translocation breakpoint are identical to 'Albacete', and (2) a subpopulation

containing individuals in which the alleles close to the translocation breakpoint are

identical to 'Barberousse'. In the first subpopulation the chromosomal arrangement will

be that of 'Albacete' (1HS-3HL, 3HS-1HL), in the second subpopulation the

chromosomal arrangement will be that of 'Barberousse' (1HS-1HL, 3HS-3HL). The

separation of the 231 DH individuals into two subpopulations was based on the data of

markers HvM20 and Bmag0136 (Figure 4). First, the markers were divided into linkage

groups 1H and 3H and subsequently sorted vertically according to their position within

each of the linkage groups based on the consensus map. Secondly, individuals were

sorted according to the origin of their allele on marker HvM20; more or less the same

effect was obtained if the markers were sorted according to Bmag0136. The split of the

individuals into two groups was not perfect; 53 individuals had to be excluded because

they had deviating chromosomal combinations within 5 cM from the presumed

translocation breakpoints. Some of these deviations concerned so-called 'singletons';

they are likely due to observation errors or caused by gene conversions.

Figure 4. Graphical genotypes of individuals markers on linkage 1H and 3H according to the

consensus map of Wenzl et al. (2006). Individuals have been divided into two types

with regard to their alleles at the translocation breakpoints: the 'Albacete' type (shown in

red), carrying the translocation, and the 'Barberousse' type (shown in green), with

'normal' chromosome arrangement.


21

In a doubled haploid population markers are expected to segregate according to a 1:1

ratio. However, due to the division into subpopulations, markers near the translocation

breakpoints show severe segregation distortion in each of the subpopulations. The

distortion decreases as markers are further away from the translocation breakpoints.

Severe segregation distortion significantly affects estimation of genetic distances, but

will not seriously affect the marker order (Hackett and Broadfoot 2003). Therefore, in

order to construct robust linkage maps, markers with severe segregation distortion (in

this case markers with segregation ratios below 30% or above 70%) were eliminated. In

both subpopulations 37 markers out of 75 were removed, leaving 14 markers for 1H and

24 markers for 3H; these markers were common in both subpopulations.

The two subpopulations were considered separately to construct independent linkage

maps for the chromosomes involved in the reciprocal translocation. Subpopulation 1

(with the 'Albacete' allele near or at the translocation breakpoint) contained 92 DHs;

Subpopulation 2 ('Barberousse' allele near the translocation breakpoint) contained 86

DHs. The two subpopulations were then subjected to independent linkage analyses.

Finally the linkage maps of the two subpopulations were integrated. Results are shown

in Figure 5. The order of the markers for the 'Albacete' and the 'Barberousse' population

are identical, but differences in distance are present.

bPb-3622bPb-1165bPb-1348

bPb-3776

bPb-9414bPb-8973

bPb-7306

1HS-Albacete

bPb-1165bPb-3622bPb-1348

bPb-3776

bPb-9414bPb-8973

bPb-7306

1HS-Integrated

bPb-1165bPb-3622bPb-1348

bPb-3776

bPb-7306bPb-9414bPb-8973

1HS-Barberousse

0

5

10

bPb-5555bPb-4022

bPb-1264bPb-9945bPb-9583

bPb-7199bPb-7770

bPb-7448

bPb-2929

3HS-Albacete

bPb-4022bPb-5555

bPb-9583bPb-9945bPb-1264

bPb-7199bPb-7770

bPb-7448

bPb-2929

3HS-Integrated

bPb-4022bPb-5555

bPb-9583bPb-9945bPb-1264

bPb-7770bPb-7199

bPb-7448

bPb-2929

3HS-Barberousse

0

5

10

15

20

25

30

Chapter 2

22

Figure 5. Linkage maps of the short and long arms of linkage groups 1H and 3H obtained for the

individuals of type 'Albacete' and for type 'Barberousse' at the translocation breakpoints.

The maps of the two types have been connected by their corresponding integrated maps.

The maps were obtained for markers with a segregation ratio between 0.3 and 0.7.

Discussion

The methods developed in this paper provide essential tools for disentangling 'pseudo-

linkage' between markers in a population derived from a translocation heterozygote.

The methods can be implemented using standard software. In this paper a high-quality,

consensus map of 'normal' barley (used as a reference) is essential in several steps of

the analysis: (1) interpretation of the three-dimensional principal coordinate plot (Figure

2), (2) determination of the translocation breakpoints on chromosomes 1H and 3H of

'normal' barley (Figure 3), and (3) assignment of markers to the respective chromosome

arms (1HS, 1HL, 3HS and 3HL) in 'normal' barley (Figure 4). Without a high-quality,

consensus map of 'normal' barley, step (2) will be impossible, and steps (1) and (3) will

be more difficult. The chromosome arms designated 1HS, 1HL, 3HS and 3HL become

arbitrary chromosome arms.

bPb-3389

bPb-4144bPb-1213bPb-5249bPb-3089

bPb-9108bPb-5014

1HL-Albacete

bPb-3389

bPb-3089bPb-4144bPb-1213bPb-5249

bPb-9108

bPb-5014

1HL-Integrated

bPb-3389

bPb-3089bPb-1213bPb-4144bPb-5249

bPb-9108

bPb-5014

1HL-Barberousse

0

5

10

15

20

25

30

35

40

45

50

bPb-8506bPb-2550bPb-8621

bPb-9111

bPb-5666bPb-0789bPb-9599bPb-7827bPb-6383bPb-3899bPb-8419bPb-7815bPb-0200

bPb-0361

bPb-7724

3HL-Albacete

bPb-8506bPb-2550bPb-8621

bPb-9111

bPb-5666bPb-3899bPb-0789bPb-7827bPb-6383bPb-9599bPb-7815bPb-8419bPb-0200

bPb-0361

bPb-7724

3HL-Integrated

bPb-2550bPb-8506bPb-8621

bPb-9111bPb-5666bPb-6383bPb-3899bPb-0789bPb-7827bPb-9599bPb-7815

bPb-8419bPb-0200

bPb-0361

bPb-7724

3HL-Barberousse

0

5

10

15

20

25

30

35

40

45

50

55


23

In a preliminary linkage analysis, six main linkage groups were detected, one of them

joining markers from chromosomes 1H and 3H. As indicated by an earlier study this

"mixing" of markers of chromosomes 1H and 3H was attributed to the presence of a

reciprocal translocation between these chromosomes. In this study the position of the

translocation breakpoint could be determined at about 60 cM on chromosome 1H and

65 cM on chromosome 3H (positions refer to the consensus map of 'normal' barley),

which correspond with the centromeric regions of these chromosomes. These positions

were confirmed in this study when all available markers from 1H and 3H were used to

determine in more detail which markers were involved in the translocation breakpoints.

In another DH1 population obtained from a cross of ‘Albacete’ and 'Plaisant' (results not

shown), the translocation breakpoints were found at similar positions.

In order to characterize the translocation breakpoint we identified 92 DHs as carrying

the translocation and 86 DHs with the standard chromosome arrangement. Fifty three

genotypes could not be classified in either of the two subpopulations due to deviating

chromosomal combinations which may be caused by scoring errors. In marker studies

like these scoring errors should be avoided by using very accurate marker systems.

Nevertheless, it is interesting to note that, regardless of the true nature of the 53 non-

classified types, the presence of this chromosome rearrangement did not affect the

success rate in the double haploid regeneration process. As a result, two different

genetic linkage maps were obtained, one with the two interchanged chromosomes

together (1HS·3HL + 1HL·3HS, 'Albacete' type) and the other with the two normal

chromosomes together (1HS·1HL + 3HS·3HL, 'Barberousse' type).

It is expected that barley varieties carrying chromosomal segments containing the

reciprocal translocation between chromosomes 1H and 3H, have an advantage under

certain environmental conditions. So, for future breeding purposes, it may be

worthwhile to be able to follow individuals carrying interchanged chromosomes. In our

case, this is the 'Albacete' haplotype. This requires the development of markers close

enough to the translocation breakpoints with allelic combinations that allow

differentiation between translocated and non-translocated origin of the chromosomal

segments around the translocation breakpoints; in our case marker haplotypes that

distinguish between 'Albacete' and all other material used in the breeding program.

Away from the translocation breakpoints, a mixing of haplotypes will occur due to

Chapter 2

24

recombination. In the end, this would allow the construction of a specific linkage map

of the karyotype with a chromosomal rearrangement close to the translocation

breakpoints.

A genetic consequence of reciprocal translocation is that linkage relationships in a

translocation heterozygote are altered as recombination between loci may be

significantly reduced, particularly within the interstitial segment and between genes

close to the translocation breakpoint. If the translocation breakpoint is located at or near

the centromeric region, the interstitial zone becomes really narrow or even null and,

therefore, the recombination that may take place will be due to interference effects near

the translocation breakpoint. In our data we have not found a common set of completely

linked markers from chromosome 1H and 3H, although a few showed very low levels of

recombination. These rare recombinants can be due to scoring errors or, what is more

likely, due to the fact that the interstitial zone is practically nonexistent.

The genomic SSR markers linked closely to the translocation breakpoint on

chromosome 3H were identified flanking the centromere at 55 cM in the Lina ×

Hordeum spontaneum 'Canada Park' genetic map, between Bmac0067, Bmag0136 and

Bmag006 in the short arm and Bmac0209 in long arm covering a genetic distance of 5

cM (Künzel and Waugh 2002). However, this region (with suppressed recombination)

covered 36% of the entire chromosome length on the physical map. For chromosome

1H, no articles were found, which relate physical distance to genetic distance using

genomic SSR markers along the entire chromosome; only one RFLP-based map

observed this phenomenon (Künzel et al. 2000). The gene density around the

translocation breakpoints can be inferred using the synteny observed for barley-rice.

Mayer et al. (2009) mentioned that approximately 20% of all genes on barley

chromosome 1H are located in centromeric and subcentromeric regions with very low

recombination frequencies. A similar gene density can be expected for barley

chromosome 3H; Smilde et al. (2001) reported a 30-fold reduction of recombination

around the barley 3H centromere.

Livingstone et al. (2000) state that karyotypic rearrangements, such as reciprocal

translocations, lead to high variances of inter-marker distances for markers on

chromosomes involved in the reciprocal translocation away from the translocation


25

breakpoints, in repeated attempts to construct a linkage map (see also Durrant et al.,

2006). Markers close to the translocation breakpoints show small variances of inter-

marker distances. However, high variances may also be caused by deficiencies in the

data. The methods developed in this paper provide a novel combination of methods

available in standard (statistical) software that can be used to identify the true

background of 'pseudo-linkage' in a straightforward manner.

In conclusion, the results of this study confirm that there is a reciprocal translocation as

the result of an interchange of chromosome arms between 1H and 3H. The markers

found to be linked to the translocation breakpoints are HvM20 and EBmac0501 for 1H

and Bmag0136, bPb-9746 and a reduced set of genomic SSR markers for 3H, which are

located around the centromere. Linkage analysis revealed that alternative arrangements

involving the short and long chromosome arms of 1H and 3H may be possible.

However, the most frequent arrangement is 1HS·3HL + 3HS·1HL. In addition,

regardless of the presence of a reciprocal translocation we have produced a linkage map

for the 'Albacete' x 'Barberousse' population that will be used to identify quantitative

trait loci (QTLs) for agronomic traits in future work.

Acknowledgements

This study has been supported by the Spanish Ministry of Science and Innovation

(Project AGL2008-05541-C02 and the Agrogenomics CONSOLIDER). We are grateful

to Dr. Martin Boer who provided us with simulated data which helped us in better

understanding the mapping problems arising from the presence of a reciprocal

translocation. Comments by the Editor and two referees are gratefully acknowledged.

Chapter 2

26

27

Chapter 3

Genetic characterization of a reciprocal translocation present

in a widely grown barley variety

A. Farré1,2 · A. Cuadrado3 · I. Lacasa-Benito1 · L. Cistué4 · I. Schubert5 · J. Comadran6 ·

J. Jansen2 · I. Romagosa1,7

Published in Mol Breeding (2012) DOI: 10.1007/s11032-011-9698-z

Abstract

Artificially induced translocation stocks have been used to physically map the barley

genome; however, natural translocations are extremely uncommon in cultivated

genotypes. ‘Albacete’ is a barley variety widely grown in the last decades in Spain and

carrying a reciprocal translocation which obviously does not affect its agronomical

fitness. This translocation has been characterized by a combination of cytological and

molecular genetic approaches. First, recombination frequencies between markers on

chromosomes 1H and 3H were estimated to determine the boundaries of the reciprocal

interchange. Secondly, 1H-3H wheat barley telosome addition lines were used to assign

selected markers to chromosome arms. Thirdly, fluorescence in situ hybridization

(FISH) with rDNA probes (5S and 18S-5.8S-26S) and microsatellite probes [(ACT)5,

(AAG)5 and (CAG)5] was used to determine the locations of the translocation

breakpoints more precisely. Fourthly, fine-mapping of the regions around the

translocation breakpoints was used to increase the marker density for comparative

genomics. The results obtained in this study indicate that the translocation is quite large

with breakpoints located on the long arms of chromosomes 1H and 3H, between the

pericentromeric (AAG)5 bands and above the (ACT)5 interstitial distal bands, resulting

1Department of Plant Production and Forest Science, University of Lleida, Lleida, Spain; 2Biometris, Wageningen University and Research Centre, Wageningen, the Netherlands; 3Department of Cell Biology and Genetics, University of Alcalá de Henares, Alcalá de Henares, Spain; 4Estación Experimental de Aula Dei, CSIC, Zaragoza, Spain; 5Department of Cytogenetics, Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany; 6Genetics Programme, The James Hutton Institute , Dundee, Scotland; 7Centre UdL-IRTA, University of Lleida, Lleida, Spain

Chapter 3

28

in the reciprocal translocation 1HS.1HL-3HL and 3HS.3HL-1HL. The gene content

around the translocation breakpoints could be inferred from syntenic relationships

observed among different species from the grass family Poaceae (rice, Sorghum and

Brachypodium) and was estimated at approximately 1,100 and 710 gene models for 1H

and 3H, respectively. Duplicated segments between chromosomes Os01 and Os05 in

rice derived from ancestral duplications within the grass family overlap with the

translocation breakpoints on chromosomes 1H and 3H in the barley variety ‘Albacete’.

Keywords Reciprocal translocation Barley Translocation breakpoint

Fluorescence In Situ Hybridization Comparative genomics

Introduction

Reciprocal translocations, interchanges of chromosome segments between two non-

homologous chromosomes, are one of the most common structural chromosomal

rearrangements occurring in plant species. Translocations in plants have been widely

described by Burnham (1956). Permanent translocation heterozygotes were first

observed by Gates (1908) in Oenothera species which received generous cytological

and genetic studies by Cleland (1922) and Belling and Blakeslee (1926). McClintock

(1930) was the first to supply cytological evidence of interchanges in economically

important crops such as maize. Translocations have been widely utilized in both applied

and fundamental scientific research for chromosome mapping, in particular for

assigning linkage groups to chromosomes, development of physical maps in plants

(Kim et al. 1993; Künzel et al. 2000; Sorokin et al. 1994; Marthe and Künzel 1994), and

to improve our understanding of meiotic chromosome pairing behaviour (Rickards

1983). They have been reported in a number of crop species, such as rye (Benito et al.

1994), soybean (Mahama and Palmer 2003), Prunus (Jáuregui et al. 2001), Lens

(Tadmor et al. 1987), pea (Kosterin et al. 1999), wheat (Naranjo et al. 1987) and

Brassica napus (Osborn et al. 2003).

Chromosomal interchanges, and translocations in general, can be artificially induced in

somatic or meiotic cells by ionizing radiation or mutagens. They may also occur

Genetic characterization of a reciprocal translocation present in a widely grown barley variety

29

spontaneously, although there are few cases of spontaneous reciprocal translocations

described in cultivated barley. Konishi and Linde-Laursen (1988) investigated 1,240

cultivated barley lines and 120 wild barley lines to detect spontaneous reciprocal

translocations, which were identified by both semi-sterility associated to test crosses

and subsequent Giemsa banding technique. Of the 1,240 cultivated barley lines, four

Ethiopian landraces carrying a reciprocal translocation had the same breakpoints at the

centromere involving chromosomes 2H and 4H (2HS·4HS and 2HL·4HL), suggesting

that the chromosomes involved in the rearrangement had a common origin. Of the 120

wild barley genotypes, three carried translocations between chromosomes 2H and 4H,

3H and 5H and 3H and 6H, respectively. Xu and Kasha 1991 identified a chromosomal

interchange between chromosomes 3H and 4H using N-banding and in situ

hybridization techniques in a wild barley cross. The plant heterozygous for the

interchange was derived from the backcross of ‘Su Pie’ with pollen from a triploid

interspecific F1 hibrid of ‘Su Pie’ × tetraploid Hordeum bulbosum accession GBC141.

One of the consequences of a reciprocal translocation is the suppression of genetic

recombination in a translocation heterozygote in the interstitial zone (the chromosome

segment between the centromere and the breakpoint). The suppression depends on the

centromere coorientation frequency at metaphase I (alternate or adjacent segregations)

and upon the chiasmata (crossover) frequency expected in both interstitial segments

(Hanson and Kramer 1949; Burnham and Hagberg 1956; Kasha and Burnham 1965;

Sybenga 1975). Recombination suppression in the interstitial zone affects the linkage

relationships in a translocation heterozygote which results in “pseudo-linkage” between

the genes of the two chromosomes involved in the reciprocal translocation and

subsequent disturbed linkage maps. Another consequence of reciprocal translocations is

the occurrence of gametic sterility of which depends on the frequency of the alternate or

adjacent orientation in the quadrivalent. In barley, an excess of alternate over adjacent

segregation of the chromosomes at meiotic metaphase I would explain the average 25%

sterility caused by the interchange (Kakeda and Miyahara 1995).

Plant accessions carrying chromosome rearrangements such as translocations have been

identified in the past by its effects on partial pollen and seed sterility (i.e. Jáuregui et al.

2001). However, depending on the chromosome breakpoints, a translocation can result

in the disruption or misregulation of normal gene functions. Thus, special interest

Chapter 3

30

resides on the characterization of the physical locations of the translocation breakpoints

on the genome allowing physical mapping of genes involved in the translocation on the

chromosomes. These can be delimited by a combination of cytogenetics and molecular

genetics. In barley, chromosome identification can be achieved by using in situ

hybridization with ribosomal RNA probes (Brown et al. 1999). In addition, with

labelled SSRs it is now possible to cover the physical map with many landmarks

distributed along all chromosome arms (Cuadrado and Jouve 2007). Undoubtedly, this

rich set of chromosome markers should help to identify the barley breakpoints more

precisely than conventional staining techniques.

In the present paper, we aim at determining the positions of the translocation

breakpoints in the Spanish six-row barley variety ‘Albacete’. Translocations may have

dramatic consequences such as modified phenotypes. In fact, ‘Albacete’ is the only

extensively cultivated barley variety known to carry a reciprocal translocation between

chromosomes 1H and 3H without any major reduction in fitness. It is adapted to low-

yielding West Mediterranean areas and it has been the most widely grown cultivar in the

driest Spanish areas for the last decades (over a million ha per year). The translocation

was first identified by Cistué (unpublished) upon meiotic analysis of semi-sterile F1

hybrids involving this variety.

In tracing the possible origin of the reciprocal translocation in ‘Albacete’ we use

syntenic relationships between different families of the grass family Poaceae. For the

location and characterization of the translocation breakpoints we used a combination of

molecular genetical and cytological techniques. Dense genetic linkage maps of the

chromosomes involved in the reciprocal translocation will be used to identify markers

in the vicinity of the translocation. Pseudo-linkage arising from suppressed

recombination in the interstitial space may result in increased similarities between

markers located on the two chromosomes involved in the reciprocal translocation and

can be used to fine-map the recombination breakpoints. Further validation and physical

characterisation of the translocation breakpoints will be achieved by the use of wheat-

barley telosome addition lines and fluorescence in situ hybridization with rDNA probes

(5S and 18S-5.8S-26S) and microsatellite probes [(ACT)5, (AAG)5 and (CAG)5] of

‘Albacete’ and doubled haploid lines derived from crosses between ‘Albacete’ and

cultivars with a standard chromosome arrangement.


31


Linkage analysis

Two bi-parental doubled haploid (DH) mapping populations were used. The first

mapping population, ‘Albacete’ × ‘Barberousse’ (AB), consists of 231 DH lines derived

from anther-culture from the cross between the translocation-carrying six-row winter

variety ‘Albacete’ and the six-row winter variety ‘Barberousse’. DNA isolation and

genotyping data, SSR and DArT®, were performed according to Farré et al. (2011). The

second mapping population, (‘Albacete’ × ‘Plaisant’) × ‘Plaisant’ (APP), consists of 94

DH lines derived from the cross of a DH line produced from the ‘Albacete’ × ‘Plaisant’

F1, which carried the ‘Albacete’ reciprocal translocation, backcrossed to ‘Plaisant’.

DNA was extracted from leaf tissue using kit DNeasy Plant Mini Kit (Quiagen,

Valencia, CA, USA). A set of 3072 EST-based high confidence SNP markers were

genotyped using GoldenGate BeadArray technology (Illumina) as previously described

(Close et al. 2009).

The allocation of markers to linkage groups as well as their genetic map position were

based on the published barley consensus map (Wenzl. et al. 2006) for the AB

population and Close et al. (2009) for the APP population. The position of the

translocation breakpoints was first inferred according to the methods described by Farré

et al (2011).

Wheat-barley telosome addition lines

The chromosome arm locations of seven SSR markers on the chromosomes of the

barley cultivar ‘Betzes’ were checked on the ‘Chinese Spring’-‘Betzes’ (CS-B) wheat-

barley telosome addition lines for chromosomes 1H and 3H. CS-B telosome addition

lines for the chromosome 1H and 3H and chromosome arms 1HS, 3HS and 3HL were

used to assign selected markers to chromosome arms. No telosome addition line for

chromosome arm 1HL was available. Genomic DNA from these addition lines were

kindly provided by Rafiqul Islam (School of Agriculture, Food and Wine. The

University of Adelaide, Australia) and Marion Röder (Leibniz Institute of Plant

Genetics and Crop Plant Research. IPK, Germany).

Chapter 3

32

Fluorescence in situ Hybridization

Plant material and root tip and chromosome preparation

Root tips were obtained from seedlings of Hordeum vulgare cv. ‘Albacete’. Seeds were

germinated on moist filter paper for 24 h at 25ºC and then kept at 4ºC for 72h followed

by 25ºC for 24h to synchronize cell division. The seedlings were then transferred to ice-

cold water for 24h to accumulate metaphases before tissue fixation in ethanol-glacial

acetic acid (3:1) (Cuadrado and Jouve 2007). Chromosome preparations were prepared

as described by Schwarzacher et al. (1989). Briefly, root tips were macerated with an

enzymatic mixture and then squashed in a drop of 45% acetic acid. After removing the

cover slips by quick freezing, the slides were air dried.

DNA probes and in situ hybridization

The three oligodeoxyribonucleotide probes [(ACT)5, (CAG)5 and (AAG)5] were

provided by Roche labelled at their 5’ and 3’ with digoxigenin or biotin. The novel and

rapid non-denaturating FISH (ND-FISH) technique developed by Cuadrado and Jouve

(2010) was carried out to detect SSR-enriched chromosome regions.

The other probes, pTa71 (a plasmid containing the 18S-5.8S-25S rDNA and the

intergenic spacer of Triticum aestivum) and pTa794 (contains a 410-bp BamHI

fragment of 5S rDNA isolated from wheat Triticum aestivum) were labelled by nick

translation and PCR, respectively (Leitch and Heslop-Harrison 1992; Leitch and

Heslop-Harrison 1993; Pedersen and Linde-Laursen 1994; Brown et al. 1999).

Chromosome and probe denaturation and the in situ hybridization steps were carried out

as described in Cuadrado et al. (2000).

Fluorescence microscopy and imaging

Slides were examined with a Zeiss Axiophot epifluorescence microscope. The separate

images from each filter set were captured using a cooled CCD camera (Nikon DS) and

processed using Adobe Photoshop, employing only those functions that are applied

equally to all pixels in the image.


33

Results

Similarities between markers on chromosomes 1H and 3H in the AB population

In order to identify DArT and SSR markers in the vicinities of the reciprocal

translocation breakpoints, we explored recombination frequencies, between the markers

located on chromosomes 1H and 3H. The allocation of markers to linkage groups as

well as their genetic map position were based on the published barley consensus map

(Wenzl et al. 2006). A total of 78 out of 305 polymorphic markers were mapped on

chromosomes 1H and 3H for the AB population. A graphical representation of the

recombination frequencies was presented by Farré et al. (2011) which shows that

markers on chromosome 1H and 3H were strongly related. This suggests the presence

of a reciprocal translocation between these chromosomes. So, for the AB population,

the markers with recombination frequencies close to zero were located in the consensus

map around 59-64 cM and 66-70 cM for 1H (HvM20 and EBmac0501) and 3H

(Bmac209, Bmac067, Bmag0006 and Bmag0136), respectively, which corresponds

with the pericentromeric regions of both chromosomes 1H and 3H.

1H and 3H wheat-barley telosome addition lines

Wheat-barley chromosome addition lines were then used to assign the chromosome arm

location of the SSR markers found to be closely linked to the translocation breakpoints

using their presence/absence as detected in hexaploid wheat T. aestivum cv. ‘Chinese

Spring’ (CS) and barley H. vulgare cv. ‘Betzes’ using PCR . For chromosome 3H, 3 out

of 4 SSR markers were found to be located on the short arm and the other one on the

long arm (positions reported by Künzel and Waugh 2002). Using 1H wheat-barley

addition lines the two SSR markers used mapped on different chromosome arms.

HvM20 amplified in both CS and Betzes and, therefore, did not have any diagnostic

value.

Fluorescence in situ hybridization analysis

Further progress in localizing the translocation breakpoints can be expected from direct

cytological observations of barley chromosomes by FISH using probes that were used

Chapter 3

34

successfully as anchored chromosomal markers. The following locations of pTa794

(5SrDNA) were reported: interstitial on chromosome arms 2HL and 3HL, distal on 4HL

and proximal on 7HS (Leitch and Heslop-Harrison 1993). In addition to the two NOR-

bearing barley chromosomes, 5HS and 6HS, the locations of four minor rDNA loci with

pTa71 (18S-5.8S-26S rDNA) were reported on chromosome arms 1HS, 2HS, 4HS and

7HS differentiated by their position and intensity (Pedersen and Linde-Laursen 1994).

Thus the use of these two ribosomal probes should allow easy identification of all

barley chromosomes including chromosomes 1H and 3H.

First, two-colour FISH was carried out with pTa71 and pTa794 in pollen mother cells of

a hybrid between ‘Albacete’×‘Plaisant’. The expected chromosome pairing occurred

during meiotic I prophase for a heterozygous genotype for the chromosomic

arrangement, in which five bivalents and one quadrivalent were observed (Fig. 1a).

Bivalents for the two satellited chromosomes, 5H and 6H, with the strongest pTa71

signals, and the bivalents formed by chromosomes labelled with both probes, 2H, 4H

and 7H, were identified despite the weak signals observed in the Figure 1. Thus,

chromosome 1H, with the stronger pTa71 signal between the non-satellited

chromosomes, and 3H are the chromosomes involved in the quadrivalent (Fig. 1b,c).

We subsequently analysed mitotic metaphases of ‘Albacete’ (Fig. 1d-h). Chromosomes

2H, 4H, 5H, 6H and 7H showed the expected and distinctive FISH pattern of ribosomal

probes. In addition, one pair of submetacentric chromosomes with a rather strong

pTa71 signal on its short chromosome arm and pTa794 signal on its long chromosome

arm and another pair of metacentric chromosomes without any ribosomal signals,

confirmed the presence of a reciprocal translocation resulting in two chromosomal

combinations 1HS-3HL and 3HS-1HL, respectively (Fig. 1f). These two chromosomes

are shown in Fig. 1i. Therefore, the translocation breakpoints are located below the

pTa71 signal on 1HS and above the pTa794 signal on 3HL.

More information about the exact position of the translocation breakpoints can be

obtained by identifying relocated FISH landmarks on chromosomes 1H and 3H. To this

aim three microsatellites probes, (ACT)5, (CAG)5 and (AAG)5 were chosen for their

characteristic patterns on these chromosomes (Cuadrado and Jouve 2007). As expected,

(ACT)5 resulted in a distinct pattern of FISH signals on chromosomes 2H, 3H, 4H, 5H,


35

and 6H. The characteristic signals on the long arm of chromosome 3H were found on

the translocated chromosomes 1HS-3HL (Fig 1g and i). These results suggest that the

translocation breakpoints are located below the pTa71 signal on 1HS and above the

(ACT)5 signal on 3HL (Fig. 1e). The (AAG)5 microsatellite probe facilitates the

identification of all barley chromosomes thanks to a rich pattern of signals of different

intensities located in the pericentromeric and interstitial chromosomal regions (Fig. 1h).

The characteristic patterns obtained in the translocated chromosomes are similar to the

patterns found in other barley varieties with normal 1H and 3H chromosomes and

suggest that the translocation breakpoints are located below the pericentromeric AAG

signals on the long arms of chromosomes 1HL and 3HL (Fig. 1i-j). Results obtained

with the (CAG)5 probe suport the detection and identification of the translocations

1HS.1HL-3HL and 3HS.3HL-1HL. The signals obtained in the centromere of

translocated chromosomes 3HS-1HL were stronger than on 1HS-3HL (Fig 1j).

Chapter 3

36

Figure 1. FISH results with rDNA probes (5S and 18S-5.8S-26S) and microsatellite probes

((ACT)5, (AAG)5 and (CAG)5). (a-c) In situ hybridization of rDNA probes pTa71 (red)

and pTa794 (green) in pollen mother cells of hybrid between ‘Albacete’ × ‘Plaisant’

(Arrows indicate the quadrivalent): (a) DAPI staining for DNA; (b) pTa71 and pTa794

probes; (c) combination of DAPI and pTa71 and pTa794 probes. (d-h) Root-tip

metaphase chromosomes from barley (Hordeum vulgare cv. ‘Albacete’) after DAPI

staining and in situ hybridization with biotin-labelled probes (detected by red Cy3) or

digoxigenin-labelled probes (detected by green FITC): (d) DAPI staining for DNA; (e)

rDNA probes and (ACT)5 (arrows indicate the characteristic ACT signals on 3HL and

arrowheads the 45S rDNA loci on 1HS); (f) pTa71 and pTa794 (arrows indicate the 5S

rDNA loci on 3HL and arrowheads the 45S rDNA loci on 1HS); (g) (ACT)5 (arrows

indicate the characteristic ACT signals on 3HL); (h) (AAG)5 and (ACT)5 (arrowsheads

indicate the characteristic ACT signals on 3HL. Lines indicated the pericentromeric


37

AAG signals on chromosomes 1H and 3H); (i-j) translocated chromosomes hybridized

with pTa71, pTa794, (AAG)5, (ACT)5 and (CAG)5. Scale bar represent 10 µm.

Fine-mapping of the translocation breakpoint region

In order to increase the marker density around the translocation breakpoints the APP

population genotyped with SNP was used. As (AAG)5 and (ACT)5 microsatellite probes

have proved to be useful to determine the translocation breakpoints on 1H and 3H

chromosomes, they were also chosen for detailed cytogenetic characterization of 8 out

of 94 DH lines from the APP population (Figure 2). These DH lines were selected

according to the ‘Albacete’ SNP allele distribution along 1H and 3H aiming to narrow

down the position of the translocation breakpoints. The allocation of markers to linkage

groups as well as their genetic map position were based on the published barley

consensus map (Close et al. 2009). 755 out of 3072 SNP markers were polymorphic for

the APP population; of these 212 markers mapped on chromosomes 1Hand 3H. From

Figure 2 it can be observed that 8 markers around 50-52.5 cM on 1H (11_20427,

11_20660, 12_11209, 12_31208, 11_31381, 11_20912, 11_21312 and 12_30350) and

30 markers around 43.2-55.6 cM on 3H (12_21533, 11_11002, 11_21101, 11_11086,

11_11501, 11_10137, 11_10328, 11_20970, 12_30039, 12_30130, 12_30318,

12_31008, 12_31372, 11_10365, 12_10155, 12_31502, 11_10008, 11_20102,

11_10224, 11_20333, 11_20428, 11_20439, 11_10456, 11_20796, 11_20856,

11_20890, 11_21062, 11_21147, 11_11124 and 11_11337) were close to translocation

breakpoints. This set of SNP markers was used to determine the gene content around

the translocation breakpoints with rice, Brachypodium and Sorghum using Strudel

(http://bioinf.scri.ac.uk/strudel/; Bayer et al. 2011). Inferred gene contents for rice,

Brachypodium and Sorghum yielded around 1,100, 600 and 550 for the region on 1H

and 710, 410 and 430 gene models for 3H, respectively.

Chapter 3

38

Figure 2. Fine-mapping of the translocation breakpoint region using eight selected lines from the

APP mapping population. Graphical genotypes of the eight selected DH lines (top).

Blue and yellow colours indicate ‘Albacete’ and ‘Plaisant’ parental alleles respectively.

Genomic region in the vicinity of the reciprocal translocation breakpoints are indicated

with grey colour. Horizontal dashed lines are drawn every 10 cM with the distance

proportional to the number of SNPs markers. Line number are shown using green and

red colours according to the presence or not of the reciprocal translocation, respectively

(line nº30200 was used as a positive control whereas 3.1 24 as a negative). On the

bottom, In situ hybridization of (ACT)5 (red or green) and (AAG)5 (red) in root-tip

metaphase chromosomes 1H and 3H after DAPI staining and in situ hybridization with

biotin-labelled probes (detected by red Cy3) or digoxigenin-labelled probes (detected by

green FITC).

Discussion

The combination of cytogenetics and molecular genetics allowed us to determine the

translocation breakpoints on chromosomes 1H and 3H of the barley variety 'Albacete'

more accurately than with conventional staining techniques. The success of the

combination of methods depends on the locations of the translocation breakpoints and

on the presence of differential signals on the chromosomes involved (Xu and Kasha,

1991).

In the present study, the positions of the translocation breakpoints have been determined

using a number of approaches. First, an analysis involving recombination frequencies


39

between markers was used to determine markers located near the translocation

breakpoints with a high degree of precision (Farré et al. 2011). SNP and microsatellite

markers putatively flanking the translocation breakpoints were identified in the AB and

APP mapping populations in the pericentromeric regions of chromosomes 1H and 3H.

Secondly, 1H and 3H wheat-barley telosome addition lines were used to assign a

number of markers closely linked to the translocation breakpoints to their proper

chromosome arms and to validate the genetic mapping results. For the genomic SSR

markers on 3H chromosome, the positions are in good agreement with the positions

reported by Künzel and Waugh (2002). They placed 24 microsatellite loci onto the

physical RFLP map of barley chromosome 3H using the map position of the

translocation breakpoints as reference (Künzel et al. 2000). Our genomic SSR markers

on 3H chromosome were identified to be flanking the centromere (positioned at 55 cM)

in the ‘Lina’×Hordeum spontaneum Canada Park genetic map, where Bmac0067,

Bmag0136 and Bmag0006 on the short arm and Bmac0209 on the long arm cover a

genetic distance of 5 cM. It is well known that genetic map distances between markers

along chromosomes correlate poorly with physical distances, particularly in the large

cereal genomes where closely linked markers which genetically map near the

centromere represent considerable physical distances (Schwarzacher 2003). As a

consequence, most of the chromosomal gene content is trapped in chromosome

segments with severely suppressed recombination. According to Künzel and Waugh

(2002) the region flanked by our four SSR covers 36% of the entire 3H chromosome

length on the physical map. For chromosome 1H, no studies were found relating genetic

to physical distance using the genomic SSR we identified close to the translocation

breakpoint. Although being pericentromeric we may expect results similar to those

reported for 3H. In general, Triticeae centromeres are characterised by suppressed

recombination (Schwarzacher 2003; Rostoks et al. 2002). In barley, suppressed

recombination rates in proximal segments and high recombination rates in distal regions

were demonstrated by Pedersen et al. (1995). Later, Künzel et al. (2000) reported that

most recombination was confined in a relatively small chromosomal region, mostly at

the arm ends, alternating abruptly with regions of severely suppressed recombination.

Our approach allowed us to identify and genetically delimit the physical regions in

which the reciprocal translocation took place. However, as the regions involved in the

translocation are located in the vicinity of the centromeres, given the recombination

Chapter 3

40

suppression, they represent fairly large physical regions on both chromosomes 1H and

3H. FISH was used to validate the positions of the translocation breakpoints on the

chromosomes involved in the chromosomal interchanges, which was found to be a

useful approach to characterize non-recombinant regions.

The proposed positions of the breakpoints on the long arms of chromosomes 1H and 3H

can be attributed to the combined use of rDNA and microsatellite probes. Once the

translocation between chromosome 1H and 3H was confirmed using the ribosomal

probes (pTa71 and pTa794) and (ACT)5, the reasons that led us to concluding that the

breakpoints are on the long arms of chromosomes 1H and 3H (resulting in the

reciprocal translocation 1HS.1HL-3HL and 3HS.3HL-1HL) are multiple. Firstly, the

signals obtained using the (AAG)5 probe (which were similar to banding patterns

obtained by C-banding) on the short arms of both chromosomes are the same as those

observed in other barley varieties which indicates that the short arms are complete until

the centromere and not involved in the reciprocal interchange (Pedersen and Linde-

Laursen 1994; Cuadrado and Jouve 2007). However, a discrepancy in the number of

bands on 3HL among different barley varieties was found; some barley lines such as

‘Plaisant’, ‘Gaelic’ and ‘Hispanic’ carried two bands compared with just one for

varieties as ‘Albacete’, ‘Dobla’ and ‘Golden Promise’ (Á. Cuadrado, personal

communication). The lacking of a band near the centromere could be a polymorphism in

these varieties (unpublished data). Besides that, it is important to note that the signal

intensity of the pericentromeric band present on 3HL is stronger than the one present on

1HL, which is characteristic for all barley varieties. Therefore, these results suggest that

the translocation breakpoints are located below this band. Secondly, the differences in

intensity found in the centromeres of the translocated chromosomes with the

(CAG)5 probe are consistent with those obtained for Plaisant (a variety with an standard

chromosome arrangement). Signals on chromosome 3H were stronger than on 1H

(Cuadrado and Jouve 2007) suggesting that the translocation breakpoints are located

below the centromere on both chromosomes. Thirdly, the interchanged chromosomes

1HS.1HL-3HL and 3HS.3HL-1HL are more similar in total length and more

submetacentric and metacentric, respectively, compared with published ‘normal’ barley

karyotypes in which centromeres of chromosome 1H, the smallest barley chromosome,

and 3H are located at 41 and 44% FL (fraction length), respectively (arm ratios for 1H

and 3H were estimated at 1.4 and 1.3 milliGeNomes (mGN), respectively, and


41

chromosome arms are the following: 51 mGN (1HS), 72 mGN (1HL), 64 mGN (3HS)

and 83 mGN (3HL); Taketa et al. 2003). To summarize, the different patterns of these

SSR probes have proven to be of a great value for localizing and validating the

translocation breakpoints on 1H and 3H chromosomes in the Spanish barley variety

‘Albacete’. The results obtained in this study suggest that the translocation breakpoints

are located on the long arms of both chromosomes between the (AAG)5 and

(ACT)5 pericentromeric bands for 3HS.3HL-1HL and below the

(AAG)5 pericentromeric band for 1HS.1HL-3HL leading to a interstitial zone with

suppressed recombination.

For barley and other not yet sequenced species synteny conservation with related

Poaceae species sequenced genomes such as rice, Brachypodium, maize or Sorghum

(Mayer et al. 2011) can be explored and exploited for studying genome evolution and

identification of candidate genes for traits of interest. So, an interesting point is to use

the shared syntenic relationships observed among different species from the grass

family Poaceae to determine the gene content around the translocation breakpoints. To

explore genome co-linearity of barley with rice, Brachypodium and Sorghum we

employed Strudel (http://bioinf.scri.ac.uk/strudel/), a standalone Java desktop

application that allows the simultaneous multi-way comparison of several genomes

(Bayer et al. 2011), on a reduced set of SNP markers selected using a cytogenetical and

molecular characterization of the APP population.

The gene contents, as inferred from rice Os01/Os10 and Os05 chromosomes, around the

translocation breakpoints were estimated as approximately 1,100 and 710 for

chromosomes 1H and 3H, respectively. As a proportion of the genes represent

retroelement-like components and pseudo-genes, the final number of functional genes in

barley must be smaller. Inferred gene contents for Sorghum and Brachypodium yielded

similar figures, around 600 (Sb09/Sb01) and 550 (Bradi02/Bradi03) genes for the

region on 1H and 410 (Sb02) and 430 (Bradi03) gene models for 3H, respectively. This

gene content is in good agreement with the gene content reported by Mayer et al. (2011)

who estimated that the barley genome contains in the order of 32,000 genes. With such

a large gene content the use of a candidate gene approach aiming at identifying which

gene(s) may have been altered by the translocation conferring a higher drought

tolerance to ‘Albacete’ is not practical.

Chapter 3

42

Whole-genome duplication analyses have been documented in grass species. Thiel et al.

(2009) identified shared duplicated segments that originate from the last common

ancestor and that remain in the barley genome. A large degree of synteny existed

between barley chromosome Hv1H and rice chromosome Os05 as well as between

Hv3H and Os01. The barley chromosome Hv3H corresponded to the ancestral

chromosome type of rice chromosome Os01. The structure of chromosome 1H could be

explained by combining the ancestral type of two rice chromosomes, where the first

(A10) appears to be nested in the second (A05). An interesting observation arising from

the comparative mapping of several Poaceae species is the presence of duplicated

segments between chromosomes Os01 and Os05 in rice derived from ancestral

duplications within the grass family (Guyot and Keller 2004) which are overlapping

with the translocation breakpoints on chromosomes 1H and 3H in ‘Albacete’.

Moreover, there are also large grass ancestral genome duplications affecting rice

chromosomes Os03 and Os07 homologous to barley chromosomes 2H and 4H. Smaller

ancestral duplications are present in regions of the rice genome homologous to barley

chromosomes 3H-5H and 3H-6H, which are also involved in spontaneous reciprocal

translocations in barley (Konishi and Linde-Laursen 1988).

In conclusion, the widely grown Spanish barley variety ‘Albacete’ carries a large

pericentric chromosome rearrangement between chromosomes 1H and 3H without any

major change in fitness. SNP and microsatellite markers located in the proximity of the

reciprocal translocation breakpoints were identified in both AB and APP mapping

populations within the pericentromeric regions of both chromosomes. The physical

characterization suggested that the translocation breakpoints are located on the long

arms of both chromosomes between the (AAG)5 and (ACT)5 pericentromeric bands

for 3HS.3HL-1HL and below the (AAG)5 pericentromeric band for 1HS.1HL-3HL. The

gene content in this region was estimated at approximately 1,100 and 710 gene models

for 1H and 3H respectively. Presence of duplicated segments between chromosomes

Os01 and Os05 in rice derived from ancestral duplications within the grass family

(Guyot and Keller 2004) overlaps with the translocation breakpoints on 1H and 3H

chromosomes in the barley variety ‘Albacete’. However, no current evidence is

available of whether similar gene contents on different chromosomes arising from


43

ancestral duplications play a role in spontaneous chromosomal exchanges through non-

homologous chromosome pairing.

Acknowledgments


(Project AGL2008-05541-C02 and the Agrogenomics CONSOLIDER Center).

Chapter 3

44

45

Chapter 4

Agronomic effects of a large reciprocal translocation present in a widely grown Spanish barley variety

A. Farré1,2 · A. Visioni1 · I. Lacasa-Benito1 · L. Cistué3 · J. Jansen2 · I. Romagosa1,4

Published in Euphytica (2012) 185:119-122

Abstract

A large spontaneous reciprocal translocation is present in a widely grown Spanish

barley cv. 'Albacete'. It has been hypothesized that high popularity of ‘Albacete’ with

farmers, particularly in semi-arid areas where barley is grown under rainfed conditions,

may be due to the presence of this translocation. Agronomic effects of this translocation

were studied at two locations and two growing seasons in a set of 245 doubled haploid

lines derived from the F1s of four crosses involving 'Albacete'. The results have shown a

significant positive main effect of the translocation on the thousand kernel weight and a

significant environment by translocation interaction for the thousand kernel weight,

lodging and tiller number. However, the results do not support the hypothesis that this

chromosomal structural change alone provides an increased adaptation to low-yielding

sites.

Keywords Reciprocal translocation Barley Breeding Adaptation

1Department of Plant Production and Forest Science, University of Lleida, Lleida, Spain; 2Biometris, Wageningen University and Research Centre, Wageningen, the Netherlands; 3Estación Experimental de Aula Dei, CSIC, Zaragoza, Spain; 4Centre UdL-IRTA, University of Lleida, Lleida, Spain

Chapter 4

46

Introduction

Spontaneous reciprocal translocations seldomly occur in cultivated barley; only a few

cases have been described (Konishi and Linde-Laursen 1988). Translocations usually

reduce the agronomic value; ‘Albacete’ is the only extensively cultivated barley variety

carrying a reciprocal translocation without apparent loss of agronomic value. In Spain it

has been grown for decades on up to 1 million ha/year. The reciprocal translocation was

identified in a meiotic analysis of semi-sterile F1 hybrids involving ‘Albacete’ (Vazquez

and Sanchez-Monge 1989; see also Farré et al. (2011)). Farré et al. (2012) performed a

molecular and cytogenetic characterization of the reciprocal translocation and

determined the position of the translocation breakpoints. Drought is the main factor

limiting the yield of cereals in environments with high temperatures and limited rain

during the grain-filling period (López-Castañeda and Richards 1994). It is unknown

whether the reciprocal translocation has a positive effect on drought tolerance and other

traits that make it worth to be introduced in the barley germplasm. In the present study,

248 doubled haploid (DH) lines from four crosses involving ‘Albacete’ as one of the

parents will be used to phenotypically characterize the effects of the presence of the

reciprocal translocation.


Plant material

Different agronomic traits were evaluated in 245 DH lines of barley derived from the

F1s between ‘Albacete’ and ‘Barberousse’, ‘Plaisant’ and ‘Orria’ and a DH line derived

from ‘Plaisant’×‘Orria’. ‘Albacete’ is a variety with a long cycle and an alternative

growth habit. It is drought tolerant with a stable grain yield production. ‘Barberousse’ is

known for its good productivity and easy adaptation; it is sensitive to drought. ‘Plaisant’

shows good adaptation and high-yield under Spanish conditions. ‘Orria’ is a Spanish

variety of CIMMYT origin, well adapted to fertile, rainfed environments. The DH lines

were scored for the presence of the reciprocal translocation using molecular data (Farré

et al. 2011). The number of lines carrying/not carrying the translocation were 41/54,

18/20, 40/27, 36/9 for A×B, A×O, A×P and A×(P×O), respectively.

Phenotyping


47

Four field trials were carried out at two rainfed locations in North-Eastern Spain in

2008/2009 and 2009/2010: Gimenells (41º 37’N, 0º 22’E, 248m) and Foradada (41º

51’N, 1º 0’E, 407m). Experiments contained one or two replicates per DH line

augmented by four replicated checks in a rectangular set-up.

Data analysis

For each population the average broad sense heritability was estimated. For each trait,

Best Linear Unbiased Estimates (BLUEs) of DH individuals were estimated by

removing spatial effects. The BLUEs were further analysed using the mixed model

facilities of Genstat version 13 (Payne et al. 2009), heterogeneous variances within

population were corrected.

Results and Discussion

(Table 1) Broad sense heritabilities (H2) ranged from 0.27 to 0.84. A highly significant

main effect of the reciprocal translocation was obtained for TKW; DH lines carrying the

reciprocal translocation had a greater TKW than those with a standard chromosome

arrangement (34.8 vs 32.9 gr, respectively). No significant main effects were found for

the other traits. For TKW, lodging and till number a significant environment by

translocation interaction was found. More lodging was recorded at Gimenells and for

the RT genotypes. Differences in the response of the RT to till number may be

associated to specific meteorological conditions. In conclusion, the results do not

support the hypothesis that the reciprocal translocation alone provides an increased

adaptation to low-yielding sites; TKW is the only trait which is clearly enhanced by the

reciprocal translocation. Future work combining the results from this study with QTL

analysis will be carried out to characterize the effects of the reciprocal translocation and

QTL simultaneously.

Chapter 4

48

Tab

le 1

. (a

) S

umm

ary

of t

he m

ixed

mod

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n (R

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osom

e ar

rang

emen

t (no

RT

) in

fou

r tr

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(th

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gnif

ican

t lev

els

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the

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(b)

Ave

rage

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the

two

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ps in

4

tria

ls (

carr

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ecip

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50

cm, E

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and

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o tw

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ta w

as n

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test

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test

p-

valu

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men

t (E

) 3

1468

9.0

<0.

001

6287

1.4

<0.

001

7336

0.5

<0.

001

195.

2 <

0.00

1 55

9.6

<0.

001

2982

.0

<0.

001

P

opul

atio

n (P

op)

3 3.

8 0.

292

27.0

<

0.00

1 4.

1 0.

263

19.7

<

0.00

1 11

.0

0.01

6 37

.4

<0.

001

R

T

1 0.

2 0.

625

0.2

0.66

7 1.

5 0.

218

2.7

0.10

3 0.

7 0.

402

21.0

<

0.00

1

Pop

.RT

3

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49

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Chapter 4

50

Acknowledgements


(Project AGL2008-05541-C02 and the Agrogenomics CONSOLIDER Center).

51

Chapter 5

Construction of an integrated genetic linkage map of barley (Hordeum vulgare L.) involving a parent carrying a reciprocal

translocation

A. Farré1,2, I. Romagosa1,3, L. Cistué4, J. Jansen2

Abstract

Using DArT® markers, an integrated genetic linkage map has been constructed by

combining five interconnected biparental doubled haploid (DH) populations of barley

involving four barley varieties. Three populations share 'Albacete' as a parent. 'Albacete'

carries a reciprocal translocation between chromosomes 1H and 3H which complicates

the construction of genetic linkage maps due to ‘pseudo-linkage’ between markers on

the chromosomes involved in the translocation. Levels of polymorphism varied

considerably among populations; the highest level was observed for ‘Albacete’ ×

‘Barberousse’ (65.68%) and ‘Albacete’ × ‘Plaisant’ (60.86%) whereas ‘Barberousse’ ×

‘Plaisant’ (22.08%) showed the lowest level. Only markers polymorphic in at least two

populations were used for constructing the integrated map. As a consequence,

construction of an integrated linkage map involves huge numbers of missing data. The

algorithm used for constructing the integrated map is based on minimization of the

number of recombination events between adjacent markers using hidden inheritance

vectors. This algorithm enabled us to develop a robust integrated linkage map involving

complex chromosomal rearrangements. The integrated map consists of 310 markers

covering 938 cM for all chromosomes except 1H and 3H. The number of markers per

chromosome varied between 17 (4H) and 92 (7H).

Keywords Integrated map DArT Reciprocal translocation Barley

1Department of Plant Production and Forest Science, University of Lleida, Lleida, Spain; 2Biometris, Wageningen University and Research Centre, Wageningen, the Netherlands; 3Centre UdL-IRTA, University of Lleida, Lleida, Spain; 4Estación Experimental de Aula Dei, CSIC, Zaragoza, Spain

Chapter 5

52

Introduction

High-density genetic linkage maps have been constructed for many crop species,

including barley (Hordeum vulgare L.). They are increasingly used in plant research to

understand genomic organization and evolution, the determination of synteny

relationships, gene tagging and map-based cloning. One of the most important

objectives for developing high-density genetic maps is to identify precise locations of

genes and quantitative trait loci (QTL) associated with traits of interest. This objective

can be achieved by constructing consensus maps using information from multiple

populations. In principle, the use of multiple populations has many advantages over the

use of a single population. In particular, a larger number of markers can be placed on a

single map providing greater genome coverage. Marker order and intermarker distances

can be estimated more accurately, and possible chromosomal rearrangements and gene

duplication can be determined.

Although many consensus maps have been produced in barley (Karakousis et al. 2003;

Langridge et al. 1995; Marcel et al. 2007; Qi et al. 1996; Stein et al. 2007; Varshney et

al. 2007; Rostoks et al. 2005), the consensus map which provided us the opportunity to

compare the order of the DArT markers on our integrate linkage maps with the order of

the same markers on a high-density genetic map was constructed by Wenzl et al. (2006).

This map was based on segregation data from seven DH populations and three

populations of RIL, comprising 2,935 loci (2,085 DArT, 850 SSR, RFLP and/or STS

markers) and spans 1,161 cM. Later, this map was improved by incorporating 607

newly developed DArT markers to create a new integrated map of the barley genome

containing 3542 markers (Alsop et al. 2010). Other saturated genetic maps were

developed using DArT markers in barley for instance the one which was constructed by

Hearnden et al. (2007). This was developed from an F1-derived doubled haploid

population generated from a cross between cultivated barley (Hordeum vulgare) and the

subspecies H. vulgare ssp. spontaneum. The map comprises 1,000 loci, amplified using

536 SSR (558 loci) and 442 DArT markers.

The construction of high-density genetic linkage map requires powerful methods, which

can perform the necessary calculations in a limited amount of time. There are several

programs that can be used to build consensus maps, including JoinMap, Carthagene and

Construction of an integrated genetic linkage map of barley (Hordeum vulgare L.) involving a parent carrying a reciprocal translocation

53

PhenoMap (Stam 1993; De Givry et al. 2005; (GeneFlow Inc., Centreville, VA.). The

most important point to keep in mind when building a consensus map is that markers

are sorted correctly. For that, two aspects have to be considered: the mapping criterion

and the mapping algorithm (Van Os et al. 2005). The mapping criteria that have been

proposed include the maximum likelihood, the minimum sum of adjacent recombination

fractions (SARF), the maximum sum of adjacent LOD scores (SALOD), the minimum

number of crossovers and the ‘least square locus order’. For the mapping algorithms

several approaches have been proposed like branch-and-bound, seriation and simulated

annealing. A widely used platform for the construction of genetic linkage maps is

provided by JoinMap®. The map integration facilities were developed in a period that

segregating markers were scarce and many populations had to be combined to obtain

adequate genome coverage. However, the regression algorithm of JoinMap® fails when

it is required to integrate linkage maps involving large numbers of markers.

Jansen (2005) introduced an algorithm for constructing genetic linkage maps for full-sib

families of outbreeding species, which typically involves the integration of maternal and

paternal maps. In outbreeding species, markers may have different segregation types,

i.e. some markers only segregate only in the mother, and other markers only segregate

in the father. This leads to missing information about the inheritance of genomic

fragments. The algorithm is based on minimization of the number of recombination

events between adjacent markers using hidden inheritance vectors. Inheritance vectors

are used to indicate the grandparental origins of alleles.

The aim of the present study was to adapt the algorithm developed by Jansen (2005) to

cope with multiple populations derived from crosses between pure lines. In this

situation missing data occur due to the fact that markers may segregate in some

populations but not in others. This paper presents the results of integrating marker data

obtained using DArT technology from five interconnected DH populations of barley

into a single consensus map. Three of these DH populations have one parent in

common: ‘Albacete’ which is known to carry a reciprocal chromosomal translocation

between chromosomes 1H and 3H. To construct linkage maps in the populations

obtained from reciprocal translocation heterozygotes we followed the novel statistical-

genetic approach developed by Farré et al. (2011) which disentangled the 'pseudo-

Chapter 5

54

linkage' between the markers from the chromosomes involved in the reciprocal

translocation making use of the consensus map obtained by Wenzl et al. (2006).


Mapping populations

Five connected DH populations were derived from crosses between four parents:

‘Albacete’, ‘Barberousse’, ‘Plaisant’ and ‘Orria’. ‘Albacete’ is a six-row facultative

variety selection from a local Spanish landraces with a relatively long cycle and an

alternative growth habit. It is drought tolerant showing a relatively stable grain yield

production. ‘Barberousse’ ('Ager' × ['W.259-711' × ('Hatif' × 'Ares')]), a six-row feed

winter variety released in France in 1977, is known for its good productivity and easy

adaptation although it is more sensitive to drought. ‘Plaisant’ ('Ager' × 'Nymphe') is a

six-row French winter malting cultivar released in 1979. ‘Orria’ ({[('Api' × 'Kristina') ×

'M66.85'] × 'Sigfrido's} × '79W40762') is a Spanish six-row facultative variety obtained

from a cross made at CIMMYT; it is well adapted to fertile, rainfed environments.

DH lines were obtained from the F1s using the anther-culture technique (Cistué et al.

2003). The five DH populations that will be used to construct the integrated linkage

map are shown in Figure 1, together with the numbers of DH lines per population and

polymorphic DArT markers.

Figure 1. Set-up of the five DH populations with the number of DH lines (top) and the number of

DArT markers (bottom).

DNA isolation and genotyping

Albacete Plaisant

Barbarrousse Orria

181 DHL709 DArT®

39 DHL729 DArT®

54 DHL276 DArT®231 DHL

709 DArT®186 DHL

472 DArT®


55

Genomic DNA of the DH lines was extracted from fresh leaf tissue using the Qiagen

DNeasy 96 plant Kit. A genome wide scan was carried out using Diversity Arrays

Technology (DArT®) (www.diversityarrays.com). This technique is based on DNA

hybridization, does not require a priori sequence information and is carried out on a

microarray platform which allows high-throughput screening of hundreds of molecular

markers simultaneously (Jaccoud et al. 2001, Wenzl et al. 2004). The polymorphisms

scored are the presence (1) or absence (0) of hybridizations to individual array elements.

The locus designations used by Triticarte Pty. Ltd. were adopted in this paper. DArT

marker names consist of the prefix “bPb”, followed by numbers corresponding to a

particular clone in the genomic representation, where b stands for barley, P for PstI

(primary restriction enzyme used) and b for BstNI (secondary restriction enzyme).

Genetic linkage map construction

The first step in the construction of the consensus map was to assess each DH

population separately. For each DH population quality-filtered datasets were prepared

by removing markers and DH lines in two different steps: pre-mapping and post-

mapping diagnostics. For pre-mapping diagnostics markers were removed according to

the following criteria: (1) Q value (estimate of marker quality) less than 77, (2) markers

with more than 10% missing data and (3) markers with segregation ratio less than 0.2 or

greater than 0.8. DH lines were discarded according to high segregation distortion ratio

(above 80%). For post-mapping diagnostics, JoinMap® 4.0 (Van Ooijen, 2006) was

used to: (1) determine the number of linkage groups present in each population using a

recombination frequency of 0.20, (2) remove markers that do not fit well by the

“nearest-neighbour stress” criterion and (3) discard DH lines with large number of

recombinations per individual (more than 20).

The novel statistical-genetic approach developed by Farré et al (2011) was followed to

construct linkage maps in the populations obtained from reciprocal-translocation

heterozygotes making use of the consensus map obtained by Wenzl et al. (2006).

Briefly, the five chromosomes showing a standard arrangement were analyzed

separately. Then, for chromosomes 1H and 3H four stages were followed: (i) the

recombination frequencies between the markers from 1H and 3H were calculated, which

Chapter 5

56

allowed us to select the markers close to the TB; (ii) based on the genotype for those

markers the DH lines were separated into two distinct subpopulations: S1 which around

the translocation breakpoint the DH lines are identical to ‘Albacete’, so they are

expected to carry the translocation between 1H and 3H chromosomes (1HS·3HL +

3HS·1HL) and S2 which close to the TB the alleles are identical to standard type

(‘Plaisant’, ‘Barberousse’ or ‘Orria’), this indicates that they have a standard

chromosomal arrangement (1HS·1HL + 3HS·3HL); (iii) the segregation ratios for each

marker were calculated for each of the two subpopulations, markers showing

segregation ration less than 0.3 or greater than 0.7 were removed; (iv) the two

subpopulations were considered separately to obtain independent linkage maps for the

short and long arms of 1H and 3H. The final product consists of integrated linkage maps

of the chromosome parts away from the translocation breakpoint.

The markers used for constructing the consensus map were those which segregated in

more than 300 DH lines for all chromosomes except for 1H and 3H; in that case, the

markers selected were those that mapped in more than 150 DH lines. Therefore, all

markers used were segregating in at least two mapping populations.

Integrated linkage maps were obtained by a simplified version of the algorithm

described by Jansen (2005) and developed for full-sib families of outbreeding species.

The algorithm has also been applied succesfully in F2 populations with dominant

markers (Jansen 2009). The algorithm aims at obtaining the marker order with the

smallest number of recombinations between adjacent markers on hidden inheritance

vectors. Inheritance vectors represent the grandparental origin of alleles in binary form:

0 = allele of DH line is identical to allele of grandmother (= female parent of cross), 1 =

allele of DH line is identical to allele of grandfather (= male parent of cross). Since DH

lines contain information from a single meiosis, inheritance vectors for DH lines consist

of a single digit. If the parents differ with regard to hybridization with DArT probes (i.e

polymorphic parents) and hybridization data are present for the DH lines, hybridization

data can be converted uniquely into inheritance vectors according to the scheme in

Table 1. In other cases information about the transmission of alleles is missing and the

inheritance vectors may assume the value zero or one. Two steps were performed to

obtain the integrated maps for each linkage group separately. In the first step, a

framework map is constructed for a set of markers which are selected because they


57

cover the whole linkage map using the spatial sampling procedure. In the next step, all

non-selected markers will be attached on the previous map close to the nearest selected

marker. Linkage maps were drawn using MapChart 2.2 (Voorrips, 2002).

Table 1. Conversion of hybridization data into inheritance vectors

Results

Single populations

Pre-mapping diagnostics

Linkage maps are strongly affected by scoring errors. Therefore, high quality genotypic

data is critical. Thus, in order to get robust estimates very stringent criteria were used

for data filtering. For each DH population separately, markers and DH lines were

excluded according to different criteria. In the case of the markers, although a total of

2,895 DArT® polymorphic markers were found by the Australian company Triticarte

Pty for the five DH populations, 545 markers were removed according to: Q value (195

markers), missing data (230 markers) and high segregation distortion ratios (120

markers). The results are shown in Table 2. Population A×O has a remarkably large

number of markers with an extreme segregation ratio. This may be due to the small

population size (only 39 DH lines). As a result, 2,350 DArT markers can be used for the

map construction. In the case of DH lines, a total of 691 DH lines were available for the

construction of linkage maps but 7 individuals were discarded due to the high

segregation distortion ratios (above 80%) caused by very limited recombination as they

consisted almost entirely of one parental haplotype (5 like ‘Albacete’ and 2 like

‘Plaisant’ from A×B and P×O crosses, respectively).

DH line: Hybridization

DH line: No-hybridization

DH line: Missing data

Grandmother: hybridization Grandfather: no hybridization

0 1 0, 1

Grandmother: no hybridization Grandfather: hybridization

1 0 0, 1

Chapter 5

58

Table 2. Summary of individual mapping data used to construct the consensus map (* = in the

case of A×O population markers with more than 5% of missing data were removed; Pop

= population).

Post-mapping diagnostics

Markers that according to the information supplied by the Australian company Triticarte

Pty belonged to more than one chromosome or mapped on different loci within the

same chromosome were not removed and location was attempted in the correct

chromosome (16, 5, 13, 13 and 8 markers from A×B, A×O, A×P, P×O and B×P crosses,

respectively). 38 out of 684 DH lines were discarded because of an extremely large

number of recombinations per individual (6, 2, 1, 28 and 1 for A×B, A×P, A×O, P×O

and B×P crosses, respectively). As a result, a total of 646 DH lines were used for the

linkage maps construction.

Polymorphisms between parents

The first step required in the construction of a linkage map is to check the parental lines

for polymorphism. A high level of polymorphism between parents facilitates the

construction of high-density consensus map. The level of polymorphism among

populations for each chromosome is represented in Figure 2 and SEM I_Table 3. The

location of markers to chromosomes and their positions was obtained from the

consensus map of barley (Wenzl et al. 2006). This clearly shows the highest level of

polymorphism revealed by DArT markers between parents of the A×B (65.68%) and

A×P (60.86%) mapping populations. However, B×P exhibits the lowest level (22.08%),

in almost all chromosomes followed by A×O (38.66%). For the parental lines ‘Plaisant’

Pop. No. polymorphic Markers

Number of markers excluded per criterion

Available polymorphic markers

Q value Missing data Segregation ratio

A×B 709 16 85 8 600 A×P 709 64 51 2 592 A×O 729 51 34* 108 536 P×O 472 50 40 0 382 B×P 276 14 20 2 240 Total 2,895 195 230 120 2,350


59

and ‘Orria’ (52.89%), 1H was the highest level (92.23%) while the lowest is observed

on 4H (9.62%). In the present study, the percentage of polymorphism of the individual

chromosomes for all mapping populations ranged from 13% (4H) to 95.8% (6H).

Figure 2. Polymorphism among populations for each chromosome. The allocation of markers as

well as their position were estimated based on the consensus map of barley (Wenzl et al.

2006) (horizontal lines are drawn every 10 cM; red colour indicated the regions of the

consensus map without coverage).

Chapter 5

60

Individual maps

In all populations and for the recombination value used (r = 0.2), more than seven

linkage groups corresponding to each of the barley chromosomes were obtained because

in a lot of cases each chromosome was split in more than one linkage group. It is

important to note that markers near the centromeric region for chromosomes 1H and 3H

based on the consensus map appeared together in the same linkage group for the DH

lines derived from the cross between ‘Albacete’ and another parental (A×B, A×P, and

A×O). This confirms the presence of the reciprocal translocation previously studied in

the DH population derived from the cross between ‘Albacete’ and ‘Barberousse’ (Farré

et al. 2012). Table 4 shows the selected markers close to the translocation breakpoint

used to divide the DH line for each population into two distinct subpopulations; not all

selected markers coincide among populations, this is because some markers were

removed according to the criteria described in Farré et al. 2011 or they were not within

the 5 cM from the presumed translocation breakpoints.

The mapping populations with the highest number of mapped loci were A×B (521

markers) and A×P (514 markers) while the lowest was observed for B×P (225 markers).

The total length of the individual maps ranged from 1,623 cM (A×P) to 683 cM (B×P).

For the three populations that share ‘Albacete’ as a parent, 5H was the individual

linkage group with the highest map length (252, 296 and 243 cM from A×B, A×P and

A×O crosses, respectively); for P×O and B×P population was 7H (243 cM) and 3H (221

cM), respectively; whereas the smallest linkage group varied among mapping

populations. In the case of A×B and A×P, 1H was the linkage group with the smallest

map length (149 and 160 cM, respectively). For A×O and P×O it corresponded with 7H

(85 cM) and 4H (92 cM), respectively. And for B×P, the map length for the linkage

groups 5H and 6H was 0 cM because they had 4 markers which mapped in the same

position. The greatest gap in all mapping populations was on chromosome 3H (104, 76,

130, 81 and 60 cM from A×B, A×P, A×O, B×P and P×O crosses, respectively).

It is important to note that some markers that according to the information supplied by

the Australian company Triticarte Pty could be mapped in more than one chromosome

or multiple loci on the same chromosome were located correctly (9, 5, 6, 2 and 2

markers from A×B, A×P, A×O, B×P and P×O population, respectively). However,


61

some markers mapped on different chromosomes according to the consensus map (bPb-

0413, bPb-6063, bPb-5389 and bPb-4963 mapped on 5H instead of 2H; bPb-6109 and

bPb-7181 on 7H instead of 3H and 6H, respectively).

Comparison of the individual maps with the consensus map of Wenzl et al (2006)

The individual map distances generated by the algorithm developed by Jansen et al.

(2001, 2005 and 2009) are larger than those on the consensus map of barley (Wenzl et

al. 2006). For population, the overestimation of distances relative to the consensus map

distance was calculated. The A×P and A×B populations had the highest percentage, 40

and 22%, respectively, while the smallest percentage was for A×O (4%) and B×P (-

41%).

Chapter 5

62

Table 4. Summary of the selected markers used to divide the DH lines for each mapping

population and subpopulation data (S1: 1HS·3HL + 3HS·1HL and S2: 1HS·1HL +

3HS·3HL).

Population

S1 S2 Linkage group

1H 3H

No. lines

Markers with segregation distortion (<30%, >70%)

No. lines

Markers with segregation distortion (<30%, >70%)

Marker loci

Consensus map position (cM)

Marker loci

Consensus map position (cM)

A×B 88 65 85 69 bPb-9717 58.7 bPb-6329 66.5

bPb-6621 59.1 bPb-0094 69.3

bPb-4949 59.2 bPb-5771 69.3

bPb-0910 59.4 bPb-5012 69.8

bPb-9957 63.3 bPb-8321 70.4

bPb-9360 64.4

A×P 66 50 80 60 bPb-5749 63.3 bPb-0094 69.3

bPb-9767 63.3 bPb-5771 69.3

bPb-9957 63.3 bPb-8283 69.6

bPb-1193 62.2 bPb-5012 69.8

bPb-3382 62.2 bPb-8321 70.4

bPb-1791 67.1

A×O 18 61 15 55 bPb-5749 63.3 bPb-0040 72.2

bPb-9767 63.3 bPb-3805 72.2

bPb-9957 63.3 bPb-3317 78.6

bPb-1193 62.2 bPb-8410 78.6

bPb-3382 62.2


63

Multiple populations

Integrated maps

The construction of the consensus map was carried out for each chromosome separately

using the algorithm developed by Jansen et al. (2001, 2005, and 2009). For

chromosomes 1H and 3H two independent integrated maps were obtained using the

markers from A×B, A×P, A×O and B×P, P×O mapping populations separately.

The integrated maps of seven barley chromosomes are presented by Figure 4 and Table

5. This map has a total length of 938 cM with 310 markers for all chromosomes except

1H and 3H providing an average density of one marker every 3.02 cM. The individual

linkage groups ranged from 228 cM (5H) to 148 cM (4H). The numbers of common

markers varied greatly between linkage groups: 17 on 4H compared to 92 on 7H. On the

integrated map, linkage group 7H had the greatest number of markers (92) with an

average marker density of 2.19 cM followed by linkage group 6H (75) with an average

marker density of 2.14 cM. Linkage group 4H had the smallest number of markers (17)

and the highest marker density (8.70 cM). The highest gap is in linkage group 4H (41

cM). The resulting maps for each population compared with the integrated are shown on

SEM II_Figure 3 and Table 5.

Comparison of integrated map with the consensus map of Wenzl et al (2006)

At completion of construction of the map a comparison was made between the order of

loci on the consensus map and the integrated map which showed a high level of

conservation of DArT marker order with the exception on 4H and for bPb-7335 marker

on 3HS for A×O/A×P/A×B integrated map which is located on 3HL on the consensus

map. The linkage group distances are larger than those on the consensus map. Linkage

group 1H obtained using markers data from P×O and B×P mapping populations had the

highest percentage (27%) followed by 7H (22%). The smallest percentage was in 1H

obtained using markers data from A×B, A×P and A×O mapping populations (-27%).

Chapter 5

64

Table 5. Summary of individual and integrated mapping data (I = integrated and CN =

consensus) (length of disjoint intergroup segments within a linkage group determined

based on the consensus map; a= map obtained using marker data from A×O, A×B and

A×P populations; b= map obtained using markers data from P×O and B×P mapping

populations).

Pop 1H 2H 3H 4H 5H 6H 7H Total

A×B

No. of segments 3 2 2 3 2 1 3 Length segments (cM)

87 238 82 104 240 207 170 1,128

No. of markers 41 98 55 43 79 101 104 521 Consensus intergap

62 7 105 58 12 - 45

Estimate total 149 245 187 162 252 207 215 1,417

A×O


25 192 20 92 180 133 59 701


115 33 130 104 63 32 26

Estimate total 140 225 150 196 243 165 85 1,204

A×P


62 243 146 101 278 206 235 1,271


98 39 76 74 18 14 33

Estimate total 160 282 222 175 296 220 268 1,623

P×O


226 120 135 53 143 126 236 1,039


- 60 88 39 100 - 14

Estimate total 226 180 223 92 243 126 250 1,340

B×P


131 33 140 22 0 0 86 412


59 104 81 - - - 27

Estimate total 190 137 221 22 0 0 113 683

Integrated

No. of segments 3a 1b 2 2a 2b 3 2 1 1 Length segments (cM)

45a 193b 180 86a 114b 80 203 161 202

No. of markers 40a 63b 64 51a 30b 17 62 75 92 Consensus intergap

66a - 19 104a 41b 68 25 - -

Estimate total 111a 193b 199 190a 155b 148 228 161 202 I/CN (%) -27a 27b 19 3a -5b 0 17 9 22


65

Fig

ure

4.

Com

pari

son

of t

he i

nteg

rate

d m

aps

wit

h th

e co

nsen

sus

map

s co

nstr

ucte

d by

Wen

zl e

t al

. 20

06 (

only

com

mon

mar

kers

are

ill

ustr

ated

). C

hrom

osom

es a

re

orie

nted

wit

h th

e sh

ort a

rm a

t the

top.

The

gen

etic

dis

tanc

es a

re e

xpre

ssed

in m

ap d

ista

nces

(cM

). (

TB

= tr

ansl

ocat

ion

brea

kpoi

nt).

bPb-

8559

bPb-1

165

bPb-3

622

bPb-

1348

bPb-

3776

bPb-

8973

bPb-

0442

bPb-

7306

bPb-

9288

bPb-

1226

Clon

eID-

2221

91bP

b-94

15Cl

oneI

D-22

1017

bPb-0

851

bPb-

0760

Clon

eID-

2217

26bP

b-030

1bP

b-93

37

bPb-

3389

bPb-

9656

bPb-

8983

bPb-

3089

bPb-

9401

bPb-

8605

bPb-

4144

bPb-1

213

bPb-5

249

Clon

eID-

2216

87bP

b-91

08bP

b-003

9Cl

oneID

-221

039

bPb-

0340

bPb-

5014

Clon

eID-

2219

02

bPb-

8619

bPb-

0699

bPb-

3660

bPb-

1381

bPb-

1487

bPb-

2260

bPb-

0405

bPb-

1165

bPb-1

348

bPb-3

622

bPb-

3776

bPb-

2723

bPb-

9608

bPb-7

043

bPb-

7137

bPb-

8973

bPb-

1318

bPb-

9604

bPb-

9952

bPb-

4657

bPb-

2183

bPb-

7306

bPb-

9337

bPb-

9423

bPb-

9333

bPb-

2175

bPb-

9717

bPb-

9675

bPb-

0910

bPb-4

980

bPb-

0468

bPb-

2813

bPb-7

325

bPb-7

859

bPb-

8960

bPb-

4531

bPb-

6853

bPb-

3605

bPb-

5683

bPb-

9611

bPb-1

922

bPb-5

292

bPb-

6133

bPb-

4590

bPb-5

334

bPb-8

897

bPb-

5486

bPb-

8107

bPb-

3389

bPb-

7609

bPb-

9116

bPb-

3089

bPb-

4144

bPb-

5249

bPb-9

121

bPb-4

898

bPb-

6901

bPb-

6911

bPb-

1213

bPb-

1366

bPb-

1419

bPb-

4515

bPb-9

180

bPb-

9108

bPb-

5014

bPb-

5198

bPb-

2240

bPb-

8112

bPb-

0699

bPb-

3660

bPb-

1487

bPb-

2260

bPb-

0405

Clon

eID-2

2156

3bP

b-27

23bP

b-13

18bP

b-71

37bP

b-96

08bP

b-70

43bP

b-99

52bP

b-96

04Cl

oneID

-222

789

Clon

eID-2

2104

0bP

b-46

57bP

b-21

83

bPb-

9337

bPb-

9423

bPb-

9333

bPb-

2175

Clon

eID-2

2110

8bP

b-51

64bP

b-97

17bP

b-09

10bP

b-56

83bP

b-04

68bP

b-89

60bP

b-785

9Cl

oneID

-223

899

bPb-

9675

bPb-

3605

Clon

eID-

2208

14bP

b-73

25bP

b-28

13bP

b-68

53bP

b-498

0bP

b-45

31bP

b-52

92bP

b-96

11bP

b-19

22bP

b-53

34bP

b-45

90bP

b-88

97bP

b-72

89bP

b-54

86bP

b-61

33bP

b-81

07bP

b-76

09bP

b-30

89bP

b-91

16bP

b-91

21bP

b-48

98bP

b-69

01bP

b-13

66bP

b-12

13bP

b-69

11bP

b-52

49

bPb-

4515

bPb-

1419

bPb-

9180

Clon

eID-2

2103

9

bPb-

5198

bPb-

5014

bPb-

2240

Clon

eID-2

2421

3

bPb-

8112

bPb-7

803

bPb-3

598

bPb-

6466

bPb-7

626

bPb-8

399

bPb-5

444

bPb-

9220

bPb-8

292

bPb-3

050

bPb-

6963

bPb-

5884

bPb-1

098

bPb-4

523

bPb-

8750

bPb-8

038

bPb-4

261

bPb-

9682

bPb-4

877

bPb-3

519

bPb-8

449

bPb-2

230

bPb-9

992

bPb-

3677

bPb-

2219

bPb-3

575

bPb-6

088

bPb-4

040

bPb-9

754

bPb-7

991

bPb-1

926

bPb-3

563

bPb-

6194

bPb-4

184

bPb-9

458

bPb-7

124

bPb-5

755

bPb-3

858

bPb-7

816

bPb-6

087

bPb-2

244

bPb-

9199

bPb-1

986

bPb-

7208

bPb-8

530

bPb-1

566

bPb-

5460

bPb-

5619

bPb-8

240

bPb-

0689

bPb-6

048

bPb-

9909

bPb-

3598

bPb-

6466

bPb-

7803

bPb-

7626

bPb-

3459

bPb-

8399

bPb-

6235

Clon

eID-

2212

38Cl

oneI

D-22

0974

bPb-

5444

bPb-

9220

bPb-

8292

bPb-

3050

bPb-

6963

bPb-

5884

bPb-

4523

bPb-

8750

bPb-

1098

bPb-

8038

bPb-

4261

bPb-

9682

bPb-

4877

bPb-

9802

bPb-

9131

bPb-

2230

Clon

eID-

2227

60bP

b-35

72bP

b-39

85bP

b-20

13bP

b-36

77bP

b-99

92bP

b-22

19bP

b-35

75bP

b-60

88bP

b-404

0bP

b-975

4Cl

oneI

D-22

1652

bPb-

6194

bPb-

3563

bPb-1

926

bPb-

7991

Clon

eID-

2212

27bP

b-41

84bP

b-94

58bP

b-71

24bP

b-38

58bP

b-57

55bP

b-78

16bP

b-91

99bP

b-22

44bP

b-60

87bP

b-56

19bP

b-72

08bP

b-19

86bP

b-85

30bP

b-15

66bP

b-54

60bP

b-06

89bP

b-82

40Cl

oneI

D-22

0851

bPb-

9909

bPb-

6048

2233

37

Clon

eID-

1051

69bP

b-40

22Cl

oneI

D-10

5031

bPb-5

555

Clon

eID-

2220

55bP

b-84

57bP

b-12

64bP

b-95

83bP

b-99

45Cl

oneI

D-22

0951

bPb-

0476

Clon

eID-

2235

77bP

b-77

70bP

b-71

99bP

b-36

49Cl

oneI

D-22

3396

Clon

eID-

2208

82Cl

oneI

D-22

1142

bPb-

9745

Clon

eID-

2218

98bP

b-74

48bP

b-13

02bP

b-72

85Cl

oneI

D-22

4036

bPb-

0331

Clon

eID-

2212

74bP

b-63

61bP

b-73

35bP

b-292

9

bPb-

8506

bPb-

8621

bPb-

2550

bPb-

1609

bPb-

9111

bPb-

6249

bPb-

3867

bPb-

5666

bPb-

3899

bPb-

6383

bPb-

7827

bPb-0

789

bPb-

9599

bPb-

0945

bPb-

7815

bPb-

8419

bPb-

0200

bPb-

0735

bPb-

0361

bPb-

9965

bPb-

5795

bPb-

7724

bPb-

4022

bPb-

5555

bPb-

1264

bPb-

9583

bPb-

9945

bPb-

7770

bPb-

7199

bPb-

7448

bPb-

2929

bPb-

0312

bPb-

6347

bPb-

2440

bPb-

7872

bPb-

1681

bPb-

8506

bPb-

8621

bPb-

2550

bPb-1

609

bPb-

9111

bPb-

6249

bPb-

7335

bPb-

3899

bPb-

8557

bPb-

5666

bPb-

6383

bPb-

9118

bPb-7

827

bPb-

0789

bPb-

9599

bPb-

7815

bPb-

8419

bPb-

6631

bPb-

0200

bPb-

1928

bPb-

7164

bPb-

8322

bPb-8

907

bPb-

1411

bPb-

0361

bPb-

0164

bPb-

7724

bPb-7

481

bPb-

7705

bPb-

7918

Clon

eID-

2209

51bP

b-940

2bP

b-71

99bP

b-61

27Cl

oneID

-221

142

Clon

eID-2

2088

2

bPb-0

312

bPb-6

782

bPb-6

347

bPb-7

937

bPb-2

440

bPb-7

872

Clon

eID-2

2235

8bP

b-168

1Cl

oneID

-222

616

bPb-7

827

bPb-

6383

bPb-

9118

bPb-

8557

Clon

eID-2

2087

8bP

b-663

1

bPb-7

164

bPb-

1928

bPb-

8907

bPb-

8322

bPb-1

411

bPb-0

164

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100

105

110

115

120

125

130

135

140

145

150

155

160

165

170

175

180

185

190

195

200

2051H

-AxB/AxP/AxO

1H-consensus

1H-PxO/BxP

2H-consensus

2H3H-AxB/AxP/AxO

3H-consensus

3H-PxO/BxP

TB

TB

Chapter 5

66

Fig

ure

4. (

cont

inue

d)

bPb-

9304

bPb-

4699

bPb-

1408

bPb-

8437

bPb-

6640

bPb-

9039

bPb-

4183

bPb-

3512

bPb-

9504

bPb-

6949

bPb-

9998

bPb-

5265

bPb-

9304

Clon

eID-

2226

50bP

b-46

99

bPb-

8437

bPb-

1408

bPb-

6640

Clon

eID-

2223

52

bPb-

6949

Clon

eID-

2237

51bP

b-95

04

Clon

eID-

2225

09

bPb-

4183

bPb-

9039

bPb-

3512

bPb-

9998

Clon

eID-

2216

36

bPb-

5265

bPb-

6485

bPb-

9562

bPb-

6051

bPb-

1909

bPb-

4814

bPb-

8072

bPb-

2460

bPb-

9632

bPb-

0050

bPb-

6067

bPb-

6495

bPb-

6363

bPb-

7348

bPb-

3412

bPb-

3792

bPb-

6710

bPb-

3852

bPb-

7561

bPb-

0709

bPb-

2497

bPb-

6288

bPb-

4721

bPb-

7395

bPb-

5596

bPb-

4494

bPb-

2580

bPb-

5845

bPb-

4318

bPb-

1420

bPb-

4970

bPb-

2006

bPb-

0171

bPb-

6179

bPb-

8070

bPb-

4595

bPb-

0835

bPb-

1965

bPb-

4971

bPb-

1217

bPb-

9660

bPb-

4809

bPb-

6485

bPb-

9562

bPb-

6051

bPb-

1909

Clon

eID-

2232

99bP

b-48

14bP

b-80

72bP

b-24

60

bPb-

0349

bPb-

9632

bPb-

0050

bPb-

6495

bPb-

6067

bPb-

6363

Clon

eID-

2242

19bP

b-73

48bP

b-34

12bP

b-37

92

bPb-

3852

bPb-

6710

bPb-

0709

bPb-

7561

bPb-

4721

bPb-

6288

bPb-

2497

bPb-

9032

bPb-

5516

Clon

eID-

2232

33

bPb-

7395

bPb-

5596

bPb-

0780

bPb-

5389

bPb-

6063

bPb-

8449

bPb-

3519

bPb-

0413

Clon

eID-

2221

96bP

b-70

22bP

b-04

86bP

b-25

80bP

b-88

54bP

b-44

94bP

b-58

45bP

b-43

18bP

b-14

20bP

b-49

70bP

b-20

06Cl

oneI

D-22

2499

bPb-

8809

bPb-

0621

bPb-

0171

Clon

eID-

2213

74bP

b-80

70bP

b-45

95bP

b-08

35bP

b-61

79bP

b-19

65bP

b-49

71Cl

oneI

D-22

2075

bPb-

1217

bPb-

9660

bPb-

4809

bPb-

3780

bPb-

0426

bPb-

1009

bPb-

7193

bPb-

7362

bPb-

3586

bPb-

8528

bPb-

2930

bPb-

9852

bPb-

2672

bPb-

6419

bPb-

6069

bPb-

9651

bPb-

6661

bPb-

5252

bPb-

9807

bPb-

6457

bPb-

3427

bPb-

2881

bPb-

0245

bPb-

5910

bPb-

7179

bPb-

3746

bPb-

2464

bPb-

5822

bPb-

3487

bPb-

9114

bPb-

1666

bPb-

6567

bPb-

9082

bPb-

2593

bPb-

4750

bPb-

9051

bPb-

9835

bPb-

3068

bPb-

0451

bPb-

4178

bPb-

0606

bPb-

9063

bPb-

6477

bPb-

3470

bPb-

9349

bPb-

3144

bPb-

1029

bPb-

2304

bPb-

2863

bPb-

6677

bPb-

2940

bPb-

1621

bPb-

0403

bPb-

7146

bPb-

4626

bPb-

2137

bPb-

0426

bPb-

3780

Clon

eID-

2227

74bP

b-10

09bP

b-71

93bP

b-35

86bP

b-98

52bP

b-29

30bP

b-85

28bP

b-73

62bP

b-64

19bP

b-60

69bP

b-26

72bP

b-07

42bP

b-96

51Cl

oneI

D-22

1373

bPb-

5252

bPb-

6661

bPb-

3427

bPb-

6457

bPb-

2881

bPb-

9807

bPb-

0245

Clon

eID-

2239

14bP

b-59

10Cl

oneI

D-22

1002

Clon

eID-

2233

86bP

b-37

46bP

b-71

79bP

b-03

96Cl

oneI

D-22

0959

bPb-

2464

bPb-

5822

bPb-

6567

bPb-

1666

bPb-

9114

bPb-

3487

bPb-

4750

bPb-

2593

bPb-

9835

bPb-

9051

bPb-

9082

Clon

eID-

2215

14Cl

oneI

D-22

2255

Clon

eID-

2223

06bP

b-30

68Cl

oneI

D-22

1627

Clon

eID-

2211

05bP

b-33

09bP

b-27

55bP

b-87

70bP

b-21

85Cl

oneI

D-22

3391

Clon

eID-

2219

46bP

b-41

78bP

b-04

51bP

b-06

06bP

b-64

77bP

b-34

70bP

b-90

63bP

b-29

40bP

b-66

77bP

b-28

63Cl

oneI

D-22

2519

bPb-

3144

bPb-

9349

Clon

eID-

2237

21bP

b-02

98bP

b-21

37bP

b-46

26bP

b-23

04bP

b-71

46bP

b-04

03bP

b-16

21bP

b-10

29

bPb-

8921

bPb-

8161

bPb-

2718

bPb-

6170

bPb-

6976

bPb-

5259

bPb-

0043

bPb-

7038

bPb-

4064

bPb-

2595

bPb-

0179

bPb-

3718

bPb-

4097

bPb-

3727

bPb-

7417

bPb-

7183

bPb-

5494

bPb-

1806

bPb-

2478

bPb-

9601

bPb-

9898

bPb-

6821

bPb-

5091

bPb-

2866

bPb-

7835

bPb-

1209

bPb-

0366

bPb-

8524

bPb-

0037

bPb-

6706

bPb-

4541

bPb-

4597

bPb-

7952

bPb-

4219

bPb-

1952

bPb-

5599

bPb-

8956

bPb-

2097

bPb-

1770

bPb-

7603

bPb-

7437

bPb-

2188

bPb-

7915

bPb-

9912

bPb-

5296

bPb-

7399

bPb-

8074

bPb-

5747

bPb-

1596

bPb-

0202

bPb-

4191

bPb-

7628

bPb-

6167

bPb-

0758

bPb-

3980

bPb-

1631

bPb-

0917

bPb-

0889

bPb-

5923

bPb-

0773

bPb-

1336

bPb-

7983

bPb-

8833

bPb-

3226

bPb-

2897

bPb-

2693

bPb-

2854

bPb-

0375

bPb-

2718

bPb-

6170

Clon

eID-

2209

12bP

b-00

43bP

b-52

59bP

b-69

76bP

b-81

61bP

b-89

21bP

b-70

38bP

b-40

64bP

b-48

86bP

b-25

95Cl

oneI

D-22

1452

Clon

eID-

2224

70Cl

oneI

D-22

1538

bPb-

0179

bPb-

3718

bPb-

4097

bPb-

7417

bPb-

3727

bPb-

2478

Clon

eID-

2210

61bP

b-18

06bP

b-54

94bP

b-71

83bP

b-96

01bP

b-98

98Cl

oneI

D-22

2477

bPb-

6821

bPb-

5091

bPb-

0366

bPb-

2866

bPb-

7835

bPb-

1209

bPb-

0037

bPb-

7728

bPb-

6706

bPb-

9803

bPb-

8524

bPb-

4541

bPb-

4597

bPb-

1952

bPb-

4219

bPb-

7952

bPb-

2188

bPb-

7915

bPb-

1770

bPb-

7437

bPb-

8956

bPb-

5599

bPb-

7603

bPb-

2097

bPb-

7399

bPb-

5296

bPb-

9912

bPb-

7150

bPb-

1596

bPb-

5747

bPb-

8074

Clon

eID-

2234

44bP

b-41

91bP

b-02

02Cl

oneI

D-22

1054

Clon

eID-

2224

65Cl

oneI

D-22

2751

bPb-

0773

bPb-

7628

bPb-

1336

bPb-

5923

bPb-

0889

Clon

eID-

2221

59bP

b-09

17bP

b-61

67bP

b-07

58Cl

oneI

D-22

0949

bPb-

7983

bPb-

1631

bPb-

3980

bPb-

8833

Clon

eID-

2225

28bP

b-21

21bP

b-99

48bP

b-55

48bP

b-28

54bP

b-26

93bP

b-32

26bP

b-28

97bP

b-03

75

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100

105

110

115

120

125

130

135

140

145

150

155

160

165

170

175

180

185

190

195

200

205

210

4H-consensus

4H5H-consensus

5H6H-consensus

6H7H-consensus

7H


67

Discussion

High density genetic linkage maps provide a greater probability that the entire genome

is covered with molecular markers avoiding large gaps in the map without markers. For

the construction of high-density genetic linkage maps is of particular importance to

have several loci in common between populations. This requires a high level of

polymorphism between parents. In the present study, the highest level of polymorphism

among populations was observed for A×B and A×P whereas B×P showed the lowest

level. This appears to be in good agreement with the results obtained by Casas et al.

(1998). They estimated the genetic resemblance among a representative set of 37 barley

cultivars, including our four parents, grown in Spain using RFLP markers. A

dendrogram constructed from UPGMA cluster analysis split the 37 barley cultivars into

five distinct germplasm groups that were consistent with the history of the cultivars:

winter European (including ‘Barberousse’ and ‘Plaisant’), spring European, CIMMYT-

ICARDA materials (including ‘Orria’), the single cultivar 'Dobla' and Spanish local

materials (including ‘Albacete’). Parental lines ‘Plaisant’ and ‘Barberousse’

demonstrated the highest level of similarity in the dendrogram compared with the other

parents. This could be explained because they share ‘Ager’ as parent. The level of

polymorphism between populations is determined by the level of genetic divergence

among parents.

The integrated map developed in this paper was obtained by assembling marker data

from five interconnected DH populations which allowed us to fill a number of gaps

present in maps of individual populations. The order of the markers on the integrated

map as well as on maps of individual populations are consistent with the order on the

consensus map (Wenzl et al. 2006) except for some markers on chromosome 4H and

one marker on chromosome 3H. In our study, map distances are slightly larger than

those on the consensus map. The discrepancy in map lengths may be due to difference

in “data curation” possibly in combination to the use of different mapping criteria and

mapping algorithms.

For map integration it is very important to create high-quality datasets free of errors

because genotyping errors (which produce unexpected crossovers) and missing data

lead to map expansion, especially in regions with a high marker density. The filtered

Chapter 5

68

high quality datasets from the consensus map used in this paper to verify our integrated

map were obtained following different steps: (i) JoinMap 4.0 was used to distribute loci

into linkage groups and remove redundant lines; (ii) loci order within individual

population was determined using RECORD programme which employs a marker-

ordering criteria based on minimization of the total number of recombination events and

the algorithm applied combine elements of branch-and-bound with local reshuffling

(Van Os et al. 2005a) and (iii) lines and loci with an excess of singletons were identified

and removed using a purpose-built Perl script. Map expansion could also be reduced by

removing markers that do not fit well by “nearest-neighbour stress” and/or had high

segregation ratios. However, a more accurate method will be necessary to remove the

appropriate DH lines.

Differences in map lengths could also arise due to the different methods used by the

software packages to calculate map lengths. Whereas the consensus map was derived

using the regression mapping algorithm we focused on a multipoint maximum

likelihood (ML) mapping algorithm developed by Jansen et al. (2001, 2005 and 2009).

JoinMap® algorithm fails when it is required for integrating linkage maps with large

numbers of markers, missing data, typing errors and pairwise recombination frequencies

are not present for all marker combinations. Therefore, the algorithm applied in this

study is an efficient method for constructing good-quality dense linkage maps. Spatial

sampling used to obtain a small set of markers homogenously distributed in the linkage

group provided an efficient way to reduce map expansion.

The percentage of genome coverage of our integrated map compared with the consensus

map of Wenzl et al. 2006 from the three populations with the highest number of

individuals (A×B, A×P and P×O) are 82.0, 10.6, 86.6, 94.5 and 95.5% for 2H, 4H, 5H,

6H and 7H chromosomes respectively, this percentage improved for chromosome 2H

up to 7% more when B×P and A×O populations with the smallest number of individuals

were included in the analysis.

In conclusion, the consensus map constructed with the useful method develop by Jansen

(2005) is consistent compared with the consensus map of barley (Wenzl et al. 2006).

This will be used for QTL mapping for quantitative agronomic characters allowing us to

compare QTL between different genetic backgrounds. A high density genetic linkage


69

map allows a greater precision of QTL location than in a sparse map (fewer markers)

because the greater the distance between markers, the greater the chance of

recombination between the marker and the QTL. These cause that the magnitude of the

effect of a QTL to be underestimated (Collard et al. 2005).

Acknowledgments


(Project AGL2008-05541-C02 and the Agrogenomics CONSOLIDER).

Chapter 5

70

SUPPLEMENTARY MATERIAL I - POLYMORPHISMS AMONG PARENTS

Table 3. Level of polymorphism among populations and chromosomes (values in brackets are

expressed as percentages).

Chromosome Consensus

(cM) A×B (cM)

A×P (cM)

A×O (cM)

P×O (cM)

B×P (cM)

1H 151.90 40.80 (26.86)

39.30 (25.87)

14.60 (9.61)

140.10 (92.23)

82.10 (54.05)

2H 166.70 144.60 (86.74)

132.60 (79.54)

118.40 (71.03)

63.50 (38.09)

42.87 (25.72)

3H 184.59 74.10 (40.14)

88.30 (47.84)

17.40 (9.43)

76.50 (41.44)

63.20 (34.24)

4H 148.58 63.90 (43.01)

46.40 (31.23)

14.90 (10.03)

14.30 (9.62)

8.10 (5.45)

5H 194.15 185.30 (95.44)

168.20 (86.63)

103.0 (53.05)

89.50 (46.1)

0.30 (0.15)

6H 147.08 139.0 (94.51)

117.60 (79.96)

108.80 (73.97)

86.80 (59.02)

2.40 (1.63)

7H 165.42 113.20 (68.43)

112.60 (68.07)

70.80 (42.8)

142.0 (85.84)

56.80 (34.34)

Total (%) 65.68 60.86 38.66 52.89 22.08


71

SUPPLEMENTARY MATERIAL II- COMPARISON OF THE INTEGRATED MAP WITH THE INDIVIDUAL MAPS

Figure 3. (A-G). Individual maps and their integrated map of the seven barley chromosomes.

Chromosomes are oriented with the short arm at the top. Lines are indicated the common markers, which are presented in black and underline.

(A) Chromosome 1H

bPb-9608 bPb-0473 CloneID-104922bPb-5638CloneID-224191

bPb-9108 CloneID-221039 CloneID-105006

bPb-8935 bPb-8453 bPb-0617

CloneID-105054 bPb-1487 bPb-2260

bPb-1348 bPb-3622 bPb-1165bPb-8559bPb-3776bPb-9414bPb-8973bPb-7306 bPb-0442bPb-0851 CloneID-221726 bPb-0301bPb-0760 CloneID-221017 bPb-9415bPb-1226 bPb-9288 CloneID-222191bPb-9337

bPb-3389bPb-9656bPb-8983

bPb-3089 bPb-9401bPb-1213 bPb-5249 bPb-4144bPb-8605

CloneID-221687bPb-9108 CloneID-221039 bPb-0039bPb-0340 bPb-5014CloneID-221902

bPb-8619bPb-0699bPb-3660 bPb-1487 bPb-1381bPb-2260

bPb-8559 bPb-1165 bPb-3622bPb-1348bPb-3776bPb-8973bPb-0442bPb-7306bPb-9288bPb-1226 CloneID-222191bPb-9415 CloneID-221017 bPb-0851bPb-0760CloneID-221726 bPb-0301bPb-9337bPb-3389bPb-9656bPb-8983bPb-3089bPb-9401bPb-8605bPb-4144 bPb-1213 bPb-5249CloneID-221687bPb-9108 bPb-0039 CloneID-221039bPb-0340bPb-5014CloneID-221902bPb-8619bPb-0699bPb-3660bPb-1381bPb-1487bPb-2260

bPb-5064bPb-0405CloneID-221563 bPb-6451CloneID-222381 bPb-0487 bPb-3249bPb-1562CloneID-222534CloneID-222789CloneID-221040bPb-7306 bPb-4657 bPb-2183bPb-0851CloneID-221726 CloneID-221017 bPb-0760

bPb-9116bPb-3089bPb-1213 bPb-4898 bPb-6901bPb-9121 bPb-1366 bPb-5249bPb-6911bPb-4515 bPb-9180 bPb-1419bPb-7429

bPb-3660bPb-1487 bPb-2260bPb-5550bPb-8307 bPb-9762bPb-0589 bPb-5201 bPb-8112bPb-3116

05101520253035404550556065707580859095100105110115120125130135140145150155160165170175180185190195200205210215220225

bPb-6451 bPb-0405 bPb-2883bPb-2289 bPb-2208 bPb-5064bPb-8593bPb-8559 bPb-8212 bPb-1348bPb-1165 bPb-5242bPb-8345 bPb-3249 bPb-3579bPb-0374 bPb-0487bPb-5297 bPb-8973 bPb-9414bPb-0915 bPb-2055bPb-5638bPb-6273 bPb-4793bPb-9243 bPb-45000bPb-5866 bPb-9418 bPb-3217bPb-8359bPb-2175bPb-5164bPb-1604 bPb-4949 bPb-0910bPb-4980 bPb-9717 bPb-5962bPb-8509bPb-4170bPb-4271bPb-5425 bPb-1150bPb-4041bPb-1133

bPb-7949 bPb-8983

bPb-4515 bPb-1419 bPb-9180bPb-8570bPb-0039

bPb-8615bPb-0589 bPb-5201 bPb-9410bPb-8112bPb-0699 bPb-6873 bPb-8308

bPb-0405CloneID-221563bPb-2723bPb-1318 bPb-7137bPb-9608bPb-7043bPb-9952 bPb-9604CloneID-222789CloneID-221040bPb-4657bPb-2183bPb-9337bPb-9423bPb-9333bPb-2175CloneID-221108bPb-5164bPb-9717bPb-0910bPb-5683 bPb-0468 bPb-8960bPb-7859 CloneID-223899 bPb-9675bPb-3605 CloneID-220814 bPb-7325bPb-2813 bPb-6853 bPb-4980bPb-4531bPb-5292 bPb-9611bPb-1922bPb-5334 bPb-4590bPb-8897bPb-7289bPb-5486bPb-6133bPb-8107bPb-7609bPb-3089bPb-9116bPb-9121bPb-4898 bPb-6901bPb-1366 bPb-1213 bPb-6911bPb-5249bPb-4515 bPb-1419 bPb-9180CloneID-221039bPb-5198bPb-5014bPb-2240CloneID-224213bPb-8112

bPb-0405CloneID-221563bPb-2723bPb-1318 bPb-9608 bPb-7137bPb-7043bPb-9604bPb-9952CloneID-222789CloneID-221040bPb-2183bPb-4657bPb-9337bPb-0851bPb-9423bPb-8294 bPb-9333bPb-2175CloneID-221108bPb-5164bPb-0910bPb-9717bPb-4980 bPb-9675 bPb-9057bPb-4531 CloneID-223899 bPb-3605bPb-4662 bPb-7325 bPb-8960bPb-5683 bPb-6853 bPb-7859bPb-0468 bPb-6358 CloneID-220814bPb-2813bPb-9611bPb-1922 bPb-5292bPb-9360bPb-5486bPb-6133 bPb-4590 bPb-4614bPb-8897 bPb-5334 bPb-7289bPb-8107bPb-5339bPb-7609bPb-3089 bPb-9116bPb-1213 bPb-1366 bPb-4898bPb-6901 bPb-9121 bPb-6911bPb-5249bPb-1419 bPb-9180 bPb-4515bPb-9108 CloneID-221039bPb-5198 bPb-5014bPb-2240CloneID-224213bPb-8112bPb-3756

05101520253035404550556065707580859095100105110115120125130135140145150155160165170175180185190195200205210215220225230235

AxO AxB 1H-AxB/AxP/AxO AxP

BxP 1H-PxO/BxP PxO

Chapter 5

72

Figure 3. (continued)

Fig

ure

3. (

cont

inue

d)

(

B)

Chr

omos

ome

2H

bPb

-359

8C

lone

ID-2

223

67b

Pb

-646

6bP

b-7

803

Clo

neI

D-2

24

196

Clo

neID

-22

3332

Clo

neI

D-2

2357

6

Clo

neI

D-2

24

040

bPb-

7626

Clo

neI

D-2

2315

9bP

b-9

788

bPb

-109

8b

Pb-

5884

bP

b-4

523

bPb

-875

0C

lone

ID-2

212

38b

Pb

-835

4C

lon

eID

-10

510

5C

lone

ID-1

049

25bP

b-8

038

bPb

-121

2bP

b-7

975

bP

b-56

29bP

b-4

261

bP

b-60

63b

Pb

-968

2bP

b-8

449

bP

b-48

77C

lon

eID

-220

996

bPb

-351

9b

Pb-

5389

Clo

neI

D-2

24

250

1049

56b

Pb

-980

2bP

b-9

131

Clo

neID

-22

4126

bPb

-286

7

bPb

-683

5

bPb

-223

0C

lone

ID-2

229

64C

lon

eID

-222

760

bPb

-992

5

2Clo

neID

-22

968

bPb-

6055

bP

b-7

991

bPb

-192

6b

Pb-

3563

bP

b-6

194

Clo

neI

D-2

24

177

Clo

neID

-22

4007

bP

b-0

771

Clo

neI

D-2

22

905

bPb

-827

4

bPb

-418

4C

lone

ID-2

212

27C

lon

eID

-105

191

bPb

-803

9b

Pb-

3719

bPb

-054

1C

lon

eID

-22

143

5C

lone

ID-1

049

87

bPb

-575

5C

lon

eID

-10

485

5C

lone

ID-1

048

78b

Pb

-781

6C

lon

eID

-10

485

4C

lone

ID-2

219

83C

lon

eID

-105

190

Clo

neI

D-1

05

064

bPb

-224

4b

Pb-

9199

bPb

-608

7bP

b-1

566

bP

b-19

86b

Pb

-561

9bP

b-8

530

bP

b-54

60b

Pb

-720

8

bPb

-990

9bP

b-8

698

bP

b-62

96b

Pb

-310

2bP

b-1

085

bPb

-677

7b

Pb-

8734

bP

b-6

222

bPb

-610

5

Clo

neI

D-1

05

025

bPb-

9467

bP

b-7

890

Clo

neI

D-2

22

957

Clo

neI

D-2

2303

5b

Pb-

051

6b

Pb-

646

6b

Pb-

359

8C

lone

ID-2

223

67

bP

b-7

803

Clo

neI

D-2

2419

6C

lon

eID

-223

972

bP

b-6

297

Clo

neI

D-2

2333

2C

lon

eID

-223

147

Clo

neI

D-2

2363

1C

lon

eID

-223

665

bP

b-9

788

Clo

neI

D-2

2404

0b

Pb-

762

6b

Pb-

345

9C

lon

eID

-221

238

bP

b-5

884

Clo

neI

D-1

0492

5bP

b-8

35

4b

Pb-

310

8b

Pb-

109

8bP

b-8

75

0b

Pb-

45

23b

Pb-

803

8b

Pb-

968

2bP

b-4

26

1b

Pb-

487

7b

Pb-

224

3bP

b-9

13

1C

lon

eID

-224

126

bP

b-9

802

bP

b-2

867

Clo

neI

D-2

2276

0b

Pb-

223

0b

Pb-

357

2bP

b-3

98

5

bP

b-3

056

bPb

-64

38

bP

b-6

881

bP

b-3

575

Clo

neI

D-2

2330

3bP

b-3

67

7b

Pb-

99

92b

Pb-

221

9

bP

b-4

040

bP

b-9

754

bPb

-60

88

bP

b-3

318

Clo

neI

D-2

2165

2b

Pb-

805

2

bP

b-0

858

bP

b-3

563

bPb

-19

26

bP

b-7

991

bP

b-6

194

bP

b-8

260

bP

b-8

274

bP

b-4

184

bPb

-88

51

Clo

ne

ID-2

212

27

bP

b-9

458

bP

b-7

160

bP

b-1

967

bP

b-3

858

bP

b-5

755

Clo

neI

D-2

2198

3b

Pb-

150

5b

Pb-

601

2bP

b-3

97

8b

Pb-

77

23b

Pb-

232

2bP

b-7

81

6b

Pb-

81

73b

Pb-

521

6b

Pb-

919

9bP

b-2

24

4b

Pb-

608

7b

Pb-

561

9bP

b-8

53

0b

Pb-

72

08b

Pb-

616

9bP

b-1

98

6b

Pb-

118

4bP

b-1

56

6b

Pb-

54

60b

Pb-

159

3bP

b-8

25

5C

lon

eID

-223

260

bP

b-0

946

bP

b-1

051

bPb

-14

15

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neI

D-2

2085

1C

lon

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821

bPb

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09

bP

b-2

408

bPb

-46

91

bP

b-78

92C

lone

ID-2

230

35b

Pb-

6466

bP

b-35

98b

Pb-

8445

bP

b-78

03C

lone

ID-2

239

72C

lone

ID-2

231

47

bP

b-76

26

bP

b-34

59C

lone

ID-2

212

38b

Pb-

6235

bP

b-8

399

Clo

neID

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0974

bP

b-9

220

bPb-

5444

bP

b-61

28b

Pb-

8292

bP

b-30

50b

Pb

-696

3b

Pb-

5884

bP

b-80

38b

Pb-

9682

bP

b-4

261

bP

b-48

77C

lon

eID

-222

314

bP

b-91

31b

Pb

-166

4b

Pb-

0671

bP

b-98

02C

lon

eID

-222

357

Clo

neID

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4126

Clo

neID

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2760

bP

b-22

30b

Pb-

3985

bP

b-3

572

bPb-

2013

bP

b-02

20

Clo

neID

-22

3503

bP

b-35

75b

Pb-

9992

bP

b-36

77b

Pb-

2219

bP

b-97

54b

Pb

-404

0bP

b-60

88C

lone

ID-2

227

71b

Pb-

5440

Clo

neID

-22

1652

bP

b-81

00b

Pb-

6055

bP

b-7

991

bPb-

1926

bP

b-35

63b

Pb

-619

4

Clo

neID

-22

2810

Clo

neID

-22

0896

Clo

neI

D-2

2122

7bP

b-4

184

bP

b-26

80

bP

b-94

58b

Pb-

7124

bP

b-38

58b

Pb-

5755

Clo

neID

-22

1983

bP

b-31

65b

Pb-

7816

bP

b-0

659

bP

b-78

90b

Pb-

3334

bP

b-91

99b

Pb

-224

4b

Pb-

6087

bP

b-85

30b

Pb

-720

8bP

b-19

86b

Pb-

0303

bP

b-5

619

bP

b-15

66b

Pb-

5460

bP

b-06

89b

Pb-

8240

Clo

neID

-22

0851

bP

b-86

98b

Pb

-108

5bP

b-62

96b

Pb-

6048

Clo

neI

D-2

2333

7b

Pb-

9794

bP

b-40

93b

Pb

-745

5b

Pb-

9467

bP

b-95

20C

lon

eID

-223

912

Clo

neID

-22

3655

Clo

neID

-22

303

5bP

b-3

59

8bP

b-6

46

6bP

b-7

80

3bP

b-7

62

6bP

b-3

45

9bP

b-8

39

9bP

b-6

23

5C

lone

ID-2

212

38

Clo

neID

-22

097

4bP

b-5

44

4bP

b-9

22

0bP

b-8

29

2bP

b-3

05

0bP

b-6

96

3bP

b-5

88

4bP

b-4

52

3bP

b-8

75

0bP

b-1

09

8bP

b-8

03

8bP

b-4

26

1bP

b-9

68

2bP

b-4

87

7bP

b-9

80

2bP

b-9

13

1bP

b-2

23

0C

lone

ID-2

227

60

bPb

-35

72

bPb

-39

85

bPb

-20

13

bPb

-36

77

bPb

-99

92

bPb

-22

19

bPb

-35

75

bPb

-60

88

bP

b-4

040

bPb

-975

4C

lone

ID-2

216

52

bPb

-61

94

bPb

-35

63

bP

b-1

926

bPb

-79

91

Clo

neID

-22

122

7bP

b-4

18

4

bPb

-94

58

bPb

-71

24

bPb

-38

58

bPb

-57

55

bPb

-78

16

bPb

-91

99

bPb

-22

44

bPb

-60

87

bPb

-56

19

bPb

-72

08

bPb

-19

86

bPb

-85

30

bPb

-15

66

bPb

-54

60

bPb

-06

89

bPb

-82

40

Clo

neID

-22

085

1bP

b-9

90

9bP

b-6

04

8C

lone

ID-2

233

37

bP

b-8

399

bP

b-6

235

bP

b-5

444

bPb-

9220

bP

b-8

292

Clo

neI

D-2

2097

4bP

b-00

03b

Pb

-305

0bP

b-69

63b

Pb

-452

3b

Pb

-875

0

Clo

neI

D-2

2409

5

bP

b-3

574

bPb-

6992

bP

b-5

629

bP

b-3

572

bP

b-2

013

bPb-

3985

bP

b-9

925

bP

b-1

836

bP

b-3

575

bP

b-2

219

bP

b-8

700

Clo

neI

D-2

2290

5bP

b-76

71b

Pb

-803

9b

Pb

-371

9

bP

b-6

122

bPb-

1266

bP

b-8

949

bP

b-9

266

bP

b-9

458

bP

b-7

124

bP

b-3

858

bP

b-8

240

bPb-

0689

bP

b-8

734

bPb-

6777

bP

b-9

909

bP

b-6

048

Clo

neI

D-2

2333

7

bP

b-6

235

bP

b-0

003

bP

b-9

220

bPb

-61

28

bP

b-1

098

bPb

-82

92

bP

b-8

750

bP

b-4

523

bPb

-96

20

bP

b-9

594

bPb

-30

50

bP

b-2

107

7b

Pb-

998

4bP

b-3

23

9b

Pb-

11

89

bP

b-7

418

bPb

-68

81

bP

b-6

438

bP

b-3

056

bP

b-0

946

bPb

-15

93

bP

b-8

255

bP

b-9

395

bP

b-1

051

bPb

-14

15

bP

b-5

015

bP

b-8

698

bPb

-79

30

bP

b-6

199

bP

b-1

085

bPb

-78

90

bP

b-9

467

bP

b-6

048

bPb

-62

96

bP

b-7

434

bP

b-4

093

bPb

-68

94

bP

b-5

416

bP

b-6

280

bPb

-95

20

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100

105

110

115

120

125

130

135

140

145

150

155

160

165

170

175

180

185

190

195

200

205

210

215

220

225

230

235

240

245

250

255

260

AxO

AxB

AxP

Integrated

PxO

BxP


73

(C) Chromosome 3H

AxO AxB 3H-AxB/AxP/AxO AxP

CloneID-221259 bPb-1264 bPb-9583bPb-9945 bPb-0476

bPb-1609

bPb-6249 bPb-9111bPb-5796 bPb-8621 bPb-8506bPb-7245 bPb-2550

bPb-0789 bPb-7815

bPb-6631

bPb-5555 CloneID-105031 bPb-4022bPb-6884 bPb-4472 CloneID-105169CloneID-222055bPb-8457bPb-1264bPb-9583 CloneID-220951 CloneID-223577bPb-9945bPb-0476bPb-7770 bPb-7199 bPb-3649CloneID-223396 CloneID-220882 CloneID-221142bPb-9745CloneID-221898 bPb-7448

bPb-1302bPb-7285 CloneID-224036CloneID-221274 bPb-0331bPb-6361 bPb-2929 bPb-5289bPb-7350 bPb-7335bPb-9961

bPb-8506bPb-8621 bPb-2550

bPb-9111bPb-6249

bPb-3867 bPb-5666bPb-3899 bPb-7827 bPb-0945bPb-9599 bPb-0789 bPb-6383bPb-7815bPb-0200 bPb-8419bPb-0735

bPb-0361

bPb-9965

bPb-7724 bPb-5795

CloneID-105169 bPb-4022 CloneID-105031bPb-5555CloneID-222055bPb-8457bPb-1264bPb-9583bPb-9945CloneID-220951bPb-0476CloneID-223577bPb-7770bPb-7199bPb-3649CloneID-223396CloneID-220882CloneID-221142bPb-9745CloneID-221898bPb-7448bPb-1302bPb-7285 CloneID-224036bPb-0331 CloneID-221274bPb-6361 bPb-7335 bPb-2929

bPb-8506bPb-8621bPb-2550

bPb-1609

bPb-9111bPb-6249bPb-3867bPb-5666bPb-3899bPb-6383 bPb-7827 bPb-0789bPb-9599bPb-0945bPb-7815bPb-8419bPb-0200bPb-0735

bPb-0361

bPb-9965

bPb-5795bPb-7724

bPb-6884

bPb-7481 bPb-7705 CloneID-220951bPb-7918bPb-1264

bPb-9945

CloneID-221622bPb-9745CloneID-221551CloneID-221898bPb-7448 CloneID-221552bPb-0654bPb-1302bPb-7285bPb-1077bPb-3565bPb-5289 bPb-7350 bPb-9903bPb-2929

bPb-3630 bPb-4209

CloneID-220818

bPb-2550 bPb-8621bPb-8894

bPb-1609

bPb-2640bPb-9111

bPb-6249

bPb-0049

bPb-8021

bPb-9599bPb-2888bPb-0789CloneID-223538bPb-6383bPb-8557bPb-7827 bPb-9118bPb-7815

bPb-1822

bPb-0361

bPb-6221

bPb-7724 bPb-5256bPb-5355bPb-7247CloneID-224240bPb-9923 CloneID-221232bPb-5569

0

5

10

15

20

25

30

35

40

45

50

55

60

65

70

75

80

85

90

95

100

105

110

115

120

125

130

135

140

145

150

155

160

165

170

175

180

185

190

195

200

205

210

215

Chapter 5

74

Figure 3. (continued)

PxO 3H-PxO/BxP BxP

bPb-7918 CloneID-220951 bPb-7705bPb-7481

bPb-9797bPb-9402 bPb-7199 bPb-6127CloneID-220882CloneID-221142

bPb-7002

bPb-0312

bPb-6782

bPb-6347

bPb-7937bPb-2440

bPb-7872

CloneID-222616CloneID-222358 bPb-1681

bPb-6383 bPb-7827 bPb-8557bPb-9118

CloneID-220878 bPb-6631CloneID-222327

bPb-1928 bPb-7164 bPb-8907bPb-8322

bPb-1411

bPb-5864bPb-0164

bPb-7481 bPb-7705 bPb-7918CloneID-220951

bPb-9402 bPb-7199 bPb-6127CloneID-221142CloneID-220882

bPb-0312

bPb-6782

bPb-6347

bPb-7937bPb-2440

bPb-7872

CloneID-222358 bPb-1681 CloneID-222616

bPb-7827 bPb-6383 bPb-9118bPb-8557

CloneID-220878 bPb-6631

bPb-7164 bPb-1928 bPb-8907bPb-8322

bPb-1411

bPb-0164

bPb-48285

bPb-7918 bPb-7705 bPb-2018bPb-7481

bPb-7770 bPb-8441 bPb-3649

bPb-3603

bPb-8697 bPb-6722

bPb-4616 bPb-9336

bPb-3630 bPb-4209

bPb-5246bPb-2640 bPb-1609bPb-6695

bPb-3907bPb-0049

bPb-8419bPb-0200 bPb-1114 bPb-42312

bPb-5568 bPb-7911

bPb-6536

0

5

10

15

20

25

30

35

40

45

50

55

60

65

70

75

80

85

90

95

100

105

110

115

120

125

130

135

140

145

150

155

160

165

170

175

180

185

190

195

200

205

210

215

220

225


75

Fig

ure

3. (

cont

inue

d)

(

D)

Chr

omos

ome

4H

AxO

AxB

AxP

Integrated

PxO

BxP

bP

b-2

83

7bP

b-8

56

9bP

b-1

469

bP

b-7

27

5

bP

b-4

69

922

26

50

22

29

03

22

40

48

22

34

13

10

48

83

bP

b-8

43

7bP

b-1

40

8b

Pb-6

64

02

210

13

bP

b-3

51

2bP

b-4

33

3bP

b-0

513

bP

b-2

42

7bP

b-3

04

5bP

b-0

365

bP

b-0

13

0bP

b-3

68

4b

Pb-6

77

510

51

70

22

22

94

bP

b-4

50

122

35

44

bP

b-6

07

4b

Pb-1

49

6bP

b-0

03

6

22

14

40

bP

b-6

87

2bP

b-6

94

910

512

4

10

48

57

22

41

31

22

16

36

bP

b-9

82

0

22

379

5bP

b-9

304

222

65

0b

Pb

-46

99

22

402

0

bP

b-4

990

bP

b-2

427

bP

b-3

045

bP

b-0

365

bP

b-3

684

bP

b-4

333

bP

b-0

130

bP

b-0

513

bP

b-3

512

bP

b-0

996

22

250

9bP

b-4

501

bP

b-9

134

bP

b-6

074

bP

b-1

496

bP

b-0

036

bP

b-6

775

22

229

4bP

b-3

34

722

410

1

bP

b-7

987

bP

b-0

059

bP

b-3

829

bP

b-4

214

22

160

8

bP

b-8

701

bP

b-1

329

bP

b-9

998

bP

b-9

048

bP

b-9

440

bP

b-5

711

22

413

1bP

b-1

166

22

163

6bP

b-6

101

bP

b-9

668

bP

b-5

265

bP

b-4

765

222

650

bP

b-9

304

bP

b-4

69

9

bP

b-0

99

6b

Pb

-24

27

bP

b-3

68

4b

Pb-0

13

0b

Pb-0

36

5b

Pb

-05

13

bP

b-3

04

5b

Pb-4

33

3

222

509

bP

b-6

77

5b

Pb-6

07

4b

Pb-4

50

1b

Pb

-14

96

bP

b-9

57

9b

Pb

-00

36

bP

b-4

18

32

225

47

bP

b-9

03

9b

Pb

-32

68

bP

b-1

27

8

bP

b-9

50

42

23

751

bP

b-2

30

5b

Pb-6

94

9b

Pb-6

87

2

222

352

bP

b-4

21

4

bP

b-1

32

9b

Pb

-87

01

bP

b-9

99

8

221

636

bP

b-3

46

8

bP

b-9

82

0b

Pb

-52

65

bP

b-9

30

422

26

50

bP

b-4

69

9

bP

b-8

43

7b

Pb-1

40

8b

Pb-6

64

0

22

23

52

bP

b-6

94

9

22

37

51

bP

b-9

50

4

22

25

09

bP

b-4

18

3

bP

b-9

03

9

bP

b-3

51

2

bP

b-9

99

8

22

16

36

bP

b-5

26

5

bP

b-1

46

9bP

b-8

56

9bP

b-2

837

bP

b-7

27

5

22

40

48

22

34

13

bP

b-1

14

8

bP

b-1

40

8b

Pb-8

43

7bP

b-6

64

0

bP

b-1

76

2bP

b-8

89

6

22

25

09

22

08

46

22

22

94

22

37

51

bP

b-9

50

4

22

40

01

22

23

52

bP

b-9

99

8

bP

b-4

990

bP

b-3

512

bP

b-3

725

3bP

b-4

18

3bP

b-9

039

bP

b-6

155

bP

b-9

504

bP

b-3

34

7

bP

b-6

949

bP

b-9

340

bP

b-6

87

2bP

b-7

987

bP

b-0

059

bP

b-3

82

9

bP

b-4

240

bP

b-3

047

0 5 10

15

20

25

30

35

40

45

50

55

60

65

70

75

80

85

90

95

100

105

110

115

120

125

130

135

140

145

150

155

160

Chapter 5

76

Fig

ure

3. (

cont

inue

d)

(E

) C

hrom

osom

e 5H

AxO

AxB

AxP

Integrated

PxO

BxP

bP

b-5

31

7

bP

b-1

90

9C

loneID

-2232

99

bP

b-8

07

2b

Pb-2

460

Clo

neID

-2217

73

bP

b-0

091

bP

b-3

830

bP

b-6

56

8b

Pb-7

407

bP

b-1

82

0

bP

b-6

36

3

Clo

neID

-1049

20

Clo

neID

-2213

41

Clo

neID

-22421

9b

Pb-7

348

bP

b-3

79

2b

Pb-3

412

bP

b-6

805

bP

b-0

90

9

bP

b-6

26

0b

Pb-6

710

Clo

neID

-2229

00

Clo

neID

-22247

3C

loneID

-223686

bP

b-1

81

3C

loneID

-222163

Clo

ne

ID-2

24143

bP

b-0

48

6

bP

b-3

56

5b

Pb-2

325

Clo

neID

-2214

75

bP

b-3

11

4b

Pb-5

845

bP

b-7

32

0b

Pb-7

214

bP

b-4

058

bP

b-3

88

7bP

b-7

27

7C

loneID

-2217

14

bP

b-2

006

bP

b-1

420

Clo

neID

-2224

99

bP

b-4

970

bP

b-8

80

9

Clo

neID

-2229

06

bP

b-1

965

bP

b-6

17

9b

Pb-4

595

bP

b-0

835

bP

b-8

07

0C

loneID

-2213

74

bP

b-0

171

Clo

ne

ID-1

05144

Clo

neID

-2233

26

bP

b-5

76

6b

Pb-4

725

bP

b-6

124

bP

b-7

29

2b

Pb-7

360

bP

b-9

244

bP

b-9

562

bP

b-6

485

bP

b-6

051

bP

b-1

909

Clo

neID

-223299

bP

b-4

814

bP

b-8

072

bP

b-2

460

bP

b-6

067

bP

b-0

050

bP

b-9

632

bP

b-6

495

bP

b-6

363

bP

b-9

680

Clo

neID

-224219

Clo

neID

-221341

bP

b-7

348

bP

b-3

412

bP

b-3

792

bP

b-6

805

bP

b-5

727

bP

b-7

881

bP

b-2

762

bP

b-3

852

bP

b-6

710

bP

b-7

561

bP

b-0

709

bP

b-4

721

bP

b-2

497

bP

b-6

288

bP

b-9

032

bP

b-5

516

Clo

neID

-223

233

bP

b-5

229

bP

b-0

780

bP

b-2

171

bP

b-3

519

bP

b-0

413

bP

b-6

063

bP

b-5

389

bP

b-8

449

bP

b-7

022

Clo

neID

-222

196

bP

b-0

486

bP

b-4

494

bP

b-2

757

Clo

neID

-221475

bP

b-5

845

bP

b-4

970

bP

b-4

318

bP

b-1

420

bP

b-2

006

Clo

neID

-222

499

bP

b-8

809

bP

b-0

621

bP

b-9

085

bP

b-0

171

Clo

neID

-221374

bP

b-8

070

bP

b-4

595

bP

b-0

835

bP

b-6

179

bP

b-1

965

bP

b-1

224

bP

b-9

868

bP

b-4

971

bP

b-8

754

Clo

neID

-222075

bP

b-6

239

bP

b-1

217

bP

b-9

660

bP

b-4

809

Clo

neID

-223220

Clo

neID

-221474

Clo

neID

-224112

Clo

neID

-224153

bP

b-9

732

bP

b-9

088

bP

b-3

170

bP

b-6

051

bP

b-6

485

bP

b-9

56

2bP

b-0

085

bP

b-1

909

Clo

neID

-223299

bP

b-4

814

bP

b-8

072

bP

b-2

460

bP

b-9

632

bP

b-0

34

9bP

b-6

067

bP

b-0

050

bP

b-6

49

5

bP

b-6

363

Clo

neID

-224219

bP

b-7

348

bP

b-6

805

bP

b-0

909

bP

b-3

79

2bP

b-3

412

bP

b-0

899

bP

b-3

852

bP

b-7

627

bP

b-6

26

0bP

b-6

710

bP

b-0

709

bP

b-7

561

bP

b-6

288

bP

b-2

49

7bP

b-4

721

bP

b-9

032

Clo

neID

-1050

44

Clo

neID

-223233

bP

b-5

516

bP

b-5

596

bP

b-7

395

bP

b-8

449

bP

b-0

413

bP

b-6

06

3bP

b-0

653

bP

b-3

519

bP

b-5

38

9bP

b-8

553

bP

b-0

78

0C

loneID

-222196

bP

b-7

022

bP

b-0

486

bP

b-3

603

bP

b-2

580

bP

b-8

854

bP

b-4

494

bP

b-8

462

bP

b-3

70

0bP

b-3

910

bP

b-5

845

Clo

neID

-222215

bP

b-6

578

bP

b-1

420

bP

b-4

318

Clo

neID

-2224

99

bP

b-4

970

bP

b-2

006

bP

b-8

319

bP

b-8

809

Clo

neID

-223857

bP

b-0

621

bP

b-4

753

bP

b-3

590

bP

b-0

171

Clo

neID

-221374

bP

b-8

070

bP

b-0

835

bP

b-6

17

9bP

b-4

595

bP

b-1

965

bP

b-4

971

Clo

neID

-222075

bP

b-1

217

bP

b-9

660

bP

b-4

809

Clo

neID

-224160

bP

b-6

485

bP

b-9

562

bP

b-6

051

bP

b-1

909

Clo

neID

-223299

bP

b-4

814

bP

b-8

072

bP

b-2

460

bP

b-0

349

bP

b-9

632

bP

b-0

050

bP

b-6

495

bP

b-6

067

bP

b-6

363

Clo

neID

-224219

bP

b-7

348

bP

b-3

412

bP

b-3

792

bP

b-3

852

bP

b-6

710

bP

b-0

709

bP

b-7

561

bP

b-4

721

bP

b-6

288

bP

b-2

497

bP

b-9

032

bP

b-5

516

Clo

neID

-223233

bP

b-7

395

bP

b-5

596

bP

b-0

780

bP

b-5

389

bP

b-6

063

bP

b-8

449

bP

b-3

519

bP

b-0

413

Clo

neID

-222196

bP

b-7

022

bP

b-0

486

bP

b-2

580

bP

b-8

854

bP

b-4

494

bP

b-5

845

bP

b-4

318

bP

b-1

420

bP

b-4

970

bP

b-2

006

Clo

neID

-222499

bP

b-8

809

bP

b-0

621

bP

b-0

171

Clo

neID

-221374

bP

b-8

070

bP

b-4

595

bP

b-0

835

bP

b-6

179

bP

b-1

965

bP

b-4

971

Clo

neID

-222075

bP

b-1

217

bP

b-9

660

bP

b-4

809

bP

b-9

562

bP

b-7

599

bP

b-6

485

bP

b-5

317

bP

b-8

580

bP

b-4

814

Clo

neID

-221773

bP

b-7

407

bP

b-1

807

bP

b-6

568

bP

b-0

091

bP

b-1

820

bP

b-0

349

bP

b-6

067

bP

b-0

050

bP

b-9

632

bP

b-6

495

bP

b-5

532

bP

b-5

516

Clo

neID

-223

233

bP

b-7

395

bP

b-5

596

Clo

neID

-222196

bP

b-7

022

bP

b-7

854

bP

b-8

854

bP

b-4

494

bP

b-2

580

Clo

neID

-221714

bP

b-4

058

bP

b-7

214

bP

b-3

887

bP

b-7

277

bP

b-4

971

Clo

neID

-222075

bP

b-4

809

bP

b-5

766

bP

b-4

725

bP

b-6

124

bP

b-9

244

bP

b-7

360

bP

b-7

763

bP

b-4

863

bP

b-4

067

bP

b-0

686

0 5 10

15

20

25

30

35

40

45

50

55

60

65

70

75

80

85

90

95

100

105

110

115

120

125

130

135

140

145

150

155

160

165

170

175

180

185

190

195

200

205

210

215

220

225

230

235

240

245

250

255

260

265

270

275

280

285

290

295

300

305


77

Fig

ure

3. (

cont

inue

d)

(E)

Chr

omos

ome

6H

bPb-

042

6b

Pb

-37

80

bPb-

051

9C

lon

eID

-104

934

Clo

neID

-22

196

1C

lone

ID-2

2352

9bP

b-35

86

bPb-

666

1b

Pb

-52

52bP

b-2

058

bPb-

775

5bP

b-39

21

bPb-

374

6

bPb-

970

2b

Pb

-37

22bP

b-5

698

Clo

neI

D-2

224

84bP

b-0

055

bPb-

475

0b

Pb

-00

18

Clo

neI

D-2

232

73

Clo

neI

D-2

215

14C

lon

eID

-222

306

Clo

neI

D-2

222

55bP

b-38

83

bPb-

125

6b

Pb

-83

47bP

b-3

230

Clo

neI

D-2

232

11bP

b-97

96

bPb-

590

3b

Pb

-57

78C

lone

ID-2

225

67

bPb-

412

5C

lone

ID-2

2260

0

bPb-

347

0C

lon

eID

-104

954

bPb-

314

4b

Pb

-24

10bP

b-9

285

bPb-

230

4b

Pb

-21

37bP

b-5

167

bPb-

286

3C

lone

ID-2

2368

7bP

b-93

49

Clo

neI

D-2

209

34C

lone

ID-2

225

19

bP

b-6

677

bPb-

040

3b

Pb

-46

26bP

b-1

621

Clo

neI

D-1

051

72bP

b-9

817

bPb-

714

6bP

b-10

29

Clo

neID

-223

721

bPb-

989

0bP

b-53

46

AxO

bPb-

227

6bP

b-04

26

bP

b-3

780

Clo

neID

-222

774

bPb-

220

9bP

b-05

19

Clo

neI

D-2

235

87C

lone

ID-2

235

29

bP

b-1

009

bPb-

719

3bP

b-35

86

bPb-

736

2b

Pb

-29

30bP

b-85

28bP

b-98

52

bP

b-5

275

bPb-

267

2b

Pb

-35

54bP

b-64

19bP

b-60

69

bPb-

074

2C

lone

ID-2

2137

3bP

b-74

67

bP

b-9

651

bPb-

027

1bP

b-81

50

bPb-

716

5bP

b-52

52

bPb-

775

5bP

b-66

61

Clo

neI

D-2

232

03bP

b-64

57

bP

b-3

427

bPb-

980

7b

Pb

-28

81C

lone

ID-2

2099

8C

lon

eID

-223

914

bPb-

024

5bP

b-79

98

bPb-

455

5C

lone

ID-2

2100

2bP

b-74

92

bPb-

591

0bP

b-37

46

bPb-

717

9bP

b-03

96

Clo

neID

-220

959

bPb-

602

3bP

b-24

64

bPb-

582

2bP

b-78

21

bP

b-0

934

bPb-

656

7b

Pb

-34

87bP

b-16

66bP

b-91

14

bPb-

475

0b

Pb

-25

93C

lon

eID

-222

255

Clo

neID

-22

151

4C

lone

ID-2

2230

6C

lon

eID

-221

627

Clo

neID

-22

110

5b

Pb

-67

35bP

b-37

73

bP

b-3

908

bPb-

306

8C

lon

eID

-222

508

bPb-

877

0b

Pb

-21

85C

lon

eID

-223

391

Clo

neID

-22

194

6b

Pb

-04

32bP

b-17

24

bPb-

417

8b

Pb

-04

51bP

b-19

82

bP

b-6

477

bPb-

347

0bP

b-92

14

bPb-

491

7bP

b-28

63

bPb-

667

7b

Pb

-45

65bP

b-29

40bP

b-31

44

Clo

neID

-222

519

bPb-

934

9bP

b-51

67

bPb-

534

6C

lone

ID-2

2372

1bP

b-02

98

bPb-

102

9bP

b-21

37

Clo

neID

-223

519

bPb-

230

4bP

b-16

21

bP

b-0

403

bPb-

7146

bPb-

338

1bP

b-46

26

AxB

bPb-

0426

bP

b-3

965

Clo

neI

D-2

2360

8bP

b-37

80C

lon

eID

-222

774

Clo

neI

D-2

2352

9bP

b-10

09C

lone

ID-2

2358

7bP

b-71

93bP

b-73

62bP

b-85

28bP

b-29

30b

Pb-

985

2bP

b-35

86bP

b-84

73bP

b-64

19bP

b-26

72b

Pb-

606

9bP

b-96

51bP

b-07

42b

Pb-

883

6C

lon

eID

-221

373

bPb-

5252

bP

b-6

661

bPb-

0245

Clo

neID

-22

391

4bP

b-20

58bP

b-98

07bP

b-34

27bP

b-64

57C

lon

eID

-221

002

bPb-

5910

Clo

neI

D-2

2338

6bP

b-37

46bP

b-71

79C

lon

eID

-220

959

bPb-

0396

bPb-

2464

bPb-

3120

bP

b-5

822

bPb-

9922

bPb-

6567

bPb-

3487

bPb-

9114

bP

b-1

666

bPb-

4750

bPb-

2593

bPb-

9082

bP

b-9

835

bPb-

9051

Clo

neI

D-2

2230

6C

lone

ID-2

2151

4C

lone

ID-2

222

55bP

b-33

09bP

b-67

35C

lone

ID-2

216

27

bPb

-27

55C

lon

eID

-221

105

bPb-

3068

bPb-

2185

bP

b-8

770

Clo

neI

D-2

2194

6C

lone

ID-2

2339

1C

lon

eID

-221

935

bPb-

0451

bPb-

0606

bPb-

4178

bPb-

9063

bP

b-6

477

bPb-

3470

bPb-

8371

bPb-

9413

bPb-

7446

bPb-

2940

bPb-

6677

bP

b-3

760

bPb-

286

3C

lon

eID

-222

519

bPb-

3144

bPb-

9349

bPb-

9285

Clo

neI

D-2

2372

1bP

b-02

98bP

b-21

37bP

b-46

26bP

b-04

03b

Pb-

230

4C

lon

eID

-105

090

bPb-

7146

bPb-

1621

bPb-

1029

bPb-

9817

bP

b-9

890

bPb-

241

0

AxP

bPb

-04

26bP

b-3

780

Clo

neID

-222

774

bPb

-10

09bP

b-7

193

bPb

-35

86bP

b-9

852

bPb

-29

30bP

b-8

528

bPb

-73

62bP

b-6

419

bPb

-60

69bP

b-2

672

bPb

-07

42bP

b-9

651

Clo

neID

-221

373

bPb

-52

52bP

b-6

661

bPb

-34

27bP

b-6

457

bPb

-28

81bP

b-9

807

bPb

-02

45C

lone

ID-2

2391

4bP

b-5

910

Clo

neID

-221

002

Clo

neID

-223

386

bPb

-37

46bP

b-7

179

bPb

-03

96C

lone

ID-2

2095

9bP

b-2

464

bPb

-58

22bP

b-6

567

bPb

-16

66bP

b-9

114

bPb

-34

87bP

b-4

750

bPb

-25

93bP

b-9

835

bPb

-90

51bP

b-9

082

Clo

neID

-221

514

Clo

neID

-222

255

Clo

neID

-222

306

bPb

-30

68C

lone

ID-2

2162

7C

lone

ID-2

2110

5bP

b-3

309

bPb

-27

55bP

b-8

770

bPb

-21

85C

lone

ID-2

2339

1C

lone

ID-2

2194

6bP

b-4

178

bPb-

045

1bP

b-0

606

bPb

-64

77bP

b-3

470

bPb

-90

63bP

b-2

940

bPb

-66

77bP

b-2

863

Clo

neID

-222

519

bPb

-31

44bP

b-9

349

Clo

neID

-223

721

bPb

-02

98bP

b-2

137

bPb

-46

26bP

b-2

304

bPb

-71

46bP

b-0

403

bPb

-16

21bP

b-1

029

Integrated

Clo

neI

D-2

220

53bP

b-0

572

bPb-

074

2bP

b-64

57

Clo

neID

-223

203

bPb-

342

7bP

b-28

81

bPb-

980

7bP

b-64

21

Clo

neID

-223

914

Clo

neI

D-2

233

86C

lon

eID

-221

002

Clo

neI

D-2

218

23bP

b-71

79

bPb-

537

9C

lon

eID

-223

115

bPb-

005

5bP

b-37

22

Clo

neID

-222

484

bPb-

970

2bP

b-56

98

bP

b-5

196

bPb-

908

2b

Pb

-98

35bP

b-90

51bP

b-27

55

bPb-

330

9C

lon

eID

-221

627

Clo

neI

D-2

211

05bP

b-43

69

bP

b-6

721

bPb-

4409

bPb-

306

8b

Pb

-83

47bP

b-12

56

bPb-

979

6bP

b-57

78

bP

b-5

903

Clo

neID

-222

567

bPb-

412

5b

Pb

-66

07C

lon

eID

-222

600

bPb-

877

0b

Pb

-21

85bP

b-06

06

bP

b-0

451

bPb-

4178

bPb-

085

7bP

b-90

63

bP

b-7

015

bPb-

6477

PxO

bP

b-9

051

bPb-

919

8b

Pb

-69

59b

Pb-

908

2

BxP

0 5 10

15

20

25

30

35

40

45

50

55

60

65

70

75

80

85

90

95

100

105

110

115

120

125

130

135

140

145

150

155

160

165

170

175

180

185

190

195

200

205

210

215

220

225

230

235

240

245

250

255

260

265

270

Chapter 5

78

Fig

ure

3. (

cont

inue

d)

(E)

Chr

omos

ome

7H

AxO

AxB

AxP

Integrated

PxO

BxP

bPb-

0043

2209

1210

5125

1051

67bP

b-75

5922

1337

2241

58bP

b-80

8422

3746

1048

47bP

b-07

14bP

b-25

95bP

b-85

5822

2470

2214

52bP

b-99

8622

1538

bPb-

3718

bPb-

0179

bPb-

2076

bPb-

4097

1051

21bP

b-49

29bP

b-78

63bP

b-19

94bP

b-80

43bP

b-46

3422

1830

2242

0222

2301

bPb-

6091

bPb-

3727

bPb-

7417

bPb-

4532

bPb-

7521

bPb-

9601

bPb-

9898

bPb-

0037

bPb-

8524

bPb-

7728

bPb-

6706

bPb-

9803

bPb-

1952

bPb-

4219

1049

10bP

b-79

52bP

b-52

94

1049

7910

5109

2211

9722

2266

bPb-

5599

bPb-

8956

bPb-

2097

bPb-

1770

bPb-

2379

bPb-

7437

bPb-

7603

bPb-

2188

bPb-

7915

bPb-

6110

bPb-

1596

bPb-

5747

bPb-

8074

bPb-

4321

bPb-

6170

bPb-

2718

bPb-

5259

2212

93bP

b-69

7622

2060

2209

12bP

b-89

21bP

b-22

1622

3528

bPb-

8272

bPb-

7038

bPb-

3732

bPb-

8161

bPb-

0043

bPb-

4064

bPb-

4886

bPb-

0956

2241

5822

3746

bPb-

5935

bPb-

2595

2213

37bP

b-11

40bP

b-92

0122

1452

2215

38bP

b-37

18bP

b-01

7922

2470

bPb-

4097

bPb-

6091

bPb-

7417

bPb-

6453

bPb-

3727

2210

49bP

b-21

91bP

b-90

27bP

b-54

94bP

b-24

78bP

b-18

06bP

b-71

8322

1061

2218

32bP

b-96

01bP

b-98

9822

2477

bPb-

9181

bPb-

6821

bPb-

5091

2209

64bP

b-03

66bP

b-28

66bP

b-12

09bP

b-78

35bP

b-98

03bP

b-77

28bP

b-85

24bP

b-00

37bP

b-67

06bP

b-45

41bP

b-45

97bP

b-85

68bP

b-35

89bP

b-11

05bP

b-84

60bP

b-42

19bP

b-79

52bP

b-19

52bP

b-89

00bP

b-52

94bP

b-55

97bP

b-21

8822

1197

bPb-

7437

bPb-

7603

bPb-

3323

bPb-

1770

bPb-

7915

bPb-

6819

2222

66bP

b-55

99bP

b-89

56bP

b-17

48bP

b-20

97

bPb-

8074

bPb-

1596

bPb-

6110

bPb-

5747

bPb-

0757

bPb-

6214

bPb-

0027

bPb-

9908

bPb-

2855

bPb-

0773

bPb-

4394

bPb-

1556

bPb-

0758

bPb-

9948

bPb-

2121

2210

34bP

b-03

7510

5003

2234

76bP

b-61

70bP

b-70

04bP

b-27

18bP

b-00

4322

0912

bPb-

3127

2220

6022

1293

bPb-

6976

bPb-

5259

bPb-

7038

bPb-

4064

bPb-

0108

bPb-

9729

bPb-

8161

bPb-

8921

bPb-

4886

2215

76bP

b-25

95bP

b-44

45bP

b-58

16bP

b-58

97bP

b-37

1822

2470

2215

38bP

b-01

79bP

b-97

8322

1452

bPb-

2076

bPb-

6029

bPb-

4097

bPb-

7417

bPb-

3727

bPb-

4584

bPb-

5769

2210

61bP

b-24

78bP

b-18

06bP

b-54

94bP

b-71

83bP

b-96

01bP

b-98

9822

2477

bPb-

5091

bPb-

6821

2209

64bP

b-03

66bP

b-12

09bP

b-28

66bP

b-78

35bP

b-85

24bP

b-67

06bP

b-77

28bP

b-00

37bP

b-98

03bP

b-45

41bP

b-79

52bP

b-42

19bP

b-19

52bP

b-35

61

bPb-

7150

bPb-

7399

bPb-

5296

bPb-

9912

bPb-

1847

bPb-

6386

2234

4422

2913

2229

8022

2465

2227

51bP

b-65

95bP

b-02

02bP

b-41

9122

1054

2241

88bP

b-49

2422

4212

bPb-

8860

bPb-

2855

bPb-

4071

bPb-

0773

bPb-

7628

bPb-

1336

1050

43bP

b-09

17bP

b-59

23bP

b-08

89bP

b-61

6722

2159

bPb-

0758

bPb-

3980

2209

49bP

b-16

31bP

b-79

83bP

b-09

81bP

b-88

3322

2528

bPb-

9948

bPb-

5548

bPb-

2121

bPb-

2897

bPb-

2693

bPb-

2854

bPb-

3226

2219

34bP

b-07

8322

1600

2219

0722

3518

bPb-

2718

bPb-

6170

2209

12bP

b-00

43bP

b-52

59bP

b-69

76bP

b-81

61bP

b-89

21bP

b-70

38bP

b-40

64bP

b-48

86bP

b-25

9522

1452

2224

7022

1538

bPb-

0179

bPb-

3718

bPb-

4097

bPb-

7417

bPb-

3727

bPb-

2478

2210

61bP

b-18

06bP

b-54

94bP

b-71

83bP

b-96

01bP

b-98

9822

2477

bPb-

6821

bPb-

5091

bPb-

0366

bPb-

2866

bPb-

7835

bPb-

1209

bPb-

0037

bPb-

7728

bPb-

6706

bPb-

9803

bPb-

8524

bPb-

4541

bPb-

4597

bPb-

1952

bPb-

4219

bPb-

7952

bPb-

2188

bPb-

7915

bPb-

1770

bPb-

7437

bPb-

8956

bPb-

5599

bPb-

7603

bPb-

2097

bPb-

7399

bPb-

5296

bPb-

9912

bPb-

7150

bPb-

1596

bPb-

5747

bPb-

8074

2234

44bP

b-41

91bP

b-02

0222

1054

2224

6522

2751

bPb-

0773

bPb-

7628

bPb-

1336

bPb-

5923

bPb-

0889

2221

59bP

b-09

17bP

b-61

67bP

b-07

5822

0949

bPb-

7983

bPb-

1631

bPb-

3980

bPb-

8833

2225

28bP

b-21

21bP

b-99

48bP

b-55

48bP

b-28

54bP

b-26

93bP

b-32

26bP

b-28

97bP

b-03

75

2220

60bP

b-68

68bP

b-69

76bP

b-89

21bP

b-97

29bP

b-37

32bP

b-40

64bP

b-80

84bP

b-81

61bP

b-08

44bP

b-07

14

bPb-

1994

bPb-

7863

2218

3022

1832

bPb-

2478

2210

61bP

b-18

06bP

b-28

28bP

b-54

94bP

b-51

72bP

b-61

56bP

b-25

33bP

b-50

74bP

b-03

24bP

b-89

39bP

b-13

60bP

b-67

47bP

b-58

5222

2477

bPb-

6821

bPb-

7835

bPb-

2866

bPb-

4541

bPb-

4597

bPb-

5126

bPb-

3227

bPb-

8396

bPb-

7915

bPb-

1770

bPb-

2188

bPb-

7437

bPb-

5599

bPb-

6975

bPb-

8956

2224

56bP

b-73

99bP

b-52

96bP

b-25

61bP

b-71

50bP

b-99

12bP

b-15

96bP

b-80

74bP

b-57

47bP

b-61

1022

3444

2241

2122

3782

2210

2722

1941

2230

15bP

b-41

91bP

b-02

0222

1054

2227

5122

2465

2234

00bP

b-06

39bP

b-88

60bP

b-28

55bP

b-43

89bP

b-51

88bP

b-88

67bP

b-16

69bP

b-61

86bP

b-17

67bP

b-77

3922

2295

bPb-

3145

1026

07bP

b-03

6422

0913

2221

60bP

b-08

89bP

b-09

1722

2159

bPb-

6167

bPb-

5923

bPb-

1336

1050

43bP

b-76

28bP

b-07

58bP

b-79

8322

0949

bPb-

3980

bPb-

1631

2225

28bP

b-88

33bP

b-55

48bP

b-99

48bP

b-32

32bP

b-58

98bP

b-28

54bP

b-28

97bP

b-26

93bP

b-32

2622

1034

bPb-

0375

bPb-

8157

bPb-

9971

bPb-

2188

bPb-

2379

bPb-

5597

bPb-

7915

bPb-

1770

bPb-

8956

bPb-

5599

bPb-

6819

bPb-

2097

bPb-

8213

bPb-

7603

bPb-

7437

bPb-

1748

bPb-

7686

bPb-

3227

bPb-

1079

bPb-

5768

bPb-

8005

bPb-

5747

bPb-

1596

bPb-

6110

bPb-

8074

bPb-

0757

bPb-

7150

bPb-

2561

bPb-

5296

bPb-

9912

bPb-

6386

bPb-

1847

bPb-

0202

bPb-

8658

bPb-

7181

bPb-

9662

bPb-

4191

bPb-

9329

bPb-

6595

bPb-

8901

bPb-

4488

bPb-

6214

bPb-

4743

bPb-

0027

bPb-

3055

bPb-

9908

bPb-

4394

bPb-

6166

bPb-

2328

bPb-

7983

bPb-

9944

bPb-

4090

bPb-

0917

bPb-

8778

bPb-

5923

bPb-

7628

bPb-

7345

bPb-

0981

bPb-

1336

bPb-

6626

bPb-

8833

bPb-

9866

bPb-

4552

bPb-

8103

bPb-

2693

bPb-

6109

bPb-

2854

bPb-

5099

bPb-

7882

bPb-

1232

bPb-

6476

bPb-

0375

bPb-

9884

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100

105

110

115

120

125

130

135

140

145

150

155

160

165

170

175

180

185

190

195

200

205

210

215

220

225

230

235

240

245

250

255

260

265

270

275

280

285

290

295

300

305

310

315

79

Chapter 6

QTL analysis in multiple interconnected barley doubled haploid populations in the presence of a reciprocal

translocation

A. Farré1,2, A.M. Casas3, L. Cistué3, I. Lacasa-Benito1, P Hedley5, M Macaulay5, WTB

Thomas5, I. Romagosa1,6, F.A. van Eeuwijk2 and J. Jansen2

Abstract

Multiple connected populations address broader diversity than biparental populations

which have been widely used for QTL analysis. The use of multiple connected

populations allows a more global comparison of the effects of all QTL alleles

segregating in the populations simultaneously and allows investigation of interactions

between QTL and genetic background. In this study, a new approach was developed for

QTL detection in a multi-population and a multi-environment analysis. Five

interconnected biparental doubled haploid (DH) populations of barley derived from

crosses between pure lines were used. Three of the populations have a common parent

which is known to carry a reciprocal chromosomal translocation between chromosomes

1H and 3H. Days do heading (DtH) and thousand kernel weight (TKW) will be used to

develop the methods. The QTL found for DtH and TKW are consistent with the results

of previous QTL studies. The integral approach used in this study provided a direct

comparison of the effects of the four parental alleles. Only for TKW was a direct effect

of the reciprocal translocation was found; DH lines carrying the reciprocal translocation

had a greater TKW than those with a standard chromosome arrangement.

Keywords Reciprocal translocation Barley Translocation breakpoint Connected

populations Quantitative trait locus

1Department of Plant Production and Forest Science, University of Lleida, Lleida, Spain; 2Biometris, Wageningen University and Research Centre, Wageningen, the Netherlands; 3Estación Experimental de Aula Dei, CSIC, Zaragoza, Spain; 5James Hutton Institute, Invergowrie, Dundee DD2 5DA, UK; 6Centre UdL-IRTA, University of Lleida, Lleida, Spain

Chapter 6

80

Introduction

In breeding programs most traits of agronomic interest display continuous variation due

to the contributions of many genes with small effects. Such genes are usually called

quantitative trait loci (QTL). Quantitative traits, also called complex traits in contrast to

simple Mendelian traits, are traits where the relation between genotype and phenotype

cannot be observed directly. Examples are yield, quality or some forms of disease

resistance. QTL mapping has been widely used during the last two decades thanks to the

abundance of molecular markers in combination with the development of powerful

methods for statistical analysis (Kearsey and Farquhar, 1998; Bernardo 2008, Zhu et al.

2008) implemented in user-friendly software (i.e. MapMaker/QTL (Lincoln and Lander

1990), QTLCartographer (Basten et al. 1999), MapQTL®5 (Van Ooijien 2004), Genstat

(Payne et al. 2011). QTL mapping tools are useful for dissecting complex traits and for

identifying favourable alleles in diverse germplasm, to estimate several genetic

parameters that underlie phenotypic variation, including the number of loci, the type and

magnitude of their effects, interactions between genes (epistasis), and gene-by-

environment interactions (Symonds et al. 2005). Understanding the response of QTLs in

different environments or genetic backgrounds can lead to the development of improved

crop varieties through marker-assisted selection (MAS) which is the most evident

application of QTL analysis together with QTL cloning. But while thousands of marker-

trait association studies have been conducted in many plant species for many traits

(Holland 2007), only a few QTLs have been cloned (Liu et al. 2002, 2003; Price 2006;

Salvi et al. 2005; Ramsay et al. 2011). Until recently mainly biparental populations

(derived from single crosses of two inbred lines) were used to detect and map QTLs in

plants. Genetic analysis of biparental populations only allows differentiation between

alleles for which the parents differ. In general unrelated parents were carefully selected

to maximise marker polymorphism and trait divergence, i.e., Oregon Wolfe barley

mapping population (Costa et al. 2001), barley crosses between wild and cultivated

varieties (Backes et al. 2003), winter and spring varieties (Laurie et. 1995; Hayes et al.

1993; Francia et al. 2004) or resistant and susceptible (Arru et al. 2003). As a result,

some QTLs explaining quantitative variability in the population can be missed because

only the effect of major genes can be studied in such biparental populations (Edwards et

al. 1992). Moreover, results based on biparental populations are based on a small part of

QTL analysis in multiple interconnected barley doubled haploid populations in the presence of a reciprocal translocation

81

the germplasm, results may not apply to other genetic backgrounds (Parisseaux and

Bernardo 2004). So, following this strategy only a small part of the total diversity

available to breeders is explored.

As an alternative, multiple connected biparental populations may be developed. These

are particularly interesting because: (i) the genetic variability addressed is increased, (ii)

they allow a global comparison of the effects of all QTL alleles segregating in the

populations simultaneously thereby increasing the power of QTL detection, but also

allowing the identification of the parental origins of favourable alleles, and (iii)

interactions between QTL and genetic background, which may be an indication of

epistatis, may be investigated (Muranty et al. 1997). For all these advantages, studies

involving connected populations have been reported in cereals. For example, in barley

Cuesta-Marcos et al. (2008a) used 281 doubled haploid lines derived from 17 F1

involving 14 different parental cultivars, to validate the effect of the main QTL

determining heading date. In maize, studies based on multiparental connected

populations were carried out to compare multiparental connected designs with

biparental populations with regard to MAS and phenotypic selection (Blanc et al. 2006,

2008). Here a diallel cross design consisting of six connected F2 populations, derived

from four parental inbreds, was used. Recently, Liu et al. (2010) used three connected

RIL populations derived from the crosses among three parents to find QTLs for the

number of spikelets per panicle and 1,000-grain weight in rice. Other more complex

populations have been proposed, for example, MAGIC (multiparent advanced

generation intercross, Cavanagh et al. 2008), NAM (nested association mapping; Yu et

al. 2008; Buckler et al. 2009) and AMPRIL (a multiparent recombinant inbred line

population, Huang et al. 2011). These studies require genome-wide a high density of

markers and use re-sequencing technology.

The aim of the present paper is to develop an approach for a multi-population and multi-

environment QTL analysis in the presence of a reciprocal translocation. To illustrate our

approach, we analysed days to heading (DtH) and thousand kernel weight (TKW) using

a large number of doubled haploid lines from the F1 of five crosses produced from

Chapter 6

82

different combinations of four parents, one of which was ‘Albacete’. DtH was selected

because is independent of the reciprocal translocation and TKW because it was the only

trait showing a significant positive effect of the reciprocal translocation in ‘Albacete’

(Farré et al 2012b). ‘Albacete’ is known to carry a reciprocal chromosomal

translocation between chromosomes 1H and 3H (Vazquez and Sanchez-Monge, 1987;

Lacasa-Benito et al. 2005; Farré et al. 2011; Farré et al. 2012). This complicates the

QTL analysis due to ‘pseudo-linkage’ between markers on chromosomes involved in

the interchange. Close to the translocation breakpoints recombination is suppressed

(Burnham, 1962; Sybenga, 1975) and, as a consequence, markers in those regions were

removed; see also Farré et al. (2011). The final linkage maps consist of the distal parts

of the chromosomes involved in the translocation (1HS-1HL and 3HS-3HL). The

genotyping was performed using Diversity Arrays Technology (DArT®). The DArT

markers were positioned on the barley chromosomes according to the barley consensus

map (Wenzl et al. 2006).


Plant material

Agronomic traits were evaluated on anther-culture derived DH lines of barley. The lines

were derived from five F1s obtained by crossing four parents: ‘Albacete’, ‘Barberousse’,

‘Orria’ and ‘Plaisant’. ‘Albacete’ is a landrace variety with a relatively long cycle and

an alternative growth habit. It is drought tolerant showing relatively stable grain yield

production under Spanish conditions. ‘Albacete’ carries a reciprocal translocation

between chromosomes 1H and 3H (Farré et al 2011; Farré et al. 2012a). ‘Barberousse’

is known for its good productivity and easy adaptation, although it is sensitive to

drought in Spain. ‘Orria’ is a Spanish variety of CIMMYT origin that is well adapted to

fertile, rainfed environments. ‘Plaisant’ shows good adaptation and has a high yield

under Spanish conditions. The vernalisation and photoperiod characteristics of the

parents are given in SEM_Table1. The allele representation within each population for

‘Albacete’, ’Barberousse’, ‘Plaisant’ and ‘Orria’ were 336, 166, 138 and 218

descendants, respectively.


83

Genotyping

Genomic DNA of the DH lines was extracted from fresh leaf tissue using the Qiagen

DNeasy 96 plant Kit. A genome wide scan was carried out using Diversity Arrays

Technology (DArT®) (www.diversityarrays.com). In a single assay, DArT uses

microarrays to detect DNA polymorphisms at several hundred genomic loci spread over

the entire genome. It is based on hybridising labelled genomic representations of

individual DNA samples on a micro-array, which contains a large number of DNA

fragments derived from the total genomic DNA of the species under consideration

(Wenzl et al. 2004). Polymorphisms are scored as the presence (= 1) or absence (= 0) of

hybridization to individual array elements. The locus designations used by Triticarte

Pty. Ltd. were adopted in this paper. DArT marker names consist of the prefix “bPb”,

followed by numbers corresponding to a particular clone in the genomic representation,

where b stands for barley, P for PstI (primary restriction enzyme used) and b for BstNI

(secondary restriction enzyme). For each DH population quality-filtered datasets were

prepared by removing markers and DH lines according to Farré et al. 2011. Individual

linkage maps were constructed for the three largest populations (A×B, A×P and P×O).

For A×B and A×P, linkage groups 1H and 3H were split in two as they carry the

reciprocal translocation (Farré et al. 2011). For P×O, 1H and 3H formed a single linkage

group, respectively. DArT markers were located on the barley chromosomes according

to the barley consensus map (Wenzl et al. 2006). The markers used for constructing the

consensus map were those which segregated in at least two mapping populations. DArT

markers located around the translocation breakpoints were removed according to Farré

et al. (2011) resulting in two sub-linkage groups for chromosome 1H and 3H (1HS-1HL

and 3HS-3HL).

Experimental design

Four field trials were carried out at two locations (Gimenells (41º 37’N, 0º 22’E, 248m,

dry, rainfed); Foradada (F; 41º 51’N, 1º 0’E, 407m, dry, rainfed) in North-Eastern Spain

(Catalonia) in two growing seasons (2008/2009 and 2009/2010). Details of the

environmental conditions are given in SEM_Table2. Experimental designs followed a

Chapter 6

84

latinized row and column alpha design with a single replication for most DH lines

augmented by four replicated checks (parents) that were randomly included in a

diagonal fashion along rows and columns. The experiments contained a total of 600

plots arranged in 30 rows and 20 columns, except Foradada-2008/2009 which contained

630 plots arranged in 15 rows and 42 columns. Plots consisted of eight rows, 4 m long

and 15 cm apart and were sown at a density of 300 seeds m2 and an accoding with

standard crop practise in terms of plant density, herbicide treatment and fertilizanty

rates.

Phenotyping

To illustrate our approach we analysed two traits: days to heading and thousand kernel

weight. Days to heading (measured as the number of days between 1st of January until

50% of spikes on a plot had extruding anthers) was selected because it is a major

selection criterion in all plant breeding programs of barley as it determines crop

adaptation. Besides that, it is a highly heritable trait with significant QTLs and its

biological basis has been well characterised in model plants (Arabidopsis; Greenup et

al. 2009) with many barley homologues identified (Higgins et al. 2010). None of the

major genes known to affect flowering time in barley are located in the region of the

reciprocal translocation (Laurie et al. 1995) so days to heading should be independent of

the reciprocal translocation. Thousand kernel weight (measured in grams) was selected

because it was the only trait showing a significant positive effect of the reciprocal

translocation in ‘Albacete’ (Farré et al 2012b).

Data analysis

The observations of each experiment (different site and year combinations) were

analysed by means of a mixed model using Genstat 14 procedures (Payne et al. 2011).

Spatial effects were eliminated by incorporating rows and columns in the random part

of the mixed model. We allowed the mixed model to have unequal variances for

populations, which made it possible to estimate the heritabilities of the traits for all

combinations of sites, years and populations separately. Finally, for each trait Best

Linear Unbiased Estimates (BLUEs) of the contributions of the genotypes were


85

obtained for further analysis. The BLUEs were subjected to QTL analysis. The BLUEs

were also used to calculate for each genotype the difference between the two locations,

the two years and the interaction between locations and years. These constrasts were

also subjected to QTL analysis.

QTL analysis

QTL analysis has been carried out using Genstat 14 (Payne et al. 2011). For all

individuals the probabilities associated with the descent states 0 (maternal allele) and 1

(paternal allele) at marker loci were obtained using the procedure

QIBDPROBABILITIES, based on the DArT genetic linkage map (Wenzl et al. 2006).

Here, maternal and paternal refer to the parents of the cross (F1) from which each DH

population was derived. The descent probabilities for individual j (= 1, 2 ... Ni) of

population i (= 1, 2 ... 5) at locus k were arranged in vectors p0k and p1k, respectively; k

= 1 ... M. Subsequently, the descent probabilities were used to calculate regressors xik,

accounting for allelic differences within populations (irrespective of the parents). Here,

xik= p0k – p1k if the corresponding individual belongs to population i and xik= 0,

elsewhere. For each marker, the regressors x1k, x2k ... x5k represent 4 degrees of freedom.

The regressors for the general (additive) effect of the four parents, denoted by apk (p = 1,

2, 3, 4), were obtained as follows:

a1k = x1k+x2k+x3k,

a2k = -x1k +x4k,

a3k = -x2k -x5k,

a4k = -x3k-x4k +x5k.

Parent 1 (‘Albacete’) is the mother of populations 1, 2 and 3, parent 2 (‘Barberousse’) is

the father of population 1 and the mother of population 4, parent 3 (‘Orria’) is the father

of populations 2 and 5, and finally parent 4 (‘Plaisant’) is the father of populations 3 and

4 and the mother of population 5. It should be noticed that , i.e. the

regressors for the general additive effects of the parents represent 3 degrees of freedom.

Differences in ‘fit’ between the sets of regressors {x1k, x2k ... x5k} on the one hand, and

the sets of regressors {a1k, a2k, a3k, a4k} are due to additive x genetic background

Chapter 6

86

interaction or specific additive effects, and may be an indication of epistasis (Jannink

and Jansen, 2001; Jansen et al. 2009).

Interval mapping was carried out using a mixed model. The mixed model accounted for:

(i) the presence of the reciprocal translocation in the populations that were derived from

‘Albacete’, (ii) differences between population means and (iii) allowed for

heterogeneous variances between populations. Tests for putative QTL were based on the

Wald statistic with the appropriate numbers of degrees of freedom. Initially a forward

selection of marker loci was carried out using a liberal threshold of 3.0 for minus the

logarithm of the p-value associated with the Wald statistic. Only the most significant

marker loci selected in this way were added to the set of cofactors used in the mixed

model. This was followed by backward elimination of the marker loci selected in the

previous step using a threshold of 3.5 (which conforms to the usual threshold obtained

by Li and Ji (2005) for this situation). It should be noticed that in a standard QTL

analysis the Wald statistics involves one degree of freedom for the numerator; here the

number equals three). In the output, contrasts between parents were presented as

differences from parent 1 (‘Albacete’) and appropriated standard errors were calculated.

The effect of the reciprocal translocation was tested by incorporating the effects of the

final set of cofactors obtained by backward elimination.

Results

Genetic map

A total of 364 previously mapped markers (Wenzl et al. 2006) were polymorphic in at

least two of the DH populations with between 75 (B×P) and 274 markers (P×O)

polymorphic in individual populations. No markers were segregating in all five

populations; 14 markers were polymorphic in four populations although the highest

number of polymorphic markers was found across three populations (171 markers). The

number of markers per chromosome varied between 30 (1H) and 86 (4H). The map

used in this study covered 1,111 cM for all seven chromosomes. Chromosomes 1H and

3H were split in two linkage groups due to the presence of the reciprocal translocation

(1HS-1HL and 3HS-3HL; Farré et al. 2011). The DArT markers located around the


87

translocation breakpoints were removed according to Farré et al. (2011). The greatest

gap was on chromosome 4H (64 cM).

Figure 1. Genetic linkage map. Map distances based on the barley consensus map (Wenzl et al. 2006). Linkage groups 1H and 3H were split in two sub-linkage groups: 1HS-1HL and 3HS-3HL.

Agronomic results

For DtH, Barberousse was on average the earliest and Albacete the latest parent, with a

difference of three days. For TKW, Albacete had on average the highest parental value

and Barberousse the lowest, with a difference of 3.1 g.

Means of the DH lines for DtH values ranged from 109.5 to 124.7 days at G9 and F10,

respectively. For TKW, the values ranged from 27.2 gr at G9 to 39.5 g at G10. For both

traits, the magnitude of the correlations varied across environments but not the sign

which is always positive for all the trials. The highest correlation coefficient (0.76) was

observed between G10 and F9 while the lowest (0.29) was between G9 and F10 which

could be explained by the extremely different mean values for DtH. However, for TKW

the lowest values were observed between G9 and the other environments (0.40 to 0.46).

The correlation between traits (DtH and TKW) for the various environments was -0.22

indicating that late flowering genotypes were associated with higher TKW.

1HS

0

2H

25

3HL

50

5H

75

7H

100

125

150

175

200

3HS 6H 1HL 4H

Pos

ition

(cM

)

Chromosome

Chapter 6

88

QTL analysis in single populations across environments

First a multi-environment QTL mapping was performed for the three largest populations

(A×B, A×P and P×O) for DtH and TKW to detect QTL and QTL×E interaction. The

results are presented in Table 1 and Figure 2. For DtH, the numbers of QTL detected

were 4, 2 and 4 for A×B, A×P and P×O, respectively. None of the QTL were present in

all three populations. In A×B, four QTLs were detected on chromosomes 2H, 3H, 5H

and 6H with Albacete alleles delaying flowering date. Only one QTL found on

chromosome 2H at 47 cM (consensus map of Wenzl et al. 2006) was detected in all four

environments (with effects ranging from -0.37 to -1.00 days). For A×P, two QTLs were

detected on chromosome 2H (68cM) and 3H (10 cM) with delayed flowering time for

Albacete alleles. Both are stable QTLs as they did not show any difference for additive

effects between trials. For P×O, four QTLs were determined on chromosomes 2H(2x),

3H and 5H. When more than one peak was found on a chromosome, the peaks were

well spaced; the two peaks on chromosome 2H were located at 49 and 122 cM. The first

one presented an effect in opposite directions for F10 and G9 showing QTL×E

interaction. The delay of flowering time in F10 is due to the Orria allele and in G9 due

to the Plaisant allele. Apart from this QTL all the others did not show any difference

between trial for additive effects (stable QTLs). The QTLs on 2H (49 cM) and 5H (127

cM) coincide with the ones detected in A×B population.

For TKW, QTLs were only detected in A×B and P×O. In A×B, only one QTL was

detected on 3H chromosome with the Barberousse allele giving an increasing of TKW.

In P×O, four QTLs were found: on chromosomes 3H, 5H(2x) and 6H. The QTLs on 3H

(97 cM) and 5H (120 cM) showed effects that were opposite to the effects for the other

QTLs in which Plaisant alleles gave an increase of TKW.

Table 1. QTLs, their locations and effects for DtH and TKW from the three DH populations (A×B, A×P and P×O) for 4 trials in Gimenells (G) and Foradada (F), 2009 and 2010 (Pop = population; CR = chromosome; se = standard error; additive effect: a positive value means that the second parent allele (B, P or O) increases the trait; the chromosome locations were referred to Wenzl et al. 2006).


89

Tra

it

Pop

C

R

cM

Mar

ker

-Log

10(P

) A

ddit

ive

effe

ct (

se)

F10

F

9 G

10

G9

DtH

A

×B

2H

47

bP

b-48

77

9.48

-0

.37

(0.1

41)

-0.8

8 (0

.137

) -0

.79

(0.1

30)

-1.0

0 (0

.175

)

3H

19

bPb-

9745

5.

46

-0.0

6 (0

.160

) -0

.55

(0.1

55)

-0.7

7 (0

.147

) -0

.70

(0.1

98)

5H

12

7 bP

b-44

94

6.02

-0

.31

(0.1

47)

-0.4

2 (0

.142

) -0

.52

(0.1

35)

-0.0

8 (0

.182

)

6H

64

bPb-

5822

4.

41

-0.1

0 (0

.142

) -0

.62

(0.1

38)

-0.4

3 (0

.131

) -0

.78

(0.1

77)

A×

P

2H

68

bPb-

0220

6.

63

-0.6

4 (0

.124

) -0

.64

(0.1

24)

-0.6

4 (0

.124

) -0

.64

(0.1

24)

P

×O

3H

10

bP

b-99

45

5.52

-0

.58

(0.1

24)

-0.5

8 (0

.124

) -0

.58

(0.1

24)

-0.5

8 (0

.124

) 2H

49

bP

b-69

92

10.7

1 0.

75 (

0.20

2)

0.29

(0.

145)

0.

16 (

0.15

9)

-0.8

1 (0

.200

)

2H

122

bPb-

1266

4.

25

0.62

(0.

154)

0.

62 (

0.15

4)

0.62

(0.

154)

0.

62 (

0.15

4)

3H

66

bP

b-24

40

4.11

0.

58 (

0.14

6)

0.58

(0.

146)

0.

58 (

0.14

6)

0.58

(0.

146)

5H

127

bPb-

4494

6.

92

-0.7

3(0.

137)

-0

.73(

0.13

7)

-0.7

3(0.

137)

-0

.73(

0.13

7)

TK

W

A×

B

3H

1 bP

b-55

55

4.31

0.

73 (

0.34

0)

1.27

(0.

366)

2.

01 (

0.40

6)

0.77

(0.

375)

A

×P

-

- -

- -

- -

- P

×O

3H

97

bP

b-67

22

5.08

1.

08 (

0.24

2)

1.08

(0.

242)

1.

08 (

0.24

2)

1.08

(0.

242)

5H

1 bP

b-64

85

10.1

0 -1

.67

(0.3

62)

-1.8

2 (0

.371

) -2

.48

(0.3

55)

-0.9

6 (0

.285

)

5H

120

bPb-

7854

8.

33

1.44

(0.

245)

1.

44 (

0.24

5)

1.44

(0.

245)

1.

44 (

0.24

5)

6H

68

bP

b-56

98

7.82

-1

.27

(0.2

24)

-1.2

7 (0

.224

) -1

.27

(0.2

24)

-1.2

7 (0

.224

)

Chapter 6

90

Figure 2. Example of multi-environment QTL analysis using the data from P×O population for 4 trials in Gimenells (G) and Foradada (F), 2009 and 2010 which was analyzed using Genstat 14 ((a) DtH and (b) TKW). Top panel shows the genome-wide profile, the blue line indicates the profile of –log10 (P-value) for composite interval mapping scan where test is for QTL expression in at least one environment. The red horizontal line shows the threshold value for significance. Low panel shows the representation of QTL allele effects in individual environments. Blue and yellow indicate the size and direction of the QTL effect in each environment for the first and the second parent, respectively. The green line at the top shows the significance for the overall test on QTL presence in the upper panel

10

1H 3H 5H 7H

QTL effects

G9

G10

F9

F10

0

4

8

2H 6H

7H 6H

2

5H 4H 3H 2H

4H

6

1H

Env

ironm

ents

Chromosomes

-log

10(P

)

(a)

p

1H 3H 5H 7H

QTL effects

G9

G10

F9

F10

2

4

6

10

2H 6H

7H

8

6H 5H 4H

4H

3H 2H

0

1H

-log

10(P

)

Chromosomes

Env

ironm

ents

(b)


91

QTL analysis across environments

For the multi-population QTL analysis across environments, the data from the five

populations and the seven chromosomes were used together to detect QTLs using the

overall mean for each genotype from the BLUEs obtained for each trial and the contrast

between locations, years and the interaction (Table 2).

For DtH, a total of 4 QTLs were detected. Three were found using the mean and the

other one was detected using the contrast between locations and years. In the first case,

all three QTLs showed negative additive effects for the three parental alleles (ranged

from -0.09 to -0.80 days) indicating an early flowering time compared to Albacete

allele. The QTL with the biggest effect was located on 3H at 10 cM. In the second case,

one peak was found on chromosome 2H at 148 cM. For the contrast between the two

locations, compared to Albacete the other parental alleles had negative effects (-0.01 to

-1.75 days). For the contrast between the two years, Barberousse and Plaisant had

positive parental allele effects whereas Orria showed earlier flowering time.

For TKW, two QTL was detected for the overall mean one chromosomes 5H at 17 cM.

In this case the effect was highly dependent on the parental allele: two increasing TKW

alleles (0.44 to 1.10 g) were specific to Plaisant and Barberousse and one decreasing

TKW allele (-0.96 g) came from Orria. No QTL×E interaction was found for TKW. No

QTLs were found for both traits in the same position.

Chapter 6

92

Table 2. Comparison of QTLs for DtH and TKW using multi-population multi-environment analysis (CR= chromosome; the chromosome location were referred to Wenzl et al. 2006; additive effect: a positive value means that the parent allele increase the trait compared to Albacete; se = standard error; G vs F = contrast between Gimenells and Foradada; 09 vs 10 = contrast between 2009 and 2010).

Effect of the reciprocal translocation

For the populations in which Albacete was one of the parents (A×B, A×P and A×O), the

presence of the reciprocal translocation was included in the QTL analyses to check if

the reciprocal translocation had an effect on DtH and TKW. Table 3 shows that there

was no evidence of a significant effect of the reciprocal translocation on DtH but for

TKW the lines carrying the reciprocal translocation showed higher TKW than the ones

without it (0.47 to 2.19 g). A positive additive effect of the reciprocal translocation was

found in F9, F10 and G10 for TKW.

Table 3. Estimates of the effects of the reciprocal translocation using the data from A×B, A×O

and A×P populations (se = standard error).

Trait -log10(P) RT vs no RT (se)DtH F9 0.487 0.27 (0.275)

F10 0.323 -0.17 (0.245) G9 0.148 -0.12 (0.337) G10 0.251 0.16 (0.272)

Mean 0.024 0.02 (0.244) PCA1 0.105 -0.00 (0.005)

TKW F9 5.187 2.16 (0.479) F10 5.750 2.19 (0.459) G9 - - G10 0.349 0.47 (0.616)

Mean 3.331 1.39 (0.396) PCA1 - -

Trait mm CR cM -log10(P) Parental additive effects (se)

Barberousse Orria Plaisant DtH Mean bPb9925 2H 64 6.04 -0.77 (0.166) -0.09 (0.202) -0.43 (0.149)

bPb9945 3H 10 9.24 -0.50 (0.134) -0.63 (0.194) -0.79 (0.125) bPb5596 5H 101 4.23 -0.58 (0.209) -0.80 (0.211) -0.37 (0.140) G vs F bPb1986 2H 148 7.14 -0.01 (0.262) -1.75 (0.159) -0.16 (0.206) 09 vs 10 bPb1986 2H 148 4.60 0.03 (0.243) -1.30 (0.347) 0.05 (0.235) interaction - - - - - - -

TKW Mean bPb7407 5H 17 7.31 1.10 (0.298) -0.96 (0.339) 0.44 (0.281) bPb-3512 4H 68 4.52 1.21 (0.272) 0.59 (0.338) 0.11 (0.253) G vs F - - - - - - - 09 vs 10 - - - - - - - interaction - - - - - - -


93

So far the general additive effects of parents were estimated. Specific additive effects

were estimated to analyse background interaction. No interactions between QTL and

genetic background were found.

Discussion

In the Mediterranean climate, characterized by low rainfall, high temperatures and high

light intensity leading to high evaporation, it is important to develop cultivars well

adapted to drought-prone conditions by improving characters related to yield. The

differences observed across environments for DtH and TKW can be attributed to

differences in climatic and other environmental conditions, especially differences in

rainfall. Usually, Foradada is colder and wetter than Gimenells. G9 was the earliest to

flower (12-30 April) whereas F10 the latest (2-14 May). The lowest values for both DtH

and TKW were found in G9, whereas the highest values were obtained in F10 and G10

for DtH and TKW, respectively. The main differences between years and locations were

due to the distribution of rainfall during the growth cycle. During the grain-filling

period (May-June), 2010 had a higher cumulated rainfall compared with 2009 which

could explain the higher TKW values obtained in 2010. Besides, the grain-filling period

was longer in 2010 than in 2009 (40 and 32 days, respectively). This difference in the

days of grain-filling, combined with limited rainfall and higher temperatures could

explain the low TKW values obtained for G9 (27 g) compared to the other

environments (30, 36 and 39 g for F9, F10 and G10, respectively).

The four parents (‘Albacete’, ‘Barberousse’, ‘Orria’ and ‘Plaisant’) used in the present

study show differences in the vernalization and photoperiod genes (Table 1,

supplementary material). All of them are winter varieties with a full or partial

vernalization requirement, performing similar when sown in autumn. Under these

conditions, ‘Albacete’ shows slightly later heading dates than the other parents (Igartua

et al. 1999). Under winter or spring sowing conditions, ‘Barberousse’ and ‘Plaisant’ are

clearly delayed. So, under the conditions of the experiments carried out in this study

major effects of flowering genes cannot be expected.

Chapter 6

94

It is known that genetic variation for genes controlling flowering time has provided

adaptation to different environments maximizing grain yield in cereal varieties

(Cockram et al. 2007). The genetic factors determining flowering time in barley have

been exhaustively studied and can be divided into: photoperiod-responsive genes (day

length), vernalization-responsive genes (response to a low temperature period to induce

transition from vegetative to reproductive stage) and ‘earliness per se’ genes (plant

response to a temperature sum over a certain period) (Boyd et al. 2003). In the QTL

analysis for each population separately, no QTLs were common among all three

populations. A×B and P×O had two QTL in common and A×B and A×P had one. The

most significant QTL for DtH was located on 2HS at 47-49 cM. By comparing genetic

maps (Wenzl et al. 2006; Cuesta-Marcos et al. 2008a; Close et al. 2009; Aghnoum et al.

2010) we assumed that this QTL corresponded to the location of PpdH1, one of the

major genes responsible for photoperiodic response expressed under long days (Laurie

et al. 1995; Turner et al. 2005; Sameri et al. 2011; Borràs-Gelonch et al. 2012). Yet, in

another study in the Mediterranean area, using a large panel of genotypes, Comadran et

al. (2008) concluded that under autumn sowing and latitudes under 43ºN it is unlikely

that PpdH1 might be effective. In P×O, PpdH1 had an opposite effect depending on the

environment. In F10 the delay of flowering time is due to ‘Orria’ allele whereas in G9 is

because of ‘Plaisant’. Similar findings were reported for the ‘SBCC145’×’Beatrix’

population (Ponce-Molina et al. 2012). They found an effect of this gene in an autumn

sowing with the insensitive allele (‘Beatrix’) conferring earliness; the effect changed in

winter sowing where the sensitive allele (‘SBCC145’) led to earlier flowering. This

QTL was also found in other studies using ‘Scarlett’×’ISR42-8’ (Wang et al. 2010) and

‘Steptoe’×’Morex’ (Borràs-Gelonch et al. 2012). An interesting finding was observed

for PpdH1 in A×B population in which ‘Albacete’ allele somewhat delayed flowering

time. However, both parents carry the dominant, long photoperiod responsive allele,

with the same polymorphism in the SNP that is used to differentiate the

dominant/recessive alleles (Turner et al. 2005). This result suggests that, there may be

more alleles for PpdH1. Resequencing the PpdH1 gene, Jones et al. (2008) identified 83

polymorphisms in a set of 266 barley accessions (194 European landraces and 72 wild

barley accesions). Among them 10 Spanish landraces were present. Although they carry


95

the dominant, long photoperiod responsive SNP allele they show other polymorphisms

along the PpdH1 gene which could be related with different phenotypic effects.

The other common QTL was detected on 5HL at 127 cM , where is located Vrn-H1, a

major gene which determines the vernalization requirement (Laurie et al. 1995;

Trevaskis et al. 2003; Cuesta-Marcos et al. 2008a,b). In our study, ‘Barberousse’ and

‘Plaisant’ are two typical winter varieties with full vernalization requirement as they

carry a recessive allele at vrnH1 and a dominant allele at VrnH2. In contrast, ‘Albacete’

and ‘Orria’ carry an intermediate (VRNH1-4) allele, which has been found to be

associated with a reduced vernalization requirement (Casao et al. 2011). In P×O, ‘Orria’

alleles conferred earliness. Different results were obtained in A×B population in which

‘Albacete’ alleles delayed flowering time. The flowering difference in A×B is between

0.16 to 1 day whereas in P×O is 1.5 days. For A×B and A×P, the common QTL was

found on 3HS at 10 cM, which we predict to be in the region of QHea.S42-3H.a (von

Korff et al. 2006). A QTL on chromosome 2H (122 cM detected in P×O) is in the same

region that a QTL found in two association mapping studies (Comadran et al. 2011;

Wang et al. 2012). Other QTLs such as that found on 3H (66 cM detected in P×O) or

6H (64 cM detected in A×B) could be specific to backgrounds of these populations.

Concerning TKW, no QTL were found in common between populations, although the

greatest number of QTL was found in the P×O population. Two other QTL on 5H (120

cM) and 6H (68 cM) are in similar regions to those reported by von Korff et al. (2008)

in the ‘Tadmor’ × ‘ER/Apm’ population.

Until recently the populations used to detect and map QTLs in plants were biparental

populations which have been widely employed by selecting two contrasting parents to

guarantee marker polymorphism and trait divergence (e.g. Backes et al. 2003). This

approach is not particularly applicable to plant breeding because QTLs can be missed as

they do not segregate in the particular cross. Nowadays, the development of multiple

connected populations for QTL analysis is increasing because it: (i) improves the power

to detect QTL and the accuracy of the estimation of their effects and positions; (ii)

increases variability addressed; (iii) permits direct comparison of the epistatic

Chapter 6

96

interactions between parental alleles at specific genome regions across genetic

backgrounds (Rebaï et al. 1997; Verhoeven et al. 2006; Blanc et al. 2006, 2008; Cuesta-

Marcos et al. 2008a; Liu et al. 2010). For that reason, it is necessary to develop new

QTL mapping methodologies for populations derived from more than two parents due

to the fact that most current statistical methods developed for QTL mapping are based

on bi-parental populations (Hackett 2002).

In this study, a new approach was developed for QTL detection in multi-population

analysis in the presence of a reciprocal translocation. This approach was applied using

DtH and TKW providing us with the opportunity to directly compare general additive

effects among four parental alleles. In this paper we mainly looked at the contrast of

Albacete with the other parents involved in creating the populations. For DtH, three

major QTLs, whose positions agree with previously studies, were found at the following

locations: on chromosome arm 2HS at 64-72 cM in the region of Eam6, identified as the

main heading date QTL in Mediterranean conditions (Cuesta-Marcos et al. 2008a,b; von

Korff et al. 2008; Comadran et al. 2011; Wang et al. 2012); on chromosome 3HS at 10

cM, which we predict to be in the region of QHea.S42-3H.a (von Korff et al. 2006) and

finally on chromosome 5HL at 101 cM, in the region of a minor QTL found in ‘Beka’ ×

‘Mogador’ (Cuesta-Marcos et al. 2008b). For TKW, two QTLs were found. One on the

short arm of chromosome 5H could be related to that on detected in

‘TX9425’×’Franklin’ (Wang et al. 2010b) and another one on the chromosome arm

4HS at 68 cM which corresponds with the QTL found by Teulat et al. (2001). QTLs

only found in the present study could be specific to one environment or, when detected

across environments, specific to the genetic backgrounds employed (i.e. for DtH, the

QTL found on chromosome 2HL at 148cM). None QTL were found for both traits at

the same position.

The results obtained when we included the presence of the reciprocal translocation in

the QTL analyses are in agreement with the results obtained by Farré et al. (2012b) in

which the reciprocal translocation affected only TKW. Other studies in

‘Blenheim’×’E224/3’ detected QTL in the region of the translocation (Thomas et al.


97

1995; Powell et al. 1997). DH lines carrying the reciprocal translocation had a greater

TKW than those with a standard chromosome arrangement. Identifying the regions that

improve traits related to yield (i.e. TKW) allows the breeders to use marker-assisted

selection for the introgression of favourable alleles into their germplasm (in our case the

‘Albacete’ haplotype). All genes present in the interstitial zone of a translocation

heterozygote are tightly linked due to the suppression of genetic recombination, and as a

consequence they can be transferred as a block to other backgrounds. In breeding

programs, the use of hybrids derived from one parent carrying a reciprocal translocation

in breeding programs could lead to problems in seed production as a consequence of

semi-sterility. Although semi-sterility disappears once the individuals become

homozygous for the translocation.

Acknowledgments


(Project AGL2011-30529-C02-02 and the Agrogenomics CONSOLIDER Center). The

James Hutton Institute is supported by the Scottish Government Rural and Environment

Science and Analysis Services (RESAS) Division.

Chapter 6

98

SUPPLEMENTARY MATERIAL

Table 1. Summary of the vernalization and photoperiod gene structure of the parents used in the

production of the doubled haploid populations.

Table 2. Means of temperature (T) and cumulated rainfall (R) during the months of the growth cycle

of the four trials: F9= Foradada 2008/2009, F10= Foradada 2009/2010, G9= Gimenells

2008/2009 and G10= Gimenells 2009/2010 (http://xarxes.meteocat.com).

Growth type

HvFT3 (PpdH2;1H)

SNP22 (PpdH1;2H)

HvZCCT (VrnH2;4H)

HvBM5 (VrnH1;5H)

HvFT1 (VrnH3;7H)

‘Albacete’ Facultative dominant dominant dominant intermediate recessive ‘Barberousse’ Winter recessive dominant dominant recessive recessive ‘Orria’ Facultative recessive recessive dominant intermediate recessive ‘Plaisant’ Winter recessive dominant dominant recessive recessive

Trial Nov Dec Jan Feb Mar Apr May June July Total

F9 R (mm) 33.8 30.6 50.6 34.6 52.2 115.2 9.4 29.5 28.7 384.6 T (ºC) 5.4 3.1 3.5 4.9 8.1 10.2 17.0 21.6 24.1 10.9

F10 R (mm) 10.0 67.8 61.6 32.6 64.1 14.6 54.0 102.1 4.9 411.7 T (ºC) 8.3 3.7 2.8 3.9 6.6 11.3 13.7 18.8 24.4 10.4

G9 R (mm) 23.6 25.6 21.6 13.6 31.0 90.4 8.6 16.4 31.2 262.0 T (ºC) 6.8 4.4 4.4 6.8 9.8 12.1 18.9 22.9 24.6 12.3

G10 R (mm) 5.5 45.5 65.8 26.7 38.4 19.1 27.3 54.3 0.2 282.8 T (ºC) 10.4 5.5 5.1 5.7 8.8 13.2 15.8 20.3 25.5 12.3

99

Chapter 7

General discussion

Alba Farré

Breeding programs in Mediterranean environments are focused on the development of

varieties with high yield and yield stability across environments. However, crop

productivity is limited by drought, one of the most important abiotic stress factors in the

Mediterranean basin (Araus et al. 2003). A Spanish barley variety, ‘Albacete’, which is

drought tolerant and shows adaptation to low-yielding sites was the basis of the present

thesis. ‘Albacete’ was selected because it is an extensively cultivated variety in the

poorest Spanish areas. It is known to carry a reciprocal translocation between

chromosomes 1H and 3H without apparent loss of agronomic value. One of the main

objectives of the present thesis was to investigate whether the reciprocal translocation

has a positive effect on drought tolerance and other traits that make it worth to introduce

genes in the vicinity of the translocation breakpoints into the barley germplasm.

Balanced chromosomal rearrangements such as reciprocal translocations or inversions

seem to be the most common rearrangements in plants (see interchanges in individual

species in the summary by Burnham, 1956, pp.459-522) which not always produce

phenotypic effects either in the heterozygous or homozygous state, other than reducing

heterozygote fertility as a result of duplications and deficiencies. Their maintenance

largely depends on their effects upon two properties: (i) the survival of individuals and

(ii) their fertility (Rees 1961). Wallace (1959) postulates that at the margin of a species

distribution, a translocation heterozygote with one of the better marginal genotypes may

have a relative advantage that compensates for the expected semi-sterility. Furthermore,

the semi-sterility disappears once the individuals become homozygous for the

translocation, i.e. once a pure line is produced. Deleterious effects may arise when a

breakpoint occurs within genes, generally disrupting gene functions; this is called a

‘position effect’. The best established example of a position effect in plants is in

General Discussion

100

Oenothera and involves the factors Ps (broad red and narrow green stripes on the sepals)

and Pr (red or rubricalyx); the translocation of a segment carrying the factor for broad

red calyx stripes (Ps) to a new position resulted in variegated patches of red (Pr). When

the locus was transferred back to the normal chromosome by crossing-over, the normal

phenotype was restored. (Catcheside, 1947). Other examples were found in Drosophila

(Ephrussi and Sutton, 1944; Lewis, 1950; Muller, 1954) and maize (Brink, 1932, 1954;

Roberts, 1942; Jones, 1944; McClintock; 1951, 1953).

The emergence of new species is often accompanied by structural chromosome changes

(Stebbins, 1971; Levin, 2002) which have played an important role in plant evolution

showing adaptive features of many natural populations. For instance, some species of

the genus Clarkia are notorious for a high frequency of translocation heterozygotes (C.

williamsonii (Wedberg et al. 1968); C. amoena (Snow, 1963); C. unguiculata (Mooring,

1958); C. exilis (Vasek, 1960); C. elegans (Lewis, 1951); C. dudleyana (Snow, 1960)).

The frequency of translocation heterozygotes in wild populations of Clarkia

williamsonii was found to be strongly correlated with habitat; heterozygotes are

abundant in populations in foothill woodlands and infrequent in populations at higher

elevations in the yellow pine forest. The constancy of the distributions of heterozygotes

strongly suggests that they have an adaptive role in populations (Wedberg et al. 1968).

This adaptive role has not only been studied in plants but also in other species like the

yeast Saccharomyces cerevisiae. Colson et al. (2004) investigated the effect of a

reciprocal translocation involving chromosomes VI, VII and XVI on the whole

organism’s evolutionary fitness. They found that this naturally occurring rearrangement

had the potential to provide a selective advantage in certain environmental conditions.

These results support the idea of chromosomal evolution involving fixation of major

rearrangements by natural selection. In barley, Konishi and Linde-Laursen (1988)

identified four Ethiopian cultivated landraces carrying a reciprocal translocation with

the translocation breakpoints at the centromere region involving chromosomes 2H and

4H, suggesting a common origin.

General Discussion

101

An interesting example is given by the T5B:7B-1 translocation which is frequent in

hexaploid wheat. It was first identified in French bread wheat (T. aestivum ‘Cappelle-

Desprez’; Riley et al. 1967) and was found later in many other varieties of T. aestivum

(Baier et al. 1974; Bourgeois et al. 1978; Seal, 1982; Vega and Lacadena 1983; Lange et

al. 1987; Schlegel and Schelgel 1989; Friebe and Gill 1994; Hohmann et al. 1996;

Schlegel 1996). Its broad distribution can result from selective advantages of rearranged

genotypes in diverse environmental conditions which may have significant breeding

potential (Miura et al. 1992; Law and Worland 1997). For instance, Law and Worland

(1997) indicate that the 5BS-7BS translocation was responsible for a substantial part of

the adult plant yellow rust resistance of these varieties although it cannot be solely

responsible for the resistance. These authors suggest that the gene(s) involved in

resistance to yellow rust are closely linked to the translocation breakpoints adding an

important attribute to the translocation favouring its selection. They also found some

indication for a yield advantage associated with the 5BL arm. Yasumuro et al. (1998)

suggest that most commercial bread wheat cultivars inherited translocations from their

landrace ancestors; the maintenance of these translocations in landraces and their

transmission to commercial varieties may reflect the significant breeding potential of

translocated chromosomes. A reciprocal chromosomal transposition in Brassica napus

between interstitial homeologous regions on linkage groups N7 and N16 gave

significantly higher seed yields (Osborn et al. 2003).

In the present study, the agronomic effects of the presence of the reciprocal

translocation on some interesting agronomic traits (associated to development, yield and

yield components and architecture traits) were tested using a mixed model procedure

dividing a set of 248 doubled haploid lines in two groups (carrying or not the reciprocal

translocation) (Chapter 4). A highly significant main effect of the translocation was

obtained for TKW; no significant main effects could be detected for other agronomic

traits. It has been hypothesized that the high level of farmer’s acceptance of ‘Albacete’

particularly for semi-arid rainfed areas may be due to the presence of this translocation.

However, the adaptation to low-yielding sites cannot be attributed to this chromosomal

structural change alone.

General Discussion

102

Plant accessions carrying chromosome rearrangements such as translocations have been

identified by the resulting partial pollen and seed sterility and by the apparent linkage of

genes whose normal loci are on separate chromosomes (i.e. Jáuregui et al. 2001).

Special interest resides in the identification of chromosomes involved in the

interchanges and determination of the translocation breakpoints as it will provide new

information on the origin of chromosomal rearrangements. It will also allow physical

mapping of genes involved in the translocation on the chromosomes. These can be

achieved by a combination of cytogenetics and molecular genetics (Chapter 3). The

translocation breakpoints on 1H and 3H chromosomes in the barley variety ‘Albacete’

overlaps with duplicated segments between chromosomes Os01 and Os05 in rice

derived from ancestral duplications within the grass family (Guyot and Keller 2004;

Thiel et al. 2009). Among other causes the original interchange may have originated

from a crossing-over between duplicated segments in non-homologous chromosomes

(Burnham, 1956). Identification of structural changes is crucial in utilizing genetic pools

of wild and cultivated varieties in breeding programs (Badaeva et al. 2007). Due to the

suppression of genetic recombination, the genes in the interstitial zone of a translocation

heterozygote are linked and can be transferred as a block to other backgrounds. So,

chromosome segments carrying the reciprocal translocation are worth to be transferred

in the barley germplasm. The time needed to incorporate favourable alleles into the

germplasm can be reduced due to the development of specific molecular markers.

The incorporation of molecular technologies in plant breeding programs allows linkage

analysis of agronomically important traits. For that purpose, linkage map construction

using data from molecular markers is an indispensable tool. Major complications arose

in populations based on reciprocal translocation heterozygotes as recombination

between loci around the translocation breakpoints is suppressed (Burnham, 1962;

Sybenga, 1975). Consequently, markers in these regions become ‘pseudo-linked’. In

order to disentangling this ‘pseudo-linkage’ a novel statistical-genetic approach was

developed making use of a high-quality consensus map of ‘normal’ barley (Wenzl et al.

2006) (Chapter 2). An alternative study investigated the effects of karyotypic

differences on the construction of linkage maps (Livingstone et al. 2000). They used

Mapmaker/EXP to create several genetic maps to examine intermarker distances using

General Discussion

103

two simulated datasets for F2 progeny which differed by a reciprocal translocation or a

reciprocal translocation and an inversion. They found alternative maps corresponding to

different chromosomal rearrangements around the translocation breakpoints. Using this

study as a reference, Durrant et al. (2006) introduced QuadMap, a software application,

to analyze linkage maps affected by translocations. Quadmap constructs and compares

multiple maps using Mapmaker/EXP. It generates multiple maps, permutates the marker

order, and analyzes the data from the linkage groups involved in the translocation

simultaneously using a large number of iterations. It gives the frequencies, average

intermarker centimorgan distance and centimorgan distance variance of each marker

pair. Large intermarker distance variance was proposed as an indication of the presence

of a breakpoint. However, high variances may also be caused by deficiencies in the

data. The methods developed in the present study can be implemented using standard

statistical software. When a consensus map is not available the minimum spanning tree

method (MST) can be used as an alternative to the principal coordinate analysis. This

allows us to separate the markers around the translocation breakpoint from the short and

long chromosome arms. This alternative strategy is based on (1) disentangling the

"pseudo-linkage" using the minimum spanning ; (2) remove markers around the TBs

according to a define threshold in terms of recombination frequencies and (3) four

independent marker sets will be used to construct the final linkage maps of the distal

parts of the chromosomes involved in the translocation.

The first steps for the introgression of favourable alleles into germplasm are the

construction of a high-quality linkage maps (Chapter 5) followed by QTL analysis

(Chapter 6) which allows the identification of the precise location of chromosome

regions associated with traits of interest. This goal can be achieved by constructing

consensus maps using information from multiple populations which provides greater

genome coverage avoiding large gaps in the map without markers and the marker order

and intermarker distances can be estimated more accurately. This requires having

common markers among populations which depends on the high level of polymorphism

between parents. In the present study, the highest level of polymorphism among

populations was observed for A×B and A×P whereas B×P showed the lowest level. This

appears to be in good agreement with the results obtained by Casas et al. (1998). They

General Discussion

104

demonstrated that parental lines ‘Plaisant’ and ‘Barberousse’ showed the highest level

of genetic similarity compared with the other parents. This could be explained because

they share the cultivar ‘Ager’ as one the parents. So, to enhance the chance of detecting

more polymorphic markers the parents should be divergent. But this can result in

populations that are not representative of germplasm used in breeding programs. It also

has a direct consequence for the QTL analysis because if marker alleles are non-

segregating in the B×P population also QTL will have a higher chance of being non-

segregating.

High-quality genetic linkage maps are of great importance for robust QTL mapping. For

that, high-quality datasets free of errors are essential as genotyping errors and missing

data lead to map expansion, especially in regions with a high marker density. In our

study discrepancies in map lengths, compared with the reference consensus map (Wenzl

et al. 2006), may be due to difference in “data curation” possibly in combination to the

use of different mapping criteria and mapping algorithms (Van Os et al. 2005). The

algorithm applied in this study which was adapted from the algorithm developed by

Jansen (2005), is an efficient method for constructing high-quality dense, integrated

linkage maps. This algorithm enabled us to develop a robust integrated linkage map

involving complex chromosomal rearrangements.

New QTL mapping methodologies have to be developed to cope with multi-population,

multi-environment analysis. Until now, most QTL studies were performed using

biparental populations (F2 or F× families, backcross, recombinant inbred lines, near-

isogenic lines and double haploids) which were obtained by crossing two inbred parents

with contrasting difference in phenotypic traits of interest (Semagn et al. 2010).

Consequently, a small part of the total variability for breeders is explored. So, the

development of multiple connected populations has become useful to: (i) increase the

variability addressed; (ii) allow global comparison of the effects of all QTL alleles

segregating in the different populations increasing the power to detect QTL, the

accuracy of the estimation of their effects and position and identifying the parental

origin(s) of favorable alleles at each QTL; and (iii) addressed interactions between QTL

and the genetic backgrounds (Muranty et al. 1997). As an alternative, other more

General Discussion

105

complex populations have been proposed to exploit the advantages of both linkage

analysis and association mapping such as the MAGIC populations (multiparent

advanced generation intercross) (Cavanagh et al. 2008), the nested association mapping

populations (NAM) design based on a huge set of recombinant inbred lines derived

from a large number of founder genotypes (Yu et al. 2008; Buckler et al. 2009) and

AMPRIL populations (a multiparent recombinant inbred line population) (Huang et al.

2011). For instance, NAM population captured approximately 136,000 crossover

events, corresponding, on average, to three crossover events per gene (McMullen et al.

2009). This NAM was derived from the crosses between 25 diverse inbred maize lines

and a reference line (B73) comprising 5000 RILs, 200 RILS per family. This allows

genetic factors to be mapped to very specific regions of the genome. These studies

genome-wide require a high density of markers and use re-sequencing technology.

The results obtained using the new methodology implemented in this study for a multi-

population, multi-environment QTL analysis was found useful to directly compare

additive effects among four parental alleles (Albacete, Barberousse, Orria and Plaisant)

(Chapter 6). The reciprocal translocation affected thousand kernel weight. DH lines

carrying the reciprocal translocation had a greater TKW than those with a standard

chromosome arrangement. These results are in concordance with the results found by

Farré et al. 2012 (Chapter 3).

The progress made with new marker technologies (such as DArT and SNP markers)

allow high throughput and low cost genotyping which provides the opportunity to

develop high-quality linkage maps. Currently, the new challenge in plant science is the

plant phenotyping which is considered to be the new bottleneck. The ‘phenotyping

bottleneck’ can be addressed by combining novel technologies such as robotics,

noninvasive imaging and analysis using powerful computing. This brings us to the age

of ‘phenomics’.

General Discussion

106

The present study was focused on the characterization of a reciprocal translocation

present in the widely grown Spanish barley variety ‘Albacete’. The combination of

different complementary approaches (cytogenetic, linkage and QTL mapping) led us to

develop an in-depth understanding of the reciprocal translocation and its consequences.

107

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1998. Edited by A.E. Slinkard. Printcrafters Inc., Winnipeg, Man. 122-124.

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125

Summary

Reciprocal translocations (RT) are one of the most common structural chromosomal

rearrangements occurring in plant species. Spontaneous RT are extremely uncommon in

cultivated barley. In fact, ‘Albacete’ is the only extensively cultivated barley variety

known to carry a RT without any major reduction in fitness. Previous results have

shown that 1H and 3H chromosomes are involved in this translocation which may have

a potential interest for plant breeding. A depth understanding of this RT could allowed

us to know whether this translocation is involved or not in their drought tolerance and

find some interesting phenotypic attributes that could be transfer to other barley

genotypes to develop specific germoplasm adapted to stress.

In a first step, a set of 230 doubled haploid lines derived from the cross between

‘Albacete’ and the non-translocation barley variety ‘Barberousse’ was used to develop a

statistical-genetic approach for the construction of a linkage maps in populations

obtained from RT heterozygotes. A preliminary linkage study revealed six main linkage

groups, compared to the seven linkage groups on the barley consensus map. One of the

linkage groups contained markers of chromosomes 1H and 3H. This union was due to

the presence of a RT between chromosomes 1H and 3H in the variety ‘Albacete’. The

results of this study revealed that the position of the translocation breakpoints was

placed around the centromeric regions for both chromosomes.

In a second step, a combination of cytological and molecular genetic approaches was

used in order to know how large the segments are that are involved in the interchange

between the two chromosomes. The results obtained in this study indicate that the

translocation is quite large with breakpoints located on the long arms of chromosomes

1H and 3H resulting in the RT 1HS.1HL-3HL and 3HS.3HL-1HL. The gene content

around the translocation breakpoints was estimated at approximately 1,100 and 710

gene models for 1H and 3H, respectively.

Summary

126

A large number of doubled haploid lines derived from four crosses involving ‘Albacete’

as one of the parents were used to phenotypically characterize the effects of the RT on

some interesting agronomic traits. The results suggested that the RT alone is not causing

the drought tolerance of ‘Albacete’; thousand kernel weight is the only trait which is

clearly enhanced in the lines carrying the RT. Further work combining the results from

this study with QTL analysis was carried out to phenotypically characterize the effects

of the reciprocal translocation and QTL simultaneously. For that, an integrated map was

constructed making used of a modified version of an algorithm developed by Jansen

(2005). Finally, specific QTL methodology for the simultaneous analysis of these

interconnected populations was developed; two traits: days to heading (independent of

the RT) and thousand kernel weight (affected by the RT) were used as an example.

127

Samenvatting

Reciproke translocaties behoren tot de meest voorkomende structurele herschikkingen

van de chromosomen bij planten. In gecultiveerde gerst komen spontane reciproke

translocaties zelden voor. In feite is ‘Albacete’ het enige veel geteelde gerstras waarvan

bekend is dat het drager is van een reciproke translocatie zonder dat het leidt tot een

sterke afname van ‘fitness’. Eerdere resultaten hebben aangetoond dat de chromosomen

1H en 3H betrokken zijn bij de translocatie die van potentieel belang kan zijn voor de

plantenveredeling. Meer kennis van de werking van deze reciproke translocatie zou

kunnen aantonen dat deze translocatie betrokken is bij droogtetolerantie en bij andere

interessante eigenschappen. Deze eigenschappen zouden kunnen worden overgedragen

naar andere gerstrassen met als doel het creëren van germplasm dat speciaal is

aangepast aan stress condities.

In een eerste stap zijn 230 verdubbelde haploïde lijnen afkomstig van de kruising tussen

‘Albacete’ en het gerstras ‘Barberousse’, dat geen drager is van de reciproke

translocatie, gebruikt voor ontwikkelen van een statistisch-genetische methode voor het

construeren van een genetische kaarten in populaties verkregen uit heterozygoten

waarvan een van de ouders drager is van een reciproke translocatie. Een eerste

koppelings studie liet zien dat er zes koppelingsgroepen zijn, in vergelijking met de

zeven groepen op de consensus kaart van gerst. Een van de groepen bevatte merkers van

de chromosomen 1H en 3H. Deze ‘clustering’ van merkers werd veroorzaakt door de

aanwezigheid van een reciproke translocatie tussen de chromosomen 1H en 3H in

‘Albacete’. De resultaten van deze lieten zien dat de posities breekpunten van de

translocatie zich op beide chromosomen bevonden in de centromere gebieden.

In een tweede stap is een combinatie van cytologische en moleculair-genetische

methoden gebruikt voor het bepalen van de grootte van de segmenten die betrokken zijn

bij de uitwisseling tussen de twee chromosomen. De resultaten van deze studie laten

zien dat de translocatie aanzienlijk van omvang is en waarbij de breekpunten zich

128

bevinden op de lange armen van de chromosomen 1H en 3H. Dit leidt tot de translocatie

1HS.1HL-3HL en 3HS.3HL-1HL. Het aantal genmodellen rond de translocatie

breekpunten werd bij benadering geschat op 1100 en 710 voor respectievelijk

chromosoom 1H en 3H.

Een groot aantal verdubbelde haploïde lijnen afkomstig van vier kruisingen met

‘Albacete’ als een van de ouders zijn vervolgens gebruikt voor de fenotypische

karakterisering van de effecten van de reciproke translocatie op enkele belangrijke

landbouwkundige eigenschappen. De resultaten laten zien dat de reciproke translocatie

niet alleen verantwoordelijk is voor de droogtetolerantie van ‘Albacete’. Het

duizendkorrelgewicht is de enige eigenschap die hogere waarden heeft in lijnen die de

reciproke translocatie dragen. Deze studie is daarna uitgebreid met een QTL analyse

om de gezamenlijke effecten van de reciproke translocatie en QTLs te karakteriseren.

Voor dat doel is eerst een geïntegreerde koppelingskaart geconstrueerd en vergeleken

met de consensus kaart van gerst. Tenslotte zijn er specifieke QTL methoden voor de

simultane analyse van de kruisingspopulatie ontwikkeld en toegepast. Twee

eigenschappen, het aantal dagen tot doorschieten (niet beïnvloed door de reciproke

translocatie) en duizendkorrelgewicht (wel beïnvloed door de reciproke translocatie),

werden geanalyseerd waarbij een aantal QTL werden gevonden.

129

Acknowledgements

The completion of this thesis is a result of the efforts of several people. I would like to

acknowledge those who contributed and recognize the inestimable value of their work.

First of all I would like to show my gratitude to my supervisors Ignacio Romagosa, Johannes

Jansen and Fred van Eeuwijk for their excellent work, guidance, availability, support and for

giving me this great opportunity. I would have not achieved the successful completion of this

thesis without you.

I would like to thank the people from my lab: Marian, Pilar, Andrea and particularly Eva (for

helping me getting started in the lab with her useful assistance in lab techniques, her excellent

friendship, shared lovely and fun time).

I would like to express my special thanks to the people from Biometris: Joao, Marcos, Martin,

Tahira, Patricia, Sabine, Willem, Marian, Apri, Santosh, Laura, Maggie and Paulo for their

support and kindness. Thanks Thomas and family, I really enjoyed the time I spend with you.

I warmly thank the biotech colleagues who treated me as one of them: Ariadna, Koreen, Sonia,

Svetlana, Gina, Sol, Dawey, Maite, Bruna, Chao, Griselda, Uxue, Edu, Bing, Evangelia, Judit,

Gemma, Changfu, Ludovic and other colleagues from the PVCF department. Also thanks

Teresa and Paul for their support and help when I needed.

I would like to thank co-authors of our publications for the fruitful collaboration and valuable

discussion of manuscripts: Prof. Schubert (IPK, Germany), Dr. Cistué (Estación Experimental

de Aula Dei, Spain), Prof. de Jong (WUR, The Netherlands), Dr. Cuadrado (Department of Cell

Biology and Genetics, Spain), Dr. Comadran (The James Hutton Institute, Scotland), Dr.

Lacasa-Benito, Dr. Casas (Estación Experimental de Aula Dei, Spain) and Dr. Thomas (The

James Hutton Institute, Scotland).

Many thanks go to Marian and Izak Bos. I will never forget your kind help and your warm and

generous hospitality during my stay in Wageningen.

Thanks María, Diana, Merche, Paula and Izabel, your friendship mean a lot for me.

I wish to thank my entire family for their love and encouragement. And last but not least Gerard was remarkably supportive. Thanks so much for always being there for me.

131

PE&RC PhD Education Certificate With the educational activities listed below the PhD candidate has complied with the educational requirements set by the C.T. de Wit Graduate School for Production Ecology and Resource Conservation (PE&RC) which comprises of a minimum total of 32 ECTS (= 22 weeks of activities) Review of literature (4.5 ECTS)

- General introduction

Writing of project proposal (4.5 ECTS) - Development of materials and techniques for the study of adaption to stresses in barley (Hordeum

vulgare L.) Post-graduate courses (3 ECTS)

- Applied bioinformatics in plant science (2010) - Detection and use of QTLs (2011)

Laboratory training and working visits (4.5 ECTS)

- Breakpoint localization of a reciprocal translocation present in the Spanish barley variety “Albacete”

Invited review of (unpublished) journal manuscript (2 ECTS) - Molecular Breeding: eQTLs (2009) - Theoretical and Applied Genetics: resistance in barley cultivars (2010)

Deficiency, refresh, brush-up courses (3 ECTS)

- Modern Statistics for Life Science (2008)

Competence strengthening / skills courses (1.9 ECTS) - Career assessment (2011) - Communication with the media and the general public (2011) - Information literacy including EndNote introduction (2011)

PE&RC Annual meetings, seminars and the PE&RC weekend (1.2 ECTS)

- PE&RC Weekend (2011) - PE&RC Day (2011)

Discussion groups / local seminars / other scientific meetings (7.5 ECTS)

- Biometris Statgen colloquium (2010-2011) - Biometris lunch colloquium (2010-2011) - Plant production and forest science department seminars; intermittent (2007-2011)

International symposia, workshops and conferences (4.4 ECTS) - 19th International Triticeae Mapping Initiative – 3rd COST Tritigen (2009) - Congreso de la sociedad española de genética (SEG) (2011)

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