AN ABSTRACT OF THE DISSERTATION OF
Ivan Ariel Matus for the degree of Doctor of Philosophy in Crop Science presented
on December 19, 2002.
Title: Exploiting Hordeum vulgare subsp. spontaneum Genetic Resources:
Diversity Analysis and Germplasm Development
Abstrac
Redacted for privacy
Patrick M. Hayes
Wild barley (Hordeum vulgare subsp. spontaneurn) could be a source of useful
genes for improving cultivated barley. The useful genes present in Hordeum
vulgare subsp. spontaneum may be new alleles at described loci, or these may be
entirely new genes in the sense that there is limited allelic variation at these loci in
the cultivated gerrnplasm pooi. This research was directed at gene discovery in wild
barley and involved two steps: (i) characterization of diversity using genetic
markers and (ii) development and characterization of novel germplasm for gene
discovery.
Simple Sequence Repeats (SSRs) of known map location were used to survey three
representative groups of barley germplasm: a sample of crop progenitor (Hordeum
vulgare subsp. spontaneum) accessions, a group of mapping population parents,
and a group of varieties and elite breeding lines. The objectives were to determine
the informativeness and utility of SSRs in differentiating and classifying the three
sets of barley germplasm. Crop progenitors had the highest number of alleles per
SSR locus, followed by mapping population parents and elite breeding lines. The
cluster analysis indicated a high level of diversity within the crop progenitor
accessions and within the mapping population parents. It revealed a much lower
level of diversity within the elite breeding germplasm.
A set of Recombinant Chromosome Substitution Lines (RCSLs) representing
introgressions of Hordeum vulgare subsp. spontaneum genome in to a cultivated
barley background were developed using the Advanced Backcross strategy. An
accession of Hordeum vulgare subsp. spontaneum was the donor parent and the
variety "Harrington" was the recurrent parent. The RCSLs were developed via two
backcrosses to the recurrent parent followed by six generations of selfing. The
genomic architecture of the RCSLs was determined by molecular marker
fingerprinting with SSRs. The consequences of introgressions of Hordeum vulgare
subsp. spontaneurn genome segments into the recurrent parent were assessed in
terms of inflorescence yield components, malting quality traits, and domestication-
related traits. Hordeum spontaneum subsp. spontaneum, despite its overall inferior
phenotype, contributed favorable alleles for some characters of agronomic
performance. In other cases, the introgressions caused a disruption of the
Harrington phenotype, a "reverse genetics" approach to gene discovery.
Exploiting Hordeum vulgare subsp. spontaneum Genetic Resources: Diversity
Analysis and Germplasm Development
by
Ivan Arid Matus
A DISSERTATION
submitted to
Oregon State University
in partial fulfillment of
the requirements for the
degree of
Doctor of Philosophy
Presented December 19, 2002
Commencement June, 2003
Doctor of Philosophy dissertation of Ivan Ariel Matus presented on
December 19, 2002
APPROVED:
Redacted for privacy
Major Professor, representing Crop
Redacted for privacy
Chair of the Department of Crop and Soil Science
Redacted for privacy
Dean of1he Graduate School
I understand that my dissertation will become part of the permanent collection of
Oregon State University libraries. My signature below authorizes release of my
dissertation to any reader upon request.
Redacted for privacy
Ivan Ariel Matus, Author
ACKNOWLEDGMENTS
First of all I want express my gratitude to my major professor Dr. Patrick M.
Hayes. Without his guidance, enthusiasm, support, and his human quality this
research would not be possible. I also want to thank him for financial support in the
final and critical years of my doctoral program.
I am thankful to the members of my graduate committee - Dr. Oscar RieraLizarazu, Dr. Isabel Vales, Dr. Aaron Liston, Dr. William Proebsting and Dr.
James Peterson - for their time and guidance.
Special thanks and gratitude are extended to the members of the OSU Barley
Project: Ann Corey, Tanya Filichkin, Dr. Isabel Vales, Dr. Jennifer Kling, Dr. Lol
Cooper and Dr. Luis Marquez-Cedillo, who all helped me in many aspects of my
research. Thanks to my graduate colleagues - Jan Von Zitzewitz and Kelley
Richardson - who helped me in different parts of my research and classes and to
Dr. Ariel Castro, and Carlos Rossi, former students of the OSU Barley Project.
Thanks to Caprice Rosato and Sergei Filichkin who assisted me in the automated
genotyping of SSR markers. Thanks to the faculty and staff of the Department of
Crop Science and Soil Science who directly or indirectly contributed to the success
of this work. I also want to thank my fellow graduate students from the
Department, in particular Venkhata Krishna Kishore and Sonali Gandhi, for their
friendship.
This research was supported by the North American Barley Genome Project
(NABGP) and Busch Agricultural Resources, Inc. I would like to thank the Scottish
Crop Research Institute (SCRI) for their generous prepublication sharing of SSR
primer sequences
I also want to acknowledge the financial support of the Chilean Government
through the National Agriculture Research Institute (INIA).
I want to thank my mother, my brother, my sister, and my father who passed away
while I was at Oregon State University.
I want to give a very special thanks to my beautiful family: my wife Florencia, my
son Nicolas, and my daughter Catalina. I want to tell them sorry for spending too
much time with my own work. But at same time we have to recognize that this
experience also helped us to grow as a family.
To all the ones that I forgot to mention, I am very thankful.
CONTRIBUTIONS OF AUTHORS
Dr. Patrick M. Hayes initiated, advised, and supervised all aspects of the project.
He substantially contributed in formulating hypotheses, and discussing and revising
manuscripts. Ann Corey assisted with greenhouse and field trial data collection.
Tanya Filichkin was involved in laboratory aspects of the research. Dr. Jennifer
Kling helped in the statistical analysis and contributed to the preparation of
manuscripts. Dr. Kazuhiro Sato contributed germplasm accessions, assisted in data
interpretation, and participated in manuscript preparation. Dr. Wayne Powell and
Dr. Robbie Waugh contributed prepublication SSR primer sequences, assisted in
data interpretation, and participated in manuscript preparation.
TABLE OF CONTENTS
Page
INTRODUCTION........................................................................................................ 1
GENETIC DIVERSITY IN THREE GROUPS OF BARLEY GERMPLASM
ASSESSED BY SiMPLE SEQUENCE REPEATS ..................................................... 4
ABSTRACT ............................................................................................. 5
INTRODUCTION................................................................................... 7
MATERIALS AND METHODS ...........................................................
11
RESULTS AND DISCUSSION ............................................................ 24
REFERENCES ....................................................................................... 41
DEVELOPMENT
AND CHARACTERIZATION OF RECOMBiNANT
CHROMOSOME SUBSTITUTION LINES (RCSLs) USING Hordeum vulgare
subsp. spontaneum AS A SOURCE OF DONOR ALLELES IN A Hordeum
vulgare subsp. vulgare BACKGROUND ................................................................... 46
ABSTRACT ........................................................................................... 47
INTRODUCTION................................................................................. 48
MATERIALS AND METHODS ........................................................... 51
RESULTS AND DISCUSSION ............................................................ 63
REFERENCES ....................................................................................... 95
CONCLUSIONS ........................................................................................................ 101
BIBLIOGRAPHY ..................................................................................................... 105
LIST OF FIGURES
Figure
2.1. Dendrogram of 22 Hordeum vulgare subsp. spontaneurn, 32
Hordeum vulgare subsp. vulgare mapping population parents
and genetic stocks, and 96 elite breeding lines and standard
varieties based on the genetic distance (D) as measured by
allelic variation at 42 SSR loci .......................................................................... 32
2.2. Biplot of the first two principal coordinates for 22 Hordeum
vulgare subsp. spontaneum, 32 Hordeum vulgare subsp.
vulgare mapping population parents and genetic stocks, and 96
elite breeding lines and standard varieties based on the genetic
distance (D) as measured by allelic variation at 42 SSR loci ............................ 38
3.1. Development and generation advance of recombinant
chromosome substitution lines (RCSLs) from H. vulgare subsp.
spontaneum/H. vulgare subsp. vulgare (Caesarea 2624/Harrington) introgression. See text for details ............................................. 53
3.2. Distribution of the percentage of donor parent (H. vulgare
subsp. spontaneum) genome in the recombinant chromosomes
substitution lines (RCSLs) ................................................................................. 64
3.3. Graphical genotype of RCSL 138 showing 3.2% H. vulgare
subsp. spontaneum introgression in a H. vulgare subsp. vulgare
background ........................................................................................................ 67
3.4. Graphical genotype of RCSL 16 showing 30% H. vulgare subsp
spontaneum introgression in a H. vulgare subsp vulgare
background ........................................................................................................ 68
3.5. Chi-square values for segregation distortion for chromosomes
1(7H), 5(1H) and 7(5H). The dotted lines show the 0.005
confidence level limits (92.5% and 82.2%) and the solid line
shows the expected allele frequency (87.5%) for the recurrent
parentin a BC2 population ................................................................................ 71
LIST OF FIGURES (CONTINUED)
Figure
3.6. Phenotypic frequency distributions for yield component and
domestication traits in the RCSLs..................................................................... 78
3.7. Phenotypic frequency distributions for each malting quality
traitsin the RCSLs ............................................................................................. 79
3.8. Standard deviations (SD) from adjusted correlations values for
yield component traits (thousand kernel weight (TKW), kernel
plumpness (KP), and test weight (TW)), graphically represented
above the horizontal axis. Bars below the horizontal axis show
locations of Quantitative Trait Loci (QTL) reported in the
literature. The dotted and the solid lines in the SD portion of the
figure represent, respectively, 1.5 and 2.0 SD from the mean.
Data are shown for chromosomes 1 (7H) to 7(5H), with the
corresponding linkage map bin numbers ........................................................... 83
3.9. Standard deviations (SD) from adjusted correlations values for
yield component traits (head length (HL) and seeds per head
(SH)), graphically represented above the horizontal axis. Bars
below the horizontal axis show locations of Quantitative Trait
Loci (QTL) reported in the literature. The dotted and the solid
lines in the SD portion of the figure represent, respectively, 1.5
and 2.0 SD from the mean. Data are shown for chromosomes
1(7H) to 7(5H), with the corresponding linkage map bin
numbers ........................................................................................................... 84
3.10. Standard deviations (SD) from adjusted correlations values for
malting quality traits (malt extract (ME), grain protein (P), and
diastatic power (DP)), graphically represented above the
horizontal axis. Bars below the horizontal axis show locations
of Quantitative Trait Loci (QTL) reported in the literature. The
dotted and the solid lines in the SD portion of the figure
represent, respectively, 1.5 and 2.0 SD from the mean. Data are
shown for chromosomes 1(7H) to 7(5H), with the
corresponding linkage map bin numbers ........................................................... 87
LIST OF FIGURES (CONTINUED)
Figure
3.11. Standard deviations (SD) from adjusted correlations values for
malting quality traits alpha amylase activity (AA) and wort beta
glucan (WBG)), graphically represented above the horizontal
axis. Bars below the horizontal axis show locations of
Quantitative Trait Loci (QTL) reported in the literature. The
dotted and the solid lines in the SD portion of the figure
represent, respectively, 1.5 and 2.0 SD from the mean. Data are
shown for chromosomes 1 (7H) to 7(5H), with the
corresponding linkage map bin numbers ........................................................... 88
3.12. Standard deviations (SD) from adjusted correlations values for
domestication traits (awn retention (AR) and seed shattering
(SS)), graphically represented above the horizontal axis. Bars
below the horizontal axis show locations of Quantitative Trait
Loci (QTL) reported in the literature. The dotted and the solid
lines in the SD portion of the figure represent, respectively, 1.5
and 2.0 SD from the mean. Data are shown for chromosomes
1 (7H) to 7(5H), with the corresponding linkage map bin
numbers ............................................................................................................ 91
LIST OF TABLES
Table
2.1. The twenty-two Hordeum vulgare subsp. spontaneum
accessions used for genetic diversity characterization with
(Simple Sequence Repeat) SSR markers .......................................................... 12
2.2. The fifty-three Hordeum vulgare subsp. vulgare accessions used
for genetic diversity characterization with (Simple Sequence
Repeat) SSR markers ......................................................................................... 13
2.3. The ninety-six elite lines and varieties from the Busch
Agricultural Resources, Inc. (BARI) barley improvement
program used for genetic diversity characterization with
(Simple Sequence Repeat) SSR markers ........................................................... 17
2.4. Number of alleles, amplicon size range (base pairs ((bp)),
number of unique andcommon alleles, and total number of
alleles for each (Simple Sequence Repeat) SSR locus in three
groups of barley germplasm: subsp. spontaneum, subsp. vulgare
and a sample of germplasm from the Busch Agricultural
Resources, Inc. (BARI) breeding program ........................................................ 25
2.5. Chromosome location, map position (according to Ramsay et
al., 2000 and Macaulay et al., 2001), and polymorphism
information content (PlC) values for (Simple Sequence Repeat)
SSR loci assayed in three groups of barley germplasm: subsp.
spontaneum, subsp. vulgare, and a set of lines from the Busch
Agricultural Resources Inc. (BARI) breeding program .................................... 28
3.1. Chromosome location, map position and linkage map bin
number for (Simple Sequence Repeat) SSR loci assayed in
recombinant chromosome substitution lines (RCSLs) derived
from the cross of Harrington (recurrent parent) and H. vulgare
subs p.spontaneurn accession Caesarea 26-24 (donor parent) ........................... 59
Exploiting Hordeum vulgare subsp. spontaneum Genetic Resources:
Diversity Analysis and Germplasm Development
INTRODUCTION
Knowledge regarding the level of genetic diversity present in crop ancestors, exotic
germplasm, and elite gene pools is essential for designing effective conservation
strategies and efficient breeding programs. Although it is still possible to select new
cultivars from the progeny of elite x elite crosses, genetic variation for many key traits
is limited. Thus, it is important to compare the genetic variability in wild and
cultivated populations. Genetic diversity can be measured by several criteria,
including (i) phenotype, (ii) pedigree, (iii) allelic diversity at marker loci, and (iv)
allelic diversity at loci controlling phenotypes of interest. Steps i and ii have, in many
cases, been thoroughly explored. Currently the principal thrust of many research
efforts is on step iii. With accumulating sequence information and access to higher
throughput assays, in the future attention will shift to step
iv. Currently, the
abundance, high level of polymorphism, and ease of genotyping make Simple
Sequence Repeats (SSRs) an excellent molecular marker system for many types of
genetics analyses (Liu et al., 1996).
After a thorough characterization of genetic diversity, selected accessions can be used
as gene donors. The introgression of new genes, or gene complexes, to broaden the
breeding base has the potential to reduce genetic vulnerability of crop plants
(Kannenberg and Falk, 1995), and may facilitate achieving plant-breeding objectives
(Sorrells and Wilson, 1997). However, it is challenging to introgress genes from exotic
2
accessions or ancestral species. It is generally recognized that agronomic performance
suffers when elite germplasm is crossed with exotic accessions and even more so
when crossed with ancestral species. This is due to linkage drag andlor epistasis
(Young and Tanksley, 1989; Kannenberg and Falk, 1995; Hawtin et al., 1996;
Vetelainen et al., 1996). Nonetheless, exotic or wild germplasm with undesirable
phenotypes has been successfully used to introgress useful alleles into cultivated elite
germplasm (Young and Tanksley, 1989; Vetelainen et al., 1996).
Backcrossing, a breeding strategy commonly used to introgress single or small
numbers of valuable genes into an elite cultivar, is a recurring motif in exotic or
ancestral germp!asm introgression. At the same time, molecular and statistical tools
developed for genetic dissection of quantitative traits in cultivated germplasm can be
used to identify and extract useful genes from their wild backgrounds. The integration
of gene discovery and introgression via backcrossing was first proposed and
implemented by Tanksley and Nelson (1996), who coined the term "Advanced
Backcross Strategy".
Wild barley (Hordeum vulgare subsp. spontaneum) is a source of useful genes for
improving cultivated barley. Useful genes may be new alleles at described loci (e.g.
novell alleles at the Bamyl locus (Erkkila et al., 1998), or entirely new genes (e.g. the
scald-resistance gene Ri-s 14 (Garvin et al., 1997).
This research involved three components: characterization of genetic diversity using
DNA fingerprinting, development of ancestral species introgression genetic stocks,
and genotypic and phenotypic characterization of these genetic stocks. The first
3
component was addressed via the characterization of allelic variation at Simple
Sequence Repeat (SSR) loci in Hordeum vulgare subsp. vulgare and H. vulgare subsp.
spontaneum accessions. The second component was addressed via the development of
a set of Recombinant Chromosome Substitution Lines (RCSLs) representing
insertions of the Hordeun vulgare subsp. spontaneum genome in a Hordeum vulgare
subsp. vulgare background. The third component was addressed by phenotypic
characterization of agronomic, malting quality, and domestication traits in the RCSLs
and identification of phenotype: genotype associations. The first component is
addressed in Genetic Diversity in Three Groups of Barley Germplasm Assessed by
Simple Sequence Repeats and the second and third components are addressed in
Development and Characterization of Recombinant Chromosome Substitution Lines
(RCSLs) Using Hordeum vulgare subsp. spontaneum as a Source of Donor Alleles in a
Hordeum vulgare subsp. vulgare Background.
GENETIC DIVERSITY IN THREE GROUPS OF BARLEY GERMPLASM
ASSESSED BY SIMPLE SEQUENCE REPEATS
Ivan A. Matus and Patrick M. Hayes'
'Department of Crop and Soil Science, Oregon State University.
253 Crop Science Building, Oregon State University, Corvallis, OR, 97331-3002,
USA
Oregon Agricultural Experiment Station Journal No. 11879
Genome (2002) 45(6): 1095-1106
5
ABSTRACT
Genetic diversity can be measured by several criteria, including phenotype, pedigree,
allelic diversity at marker loci, and allelic diversity at loci controlling phenotypes of
interest. Abundance, high level of polymorphism, and ease of genotyping make simple
sequence repeats (SSR5) an excellent molecular marker system for genetics diversity
analyses. In this study, we used a set of mapped SSRs to survey three representative
groups of barley germplasm: a sample of crop progenitor (Hordeum vulgare subsp.
spontaneum) accessions, a group of mapping population parents, and a group of
varieties and elite breeding lines. The objectives were to determine i) how informative
SSRs are in these three sets of barley germplasm resources, and ii) the utility of SSRs
in classifying barley germplasm. A total of 687 alleles were identified at 42 SSR loci
in 147 genotypes. The number of alleles per locus ranged from 4-3 1, with an average
of 16.3. Crop progenitors averaged 10.3 alleles per SSR locus, mapping population
parents 8.3 alleles per SSR locus, and elite breeding lines averaged 5.8 alleles per SSR
locus. There were many exclusive (unique) alleles. The polymorphism information
content (PlC) values for the SSRs ranged from 0.08 to 0.94. The cluster analysis
indicates a high level of diversity within the crop progenitor accessions and within the
mapping population parents. It also shows a lower level of diversity within the elite
breeding germplasm. Our results demonstrate that this set of SSRs was highly
informative and was useful in generating a meaningful classification of the germplasm
we sampled. Our long-term goal is to determine the utility of molecular marker
diversity as a tool for gene discovery and efficient use of germplasm.
7
INTRODUCTION
Knowledge regarding the amount of genetic variation in germplasm arrays and genetic
relationships between
genotypes
are
important
considerations
for
efficient
conservation and utilization of germplasm resources (Kresovich et al. 1995; Rusell et
al. 1 997a; Dávila et al. 1998). In the context of plant improvement, this information
provides a basis for making decisions regarding selection of parental combinations
that will maximize gain from selection and maintain genetic diversity. Information on
the amount of genetic variation present, and the location of the genetic determinants of
diversity, may be useful for germplasm conservation and targeting gene discovery
efforts (Sorrells and Wilson 1997; Jana 1999). More knowledge regarding the genetic
structure of breeding materials could help to maintain genetic diversity, which would
sustain long-term selection responses and reduce vulnerability (Troyer et al. 1998; Liu
et al. 2000).
The degree of diversity present in a sample of germplasm can be measured in terms of
morphology, pedigree, allelic diversity at marker loci and allelic diversity at genes
determining target phenotypes. Morphological characters are often influenced by the
environment and there may be limited polymorphism in cultivated germplasm.
Pedigree information is not available for wild or crop progenitor germplasm and even
within cultivated germplasm it can be difficult to differentiate between closely related
accessions because complete pedigree records are not always available (Cheres and
Knapp 1998). Allelic diversity based on genes determining key phenotypes currently
8
is not feasible in most crop plants, although the rapidly expanding EST and SNP
databases will eventually make this feasible in some germplasm arrays. Accordingly,
diversity at marker loci is currently the most feasible strategy for characterizing
diversity in wild and cultivated germplasm.
Many types of molecular markers have been used to characterize germplasm, with
each method differing in principle, application, in the type and amount of
polymorphism detected and in cost and time requirement. These include random
amplification
of polymorphic DNA (RAPDs), restriction fragment length
polymorphisms (RFLPs), amplified fragment length polymorphisms (AFLPs) and
simple sequence repeats (SSRs). SSRs are codominant, abundant, informative, and
their detection can be automated. This makes them an excellent molecular marker
system for many types of genetic analyses, including linkage mapping, germplasm
surveys and phylogenetic studies (Liu et al. 1996). Various repeat motifs (e.g. di-, tn-,
or tetra-nucleotide units) are reported to occur throughout the genome of most
eukaryotic species (Powell et al. 1996). Most SSRs are codominant, highly
reproducible, and demonstrate a high degree of allelic variation (Saghai Maroof et al.
1994; Becker and Heun 1995; Russell et al. 1997a; Struss and Plieske 1998).
Barley is an economically important cereal, ranking fourth in world crop production.
In order of importance barley is used for animal feed, brewing malts, and human
consumption (Hayes et al. 2002). Barley can be grown in a wide range of
environments. It extends far into the artic, reaches the upper limits of cultivation in
high mountains and may be grown in desert oases, where it is more salt tolerant than
9
other cereals (Harlan, 1976). Barley is considered a model species for genetic analysis.
Extensive genetic linkage maps, quantitative trait loci (QTL) information and genetic
diversity studies are available in barley (Hayes et al. 2002 and posted at
http://www.css.orst.edu/barley/nabgmp/gflsum.htm; Heun et al. 1991; Kleinhofs et al.
1993; Becker at al. 1995; Dávila et al. 1999; Pillen et al. 2000). In term of germplasm
resources, there are more than 260,000 Hordeum accessions conserved in gene banks
around the world (IPGRI 2001). Only a portion of these accessions has been
characterized at the phenotypic level, and an even smaller portion has been
characterized at the genotypic level.
Genetic diversity surveys at molecular marker loci in wild and cultivated barley have
been conducted using AFLPs (Hayes et al. 1997; Ruse!! et al. 1997a), RFLPs
(Petersen et al. 1994; Rusell et al. 1997a), RAPDs (Russell et al. 1997a), and SSRs
(Saghai Maroofet al. 1994; Russell et al. 1997b; Struss and Plieske 1998; Dávila et al.
1999; Pillen et al. 2000; Ivandic et al. 2002). SSRs have also been used for
characterizing genetic diversity in other crops including sorghum (Dean et al. 1999;
Smith et al. 2000; Djè et al. 2000), maize (Senior et al. 1998), cotton (Liu et al. 2000),
cultivated spelt wheat (Bertin et al. 2001), wheat (Prasad et al. 2000), and soybean
(Diwan and Cregan 1997).
In this study, we used a set of mapped SSRs to survey three groups of barley
germplasm: (i) a set of accessions representing the wild ancestor of cultivated barley
(Hordeum vulgare subsp. spontaneum); (ii) a set of cultivated barley accessions
including mapping population parents and genotypes of interest to our breeding
10
program; and (iii) a group of elite malting barley breeding lines, parents of these lines,
and malting quality standards. Our objectives were to determine (i) how informative
SSRs are in these three sets of barley germplasm resources, and (ii) the utility of SSRs
in classifying barley germplasm. Our long-term goal is to determine the utility of
molecular marker diversity as a tool for gene discovery and biologically meaningful
classification of germplasm.
11
MATERIALS AND METHODS
GERMPLASM
Twenty-two accessions of Hordeum vulgare subsp. spontaneum (subsp. spontaneum)
thirty-two accessions of Hordeum vulgare subsp. vulgare (subsp. vulgare) and ninetysix elite lines and varieties from the Busch Agricultural Resources, Inc. (BARI) barley
improvement program were selected for this study. The subsp. spontaneum accessions
represent different areas of geographic origin. The genotypes in the subsp. vulgare
group represent mapping population parents and lines of interest to our breeding
program and vary in terms of growth habit, end-use, row type, and geographic origin.
The principal germplasm groups in cultivated barley are currently defined by growth
habit (winter, facultative, or spring); end-use (malting, feed, or human food); and row
type (two-row or six-row, which refers to the number of fertile florets per rachis
node). The BARI lines included 86 six-row and 10 two-row spring malting barley
genotypes. Of the BARI six-rows, 82 are elite breeding lines and 4 are parents and!or
malting quality standards. Of the BARI two-rows, 7 are elite breeding lines and 2 are
parents andlor malting quality standards. Descriptors for the germplasm array are
shown in Tables 2.1, 2.2 and 2.3
Table 2.1. The twenty-two Hordeum vulgare subsp. spontaneum accessions used for genetic diversity characterization with
(Simple Sequence Repeat) SSR markers.
N
Accession
1
0UH602 (OSU1)
Source
K. Sato (Okayama, Japan)
Origin
H. spontaneum var.
transcaspicum
2
3
4
5
6
7
0UH640 (OSU2)
0UH825 (OSU3)
Ab87
(OSU4)
E36
(OSU5)
PBIOO4-7-0-015 (Ident. Accession 8321) Erez (OSU6)
PBIOO5-l-1-004 (Ident. Accession 13786) Re'im(OSU7)
PBIOO6-1-0-005 (Ident. Accession 14414) Nirim (OSU8)
PBIO1O-2-0-012 (Ident. Accession 14431) Lahav (OSU9)
Caesarea 26-24 (OSU1 1)
Sede Boquer 20-45 (OSU12)
K.Sato (Okayama, Japan)
K.Sato (Okayama, Japan)
A.Graner (BAZ, Germany)
A.Graner (BAZ, Germany)
L.Lehmann(Svalov, Sweden)
Nepal
Tibet
Israel
Israel
Israel
Israel
Israel
Israel
Israel
Israel
Israel
Iran
Iran
Israel
12
13
14
15
Wadi Qilt 23-38 (05U15)
Nahal Oren SH-5 1 (OSU 18)
L.Lehmann(Svalov, Sweden)
L.Lehmann (Svalov, Sweden)
L.Lehmann (Svalov, Sweden)
E.Nevo (Haifa, Israel)
E.Nevo (Haifa, Israel)
E.Nevo (Haifa, Israel)
E.Nevo (Haifa, Israel)
E.Nevo (Haifa, Israel)
E.Nevo (Haifa, Israel)
16
Nahal Oren SH- 18 (OSU 19)
E.Nevo (Haifa, Israel)
Israel
17
18
19
21
0UH622
0UH628
0UH647
0UH676
0UH692
K.Sato (Okayama, Japan)
K.Sato (Okayama, Japan)
K.Sato (Okayama, Japan)
K.Sato (Okayama, Japan)
K.Sato (Okayama, Japan)
22
HS 92 (Canada Park)
Kataghan, Afghanistan
Quetta, Pakistan
Sumbar, Turkmenia
Azerbaijan
Sulaymaniyah, Iraq
Israel
8
9
10
11
20
11am- 12 (OSU1 6)
11am -26 (OSU17)
Comments
Resistant to mildew and
net blotch. Black seed.
Used for making addition
lines with Chinese spring
Used as map parent
Used as map parent
Resistant to mildew and
net blotch
Resistant to net blotch
Salt and drought tolerant
From a dry place
From a dry place
From a dry place
From a dry place
Xeric from Evolution
Canyon
Xeric from Evolution
Canyon
Table 2.2. The fifty-three Hordeum vulgare subsp. vulgare accessions used for genetic diversity characterization with (Simple
Sequence Repeat) SSR markers.
N
Accession
Source
Information
Interests
Pedigree
Map Population
23
}Iaruna-nijo
K. Sato
(Okayama)
Japan; Spring Malting;
2-row
Quality QTL
Fl 0/Seijo 15
Mapping population
parent, Australia
24
Kikaihadaka
K. Sato
(Okayama)
Japan; Winter Naked;
6-row (semi-dwarf)
Food barley Mildew
Nakate hadaka/Saga hadaka 1
NA
resistance to race IX
25
Cyrrhus
Scotland (SCRI)
Syria; Spring
Landrace; 2-row
Used for producing
RCSLs at the SCRI
NA
Morex*2/Cyrrhus
26
Barke
A. Graner (BAZ)
Germany; Spring
Malting; 2-row
NA
Libelle/Alexis
NA
27
Sloop
F. Ogbonnaya
(NRE)
Australia; Spring
Malting; 2-row
Quality QTL
Schooner/TR206/Golden
Promise/W12395/3/Schoner
Alexis/Sloop
28
Schooner
F. Ogbonnaya
(NRE)
Australia; Spring
Malting; 2-row
Quality QTL
Proctor/Priora//Proctor/
NA
C13576
29
Derkado
B. Thomas
(SCRI)
Scotland; Spring
Malting; 2-row
P. striformis resistance
Mildew resistance
Lada/Salome
Derkado/Orca
30
Harrington
NAB GMP
Canada; Spring
Malting; 2-row
Agronomic/Quality
QTL
Klages/3/Gazelle/Betzes
I/Centennial
Harrington/TR306
Harrington/Morex
31
Morex
NABGMP
USA; Spring Malting;
6-row
Agronomic/Quality
QTL
CreelBonanza
HarringtonlMorex
RoyallMorex
SteptoelMorex
Dicktoo/Morex
Continued Table 2.2
32
33
Galena
Baronesse
NABGMP
NABGMP
USA; Spring Malting;
2-row
Coors Brewing Co.
Germany; Spring
Feed; 2-row
Agronomic QTL
TriumphlCrystal
Galena/Shyri
CI 105 87/Galena
Mentor/Minerva//Vada
mutantl4/Carlsberg/Unionl/O
pavsky/Salle/3fRicardo
Clark/Baronesse
Baronesse/Triangel
BCD47lBaronesse
/5/OrioIl6 I 53P40
34
Colter
NABGMP
USA; Spring Feed; 6row
P. striformis
Steptoe!Larker//Karla
Colter/Kold
susceptibly
35
Gobernadora
NABGMP
ICARDA/CIMMYT
Spring Feed; 2-row
Agronomic/Quality
QTL Fusarium
resistance
0C640/Mari!/Pioneer/3/
Mans Canon
Gobernadora/CMB 643
36
Dicktoo
NABGMP
USA; Winter Feed; 6row
Agronomic/Quality
QTL Winterhardiness
QTL
Unknown: complex cross
Dicktoo/Kompolti
Dicktoo/Morex
37
Steptoe
NABGMP
USA; Facultative
Feed; 6-row
Agronomic QTL
Wa3564/Unitan
Dicktoo!Morex
Steptoe/Morex
38
Shyri
NABGMP
ICARDA/CIMMYT
Ecuador; Spring Feed;
2-row
P. striformis resistance
Teranl 8/Kober//Lignee 640
Shyri/Galena
39
CMB643
NABGMP
ICARDA/CIMMYTSp
ring Feed; 2-row
Fusarium resistance
Shyril/GlorialComanche/3/
Shyri/Grit
Gobernadora/CMB 643
40
C110587
NABGMP
Spring 2-row
P.striiformis Diuraphis
noxia resistance
Unknown
C110587/Galena
Continued 2.2
41
Kold
NABGMP
USA; Winter Feed; 6row
P. striformis resistance
1 285/Astrix
Kold/Colter
Ko1d188Ab536
42
Orca
NABGMP
USA; Spring Feed
/Malting; 2-row
P. striformis resistance
LBIranIUNA827 1//Gloria!
ComexBowmanBC
NA
43
Tango
NABGMP
USA; Spring Feed; 6row
P. striformis resistance
BSR45/Steptoe*2
Tango x CR3O-3
44
CR 30-3
NABGMP
USA; Spring; 6-row
Map parent
BSR45/Colter*2
Tango x CR3O-3
45
88Ab536
NABGMP
USA;Winter Malting
6-row
Map parent
NE 76129/Morexl/Morex
Strider/88ab536
Kold/88Ab536
46
Strider
NABGMP
USA; Winter Feed; 6row
P. striformis resistance
Map parent
1860 164/Steptoe
Strider/88Ab536
47
Alexis
SCRI
Germany; Spring
Malting; 2-row
Agronomic/Quality
QTL
Breun K622/Trlumph
Alexis/Regtta
48
Blenheim
SCRI
Germany; Spring
Malting; 2-row
Agronomic/Quality
QTL
TriumphlEgmont
Blenheim/E2243
BlenheimIMT8 1143
49
Igri
SCRI
Germany;Winter Feed;
2-row
P. striformis resistance
Malta/Ackerman
1427!/Ingrid
Colter/Kold Igri/Franka
50
Lina
SCRI
Old Scandinavian
variety
SSR map population
NA
NA
51
Plaisant
SCRI
France;Winter Malt 6row
Winterhardiness QTL
Ager/Nymph
Dicktoo!Kompolti
Dicktoo/Plaisant
Continued Table 2.2
52
Acuario
NABGMP
Chile Spring Malting
2-row
53
OWB(D)
NABGMP
Multiple marker stock
NA
54
OWB(R)
NABGMP
Multiple marker stock
NA
NA
INRA.CF.F4:4 1 G/64-6T
(Andes 378.86)
NA
I:
17
Table 2.3. The ninety-six elite lines and varieties from the Busch Agricultural
Resources, Inc. (BARI) barley improvement program used for genetic diversity
characterization with (Simple Sequence Repeat) SSR markers.
Code
1
Line
Six row
ROBUST
2
B 1602
3
CDC SISLER
LEGACY
6B94-8253
6B95-2089
6B95-2482
6B95-2482
6B95-2482
6B95-2482
6B96-3373
6B96-3733
6B97-2037
6B97-2044
6B97-2063
6B97-2195
6B97-2213
6B97-2232
6B97-2245
6B97-2248
6B97-2311
6B97-2404
6B97-2559
6B97-2601
6B98-9008
R2
R3
No.
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
6B98-90 15
6B98-90 19
6B98-9022
6B98-9023
6B98-9025
6B98-9030
6B98-9031
6B98-9032
6B98-9058
6B98-9 102
6B98-9 105
6B98-9 119
6B98-9 170
6B98-9331
Ri
R4
R5
R6
R7
R8
R9
RiO
Ri 1
R12
R13
R14
R15
R16
R17
R18
R19
R20
R21
R22
R23
R24
R25
R26
R27
R28
R29
R30
R31
R32
R33
R34
R35
R36
R37
R3 8
R39
Pedigree
MOREX/MANKER
BUMPERJ6B78-628//MOREX/6B78-628
BT 433: ARGYLE/M34
BUMPER/KARL//BUMPER/MANKER/3/BUMPERIKARL/4/EXCEL
B1614/STANDER
6B84-2912/B1601//6B88-3213
6B89-2126/ND10981
6B89-2126/ND10981
6B89-2126/ND10981
6B89-2126/ND10981
B 1614//6B88-352 1/EXCEL
6B88-3213//6B89-2126/ND1 1055
6B88-321 3/6B90-3645
6B92-7098/STANDER
6B91-6086/EXCEL
6B92-70981M75
6B88-3255/6B91-2002
6B92-7098/M66
6B92-7098/M75
B1614/M75
6B88-3255/6B92-7098
6B88-32 1 3//6B88-3255/6B90-3095
6B92-7098/M75
6B91-2068/M72
6B88-3213/ND14161
6B90-3452//6B90-3452/M75
6B92-8 177/6B93-3 192
6B92-7098/6B92-7 166
6B93-3 192/STANDER
B2912//B2912/ND12201
6B92-7166/6B93-3192
B2912//B2912/ND12201
6B92-7166/STANDER
6B92-7166/STANDER
B1614/M75//STANDER
6B93-3192/M82
6B88-32 1 3//6B92-7098/STANDER
6B92-7098//6B92-7098/M75
6B92-8177/M83
18
Continued Table 2.3
40
6B98-9336
R40
6B93-3 192/EXCEL
41
6B98-9339
R41
B1614/1B1614/M75
42
6B98-9341
R42
6892-8177/EXCEL
43
6B98-935 1
R43
6B92-7098//6B88-3275/6B92-7098
44
6B98-9361
6B88-3213/M82
45
6B98-9363
46
6B98-9366
47
6B98-9381
48
6B98-9395
49
6B98-9438
50
6B98-9464
R44
R45
R46
R47
R48
R49
R50
51
6B98-9466
R5 1
6B88-3213//6B88-32 13/M75
52
6B98-9479
R52
6B88-3213//6B88-3275/M75
53
6B98-9500
R53
6B92-7166/6B90-3452 (BT945)
54
6B98-9508
6B92-7098/ND14119
55
6B98-95 12
R54
R55
56
6B98-95 19
R56
6B92-7098//6B92-7098/6B9 1-6086
57
6B98-9555
6B92-7098/STANDER//B 1614
58
6B98-9558
R57
R58
B2912//B2912/M75
B I 614/6B92-7098//STANDER
6B92-8177/M75
B1614//B1614/M75
6B92-7098/6B92-8 177
6B92-7166/B1614
6B92-7098/ND141 19
6B88-3213//6B88-3275/M75
6B88-3213/!6B91-2486/M75
59
6B98-9586
60
6B98-9603
R59
R60
61
6B98-9749
R61
6B92-8177/6B92-8658 (BT948)
62
STANDER
R62
EXCEL//ROBUST/BUMPER
63
6B98-9786
R63
6B92-7 166/STANDER
R64
R65
B1614/6B92-7098//STANDER
6B92-7166/6B89-2027 (BT941)
6B92-7098/M83
64
6B98-9789
65
6B98-9791
66
6B98-9814
67
6B98-9831
68
6B98-9838
R66
R67
R68
69
6B98-9844
R69
6892-7166/EXCEL
70
6B98-9852
6B92-7 166/STANDER
71
6B98-9868
72
6B98-9876
73
6B98-9879
6B92-7166/B1614
61392-7166/6B89-2027 (BT941)
6B92-7098/6B92-7 166
74
6B98-9889
75
6B98-9896
76
6B98-9920
77
6B98-9921
78
6B98-9940
79
6B98-995 8
80
6B98-9974
R70
R71
R72
R73
R74
R75
R76
R77
R78
R79
R80
81
6B98-9976
R8 1
6B92-7098//B 16 14/M75
82
6B98-9982
6B98-9986
R82
R83
B 16 14/6B92-7098//STANDER
83
6B92-8177/EXCEL
6B92-7166/6B89-2027 (BT941)
6B92-7098//B1614/M75
6B92-7098/STANDERI/B 1614
6B92-8 177/EXCEL
6B92-71661B1614
6B92-7098/6B92-7 166
6B92-7166/STANDER
6B92-7098//B 16 14/6B92-7098
6B92-7098//B 1 614/M75
B 1614/6892-7098//STANDER
19
Continued Table 2.3
6B98-9989
MOREX
88Ab536
EXCEL
84
93
95
96
R84
R93
R95
R96
6B92-7166/6B92-8177
CREE/BONANZA
Ne76129/MOREX!/MOREX
ROBUST/CREE//B ONANZA/MANKER
R85
R86
R87
R88
R89
R90
R91
R92
R94
RPB7O-268/2B75- 1 223//KLAGES
Two row
85
B 1202
86
MERIT
2B96-5038
2B96-5057
2B96-5119
2B96-5216
2B96-5360
2B96-5448
87
88
89
90
91
92
94 HARRJNGTON
MANLEY/2B80-350
2B89-4616/TR226
B 12 15/2B88-5336
2B90-50661TR129
B1215/2B88-5336
2B89-4616/TR226
B1215/2B88-5336
KLAGES/3/GAZELLE/BETZES//CENTENJAL
20
SSR ANALYSIS
DNA was extracted from leaf tissue of 2- to-3 week old plants (one plant per
genotype) using the Qiagen Dneasy 96 Plant Kit. Fifty-five SSRs of known map
location, and distributed throughout the seven linkage groups, were assayed on the 147
accessions using fluorescent-tagged primers. Forty-seven of the SSR primer sets were
developed and mapped by Ramsay et al. (2000), six by Liu et al. (1996) and two by
Becker and Heun (1995). The reverse primers were labeled with FAM, TET, NED or
HEX fluorescent dyes. DNA amplifications were performed using either an MJ
Research PTC-100 or MWG Biotech Primus 96 Plus thermal cycler. PCR reactions
were carried out in a 10
reaction mix containing 37.5 ng of template DNA, lx PCR
buffer, 0.025 units Taq DNA polymerase, (Qiagen), 0.2 mM dNTPs and 0.1 picomol
of forward and reverse primers. Information on primer sequences, and PCR
amplification conditions for each set of primers, are available at Ramsay et al. 2000, in
Liu et al. (1996) and in Becker and Heun (1995).
PCR amplified fragments from differentially labeled SSR primers and with
nonoverlaping fragment sizes were simultaneously analyzed in the same gel lane and
separated on an ABI Prism 377 DNA Sequencer at the Oregon State University
(Central Service Laboratory) or on an ABI Prism 3700 DNA Sequencer at OMIC, Inc.
(Portland, OR.). Gene Scan® software and Genotyper®
software (Applied
Biosystems, Perkin Elmer, Forster City, CA) were used for automated data collection
and to determine the allele sizes in base pairs (bp), based on the internal standard.
21
The ABI Prism systems give allele sizes in numbers of base pairs with to two decimal
places. We rounded fractional numbers to the nearest integer. Alleles with fractional
values O.5 1 were rounded upward, and alleles with fractional values O.50 were
rounded downward. Thus, for a given locus, alleles differing by 1 bp were declared
different.
Only the primer pairs yielding a single amplicon were used for the subsequent
analyses. This led to different numbers of SSRs scored in each of the three sets of
gemiplasm. Fifty-three of the SSRs were single copy in the subsp. spontaneum and
subsp. vulgare mapping population parent accessions and two were multicopy;
accordingly 53 SSRs were assayed in these two sets of germplasm. Of the 55 SSRs,
four were multicopy in the BARI germplasm. For seven of the primer sets, no
amplification products were obtained after two attempts. Accordingly, 44 SSRs were
assayed in the BARI gemiplasm. Forty-two of the 44 SSRs assayed in the BARI
germplasm were also scored in the subsp. spontaneum and subsp. vulgare sets and
these 42 SSRs, common to the three groups of germplasm, were used for the diversity
analyses, as described in the next section.
Eighteen of the 42 SSRs used for the cluster and principal coordinate analysis (PcoA)
analyses were assayed on subsp. spontaneum, subsp.. vulgare, and BARI accessions
with the ABI Prism 3700. For the remaining 24 SSRs, allele sizes for the BARI lines
were assayed on the ABI Prism 3700 and the
allele sizes for the subsp.
spontaneum/subsp. vulgare germplasm arrays were assayed on the ABI Prism 377. In
order to integrate ABI Prism 377 and ABI Prism 3700 data, the allele sizes of cultivar
22
Morex were as used as a reference. This cultivar was run for every SSR on both
platforms. SSR allele sizes for each BARE accession obtained from the ABI Prism
3700 were adjusted to ABI Prism 377 allele sizes based on the number of base pairs
differences observed for Morex. Cultivar Morex alleles for the same SSR locus were
consistently two or three base pairs smaller on the ABI Prism 3700.
On either
platform, however, repeated assessment of the same SSR gave highly reproducible
allele sizes.
DATA ANALYSIS
The genetic distance (D) among genotypes was estimated based on the proportion of
shared alleles (ps) using the formula D = 1
ps, implemented in Microsat (Minch et
al. 1997). The genetic distance matrix was used to determine the clusters of genotypes
using the unweighted pair group method arithmetic average (UPGMA) employing
NTSYSpc 2.01 (Roelf 1997). In order to assess the non-randomness of the
dendrogram, cophenetic values were computed. The normalized Mantel statistic Z
value (equivalent to the product-moment correlation coefficient r) was calculated as
described in Roelf (1997). Graphical representation of the estimated genetic
similarities between genotypes was obtained by Principal Coordinate Analysis (PcoA)
using NTSYSpc 2.01 (Roelf 1997), based on the matrix of genetic distances.
To measure the informativeness of each SSR, the polymorphism information content
(PlC) was calculated using the following formula:
plc = 1
23
where P is the frequency of the
jth
SSR allele (Smith et al. 2000). The cluster analysis
and the PcoA were performed using the 42 SSRs common to all 147 accessions. The
exclusive alleles, (allele found only in one genotype) were resolved using the taxonspecific alleles option in Microsat (Minch et al. 1997).
24
RESULTS AND DISCUSSION
NUMBER OF ALLELES AND PlC VALUES
As shown in Table 2.4, the SSRs were highly polymorphic. Considering the 42 SSRs
that were assayed on all 147 accessions there were 687 alleles, with an average of 16.3
alleles per locus. The number of alleles per locus ranged from 4 (HvLOX) to 32
(Bmag0007). Considering each group of gemiplasm, the highest average number of
alleles was detected in subsp. spontaneum, with 10.3 alleles per locus, followed by
subsp. vulgare with 8.3 and the BARI germplasm with an average of 5.8 alleles per
locus (Table 2.4). The highest number of alleles per SSR locus reported in barley is
37, based on HVM4 assayed on 104 accessions of subsp. vulgare and 103 accession of
subsp. spontaneum (Saghai-Maroof et al. 1994). These authors reported an average of
18 alleles per locus, based on four SSRs assayed in the 207 genotypes. Other
investigators have reported lower average numbers of alleles per locus in barley,
ranging from 2.1 (Becker and Heun 1995) to 12.2 (Dávila et al.1999). The number of
alleles detected will depend, in large part, on the diversity of germplasm sampled. We
found the lowest number of alleles per locus in the BARI germplasm. This very
narrow germplasm base is typical of malting barley improvement programs, which
must meet strict malting quality criteria.
Many of the alleles were exclusive, meaning they were unique to a single accession.
As shown in Table 2.4, considering all 147 accessions, 177 unique alleles were
25
identified in subsp. spontaneum (25.8%), 71 in subsp. vulgare (10.3%) and 37 in the
BARd group (5.4%). The presence of so many unique alleles could be an indication of
the relatively high rate of mutation at SSR loci and/or the inclusion of exotic
germplasm in our sample (Senior et al. 1998; Henderson and Petes 1992; Liu et al.
2000). Unique alleles are important because they may be diagnostic of particular
inbred lines or for regions of the genome specific to a particular type of genotype
(Senior et al. 1998).
Table 2.4. Number of alleles, amplicon size range (base pairs (bp)), number of
unique and common alleles, and total number of alleles for each (Simple Sequence
Repeat) SSR locus in three groups of barley germplasm: subsp. spontaneum,
subs p.vulgare and a sample of germplasm from the Busch Agricultural
Resources, Inc.(BARI) breeding program.
Locus
Number of alleles
subsp.
subsp. BARI
spontaneum vulgare
Size range
(bp)
Number of Unique Alleles
Common
subsp. BARI
subsp.
spontaneum vulgare
Total
19
11
9
159-241
iS
2
4
11
32
3
5
3
132-143
1
2
0
3
6
*
*
114-130
*
*
*
*
*
5
BmagOI2O
15
12
8
4
2
12
27
16
14
10
211-275
106-215
9
BmacOl5ó
9
2
3
16
30
HVM36
Bmag0378
10
11
4
105-149
5
4
0
7
16
7
9
5
1
3
10
14
BmacOO93
HVM63
12
6
7
131-150
138-164
0
6
0
0
8
14
7
2
4
119-139
2
0
0
5
7
Hv5s+
BmagOI25
*
*
6
236-257
*
*
*
*
*
12
14
5
116-147
4
5
0
15
24
HVM54
12
11
9
144-171
4
2
1
13
20
EbmacO4I5
10
6
4
225-256
4
2
1
6
13
HvLTPPB+
BmagOJ36
3
*
217-225
*
*
*
*
*
5
4
3
5
198-208
1
0
0
6
7
Bmag0007
HvCMA
Bmac273+
BmacOO67
14
8
6
151-244
8
2
1
10
21
BmacO2O9
9
*
179-202
*
*
*
*
*
13
Bmag0225
10
8
12
131-166
2
0
1
16
19
BmagOOJ3
11
9
7
131-179
5
4
1
12
22
HVM62
10
9
5
224-259
3
1
2
8
14
26
Continued Table 2.4
HVM4O
17
8
BmacO3lO
13
Bmag0353
HVMO3
BmacOlSl
Bmag0384
EbmacO7Ol
HvMLO3
HVM67
10
Bmac0339
BmacO2J3
Bmac0032
9
10
14
11
9
BmacOO9O
11
9
3
HVM2O
14
9
4
BmagO2lI+
11
8
*
Bmag0382
HVHVAI+
WMCIE8+
12
5
*
3
4
*
5
5
*
BmacO3I6
BmagO2J8
BmagOl73
BmacOOl8
Bmag0009
15
12
4
3
140-165
6
1
1
12
11
9
136-185
3
2
2
15
12
10
4
1
0
14
19
16
15
11
7
4
2
13
26
10
7
8
90-125
155-212
163-186
107-123
113-178
2
0
0
12
14
1
0
0
8
7
1
2
11
230-250
106-119
2
1
1
2
6
2
0
0
9
11
125-206
145-221
*
*
*
*
*
2
3
1
11
17
8
6
2
14
12
8
5
3
3
10
7
2
*
11
6
7
3
1
12
4
2
0
8
14
6
2
0
8
16
*
*
*
*
*
84-1 17
*
*
*
*
*
137-141
*
*
*
*
*
190-208
*
*
*
*
*
4
131-197
8
3
0
12
23
2
162-2 12
0
1
0
5
6
204-287
181-227
128-168
175-196
13
12
106-215
7
5
6
9
6
0
EBmacO8O6
9
8
5
134-152
170-200
159-174
BmacO3O3
16
11
6
Bmag0337
12
9
5
BmacOO96
12
8
4
EbmacO97O
4
4
3
EbmacO684
7
13
6
BmacOII3+
Bmag0223+
17
10
*
15
19
*
HVM3O
6
5
2
HvLEU+
HvLOX
Bmag0222+
Total
3
3
*
3
++Ø
3
13
8
*
545
440
255
8.3
5.8
10.3
21
23
11
Average
20
22
8
3
1
2
18
24
1
1
3
8
13
3
0
0
7
10
3
1
1
8
13
105-148
115-146
9
1
0
15
25
8
2
2
7
19
156-186
115-199
148-190
170-250
122-184
112-149
5
2
1
8
16
1
1
1
3
6
3
5
0
9
17
*
*
*
*
*
*
*
*
*
*
0
0
0
7
162-167
149-156
151-189
*
*
*
+: SSRs not included in the unique allele analysis
++: Not polymorphic in subsp. vulgare group
*: Data not available
*
1
0
1
2
*
*
*
*
*
177
71
37
402
687
16.3
27
The occurrence of the highest number of unique alleles in the subsp. spontaneum
accessions is an indication of the diversity present in this germplasm and its potential
as a reservoir of novel alleles for crop improvement. To date, H. vulgare subsp.
spontaneum has served as a source of novel alleles at known loci (e.g. Bamyl)
(Erkkila et al. 1998), and a source of entirely new alleles e.g. the scald-resistance gene
Rrs 14 located in chromosome 5(1H) (Garvin et al. 1997), which corresponds to no
known scald resistance gene in cultivated barley.
Considering the entire germplasm array, PlC values ranged from 0.08 to 0.94 (Table
2.5). The PlC values for the 53 SSRs surveyed in both the subsp. spontaneum and
subsp. vulgare accessions ranged from 0.12 (BmagO2l8) to 0.94 (Bmag0007, HVM4O
and Bmag0223). The average within the subsp. spontaneum group was 0.79, while the
average within the subsp. vulgare group was 0.75. Within the subsp. vulgare group,
PlC values ranged from 0.12 (BmagO2l8) to 0.94 (Bmag0223) while the PlC values
within subsp. spontaneum ranged from 0.42 (HvCMA) to 0.94 (Bmag0007 and
HVM4O). Within the BARI group the PlC values ranged from 0.08 (BmacOO96) to
0.84 (BmagOl 73), with an average of 0.43. Similar PlC values for SSRs are reported
in the literature (Saghai-Maroof et al. 1994; Dávila et al. 1999; Struss and Plieske
1998). In one of the most recent SSR studies in barley, lower PlC values of 0.14
0.78 were reported (Pillen et al., 2000). This may be because the SSRs were derived
from DNA sequence databases. Cho et al. (2000) compared genomic library-derived
with GenBank-derived microsatellites in rice, and reported lower PlC values for the
latter. In general, we found higher PlC values for SSRs with higher numbers of alleles,
28
as did Pillen et al. (2000). We did find high PlC values for some SSRs, even in the
narrow genetic base of the BARI germplasm, which indicates that some SSRs are
useful for differentiating between closely related accessions.
Table 2. 5. Chromosome location, map position (according to Ramsay et al., 2000
and Macaulay et al., 2001) and polymorphism information content (PlC) values for
(Simple Sequence Repeat) SSR loci assayed in three groups of barley germplasm:
subsp. spontaneum, subsp. vulgare, and a set of lines from the Busch Agricultural
Resources Inc. (BARI) breeding program.
plc
spontaneum
vulgare
BARI
Chromosome
cM
Bmag0007
1(7H)
27
0.94
0.83
0.71
HvCMA
1(7H)
85
0.42
0.67
0.19
Bmac273
BmagOl2O
BmacOI56
1(7H)
93
*
*
0.21
1(7H)
118
0.90
0.87
0.55
1(7H)
153
0.93
0.92
0.67
HVM36
Bmag0378
2 (2H)
17
0.69
0.87
0.12
2 (2H)
44
0.87
0.63
0.69
BmacOO93
2 (2H)
50
0.87
0.76
0.39
HVM63
Hv5s
BmagOI25
HVM54
2 (2H)
50
0.59
0.28
0.68
2 (2H)
62
*
*
0.40
2 (2H)
63
0.86
0.89
0.40
2 (2H)
103
0.88
0.89
0.73
EbmacO4l5
2 (2H)
105
0.81
0.65
0.45
HvLTPPB
BmagOI36
3 (3H)
25
0.58
0.49
*
3 (3H)
50
0.61
0.39
0.61
BmacOO67
BmacO2O9
3(3H)
54
0.91
0.82
0.43
3 (3H)
55
0.91
0.84
*
Bmag0225
3 (3H)
74
0.81
0.85
0.63
BmagOOl3
HVM62
3 (3H)
141
0.88
0.75
0.61
3 (3H)
154
0.84
0.84
0.65
HVM4O
BmacO3]O
4(4H)
14
0.94
0.82
0.23
4(4H)
43
0.92
0.88
0.67
Bmag0353
HVMO3
4(4H)
45
0.81
0.88
0.81
4(4H)
45
0.92
0.93
0.76
BmacOl8l
Bmag0384
4(4H)
46
0.87
0.79
0.70
4(4H)
49
0.84
0.80
0.37
4(4H)
78
0.86
0.88
0.33
4(4H)
95
0.58
0.53
0.44
4(4H)
118
0.75
0.83
0.19
Locus
EbmacO7Ol
HvMLO3
HVM67
subsp.
subsp.
29
Continued Table 2.5
Bmac0399
5 (1H)
BmacO2l3
5 (1H)
Bmac0032
5(1H)
BmacOO9O
5 (1H)
HVM2O
5 (1H)
BmagO2lJ
5 (1H)
Bmag0382
5 (1H)
HVH VA]
5 (1H)
WHC]E8
5(1H)
BmacO3l6
6 (6}{)
BmagO2I8
6(6H)
BmagOl73
6 (6H)
BmacOOl8
6 (6H)
Bmag0009
6 (6H)
EbmacO8O6
6(6H)
BmacO3O3
7(5H)
7(5H)
7(5H)
7(5H)
7(5H)
7(5H)
7(5H)
7(5H)
7(5H)
7(5H)
7(5H)
Bmag0337
BmacOO96
EbmacO97O
EbmacO684
Bmac0113
Bmag0223
HVM3O
HvLEU
HvLOX
Bmag0222
Means
25
28
55
58
58
62
97
112
164
6
78
79
102
103
119
30
35
41
54
58
61
69
69
70
114
162
0.87
0.84
0.92
0.79
0.92
0.89
0.90
0.50
0.71
0.90
0.49
0.90
0.71
0.75
0.80
0.85
0.87
0.81
0.84
0.83
0.77
0.81
0.52
0.66
0.82
0.12
0.91
0.62
0.63
0.81
0.92
0.85
0.87
0.57
0.79
0.92
0.91
0.73
0.43
0.50
0.90
0.79
0.82
0.86
0.78
0.62
0.88
0.79
0.94
0.53
0.40
0.00
0.83
0.75
*
0.20
0.41
0.21
0.39
*
*
*
*
0.45
0.14
0.84
0.25
000
0.49
0.76
0.23
0.08
0.15
0.25
*
*
0.17
*
0.14
*
0.43
+: Bmag0009 was not polymorphic in the BARI lines
++: HvLOX was not polymorphic in subsp. vulgare
*:Data not available
We used two tools to visualize estimates of genetic distance: Cluster Analysis and
Principal Coordinate Analysis. The two tools led to similar classifications; for
simplicity, the results of the two analyses will first be presented individually. At the
conclusion of this section, we will highlight key issues emerging from the two
approaches.
There was excellent agreement between the original genetic distances matrix and the
matrix of cophenetic values computed from clustered data, as measure by the
30
MANTEL test, which gave a product-moment correlation of r = 0.97 (P<0.004). In the
cluster analysis we were able to differentiate between all subsp. spontaneum, subsp.
vulgare and BARI accessions. Only accessions R7 and R9 from the BARI group could
not be differentiated; these are sister lines from the same cross. The dendrogram
(Figure 2.1) confirms the high level of genetic diversity within the subsp. spontaneum
accessions and within the subsp. vulgare accessions and the low level of diversity
present within the six-row BARI germplasm.
Four main clusters were identified within the subsp. spontaneum accessions (labeled I,
II, XVII and XVIII in Figure 2.1). The genetic distances at which these clusters
diverged averaged 0.84. The subsp. spontaneum accession HS92 originated in Israel
(Pakniyat et al. 1997) and subsp. spontaneum accession OSU8 diverged from the other
accessions at a genetic distance of 0.93. The accession HS92 was a parent of the
mapping population used to map the majority of the SSRs included in our survey
(Macaulay et al. 2001).
In general the clustering patterns of the subsp. spontaneum accessions relate to
geographical origin. Cluster I consists of accessions from East Asia, Tibet,
Afghanistan, Pakistan, Turkmenia, Azerbaijan, Iraq and Iran and only one accession
from Israel (OSU1 5). Two interesting exceptions are the parents of the Oregon Wolf
Barley population (OWB-D and OWB-R). These are subsp. vulgare multiple marker
stocks carrying dominant and recessive alleles, respectively, at loci defining the major
germplasm groups and domestication phenotypes in barley (Costa et al. 2001;
http://www.css.orst.edu/barley/WOLFEBAR/WOLFNEW.HTM).
Three
other
31
accessions within this cluster are Cyrrhus, a Syrian land race, Kakaihadaka, a winter
habit, hull-less food type from Japan, and C110587 a source of Russian Wheat Aphid
Resistance originating in North Africa. Cluster II includes two subsp. spontaneum
collected in Israel, but this cluster is distinct from the accessions in cluster XVIII,
which also originated in Israel. Other researchers have reported that classifications of
subsp. spontaneum accessions based on RFLPs (Petersen et al. 1994), AFLPs
(Pakniyat et al. 1997) and SSRs (Struss and Plieske 1998; Ivandic et al. 2002) reflect
geographic origin. Ivandic et al. (2002) explored this correspondence of allelic
structure and geographic origin and identified SSRs thought to be associated with
genes determining phenotypes conferring adaptation to specific environments.
The sample of subsp. vulgare mapping population parents and lines of interest to our
breeding program formed three clusters, III, XIV and XV, with the aforementioned
exceptions of OWB-D, OWB-R, Cyrrhus, CI 10587, and Kikaihadaka. This clusters
diverged at an average genetic distance of 0.79. These three clusters, represent
accessions corresponding to geographic origin, end-use and! or growth habit.
32
osui
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874
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R2 8
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R3 5
RB 3
564
R36
R4 0
R3 9
R6 0
Re 7
566
547
557
553
Ri 1
R5 0
554
Ri
5
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522
R84
829
STANDER
834
80
545
831
563
576
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rR4
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196 5
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569
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526
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R4 8
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512
816
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87
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88*6536
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589
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51 2 0 2
HARRI NOT ON
rI1
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8
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02
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1
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0 25
I
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0 48
I
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0 70
I
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0 93
I
Figure 2.1. Dendrogram of 22 Hordeum vulgare subsp spontaneum, 32 H. vulgare subsp vulgare
mapping population parents and genetics stocks, and 96 elite breeding lines and standard varieties based
on the genetic distance (D) as measured by allelic variation at 42 SSR loci
33
For example, in the clusters XIV and XV there are only two-row barleys that include
accessions from Europe, South America, and Australia. Haruna-nijo (Japan), Sloop
and Schooner (Australia), Acuario (Chile), Lina, Barke, Alexis, Derkado, Blenheim
(all European Union) and Galena (USA) are all spring habit two-rows used for
malting. Baronesse is a European Union (EU) two-row feed barley, and currently the
most widely grown feed variety in the Pacific Northwest of the USA. The number of
fertile florets per rachis node (two rowed vs. six rowed) defines the two major
germplasm groups within cultivated Hordeum. Two loci
the centromeric region of chromosome 2 (2H), and the
chromosome 4 (4H)
the vrsl locus located in
mt-c
on the short arm of
control this trait (Franckowiak and Lundqvist 1997; Lundqvist
and Franckowiak 1997). The Japanese and Australian two-rowed malting germplasm
was introduced from Europe approximately 100 years ago, and thus trace to a common
geographic origin. The varieties Galena and Merit are unique amongst the North
American two-rows in that they have European germplasm in their pedigrees.
The remaining accessions within cluster III include two-row and six-row accessions,
and accessions of diverse growth habit and origin. The genetic distances of 0.36 to
0.68 shown by these lines are one of the reasons that extensive linkage and QTL
mapping experiments are possible in crosses between cultivated barley (Hayes et al.
2002;
http://www.css.orst.edu/barley/nabgmp/gtlsum.htm).
intuitively reasonable
Some subgroups are
e.g. Kold and Strider are six-rowed winter habit barley
varieties released by our breeding program.
However, in other cases, quite
phenotypically distinct accessions trace to a common branch, e.g. Colter (a spring six-
34
row) from the USA and Shyri (a two-row developed in Mexico and released as a
variety in Ecuador). Our inclusion of these two varieties is that Colter is a locally
adapted, agronomically high performing genotype that is susceptible to barley stripe
rust (incited by Puccinia striformis fs.p. hordei) whereas Shyri has quantitative
resistance to this disease (Toojinda et al., 2000). Another reason for the clustering of
lines of diverse morphology, origin and/or end use may be due to the fact that three
genotypes (Shyri, Gobernadora and CMB 643) are from the ICARDA/CIMMYT
program, which uses long-term recurrent selection in very broad germplasm bases.
This breeding strategy may have disrupted marker: phenotype linkage relationships
that in other germplasm combinations led to patterns of genetic relatedness based on
origin, growth habit, or inflorescence type. Furthermore, Orca, Tango and CR 30-3 are
lines derived from marker-assisted introgression of quantitative disease resistance
genes from ICARDA/CIMMYT germplasrn into genetic backgrounds adapted to the
region serviced by our own breeding program.
Groups IV to XIII, and XVI comprised of BARI elite lines and North American barley
malting varieties are clearly more related than the other germplasm we sampled. The
cultivar Excel is not in any cluster but appears related with the six-row group. The
variety Excel is a six- row and the immediate parents of this variety are all six-rows,
and it is a parent of accessions that are present in groups IV-XIII. Genetic distances
within this group ranged from 0.03 to 0.42 in the six-row germplasm and from 0.25 to
0.50 in the two-row germplasm. This narrow genetic base, relative to the other
germplasm sampled, reflects the focus on specific malting quality attributes for the
35
North American market. Malting quality is the sum total of many components traits,
each of which individually show complex inheritance (Hayes et al. 2002). Breeders of
malting barley varieties have usually dealt with this complex inheritance by fixing as
many alleles as possible at loci determining malting quality characteristics. The result
has been an inevitable narrowing of the germplasm base.
The North American two rowed and six rowed malting barley germplasm pools have
distinct quality profiles (Marquez-Cedillo et al. 2000), and this was reflected in the
separation of the BARI germplasm and parental lines (groups IV
XIII vs. group
XVI).
The North America two-row malting varieties (group XVI) are distinct from the tworow malting accessions from Japan, Australia and Europe (groups XIV and XV). The
requirements of the North American malting and brewing industries are quite different
than those employed throughout the rest of the world. Although the North American
varieties trace to European introductions made within the past 100 years, very
different SSR alleles have been carried to fixation. In most cases, there has been little
germplasm infusion from outside North America since the initial introductions.
We found SSRs to be useful in defining meaningful relationships with a narrow
gerrnplasm base, such as the BARI six-rows. Pillen et al. (2000) and Dávila et al.
(1999) also found SSRs to be useful for discriminating between closely related
genotypes, although Russell et al. (1997b) and Plaschke et al. (1995) reported that
SSRs were not useful for classifying germplasm of related pedigree. Within the BARI
six-rows, there were subgroups clustered around the North American variety
36
standards, and these groups reflect the modest shifts in variety performance and
malting quality requirements over a 15-year period. The varieties Morex, Robust,
Excel, and Stander were released by the Minnesota Agricultural Experimental Station
beginning in 1978 with Morex and culminating in 1993 with Stander. The BARI
experimental lines form subgroups around these variety standards (except Excel, as
previously noted) based largely on pedigree. These genetic relationships may have
predictive utility in terms of identifying regions of the genome harboring genes which
determine the subtle differences in quality parameters of these variety standards and
their derived lines. This subject will be dealt with at greater length is a subsequent
report.
The second approach we used to assess the utility of SSRs for germplasm
classification was principal coordinate analysis (PCoA). A two dimensional plot of the
PCoA is shown in Figure 2.2. The first principal coordinate accounted for 31.6% of
the total variation and the second accounted for 8.2% of the total variation. The first
principal coordinate clearly differentiated between the six-row BARI accessions and
all other germplasm. The second principal coordinate differentiated between the tworow BARI accessions, the North American two-row varieties, and the remainder of the
germplasm sample. This separation of North American elite six-row and two-row
selections and varieties from the other germplasm sampled corroborates the results of
the cluster analysis. However, the PcoA approach revealed some interesting patterns
not immediately apparent in the cluster analysis. For example, the variety CDC Sisler,
a recent Canadian malting six-row, is differentiated from the BARI six-rows and
37
varieties released by the University of Minnesota (Morex, Robust, Stander and Excel).
Likewise, the variety Merit and the experimental line R89 are differentiated from the
other North American two-rows. These two selections have European two-row
germplasm in their pedigrees (L. Wright, personal communication).
As in the cluster analysis, PCoA identified a distinct group of European two-row
malting varieties, although the composition differed slightly from the cluster analysis.
Members common to both groups are Derkado, Barke, Alexis, Bleinheim, and
Baronesse. The varieties Galena, Igri, Lina, Gobernadora, Sloop and Schooner shifted
in their alignments between the two approaches. The subsp. spontaneum accessions
were differentiated from other accessions, although the winter six-row varieties Strider
and Kold and the facultative variety Steptoe were grouped with the subsp. spontaneum
accessions. Pillen et al. (2000) and Dávila et al. (1999) also found that winter habit
barley varieties were genetically more similar to subsp. spontaneum than spring habit
subsp. vulgare. The sample of cultivated subsp. vulgare germplasm of interest to our
own breeding program, which was poorly differentiated in the cluster analysis, was
also scattered in the PCoA.
0D
-
UH647
IJH628
28 -
17
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92
55-0.55
I
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0.5!
pci
Figure 2.2. Biplot of the first two principal coordinates for 22 Hordeum vulgare subsp spontaneum, 32 Hordeum vulgare subsp vulgare
mapping population parents and genetics stocks, and 96 elite breeding lines and standard varieties based on the genetic distance (D) as
measured by allelic variation at 42 SSR loci.
00
39
Our results demonstrate that this set of SSRs was highly infonnative in a range of
barley germplasm. The SSRs had high PlC values, many were multi-allelic, and there
were many unique alleles. From a breeding perspective, germplasm is often
considered to be "adapted", "exotic", or "ancestral". In our case, these three types of
gennplasm could be distinguished, based on their SSR allele architecture. The
germplasm classifications generally coincided with geographic origin (e.g. subsp.
spontaneum accessions from different parts of the Middle East) and end-use (e.g.
European spring habit malting two-rows vs. North American malting two-rows and
six-rows).
There was an interesting exception to expected groupings, namely the relatedness of
the Oregon Wolfe Barley genetic stocks to subsp. spontaneum. This intriguing
exception provides opportunities to test hypotheses regarding novel alleles. The next
question, which we propose to address in future reports, is the utility of SSRs diversity
as a tool for gene discovery in germplasm arrays. Ivandic et al. (2002), for example,
presented some exciting preliminary data on the utility of SSRs for association
analysis.
As described in Tables 2.1, 2.2 and 2.3, accessions within this array include: (i)
parents of linkage, QTL, and physical mapping populations, (ii) parents of specialized
genetic stocks, including Recombinant Chromosome Substitution, isogenic lines, and
transposon tagging stocks, (iii) sources of genomic DNA for BAC libraries, (iv)
sources of gene transcripts for ESTs, and (v) sources of unigenes for microarrays. The
40
public availability of this germplasm array, and the accompanying data, will be a
resource of long-term utility to the plant genetics community.
Acknowledgements: This research was supported by the North American Barley
Genome Project (NABGP) and Busch Agricultural Resources, Inc. We would like to
thank the Scottish Crop Research Institute for their generous prepublication sharing of
SSR primer sequences.
41
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46
DEVELOPMENT AND CHARACTERIZATION OF RECOMBINANT
CHROMOSOME SUBSTITUTION LINES (RCSLS) USING Hordeum vulgare
subsp. spontaneum AS A SOURCE OF DONOR ALLELES IN A Hordeum
vulgare subsp. vulgare BACKGROUND
I. Matus1, A. Corey1, T. Filichkin1, P. M. Hayesl*, J. Kling', K. Sato2, W.
Powell3
and
R. Waugh3
1Dept. of Crop and Soil Science, Oregon State University.
253 Crop Science Building, Oregon State University, Corvallis, OR 9733 1-3002, USA
2
Research Institute for Bioresouces, Okayama University, Kurashiki 710, Japan
Scottish Crop Research Institute, Invergowrie, Dundee DD2 5DA, UK
Received
*conesponding author, to whom proofs should be sent
Oregon Agricultural Experiment Station Journal No.
47
ABSTRACT
The ancestor of barley (Hordeum vulgare subsp. spontaneurn) may be a source of
novel alleles for crop improvement. We developed a set of "Recombinant
Chromosome Substitution Lines" (RCSLs) using an accession of Hordeum vulgare
subsp. spontaneum (Caesarea 26-24, from Israel) as the donor and "Harrington" (the
North American malting quality standard) as the recurrent parent via two backcrosses
to the recurrent parent, followed by six generations of selfing. Here we report (i) the
genomic architecture of the RCSLs, as inferred by Simple Sequence Repeat (SSR)
markers and (ii) the effects of Hordeum vulgare subsp. spontaneum genome segment
introgressions in terms of three classes of phenotypes: inflorescence yield components,
malting quality traits, and domestication traits. Significant differences among the
RCSLs were detected for all phenotypes measured. The effects of the introgressions
were assessed using association analysis, and these changes were referenced to
Quantitative Trait Loci (QTL) reported in the literature. H. spontaneum subsp.
spontaneum, despite its overall inferior phenotype, contributed some favorable alleles
for agronomic and malting quality traits. In most cases, the introgression of the
ancestral genome resulted in a loss of desirable phenotypes in the cultivated parent.
This may a useful tool for gene discovery and validation.
48
INTRODUCTION
Plant breeders have long been interested in using germplasm collections as resources
for crop improvement. Such collections are considered reservoirs of favorable alleles
not present in existing cultivars. Within a gennplasm collection, the frequencies of
these favorable alleles may be low, which makes their identification and utilization
difficult (Martin et al. 1996). This is particularly important in the case of wild species,
which often have inferior phenotypes for many characters of agronomic importance.
Whatever favorable alleles such ancestral species may contain are masked by the
agronomically unacceptable phenotype (Sorrells and Wilson 1997).
Tools developed for the genetic dissection of traits in cultivated germplasm can also
be used to identify and extract useful genes from the crop progenitors (Tanksley and
Nelson, 1996). Tanksley and McCouch (1997) described the need to thoroughly
evaluate exotic germplasm since the accessions that are most distinct from modern
cultivars may also contain the highest number of unexploited useful alleles. However,
plant breeders have long appreciated that agronomic performance suffers when exotic
germplasm is introduced into elite germplasm. This is attributed to linkage drag and/or
epistasis (Young and Tanksley, 1989; Tanksley et al. 1989; Vetelainen, 1994;
Kannenberg and Falk, 1995; Hawtin et al., 1996; Vetelainen et al., 1996; Brondani et
al. 2002). The development of DNA fingerprinting tools led to a renewed interest in
introgressing favorable alleles from exotic and wild gennplasm and successes have
49
been reported in tomato (Young and Tanksley, 1989; Fulton et al. 1997; Fulton et a!
2000), pearl millet (Poncet et al 2002), and rice (Xiao et al 1996).
The first example of this application of genotype information to germplasm
introgression was the Advanced Backcross strategy proposed by Tanksley and Nelson
(1996). This strategy uses molecular markers to identify beneficial alleles from
unadapted germplasm that are valuable for the improvement of elite cultivated
germplasm.
Barley is a crop of worldwide importance (Hayes et al. 2002) and while there
continues to be improvement in crop performance, the level of genetic diversity in
many barley breeding programs is limited (Matus and Hayes, 2002). Expanding the
genetic base of the crop is, therefore, important for continued crop improvement. The
ancestor of barley
(Hordeum vulgare
subsp.
spontaneurn)
may be a source of novel
alleles lost during the domestication process (Nevo, 1998). These may be new alleles
at loci where allelic variation has already been detected in cultivated barley (Erkkila et
al., 1998) or they could be variant alleles at loci where there is no allelic variation in
cultivated barley (Garvin et al., 1997; Lehmann et al. 1998). Accordingly, one of our
objectives was to apply the advanced backcross technique to barley, an application
that has not been reported, and to determine the effectiveness of the technique for
introgressing novel alleles from an accession of the crop ancestor.
A second and simultaneous objective was to use the lines developed by the advanced
backeross procedure as a tool for detecting and validating genes determining
quantitatively inherited phenotypes, Quantitative Trait Loci (QTL). In this context, a
1I]
set of germplasm introgression stocks can be defined as a set of Recombinant
Chromosome Substitution Lines (RCSLs) (Paterson et al., 1990; Thomas et al., 2000)
since the recombination events leading to germplasm introgressions are defined with
molecular markers. This information can be used for QTL validation and discovery
through a change in phenotype of the recurrent parent as a result of a specific alien
introgression. In order to identify such changes, due to introgression events, we used
the analysis procedure described by Grupe et al. (2001). This method involves
identifying phenotypic differences associated with differences in allele frequency
(Risch and Merikangas, 1996; Lander, 1996; McPeek, 2000; Nadeau and Frankel,
2000).
Here we report the genomic architecture of a set of RCSLs, as revealed by molecular
marker fingerprinting using Simple Sequence Repeats (SSRs), and the effects of
introgressions of H. vulgare subsp.
spontaneum
genome segments into the variety
"Harrington" in terms of three classes of phenotypes: inflorescence yield components,
malting quality traits, and domestication traits. In a subsequent report we will present
results from a more extensive characterization of agronomic and malting quality traits
in a selected subset of this germplasm.
51
MATERIALS AND METHODS
GERMPLASM DEVELOPMENT
RECOMBINANT CHROMOSOME SUBSTITUTION LINES
A Recombinant Chromosome Substitution Line (RCSL) population was developed
using the Advanced Backcross strategy of Tanskley and Nelson (1996). An accession
of Hordeum vulgare subsp. spontaneum (Caesarea 26-24) was the donor parent and
Hordeum vulgare subsp. vulgare cv. Harrington was the recurrent parent. The donor
parent was selected based on its genetic distance from Harrington (Matus and Hayes,
2002),
its
origin,
and
its
passport
data
(http://www.css.orst.edu/barley/nabgmp/germplasm.htm). Harrington was selected
because it is the North American two-row malting quality standard and the focus of
genomics research (Marquez-Cedillo et al., 2000). The recurrent parent was used as
the female and the donor as the male to obtain the F1 generation. For the BC1 and BC2
generations, the recurrent parent was used as the male. The development of the RCSLs
is shown in Figure 3.1. One hundred forty three BC1 plants were each backcrossed to
Harrington to generate the BC2 generation. From each BC2 plant, four seeds were
planted to obtain 572 BC2F1 plants. Three seeds were planted from each BC2F1 plant
generating 1716 BC2F2 plants. From each of these sets of three plants one plant was
randomly selected and four seeds were planted to obtain the
BC2F3 generation.
Subsequently, single seed descent (SSD) was used to advance progeny to the F6
52
generation. Each set of four BC2F6 plants (from a total population of 572) traces to a
single BC1 plant, as shown in Figure 3.1. All crosses and generation advance were
conducted under greenhouse conditions. There was no selection during generation
advance, because we were concerned that selection against unfavorable wild donor
traits could lead to a loss of linked favorable alleles.
Harrington x Caesarea 26-24
Harrington
F1
1
BC1
1
.......... 5 ............. 10 ............ 20 ............ 30 ............... 40 ............. 50 ............. 60 ............ 70 ....... 143 n= 143
x
BC2
BC2F1
BC2F2
4
Harrington
11=
...................................................................... o
1.1 1.2
1.3 1.4 ...... 5.1
1.1.1:3:i
143
.2 5.3 5.4 .............. 3 ).1 30.2 30.3 30.4 ................. 143.1 143.2 143.3 143.4 n=572
.............................
/
30.2.1
0.3
30.4.1 ........... 143.1.1
43.2
143.3.1
43.4
n1716
71..3T1j3
fK
BC2F3
1.1.3 1.2.1 1.3.3 1.4.2 .................... 30.1.2 30.2.3 2 0.3.1 30.4.2 ........................ 143.1.3 143.2.1 143.3.3 143.4.1 n=572
B C2 F4
1.1.3 1.2.1 1.3.3 1.4.2 ..................... 30.1.2 30.2.3 2 0.3.1 30.4.2 ...................... 143.1.3 143.2.1 143.3.3 143.4.1 zi=572
4,4,4,4,
BC1F6
n = 572
Figure 3.1. Development and generation advanced of recombinant chromosome substitution lines (RCSLs) from H.vulgare
subsp. spontaneum/H.vulgare subsp. vulgare (Caesarea 26-24/Harrington) introgression. See text for details.
54
MOLECULAR CHARACTERIZATION
One hundred forty RCSL (BC2F8) plants, plus donor and recurrent parent plants, were
grown in the greenhouse and used for DNA extraction. We used 140 of the available
143 lines in order to maximize throughput given the constraints of 96-well PCR plates
and the inclusion of replicated samples of the parents in each set of PCR reactions.
DNA was extracted from leaf tissue of two
three week old plants using the Qiagen
Dneasy 96 Plant Kit. Forty-seven polymorphic SSRs were selected from the diversity
analysis performed by Matus and Hayes (2002) based on genome distribution and
robustness, and were used for genotyping the RCSL lines and the donor and recurrent
parents. Reverse primers were labeled with FAM, TET, NED or HEX fluorescent dye.
DNA amplifications were performed using either an MJ Research PTC-100 or MWG
Biotech Primus 96 Plus thermal cycler. PCR reactions were carried out in a 10
tl
reaction mix containing 37.5 ng of template DNA, lx PCR buffer, 0.025 units Taq
DNA polymerase, (Qiagen), 0.2 nM dNTPs and 0.1 picomol of forward and reverse
primers. Information on primer sequences, and PCR amplification conditions for each
set of primers, are available in Ramsay et al. (2000), in Liu et al. (1996) and in Becker
and Heun (1995). PCR amplified fragments from differentially labeled SSR primers,
and with nonoverlaping fragment sizes, were simultaneously analyzed in the same gel
lane and separated on an ABI Prism 377 DNA Sequencer at the Oregon State
University Central Service Laboratory. Gene Scan® and Genotyper® Software
(Applied Biosystems, Perkin Elmer, Forster City, CA) were used for automated data
collection and to determine the allele sizes in base pairs, based on the internal
standard.
PHENOTYPIC EVALUATIONS
One hundred and forty three BC2F7 lines, each line tracing to a different BC1 plant, the
recurrent parent (Harrington) and the donor parent (Caesarea 26-24) were grown under
field conditions during the summer of 2000 at the University of California Field
Experimental Station at Tule Lake, California. The donor parent was grown in a single
plot separate from the recurrent parent and the RCSLs due to limited seed supply and
due to concerns that its seed would shatter and contaminate subsequent crops as an
invasive weed. A single-replicate augmented design consisting of eleven blocks was
used; in each block there were thirteen BC2F7 lines and the recurrent parent. Each plot
consisted of two rows, 2.4 m long and spaced 0.25 m rows apart. Plots were seeded
using HEGE head row planter. The seeding rate, irrigation, and fertility were in
accordance with local recommended practice (data available upon request). The plot
size and experimental design were dictated by the limited seed available from the
preceding generation of greenhouse seed increase. We recognize that the phenotype
data from such an evaluation provide only a preliminary assessment of each
genotype's potential. However, this unreplicated single environment characterization
is comparable to the "screening" used for characterizing new accessions in many
breeding programs and germplasm conservation facilities. The recurrent parent
replicated in each block provided a measure of experimental error.
56
Five agronomic, two domestication-related, and five malting quality traits were
evaluated, as described below. Samples of heads and seeds from the donor parent were
collected from the single, isolated plot in order to measure all phenotypes, except for
test weight. There was not sufficient seed produced by the plot for measurement of
this phenotype
YIELD COMPONENTS
Kernel plumpness (KP) was measured as the weight of a 100-g sample of grain
remaining on a 2.38 mm x 1.91 cm slotted sieve after 30 shaking cycles on a Seedburo
strand sizer/shaker. Test weight (TW) was measured as the weight, in grams, of grain
in a one-quart cylinder. This value was divided by 10.99 to convert to kghi1. Before
harvest a random sample of 20 physiologically mature heads was collected from each
plot. These heads were used to measure the number of seeds per head (SH), head
length (HL) and 1000-kernel weight (TKW). SH was calculated as the mean number
of seeds in a random sample of 10 heads. HL was measured on five of the heads used
for SH by measuring the length of the spike (in cm) from the base of the first fertile
floret to the tip of the uppermost seed in the head, exclusive of awns. TKW was
measured on the weight of 1000 seeds obtained after threshing the 20 heads used for
the preceding measurements.
57
MALTING QUALITY TRAITS
A 1 70-g sample of each RCSL line and the recurrent and donor parents was malted
and used to determine malting quality according to the standard procedures of the
USDA/ARS Cereal Crops Research Unit, Madison, Wisconsin. The full results of this
analysis are not reported in this paper. Rather, for illustrative purposes, five principal
malting quality parameters are reported: malt extract (%) (ME), grain protein (%)
(GP), diastatic power (°ASBC) (DP), alpha amylase (200 DU) (AA) and wort betaglucan (ppm) (WBG).
DOMESTICATION-RELATED TRAITS
Head shattering was rated in the field two weeks prior to harvest. Observations were
made based on visual assessment of the presence or absence of shattering. Plots
showing evidence of shattering were wrapped in nylon mesh bags to prevent further
seed loss. More detailed measurements were made on sub-samples of the 20 heads
sampled per plot. Seed retention (SR) was measured as the force in Newtons (N)
necessary to remove the seed from the rachis, and awn retention (AR) was measured
as the force in Newtons (N) necessary to break the midpoint of the awn. SR and AR
were measured using a Hunter force gauge (Model LKG-1; AMETEK, Inc., Hatfield,
PA). For SR, ten seeds were sampled from the central portion of five randomly
selected heads. AR was measured on the same seeds used to measure SR.
58
DATA ANALYSIS
GRAPHICAL GENOTYPING AND MAP ALIGNMENT
Graphical genotypes were generated for each RCSL line using GGT software (Van
Berloo 1999). Linkage map positions (Table 3.1) of the 47 SSRs markers used to
generate the graphical genotypes were inferred from Ramsay et al (2000) and from the
Oregon
Barley
Wolfe
map
(OWB)
(http://www.css.orst.edu/barley/WOLFEBAR/WOLFNEW.HTM).
The
parental
genome ratio was calculated by determining the proportion of the total genome
derived from recurrent parent (Harrington) versus the proportion derived from donor
parent (Caesarea 26-24), as described by Young and Tanksley (1989). Representative
graphical genotypes are shown in Figures 3.3 and 3.4. The graphical genotypes for all
RCSL lines are available in the CD enclosed in the theses.
Allele segregation at marker loci was tested using a
test. The expected allele
frequency of recurrent and donor parent alleles, respectively, in the BC2F8 lines is
87.5% and 12.5%. A graphical display of the observed allele frequency values for the
recurrent parent was generated for each chromosome, and shows the 0.005 confidence
level
limits
(92.8%
and
82.1%).
For
this
graphical
display,
and
Table 3.1. Chromosome location, map position and linkage map bin number for (Simple Sequence Repeat) SSR loci assayed in
recombinant chromosome substitution lines (RCSLs***) derived from the cross of Harrington (recurrent parent) and H. vulgare
subs p.spontaneum accession Caesarea 26-24 (donor parent).
Chri (7H) cM*
Bin** Chr2(2H) cM Bin Cbr3(311)
cM
Bin Chr4(4H) cM Bin Chr5(1H) cM
Bmag0007 27
2
BmacOl34
5
5
HvLTPPB
25
3
HVM4O
14
2
GMS2I
17
2
HvCMA
85
4
HVM36
17
6
51
4
Brnac3lO
43
5
Bmac2l3
28
4
Bmac273
93
6
Bmag378
44
9
BmacOO67
BrnagU225A
74
7
Bmag353
BinacOU32 55
7
107
8
BmacOO93 50
9
Brnag6O6
125
13
Bmagl2O" 118
Ebmag757 142
Bmacl56 156
9
48
Ebmac7Ol 78
HvMLO3 95
7
Bmag5O7
Bmac9O
Bin Chr6(6H) cM Bin Chr7(5H) cM
BmacO3l6 6
Bmag500 38
Bmagl73
BmacI8
79
Bmacl63
10
2
3
Bmac3O3
30
4
7
Binac96
4%
5
58
7
102 8
Btnag223 66
BinagJ25 63 10 BmagOOI3
141
14
12 Bmag2J]
62
9
Bmac4O
143 13 GMSO6I
126
10
Ebmac793 95 12
HVM67
118 13 Binag382 97
12
Ebmac824 141
12
Ebmac4l5 105 13
Ebmag7l8 112
13
Bmag222" 162
Bmag749 142 15
Ebmac783 180
14
GMSOOI
187
* cM position according to the map reported by Ramsay et al (2000)
** Bin map position according to the OWB BIN MAP (http://www.css.orst.edu/barleyfWOLFEBAR/WOLFNEW.HTM. See the text for details on Bin assignment
10
***RCSLs derived from the cross of Harrmgton (recurrent parent) and H. vulgare subsp. spontaneum accession Caesarea 26-24
A
Not included in the association analysis, due to missing data
Bin
1
7
11
12
13
14
60
for other analyses as described in this report, the 47 markers were assigned to
chromosome bins (Table 3.1). The SSRs were assigned to the bins defined by
Kleinhofs and Graner (2001) (http://barleygenomics.wsu.edu/ March, 2002 posting)
and
the
Oregon
Wolfe
Barley
population
data
posted
at
http://www.css.orst.edu/barley/WOLFEBAR/WOLFNEW.HTM. The OWB mapping
population includes both RFLPs and SSRs, allowing for integration of marker position
with reference to the RFLP-based bin map of Kleinhofs and Graner (2001) and the
QTL summary of Hayes et al. (2000). Each bin represents approximately 10cM. Forty
percent of the bins contained an SSR marker, as inferred from map position of these
SSRs in the OWB mapping population. In two cases there were two SSR markers per
bin (bin 9 on chromosome 2(2H) and bin 7 on chromosome 5(1H)).
PHENOTYPE DATA
Data from the Tule Lake field experiment were analyzed with SAS V 8e using PROC
MIXED and considering lines as fixed effects and blocks as random effects. The
Tukey-Kramer test was used to identify significant differences between the recurrent
parent and the RCSL line phenotypes. A normality test was performed on all the
phenotypic data sets using the PROC UNIVARIATE procedure, as implemented in
SAS V8e. Because normality was not significantly improved with transformation for
those traits that showed significant deviation, untransformed data were used for the
analyses.
61
MARKER: PHENOTYPE RELATIONSHIPS
DNA marker: phenotype associations were first identified via simple linear regression.
However the thrust of our analysis was application of the methodology proposed and
implemented by Grupe et al. (2001), which involves identifying chromosomal regions
that are highly correlated with differences in a phenotypic trait. To perform the
analysis, genotypic and phenotypic distance matrices are constructed. For the present
study, the genotypic distance matrix was obtained as the difference between alleles for
each pair-wise comparison of RCSL lines. The phenotypic data matrix was obtained
by calculating the absolute difference in phenotypic value for each pair-wise
comparison of RCSLs. SSR loci with missing data were not included in the analysis.
This led the exclusion of three SSR loci (Bmag 120, Bmag0225 and Bmag222) in the
association analysis. A correlation coefficient was obtained on the phenotypic and the
genotypic arrays for each SSR locus. These raw correlation coefficients were
normalized by subtracting the mean raw correlation and dividing this value by the
standard deviation. The pooled mean and the standard deviation were used to
normalize the raw correlation values. For more detail on this procedure, see Grupe et
a! (2001, data supplement). Only the positive correlations are presented, because
negative correlations would be expected to be of no biological significance, they
would indicate that high levels of phenotypic diversity are associated with low levels
of allelic diversity. We considered two levels of significance (1 .5 and 2.0 standard
deviations (SD) from the mean) as evidence of significant associations of SSR alleles
62
with phenotype differences. Simple linear regression was used to identify the parent
that contributed the larger phenotypic value allele, i.e. QTL allele. The results of this
analysis were compared with the barley QTL database (Hayes et al, 2000).
63
RESULTS AND DISCUSSION
GENOME ARCHITECTURE OF RCSLs
The frequency distribution of the proportion of H. vulgare subsp. spontaneum genome
introgressed into the RCSLs is shown in Figure 3.2. As shown in this figure the
percentage of the subsp. spontaneum genome ranged from 0% (lines 63 and 81) to
36.7% (line 126), with an average of 12.6%. This average showed a perfect fit to the
expected donor introgression of 12.5% for a BC2 population in absence of selection
(Stam and Zeven 1981). The 0% of donor parent introgression in lines 63 and 81 could
be due to technical failure during the emasculation process when the F1 was made,
since the recurrent parent was used as the female. During backcrossing, the recurrent
parent was used as the male. Another explanation is that the size of the introgressed
fragment was not detected due to a lack of complete genome coverage by the SSRs.
Two examples of lines with different percentages of donor parent introgression are
showed in Figures 3.3. and 3.4. RCSL 138 has only 3.2 % of H. vulgare subsp.
spontaneum genome, with a single introgressed fragment located in the distal part of
long arm of chromosome 5 (1H). Thus, based on the level of genome coverage
provided by the 47 SSRs, this line is an isoline of Harrington with a single
chromosome substitution of approximately 35 cM or less. In contrast, RCSL 16 has a
30% introgression of H. vulgare subsp. spontaneuin genome. In this case, the
introgressed fragments are distributed in all seven chromosomes. Theoretically, a
64
crossover is expected to occur in at least one arm of each chromosome at each meiosis
(Nils-Otto and Pelger, 1991). However, the relationship between chiasma, as revealed
45
40
35
30
C-)
0
25
20
n 15
z
10
5
0
0.6
5
10
15
20
25
30
35
40
Percent of donor parent genome
Figure 3.2. Distribution of the percentage of donor parent (H. vulgare subsp. spontaneum)
genome in the recombinant chromosomes substitution lines (RCSLs).
65
cytologically, and recombination, as revealed by linkage maps, is not clear. Only
recently, in humans, progress has been made in reconciling physical and genetic
distances on a chromosomic level (Lynn et a!, 2002). An inspection of molecular
marker data from multiple linkage mapping populations (Grain Genes Mapathon
http ://wheat.pw.usda.gov/ggpages/ggmapathon.html) reveals multiple map lines with
no apparent crossovers, as well as lines, such as RCSL 16, that represent mosaics of
chromosome regions tracing to each parent. In RCSL 16 there are introgressions on
chromosomes i(7H), 2(2H), 3(3H), 4(4H) and 7(5H) that could be interpreted as the
results of double crossover. However, given the relatively short distances involved and
the assumption of positive interference the probability of occurrence of such events is
quite low. Since there were two backcrosses to the recurrent parent, it is likely that
these introgressions resulted from single crossovers in the succeeding generation.
Graphical genotypes of all 140 RSCLs are available in the CD, and collectively these
lines show a range of number of introgressions and sizes of introgressed fragments.
The average length of donor chromosome segment, considering all the 140 RSCLs,
was 19.3 cM, 15.4 cM, 12.3 cM, 11.2 cM, 26.0 cM, 17.8 cM and 19.2 cM for
chromosomes 1(7H), 2 (2H), (3H), 4(4H), 5(1H), 6(6H) and 7(5H) respectively. The
average length of donor chromosome segments considering only the lines with
introgressed fragments was 39.0 cM, 30.8 cM, 38.1 cM, 27.5 cM, 43.9 cM, 46.2 cM
and 44.8 cM for chromosomes 1(7H), 2(2H), 3(3H), 4(4H), 5(1H), 6(6H) and 7(5H),
respectively. For the first case the overall average was 17.3 cM, and for the second
66
was 38.6 cM. According to Tariksley and Nelson (1996) the average length size of
donor segments in a BC2 generation set of tomato RCSLs was approximately 28 cM.
67
BmacOl34
5 00
HVM36
1700
BmacO3i
5.50
Bmacl63
HvLTPPB
.00
25.00
Bmac2l
2800
Bmuc3031 3000
Bmag5038
Bmac0093
Bmac3lO
Bmag3S3
50.00
Bmag3744.O0
00
Bmac003
Bmac9
Bmag2l
Bmac273
80.00
HvCMA
85.00
Ebmac79
95.00
105.00
.00
Bmagl73
Bmag38
BmaclS
300Ebmag7I
18.00
Ebmag757
142,00
Bmacl56
156.00
141.00
2(211)
Bmag223
66.00
GMSOOI
126.00
Ebmac82
041.00
Bmag22
162.00
79.00
97.00
Bmag5O7 -107.00
Bma120
Bmac961 41.00
I
55.00
58.00
62.00
.00
Ebmac4l
1 10.00
GMS2117 00
102.00
112.00
4(4H)
Bmac4
143.00
3(311)
6(611)
75
1(711)
Ebmac78
180.00
GMSOO1
187.00
5(1H)
7(511)
Figure 3.3. Graphical genotype of RCSL 138 showing 3.2% H.vulgare subsp.
spontaneum
introgression in a H.vulgare subsp. vulgarel background
68
BmacO 134
5.00
HVM36
50
17.00
GMS2J
Bmac2l
I
Bmac3JO
13mag353
Bmacl63
10.00
Bmac3O3
30.00
Bmac96
41.00
Bmag223
66.00
GMSO6J
126.00
14300Ebmac82
141.00
lSmag22
162.00
17.00
28.00
.00
43.00
48.00
BmacOO' 58.00
Bmac273
*180.00
HvCMA
_-85..00
Bmag2l
62.00
1
112.00
I
Ebmac7p3-J-95.00
Ebmac4J33JS 105.00
1107.00
I
18
Bmag1201 18.00
Bmag74J.4Q0
.00
4(411)
Bmac4
BmacI5O
156.00
Ebmag757}14200
2(211)
3(311)
6(6H)
175
1(7H)
cM
5
180.00
OMSOOI
187.00
5(111)
7(511)
Figure 3.4. Graphical genotipe of RCSL 16 showing 30% H.vulgare subsp spontanem
introgression in a Hvulgare subsp vulgare background.
SEGREGATION DISTORTION
As stated earlier, the average percentage of donor genome fit expectations. However,
segregation distortion was observed for some markers and chromosome regions.
Segregation distortion may arise from genetic, physiological and/or environmental
causes, and the relative contribution of each of these factors may vary (Xu et al. 1997).
Distorted segregation in a population derived by single seed descent, such as these
RCSLs, represents the cumulative effect of genetic and environmental factors.
Segregation distortion is a phenomenon that often occurs in interspecific crosses in
plants (as reviewed by Xu et al. 1997) and is particularly well documented in wide
crosses involving tomato (Fulton et al, 2000; Fooland et al, 2002), rice (Brondani et al,
2002) and pearl millet (Poncet et a!, 2000).
In barley, there has been considerable debate regarding the taxonomic relationship of
the ancestral and cultivated forms, treating the two as subspecies, e.g. H. vulgare
subsp. vulgare and H. vulgare subsp. spontaneum (Baum and Johnson, 1996). Given
this taxonomic classification, our set of RCSLs could be considered as tracing to an
exotic x elite cross rather than a wide cross, and meiotic irregularities would not be
expected. In order to explore segregation distortion in this set of RCSLs, we calculated
the goodness of fit to expected ratios for each SSR marker using a
test. The results
were then plotted for each chromosome. Examples are shown in Figures 5a
5c.
There was no segregation distortion on chromosomes 2(2H), 3(3H), 4(4H) and 6(6H).
Significant segregation distortion was observed on chromosomes 1(7H), 5(1H) and
chromosome 7(5H). On chromosome 1(7H) the SSR Bmac273, located in bin 6,
70
showed significant distortion (P< 0.025). On chromosome 5(1H), GMS2J located in
bin 2 (P< 0.01) and Ebrnac783 located in bin 14 (P< 0.005) both showed significant
segregation distortion. On chromosome 7(5H), GMSO6] (located in bin 11) showed
significant segregation distortion (P< 0.005). An excess of recurrent parent alleles was
observed only in chromosome 7(5H), while segregation distortion on the other regions
(1 (7H) and 5(1H)) favored the donor parent. As will be discussed in the section of
QTLs, no QTLs are reported in these regions.
71
a
Chromosome 1(711)
96
84
.9 80
76
72
-
2
4
3
5
7
6
10
9
8
12
11
Bin
b
Chromosome 5(111)
96
'
14
Bin
Chromosome 7(5H)
96
92
88
84
72
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Bin
Figure 3.5 (a
c)). Chi-square values for segregation distortion for chromosomes 1 (7H), 5( 1H)
and 7(5H). The dotted lines show the 0.005 confidence level limits (92.5% and 82.2%) and the
solid line shows the expected allele frequency (87.5%) for the recurrent parent in a BC2 population.
72
PHENOTYPE DATA
Significant differences among the RCSLs (P<O.Ol) were detected for KP, TW, SH,
TKW, HL, and SR. No significant differences were detected for AR. The phenotypic
distributions for the agronomic traits (KP, TW, SH and HL) were skewed toward the
recurrent parent value (Figure 3.6 (a, b, c and e). Both domestication-related traits (SR
and AR) showed skeweness; SR toward the value of both parents and AR toward the
recurrent parent (Figure 3. 6 (f and g)). For the malting quality traits (ME, GP, AA and
WBG) significant differences were detected at P<O.001; for DP, differences were
significant at P<O.03. Distributions were skewed toward the recurrent parent value for
ME and AA, and toward the donor parent value for GP and WBG (Figure 3.7 (a and
d)).
YIELD COMPONENTS
Transgressive segregation is one of the desired outcomes of exotic germplasm
introgression. Favorable transgressive segregation is evidence that the donor contains
favorable alleles. Negative transgressive segregation is a tool for gene discovery, as it
indicates where the allele replacement leads to loss of function or loss of desired
phenotype. Positive and significant (PO.05) transgressive segregation with respect to
the recurrent parent Harrington was observed for SH, TKW and HL. Veteläinen
(1994) reported that in complex crosses Using adapted cultivars, landraces, and wild
type barley, it was possible to obtain hybrids with superior TKW. Hadjichristodoulou
(1993), however, did not recover lines with better TKW from crosses between wild
73
and cultivated barley. No reports were found in the literature regarding SH and HL.
These positive phenotypic transgressive segregants are an indication that this
accession of H. vulgare subsp. spontaneum is a source of favorable alleles for
productivity related traits. We did not analyze grain yield in this experiment, because
this trait is subject to genotype x environment (GxE) interaction and therefore requires
more extensive measurement in time and space than can be afforded in this initial
screening. Instead, we focused on yield components (seed number, seed size, seed
volume, and seed weight), because these traits are more highly heritable than grain
yield.
The donor parent itself was inferior for seed size, seed volume, and seed number per
head, but superior in seed weight. Positive phenotypic transgressive segregation was
observed for all these characters, indicating this accession may carry favorable alleles
for these traits. The contribution of these components to total grain yield will be
addressed in a subsequent report based on results of multi-environment assessment of
a selected group of RCSLs. Favorable alleles from exotic and ancestral species have
also been identified in tomato (Tanksley et al, 1996; Bemacchi et al, 1998(a);
Bernacchi et al, 1998(b)), rice (Xiao et al 1998; Brondani et al 2002) and pearl millet
(Ponce et al 2002). The challenge, of course, is how to systematically and efficiently
sample the genetic variation present in the many accessions of exotic and ancestral
germplasm that are available. As shown in the section on marker: phenotype
relationships later in this report, DNA-level polymorphism may be a useful tool for
extracting favorable alleles.
74
MALTING QUALITY TRAITS
Significant (P0.05) transgressive segregation was observed for all the malting
quality traits. For ME and GP, all the RCSLs were superior and inferior, respectively,
to the donor parent. ME is the percentage of the malt that dissolves during mashing
and is a measure of all the soluble carbohydrates available for yeast nutrition in the
manufacture of beer. This value is very important since it indicates how much beer can
be produced from a given weight of malt, and as a consequence high values are
desired. The minimum ME demanded of North American two row barley is 81.0%.
There is no upper limit. Harrington, the North American malting barley standard, did
not meet the minimum specifications in this test, evidence that the environment did
not allow this genotype and presumably the RCSLs, to show their full genetic
potential for this malting quality trait. The high grain protein (GP) levels of most of
the RCSLs are not desirable from a malting quality standpoint but could be of interest
for feed barley or barley for human nutrition. North American specifications for GP
are between 11.5
13.0%. The high proteins in these data are likely due to excessive
N nutrition during crop growth (Garcia del Moral et al. 1998).
A factor responsible for the low ME in this environment may be the high grain protein
(GP), as ME and GP are generally negatively correlated (Weston et al. 1993). Alpha-
amylase activity (AA) is an important component of malting quality, because it is a
measure of the enzymatic activity of alpha-amylases, which are key enzymes
75
responsible for the hydrolysis of the barley starch grain (Hayes and Jones, 2000). The
minimum and maximum specifications are 45-60 20°DU, respectively. As shown in
Figure 3.7 (d), most RSCLs had lower AA activity than Harrington, and Caesarea 26-
24 had very low activity. in contrast, the donor parent had a much higher DP value
than the recurrent parent. Diastatic power (DP) (a measure of all the component
enzymes that can hydrolyze starch) is an essential malting quality factor. Like AA
activity, a range of values (120 to 140 °ASBC) is acceptable. Two genes - Bmyl and
Bmy2
encode the 3-amylases which are major contributors to DP activity; necessary
for quick release sugars during mashing (Hayes and Jones, 2000). For DP, RCSL lines
significantly superior to the recurrent parent were recovered. Erkkila et al. (1998)
reported that a H. vulgare subsp. spontaneum accession had high DP activity and
demonstrated that this was attributed to a novel allele at Bmyl. Wort 3-glucan (WBG)
is a measure of the overall modification of barley cell walls during malting, and values
higher than 115 ppm are not acceptable (Hayes and Jones, 2000). Again the
Harrington check was out of the acceptable range for this parameter, but the donor
parent and the majority of the RCSLs were higher than the check and would thus be
considered unacceptable. In summary, the H. vulgare subsp. spontaneum donor itself
had a very poor malting quality profile. The North American malting quality standard
was significantly better, as one would expect, but did not meet specifications, probably
due to nitrogen fertility management issues. The donor parent does not appear to be a
source of favorable alleles for ME, AA and WBG, but depending on the range of
genetic variation desired may carry positive alleles for GP and DP. In addition to the
76
positive alleles identified, the stocks may be useful in revealing the presence of genes
in the recurrent parent via substitution of inferior alleles from the donor parent. These
malting data are best viewed as a preliminary assessment of potential rather than a
definitive characterization of value. In a subsequent report, we will describe the result
of a multi-environment assessment of malting quality in a subset of this germplasm.
These tests gave a more accurate measure of the malting quality of Harrmgton and the
RCSLs.
DOMESTICATION RELATED TRAITS
A principal characteristic of wild vs. domesticated cereals is a brittle rachis. In barley,
brittle rachis is controlled by two linked dominant genes, Btrl and
Btr2,
located in
chromosome 3(3H) (Takahashi and Hayashi, 1964). Seed retention (SR) is a
phenotype distinct from brittle rachis (Chapman and Hockett, 1976). Platt and Well
(1949) defined seed retention as the event when individual florets of seeds break free
of the rachis. This trait it is not well differentiated in the wild types, but it is found in
two-rowed barley, primarily, and it is objectionable in cultivated forms. Awn
dehiscence vs. awn retention (AR) is a trait that is not frequently mentioned in the
literature, but it is undesirable in cultivated forms because it causes problem during the
threshing and cleaning processes.
The frequency distribution for SR (Figure 3.6 (f and g)) shows that even though we
practiced no selection during RCSL development, after two backcrosses to the
cultivated form most RCSLs were within the range of agronomic acceptability. There
77
was, however, one line that in had an extremely high seed retention value. A high
degree of seed retention leads to poor threshability and is problematic for mechanized
agriculture as additional effort is required for seed cleaning. The trait may be useful in
subsistence agriculture situations where crops are at risk to high wind and/or hail
damage. For AR there were no significant differences, due to the high variance about
the parental mean. Most lines were similar to the recurrent parent, Harrington, but
there were some lines with extreme values similar to the donor parent values.
78
a
b
Hith0
= 99
2
K
K
0
5
40
20
50
40
00
65
70
75
K!I pI9..p... (liP) (%) (.nl30 36w
991
80
15
90
99
iS
35
30
45
00
70
65
75
1.4 swlght (TW) (Kg/hi)
C
.2
K
.2
K
00
20
Il
22
20
24
20
30
72
43
44
45
SdThd (910
40
47
46
49
50
59
52
53
50
55
50
1000 .4-..l swIgil ff1S) (0)
r
e
O5ng1i=I0
.2
K
5
0
7
0
9
90
09
12
13
3)01520250003 4045 5055000570 7580 15909S100107
S.h5090(Sl0()70(
H..d 1.9810 (HL)
g
35
-
30
40
HarringloK
29
20
Cae0000a 26-24
10
20
30
40
50
60
70
80
290
90 100 110 120 130 140 150 160 170 180 190 200 210 220 230 200 270 290
Awo, reteooti000 (AR) (N)
Figure 3. 6. (a
the RCSLs.
g) Phenotypic frequency distribution for yield component and domestication traits in
79
b
a
05
04
06
20
16
06
17
MII56I(ME)(U)
21
22
P0#(P) (56)
d
C
25
25
20
2
2
20
#05
go
so
so
go
oo
000
110
220
000
140
050
060
ISO
ISo
100
200
50
0I&6.6o p0 (flO) (A6flc)
06
40
42
44
46
40
50
52
54
56
30
60
62
64
06
60
A1ph.-myIn(AA) (20005
e
06fl
25
20
15
I0
200
250
300
300
400
450
500
550
600
650
700
750
800
850
900
Wort beto-glosoas. (WBG) (ppfls
Figure 3.7.(a
e) Phenotypic frequency distribution for each malting quality trait in the RCSLs.
70
72
80
MARKER: PHENOTYPE RELATIONSHIPS
We first investigated genetic marker: phenotype relationships using simple linear
regression (SLR), the approach taken by Fulton et al. (2000). We then compared the
SLR results with those obtained from the method of association analysis (AA)
developed and implemented by Grupe et al. (2001). We observed that more significant
(P0.01) allele: phenotype associations were detected by SLR than with AA ( 1.5
SD). We believe this could be due to linkage of marker loci and genes determining
quantitative phenotypes andlor to the standardization of values in the association
analysis.
With SLR, markers in two or more adjacent bins were often significant for the same
trait, whereas in most cases (75%) only the marker: phenotype relationship with the
highest correlation was identified as significant with AA. In the five cases where there
were significant relationships in adjacent bins detected with AA, all exceeded 2.0 SD.
In terms of standardization of values, for AA marker: phenotype correlations for each
trait were standardized considering all correlations in all linkage groups. Accordingly,
only the associations with the highest correlations were identified as significant, e.g
1 .5 or 2 SD. There were cases where no significant relationship was detected using
SLR, but a significant relationship was detected with AA. In these cases, inspection of
the data revealed similar means for the groups of RCSLs with contrasting alleles for
the locus in question, but higher variances for the class with the fewest representatives
(RCSLs with donor parent alleles). In view of these results, we concluded that the AA
procedure of Grupe et al. (2001) may be more conservative (i.e. generate fewer false
81
positives) than SLR and we used this approach to identify marker: phenotype
relationships.
Seed number, size, mass, and volume are important components of grain yield. An
extensive literature provides evidence for yield component compensation; an increase
in one component leads to a reduction in another component with the result that
increase in grain yield is difficult to achieve (Rasmusson, 1987). Negative correlations
between traits may be due to linkage or pleiotropy, and in this regard information on
the genome location(s) of the determinant genes may be useful. In the context of
exploiting exotic germplasm, the discovery of novel genetic variation for yield traits
would be most useful. In the case of the yield-related characters measured in this
survey, we found strong evidence ( 2.0 SD) for linkage map bins associated with
TWK, KP, TW, HL, and SH, and evidence for possible relationships ( 1.5
additional regions (Figures 3.8 and 3.9). Of the associations significant at
2.0) in
2.0 SD,
several coincide with previously reported QTL: TKW on chromosome 2((2H) bins 10,
12 and 15); KP on chromosome 2(2H), bin 9; and TW on chromosome 5(1H), bin 12.
As shown in Figure 3.9, associations
2.0 SD were detected for HL on chromosome 2
(2H), bin 12 and on chromosome 3 (3H), bins 3 and 4. For SH, associations
2.0 SD
were found on chromosome 2 (2H), bins 10, 12 and 13. None of the significant
associations for HL coincided with reported QTL. For SET, there was one case of
coincidence with previously reported QTL (on chromosome 2(2H), bin 12).
Of the
2.0 SD associations, the H. vulgare subsp. spontaneum parent contributed
favorable alleles for TKW, and considering the 1.5,
2.0 SD associations, it also
82
contributed favorable alleles for SH. in the case of KP, TW, HL and SH, the donor
parent contributed "negative" alleles, but doing so, may have revealed regions of the
genome that in Harrington are important determinants of these traits. Associations
2.0 SD were identified in 14 bins. Six were coincident with previously reported QTL.
Eight putative "new" loci, unreported in the literature, were identified for TKW, KP,
HL and SH.
The phenotypic frequency distributions show positive phenotypic transgressive
segregation for TKW and SH; considered individually, the results of the association
analysis indicate that these phenotypic transgressive segregant lines could be the
consequence of introgression of favorable alleles from the donor parent. However, in
terms of multi-trait selection the data indicate that it would be difficult (in the case of
linkage) or impossible (in the case of pleiotropy) to combine the favorable alleles for
TKW from the donor parent with the SH alleles from the recurrent parent, since both
map to the same bin.
3.0
2.0
1.5
1.0
0.5
0.0
Chromosome
Bin 24681156991111341125711124779111 137812457111
Thousand-kernel weight (TKW)
U Kernel plumpness (KP)
Test weight (TW)
Figure 3.8. Standard deviation (SD) from adjusted correlations values for yield component traits (thousand kernel weight (TKW),
kernel plumpness (KP), and test weight (TW)), graphically represented above the horizontal axis. Bars below the horizontal axis
show locations of Quantitative Trait Loci (QTL) reported in the literature. The dotted and the full lines in the SD portion of the
figure represent, respectively, 1.5 and 2.0 SD from the mean. Data are shown for chromosomes 1(7H) to 7(5H), with the
corresponding linkage map bin numbers
00
w
Bin
2
4
6
8
10 12
5
6
9
9 10 12 13
15 3
flead Length (HL)
4 13 14 2
5
7 1012 13 2 4 7
7
9 12 13 14
1
3
7
8
13 2 4
5
7 1112 14
U Seeds per head (SH)
Figure 3.9. Standard deviation (SD) from adjusted correlations values for yield component traits (head length (HL) and seeds per
head (SH)), graphically represented above the horizontal axis. Bars below the horizontal axis show locations of Quantitative Trait
Loci (QTL) reported in the literature. The dotted and the solid lines in the SD portion of the figure represent, respectively, 1.5 and
2.0 SD from the mean. Data are shown for chromosomes 1(7H) to 7(5H), with the corresponding linkage map bin numbers.
00
85
Malting quality is a complex and elusive phenotype. It represents the balance of a
large number of component traits, each of which shows complex inheritance (Hayes
and Jones 2000). Accordingly, improvement in malting quality requires simultaneous
improvement in multiple components, making it an especially challenging trait to
improve via exotic germplasm introgression. At the level of 2.0 SD, two regions
were identified for ME, one in chromosome 5 (1H), bin 12 and one in chromosome
6(6H), bin 8. The first region is coincident with a previously reported QTL while the
second is not. In both cases the recurrent parent contributed the favorable alleles, and
there were no positive phenotypic segregants for this character. Malt extract is the
only malting quality character for which there is no upper limit specified. Grain
protein content is an important malting quality trait. In two-row barley grain protein
levels between 11.5
13.0% are allowed. The donor parent contributed alleles that
increased grain protein content, as shown in Figure 3.7. Bin 14 on chromosome 3 (3H)
and bin 4 on chromosome 5(1H) were strongly associated with this trait. Two
additional regions were identified on chromosome 6(6H), bins 7 and 8. None of these
genome regions had been previously associated with grain protein, and accordingly
these may represent novel alleles for genes contributing to higher grain protein.
Unfortunately, higher grain protein is not a desired malting quality trait, but these
alleles could have value for barley varieties designed for human or animal nutrition.
A very strong association (SD
2.0) was found for DP in chromosome 4 (4H), bin 13.
The donor parent contributed the higher value allele. On chromosome 7(SH) - bin 14
was significant at 2.0 SD for both AA and WBG. QTLs for AA, but not for WBG are
86
reported in this bin. On the same chromosome, strong associations were also found for
WBG with bins 4 and 5, and no QTL for this trait have been reported in these bins. In
all cases, the higher value (negative) alleles for
WBG alleles were from the donor
parent, whereas all higher value (lositive) alleles for AA came from the recurrent
parent.
A number of known function genes have been related to malting quality traits, and in
some cases correspond with QTL and may thus be candidate genes (Hayes et al.,
2003). Tn the case of the associations we detected, the Bmyl locus may be the
candidate gene for the chromosome 4 (4H), bin 13 DP relationships, where the donor
parent contributed a higher value allele. Erkkila et al. (1998) also found an accession
of H. vulgare subsp. spontaneum to have high DP, and they determined this was due
to its novel allelic structure at the Bmyl locus. The grain protein association on
chromosome 5(1H), bin 5, is coincident with the bin address of the Glul locus and
proximal to the Hurl locus. These loci encode barley storage proteins (Hayes and
Jones, 2000). The chromosome 3(3H) bin 14, region that was also associated with
grain protein is the bin address for the Cxpl locus and a family of Gib genes. Cxpl is a
carboxypeptidase gene and Gib genes encode the f3-glucanases that are important for
degrading the 3-glucans (Hayes and Jones, 2000).
3.0
2.5
2.0
1.5
1.0
0.5
0.0
Chromosome
Bin
2
4
6
8
1
1
S
6
9
Malt extract (ME)
9
1
1
1
1
3
4
1
1
2
5
7
1
Grain protein (GP)
1
1
2
4
7
7
9
1
13781 24571 11
RDiastatic power (P)
Figure 3.10. Standard deviation (SD) from adjusted correlations values for matting quality traits (malt extract (ME), grain
protein (GP), and diastatic power (DP)), graphically represented above the horizontal axis. Bars below the horizontal axis
show locations of Quantitative Trait Loci (QTL) reported in the literature. The dotted and the solid lines in the SD portion of
the figure represent, respectively, 1.5 and 2.0 SD from the mean. Data are shown for chromosomes 1(7H) to 7(5H), with the
corresponding linkage map bin numbers.
00
3.0
2.5
2.0
1.5
1.0
0.5
0.0
I
1(7H)
Chromosome
Bin
Ij
I
2
4
6
8
2(211)
1
12 5
6
9
9
I_
I
4(4H)
5(111)
II
3(311)
1
12 13 15 3
4
13 14 2
A1pha amylase (AA)
5
7
1
12 13 2
4
7
7
I
9
I
II
L ll_
__________
7(5H)
6(6H)
12 13 14
1
3
7
8
1
2
4
5
7
11
1
14
IWort beta glucan (WBG)
Figure 3. 11. Standard deviation (SD) from adjusted correlations values for malting quality traits alpha amylase activity (AA)
and wort beta glucan (WBG)), graphically represented above the horizontal axis. Bars below the horizontal axis show locations
of Quantitative Trait Loci (QTL) reported in the literature. The dotted and the solid lines in the SD portion of the figure
represent, respectively, 1.5 and 2.0 SD from the mean. Data are shown for chromosomes 1 (7H) to 7(5H), with the corresponding
linkage map bin numbers.
00
00
89
The genetic analysis of domestication traits can reveal conimonalities between
different crops in the domestication process (Patterson et al., 1995) and it may also
reveal regions of the genome that could be targeted for extensive "allele mining",
based on the hypothesis that favorable alleles, linked in repulsion with wild type
alleles at key domestication loci, could have been lost during domestication
bottlenecks. The syndrome of traits associated with domestication in barley, and the
cereals in general, are loss of shattering, reduced dormancy, and more synchronous
flowering (Zohary and Hopf, 1993). In this study, we studied only phenotypes related
to seed and awn retention. Two cycles of backcrossing to the cultivated recurrent
parent generated a set of RCSLs, most of which were more similar in overall
phenotype to the recurrent than the donor parent. Only 17 of the RCSLs showed
severe seed retention under field conditions, which would be considered diagnostic of
the ancestral allele at the Btr locus which according to Kandemir et al. (2000) lies at
the juncture of bins 4 and 5 on chromosome 3 (3H). Unfortunately, we only had
polymorphic SSR markers for bins 4 and 7. Seven of these apparently Btr RCSLs lines
had donor parent introgressions extending across bins 4 and 7. Only for HL
significantly association was found in the vicinity of
Btr
locus, and the cultivated
parent contributed the favorable alleles. Accordingly, at the level of marker resolution
and for the traits we studied, we have no evidence that this Caesarea 26-24 carries
favorable alleles in the vicinity of the Btr locus, which could have been lost during
domestication bottlenecks.
90
Within cultivated germplasm that has a non-brittle rachis, there can be genetic
variation for SR and AR, but there is limited information on the genetic basis of these
traits. We found one region in chromosome 2 ((2H), bin 6) and one in chromosome 6
((6H), bin 3) that were associated with AR. One region on chromosome 1 ((7H), bin 8
and one in chromosome 5((1H), binl2) were associated at
2.0 SD with SR. For both
traits the "negative" alleles were contributed by the donor parent. No QTLs have been
reported for these traits. The frequency distribution for SR (Figure 3.12) shows one
RCSL with extremely high SR, and this RCSL was the oniy one that had donor parent
introgressions for both SR regions. Twenty-four lines were significantly different
(P0.05) from the recurrent parent for SR. 63% of these RCSLs had a donor parent
introgression at one of the SR regions. The SR-associated bin (12) on chromosome
5
(1H) was also significantly associated with TKW, TW and ME, and Harrington
contributed the favorable marker allele associated with all traits.
3.0
2.5
2.0
1.5
1.0
0.5
0.0
Bin
2
Chromosome
4
6
8
1(711)
1
1
5
6
9
9
1
2(2H)
1
1
1
3
4
1
1
2
5
7
1
1
4(411)
3(311)
SAR
1
2
4
7
7
9
1
5(IH)
137812457111
6(6H)
7(511)
OSR
Figure 3.12. Standard deviation (SD) from adjusted correlations values for domestication traits (awn retention (AR) and seed
retention (SR)), graphically represented above the horizontal axis. The dotted and the solid lines in the SD portion of the figure
represent, respectively, 1.5 and 2.0 SD from the mean. Data are shown for chromosomes 1(7H) to 7(5H), with the
corresponding linkage map bin numbers.
-a
92
For the traits evaluated, given the level of density provided by the available SSRs and
the preliminary result of the available phenotype data, the chromosome regions
associated with domestication-related traits are not associated with alleles that would
be of value for barley improvement. In other regions of the genome, this accession of
H. vulgare subsp spontaneum does appear to have alleles that could be of value for
improvement. For improvement of yield, it may carry favorable alleles for TKW and
SH. However, finer structure analysis would be required to determine if the positive
TKW alleles from the donor parent are separable, by recombination, from negative
alleles. The single environment that was sampled led to high grain protein levels in all
selections, but the level of grain protein in the donor parent (21%) and in many of the
RCSLs was much higher than usually encountered in gemiplasm with acceptable grain
plumpness. This high level of grain protein is not desirable for matting, but it may be
useful for human andlor animal nutrition. Further analysis will be necessary to
determine what protein fractions are present and their nutritional value. The donor
parent is also a source of high diastatic power, and this may be attributable to its allelic
structure at the Bmyl locus, as Erkkila et al. (1998) demonstrated in another accession
of H. vulgare subsp. spontaneum that was also high in DP. There is an upper limit for
DP specified by the malting industry, so the value of this DP remains to be
determined. In terms of our original objectives, we have shown that an accession of H.
vulgare subsp. spontaneum is a source of favorable alleles at known loci (QTL
reported in the literature) and at previously undescribed toci. In the majority of cases,
Caesarea 26-24 had a negative effect on agronomic performance and malting quality.
93
These "negative" alleles may have value for reverse genetics strategies at the
chromosome segment level.
This collection of RCSLs, should serve as a useful set of genetic stocks for QTL
validation and discovery. Sixty percent of the genome (in term of the linkage map) has
yet to be surveyed in this material. The intensive EST mapping efforts currently
underway in barley (HarvEST at http://harvest.ucr.edu!) should generate the markers
necessary to accomplish this task, with the added advantage that candidate genes may
be assigned to significant marker: genotype relationships. The germplasm also merits
assessment as a source of favorable alleles for other phenotypes, as this accession was
collected from a particularly dry and salty site in Israel (E. Nevo, personal
communication). The association analysis methodology of Grupe et al. (2001),
although developed and applied for germplasm arrays, appears to be useful in
exploratory analysis for a population where map density is insufficient for standard
QTL analysis. The challenge yet remains to develop strategies for effectively sampling
alleles in many accessions present in germplasm banks, and to make effective use of
the alleles that are introgressed from these accessions. Effective characterization
requires more extensive and replicated phenotyping, which in turn inevitably limits the
number of accessions that can be sampled. In a subsequent report, we will describe the
results of a thorough agronomic and malting quality characterization of a subset of
these RCSLs, replicated extensively in time and space.
94
Acknowledgements: This research was supported by the North American Barley
Genome Project (NABGP). Dr. Eviatar Nevo for providing the accession of H.
vulgare subsp. spontaneum.
95
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101
CONCLUSIONS
From a breeding perspective, germplasm is often considered to be "adapted", "exotic",
or "ancestral". h our case, these three types of germplasm could be distinguished,
based on their SSR allele architecture. Our results demonstrate that the set of SSRs
was highly informative. The SSRs had high polymorphism information content (PlC)
values and many were multi-allelic. The cluster analysis indicates a high level of
diversity within the crop progenitor accessions and within the mapping population
parents. It also shows a lower level of diversity within the elite breeding germplasm.
The germplasm classifications generally corresponded with geographic origin (e.g.
Hordeum vulgare subsp. spontaneum accessions from different parts of the Middle
East) and end-use (e.g. European spring habit malting two-rows vs. North American
malting two-rows and six-rows. The high level of genetic diversity, as measured by
polymorphism at marker loci in the crop progenitor group, as compared to the elite
breeding line and variety groups, indicates that the progenitors could be a valuable
resource for crop improvement. The challenge is to make efficient use of these genetic
resources.
Agronomic performance is adversely affected when wild or exotic germplasm is
crossed with elite and adapted breeding material. In order to develop a model for
introgressing ancestral germplasm into cultivated germplasm, we used the advanced
backcross strategy to develop a set of RCSLs representing introgressions of Hordeum
vulgare subsp spontaneum genome in a cultivated barley background. We applied an
102
association analysis strategy for detecting and validating genes determining
quantitatively inherited phenotypes, Quantitative Trait Loci (QTL).
The RCSLs displayed a range of H. vulgare subsp. spontaneum genome introgression
architectures, as inferred from their SSR allele genotypes. Introgressions of donor
parent genome ranged from 0% to 36.7%, with an average of 12.6%. Significant
segregation distortion was observed on chromosomes l(7H), 5(1H) and chromosome
7(5H). Introgressions ranged from single chromosome segments to segments on up to
the seven chromosomes.
The effects of the donor parent introgression were evaluated in terms of three classes
of phenotypes: inflorescence yield components, malting quality traits and
domestication-related traits. The donor parent itself was inferior for seed size, seed
volume, and seed number per head, but superior in seed weight. Significant
differences among the RCSLs (P<O.0i) were detected for KP, TW, SH, TKW, HL,
and SS. No significant differences were detected for AR. The phenotypic frequency
distribution showed positive and significant (P0.05) transgressive segregation for SH,
TKW and HL. For the malting quality traits, significant differences were detected at
P<0.001
for ME, P. AA and WBG; for DP differences were significant
at
P<0.03.Significant transgressive segregation (P0.05) was observed for all the malting
quality traits.
Even though we practiced no selection during RCSL development, after two
backcrosses to the cultivated form most RCSLs were within the range of agronomic
acceptability. At the level of marker resolution available, and for the traits we studied,
103
we have no evidence that Caesarea 26-24 carries favorable alleles in the vicinity of the
Btr locus which could have been lost during domestication bottlenecks. The
chromosome regions associated with domestication-related traits (SS and KR) are not
associated with alleles that would be of value for barley improvement.
In other regions of the genome, this accession of H. vulgare subsp spontaneum does
appear to have alleles that could be of value for crop improvement. For improvement
of yield, it may carry favorable alleles for TKW and SH. However, finer structure
analysis will be required to determine if the positive TKW alleles from the donor
parent are separable, by recombination, from negative alleles. The single environment
that was sampled led to high grain protein levels in all selections, but the level of grain
protein in the donor parent (2 1%) and in many of the RCSLs was much higher than
usually encountered in germplasm with acceptable grain plumpness. This high level of
grain protein is not desirable for malting, but it may be useful for human and/or animal
nutrition. Further analysis will be necessary to determine what protein fractions are
present and their nutritional value. The donor parent is also a source of high diastatic
power, and this may be attributable to its allelic structure at the Bmy] locus.
We have shown that an accession of H. vulgare subsp. spontaneum is a source of
favorable alleles at known loci (QTL reported in the literature) and at previously
undescribed loci. In the majority of cases, Caesarea 26-24 had a negative effect on
agronomic performance and malting quality. These "negative" alleles may have value
for reverse genetics strategies at the chromosome segment level. This collection of
RCSLs, accordingly, should serve as a useful set of genetic stocks for QTL validation
104
and discovery. Allelic variation at marker loci in approximately 60% of the genome
(per the linkage, not physical map) was monitored in this study. Characterization of
sequence variation elsewhere in the genome should reveal additional genes of interest.
The germplasm also merits assessment as a source of favorable alleles for other
phenotypes, as this accession was collected from a particularly dry and salty site in
Israel.
The association analysis methodology appears to be useful in exploratory analysis for
a population where map density is insufficient for standard QTL analysis. The
challenge yet remains to develop strategies for effectively sampling alleles in the
many accessions present in germplasm banks, and to make effective use of the alleles
that are introgressed from these accessions. Our results indicated that these efforts
could be worthwhile.
105
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