Download Barley genetic variation: implications for crop improvement

B RIEFINGS IN FUNC TIONAL GENOMICS . VOL 13. NO 4. 341^350
doi:10.1093/bfgp/elu006
Barley genetic variation: implications
for crop improvement
María Mun‹oz-Amatriaín, Alfonso Cuesta-Marcos, Patrick M. Hayes and Gary J. Muehlbauer
Advance Access publication date 22 March 2014
Abstract
Genetic variation is crucial for successful barley improvement. Genomic technologies are improving dramatically and
are providing access to the genetic diversity within this important crop species. Diverse collections of barley germplasm are being assembled and mined via genome-wide association studies and the identified variation can be
linked to the barley sequence assembly. Introgression of favorable alleles via marker-assisted selection is now
faster and more efficient due to the availability of single nucleotide polymorphism platforms. High-throughput genotyping is also making genomic selection an essential tool in modern barley breeding. Contemporary plant breeders
now benefit from publicly available user-friendly databases providing genotypic and phenotypic information on
large numbers of barley accessions. These resources facilitate access to allelic variation. In this review we explore
how the most recent genomics and molecular breeding advances are changing breeding practices. The
Coordinated Agricultural Projects (CAPs), Barley CAP and Triticeae CAP coupled with international collaborations,
are discussed in detail as examples of a collaborative approach to exploit diverse germplasm resources for barley
improvement.
Keywords: barley; breeding; genotyping; germplasm; genome-wide association studies
INTRODUCTION
Barley is unique among crop plants for being of tremendous importance to agriculture and to science.
Advances on both fronts create a positive feedback
loop, allowing barley to be in the forefront in meeting the great challenges of climate change and
human population growth. In terms of agriculture,
barley is the fourth most important cereal crop in the
world (FAOSTAT: http://faostat.fao.org/site/339/
default.aspx). Barley grain, in the form of malt, is
the perfect nutritional source for yeast and is therefore the base of the brewing industry [1]. Barley, a
truly ancient food grain, is on the rebound as a key
component of healthy diets that can reduce the risk
of obesity, Type II diabetes and heart disease [2].The
most common use of barley, worldwide, is as a feed
grain and a robust barley feed market is an essential
component of a viable barley industry, as it can
absorb grain that does not meet malting or food specifications [3]. Despite this versatility in end-uses and
justified reputation as a stress tolerant cereal crop,
barley is in danger of descent to niche crop status.
Acreage in the USA is at an all-time low (USDANASS:
http://www.agmrc.org/commodities__
products/grains__oilseeds/barley/). In Europe,
barley acreage is being lost to other more profitable
crops [4]. The driving forces of the decline are price
and productivity: in many areas of the world, current
returns to farmers are simply not sufficient to ensure
a viable barley industry. While barley yields are
increasing [5], these increases are no match for
maize (USDA-NASS: http://www.nass.usda.gov/
Corresponding author. Gary J. Muehlbauer, Department of Plant Biology, Department of Agronomy and Plant Genetics, University of
Minnesota, St. Paul, MN 55108. Tel.: 612-624-2755; Fax: 612-625-1738; E-mail: [email protected]
Marı́a Mun‹oz-Amatriaı́n is a Research Associate at the University of Minnesota. Her research interests include the identification of
intraspecific genetic variation in barley and its association with phenotypic diversity.
Alfonso Cuesta-Marcos is a Research Assistant Professor at Oregon State University. His research focusses on applying molecular
tools and biotechnology to increase the efficiency of cereal improvement.
Patrick Hayes is a Professor at Oregon State University, Corvallis, OR, USA. His research focuses on barley—in its many forms and
uses.
Gary J. Muehlbauer is a Distinguished McKnight University Professor at the University of Minnesota. His research focuses on
genomics of crop plants.
ß The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please email: [email protected]
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Mun‹oz-Amatriaín et al.
Newsroom/2013/08_12_2013.asp). The yield gap is
not surprising: there is a tremendous private sector
investment in maize breeding, whereas barley breeding is a public sector activity in North America and a
crop of secondary emphasis for the private sector in
Europe. There is hope for closing the gap and ensuring a rightful place for barley in meeting the food,
feed and beverage needs of the future: the opportunity lies in barley’s role as a genetic model system.
Barley—a diploid (2n ¼ 2x ¼ 14) with a genome
size of 5.1 Gb—is the genetic model for the
Triticeae. There is a tremendous history of barley
genetics research (reviewed by [6]) and culminating
most recently with a draft genome sequence [7].
Throughout the late 20th century, barley was a
premier genetic model for agricultural research,
with a tremendous outpouring of research reports,
genetic stocks and data sets (GrainGenes: http://
wheat.pw.usda.gov/GG2/ggdb.shtml). In the early
days of genomics, barley briefly lost traction due to
the high cost of DNA sequencing and the smaller
genome size of Brachypodium distachyon. The availability of cost-effective sequencing and genotyping,
however, has led to a renaissance in barley genetics,
genomics and molecular breeding that should lead,
in the relatively short term, to economically important increases in efficient and tailored barley production. A key anchor to all barley genetics efforts is the
availability of a draft genome sequence [7] and the
bioinformatics tools that facilitate nimble integration
of information at the phenotypic level with difference in DNA sequence. A foundational area of
endeavor in barley genetics is characterization of
genetic resources, such as those present in the extensive germplasm collections housed at the Research
Institute for Bioresources (RIB, Japan), the Leibniz
Institute of Plant Genetics and Crop Plant Research
(IPK, Germany) and the United States Department
of Agriculture National Small Grains Collection
(USDA-NSGC, USA). There have also been parallel
efforts in Hordeum vulgare subsp. spontaneum, the wild
ancestor of barley [8, 9]. As described in greater detail
later in this article, there has been a significant investment, particularly in the USA, on characterizing
and using genetic diversity in elite breeding materials
under the auspices of the Coordinated Agricultural
Projects (CAPs) funded by the United States
Department of Agriculture (USDA). The CAP projects have focused primarily on identifying loci that
control traits showing quantitative inheritance via
genome-wide association studies (GWAS). These
QTL discoveries are being channeled into genomic
selection (GS) and marker-assisted selection (MAS)
programs. At the same time, there has been an impressive stream of gene cloning and characterization
work, including genes important in domestication
[10], physiology [11], and resistance to biotic [12]
and abiotic [13] stresses.
In this review, we describe the most recent advances in genomic tools for assessing genetic diversity
in barley and how they are being applied to characterize and exploit diverse germplasm resources.
Current strategies for directing the continuous discoveries into barley breeding are also discussed.
TOOLS FOR ASSESSING GENETIC
VARIATION
There are various types of genetic differences between individuals of the same species, including
single nucleotide polymorphisms (SNPs), small insertion/deletion polymorphisms (INDELs) and copynumber variations (CNVs). Undoubtedly, SNPs
have been the most studied type of intraspecific genetic variation. In barley, expressed sequence tag
(EST) resources supported the first ‘large scale’
SNP identification studies [14–16] and the development of the first high-throughput SNP genotyping
platform, based on the Illumina Oligo Pool Assays
(OPAs) [17]. This platform, which allows the examination of 4596 total markers in sets of 1536 SNPs,
has been extensively used by the barley community
and made it possible to develop high-density consensus genetic maps [17, 18], and to assess genetic
variation in germplasm collections (e.g. [19–22])
which can be associated with phenotypic variation
via GWAS (see section below).
The rapid improvement and declining cost of
next-generation sequencing (NGS) technologies is
revolutionizing genotyping in barley. Thousands of
SNPs discovered via resequencing of transcriptomes
(RNAseq) have been used in the development of the
new iSelect genotyping platform, which is based on
the Illumina Infinium assay and allows the simultaneous testing of 7842 SNPs [11]. Higher density genetic maps have been generated (e.g. [11]) and
integrated to build higher-resolution consensus
maps that are better reference points for assessing
and using genetic diversity [23]. Parallel SNP discovery and genotyping, via genotyping-by-sequencing
(GBS) and population sequencing (POPSEQ), have
been successfully applied to barley, resulting in
Barley genetic variation
identifying and mapping thousands to millions of
SNPs in two mapping populations [24–26]. The
newly available barley genome assembly [7], which
benefited from the high-density genetic maps for
physical map anchoring, can likewise serve as a
framework to construct genetic maps without the
necessity of a de novo map construction [27].
Moreover, this reference assembly provides access
to the majority of the barley genes, hence facilitating
the exploitation of natural genetic diversity [7].
In the past year, the development of a barley
comparative genomic hybridization (CGH) array
using whole-genome shotgun (WGS) sequences of
the reference genome has enabled exploration of the
CNV landscape in the barley genome [28]. An extensive catalog of CNVs affecting both coding and
non-coding regions has been identified among 14
accessions, revealing that CNV represents a major
source of genetic variation in the barley genome
[28]. Additionally, targeted sequencing of the
barley exome has become an option due to the development of an exome capture platform covering
over 60 Mbp of barley coding sequence [29]. This
tool can be extremely useful for identifying genetic
variation—SNPs, INDELs and CNVs—affecting the
coding regions of the genome without the ascertainment bias associated with array-based platforms [30].
CONNECTING GENOTYPE TO
PHENOTYPE
Genome-wide association studies
The development of the genomics tools described
above has provided the resources to identify loci
controlling important traits. Barley has been a
model species for developing QTL mapping
approaches and analyses based on biparental populations [6]. However, biparental populations present
several disadvantages such as the time and resources
needed for developing the specialized populations
segregating for the trait(s) to be mapped, the limitation of evaluating effects of only two alleles per
locus, and the low mapping resolution caused by
the limited recombination in the population [31,
32]. The increase in marker density achieved with
new genotyping technologies allowed the utilization
of GWAS approaches in barley [33]. Association
mapping (AM) relies on linkage disequilibrium to
find marker-trait associations in unrelated sets of accessions (e.g. the non-random association of alleles),
therefore allowing the assessment of multiple alleles
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per locus, and taking advantage of the historical recombination inherent in the population for highresolution mapping (reviewed in [34]). While the
diversity present in an association panel offers
higher possibilities to identify beneficial alleles,
population structure can cause false positive associations [35]. In barley, strong population structure is
often associated with spike row number and growth
habit, and accurate GWAS therefore requires proper
correction for the stratification due to these traits [19,
20, 36, 37]. The barley genetics and breeding community has embraced AM as an approach to identify
QTL and to provide the initial information for subsequent gene cloning.
Barley CAP and Triticeae CAP (TCAP)
A significant number of large-scale GWAS in barley
have been conducted using tools provided by
USDA-funded Barley CAP and TCAP projects.
The Barley CAP was established with the goal of
coordinated QTL mapping in breeding lines from
10 US breeding programs. Each breeding program
submitted 96 lines per year for a total of 960 lines per
year and 3840 lines for the 4 years of the project.
Each line was genotyped with 3072 OPA SNPs and
phenotyped for over 30 traits including those determining disease resistance, malting quality, agronomic
characters and food quality. The Barley CAP was a
very productive exercise in terms of generating new
knowledge and results. Three representative papers
from the Barley CAP addressing specific traits and
gene/QTL discovery are highlighted in the following narrative: these reports cover resistance to an abiotic stress that will play an important role in climate
change, a biotic stress that threatens the viability of
barley as a crop in the Upper Midwest of the USA,
and the genetic basis of malting quality—the suite of
traits that add the greatest economic value to barley.
Intuitively, climate change is associated with
global warming and therefore analysis of low-temperature tolerance (LTT) may appear to be an atavistic academic exercise. However, fall-sown
cereals—in areas with winter precipitation patterns—have a significant yield advantage of springsown cereals. Capitalizing on this advantage requires
the capacity to successfully overwinter, particularly as
production moves steadily northward (USDANASS: http://www.nass.usda.gov/). Even though
the average trend will be toward greater warming,
there will an increasing likelihood of wide fluctuations in temperature [38]. VonZitzewitz et al. [39]
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Mun‹oz-Amatriaín et al.
used a panel composed of winter and facultative
growth habit elite lines to determine the utility of
GWAS for discovery of genes determining LTT,
simply defined as the ability to survive low temperatures. GWAS was successful in identifying the principal determinants of low-temperature survival in
barley—the FRH-1 and FRH-2 loci. In one experiment, this GWAS revealed the same QTL that were
painstakingly discovered in over 20 years of biparental QTL mapping. The analysis also generated novel
and useful information on the non-additive interaction of favorable alleles at these two loci: notably,
both positive alleles are required for maximum cold
tolerance.
GWAS proved to be equally effective in validating and identifying genes associated with a biotic
stress—resistance to Fusarium Head Blight (FHB).
This devastating disease has always been a threat to
barley: throughout the 20th century, the incidence
of FHB steadily drove barley production westward.
Relatively disease-free environments were found in
Minnesota and North Dakota, which became major
barley producing states in close geographic proximity
to major urban centers, malt houses, breweries and
consumers. More recently, however, climate change
and advances in maize breeding and management
have led to epidemics of FHB in the region [40].
In terms of climate change, altered precipitation
and temperature patterns favor FHB disease development. Maize crop residues favor inoculum
buildup. The northward expansion of maize hybrids
and no-till management system has, together with
changes in climate, solidified two sides of the disease
triangle (pathogen and environment). The third side
of the triangle (susceptible host) has always existed.
There are no sources of immunity to FHB in barley
and the search for resistance to FHB has, of necessity,
focused on unadapted germplasm. Massman etal. [41]
used GWAS—based on multi-environment assessment of a large panel of Barley CAP-derived breeding lines—to detect QTL for two FHB-related traits
(severity and mycotoxin concentration in the grain).
These authors found FHB resistance QTL that had
been previously reported from biparental populations, as well as novel and useful information regarding markers that could be immediately applied to the
development of resistant varieties.
Resistance to abiotic and biotic stresses are essential attributes for successful barley varieties, but these
varieties must also have end-use properties that will
command a premium in the marketplace. Barley—in
the form of malt—is the base of beer and malting
quality, therefore, is the most direct route to assuring
economic value for barley grain. Malting quality is a
complex trait with no simple consistent definition:
different beer styles will require different malt profiles [1]. However, there are some baseline characters
essential for all malts that lead to the necessary
balance of carbohydrates and proteins essential for
yeast nutrition. Extensive research over the past
100 years has identified genes, and more
recently QTL, involved in the multiple metabolic
pathways leading to malt quality (reviewed by
[42]). Gutiérrez et al. [43] used the GWAS tools of
the Barley CAP to identify QTL for five of the most
important malting quality traits (malt extract, wort
beta glucan, alpha amylase activity, diastatic power
and grain protein content). Most of the QTL detected were close to previously mapped genes and
QTL relevant for malt and beer quality. The analysis
contributed to a deeper understanding of malting
quality genetics via the unmasking of novel alleles
and the quantification of inter-allelic interactions
and interaction of alleles with environments.
Cumulatively, these three studies typify the power
and impact of GWAS and the tools developed by the
Barley CAP.
The success of the Barley CAP, as documented
above, provided the momentum to develop the
TCAP. The TCAP seeks to explore new germplasm
sources to identify beneficial alleles for climatechange-related traits such as nitrogen and water use
efficiency, LTT and fungal disease resistance (http://
www.triticeaecap.org; Figure 1). The diverse germplasm targeted by the TCAP includes the NSGC
Barley Core, AM panels of elite breeding lines,
nested association mapping (NAM) populations and
wild barley-introgression populations. Accessing the
diversity within the NSGC Core is one of the main
goals of the TCAP, as the locally adapted landraces
and historical breeding materials stored in the collection can contain beneficial allelic variation which can
be incorporated into breeding programs. Figure 2
illustrates the phenotypic diversity existing in the
NSGC Core. Although most of the efforts are
underway, a genetic characterization of the NSGC
Core using the high-density iSelect genotyping platform has been completed. This information has been
used to determine population structure and linkage
disequilibrium within the Core, to conduct GWAS
of ‘hull cover’, ‘spike row number’ and ‘heading
date’, and to develop mini-core sets capturing the
Barley genetic variation
majority of the allelic diversity present in the Core
collection [23].
Additional international efforts
Internationally, GWAS has been effectively used for
allele mining of agronomic traits [44] and salt tolerance [45] in materials from the Barley Core
Collection [46] and the IPK Genebank. UK germplasm has been also used for GWAS of morphological [47, 48] and agronomic [48, 49] traits.
Hordeum vulgare subsp. spontaneum collections are
also being established to exploit the genetic diversity
present in the wild relative of barley. For example,
the Wild Barley Diversity Collection, comprising
over 300 wild barley accessions [8], was established
with the main goal of identifying new resistance loci
to important barley diseases. New spot blotch resistance loci have been already identified using this collection [50].
GWAS in germplasm collections can also provide
the initial information to isolate genes that control
phenotypes. A germplasm collection composed of
North American and European barley varieties was
used in the identification of one of the genes
involved in spike row morphology on chromosome
345
4H. The QTL was coincident with the IntermediumC (Int-C) locus. Rice–barley synteny was subsequently used to identify a Teosinte branched1 (Tb1)
ortholog as a candidate gene [51]. Similarly, in a
collection of UK barley cultivars, a combination of
GWAS and comparative genomics identified a candidate gene for the anthocyanin pigmentation locus
ANT2 [47]. Another approach to GWAS for gene
isolation was used by Comadran et al. [11] in the
identification of a barley flowering time gene.
Signatures of divergent selection revealed by FST
analysis in a selected panel of spring- and winterhabit cultivars were used to identify a barley homolog of Antirrhinum CENTRORADIALIS (HvCEN) as
a contributor to the spring growth habit and environmental adaptation [11].
Copy-number variation studies
Recent studies have revealed that CNVs (i.e. deletions, insertions and duplications ranging from a few
to several thousand base pairs in size) are a very
common type of genetic variation in plant genomes
(reviewed in [52]). CNVs can have important
phenotypic consequences by changing gene dosage,
interrupting coding sequences or altering the copy
SNP genotyping
OPA platforms
iSelect platform
384-custom platform
GBS
CAP barley germplasm
NSGC Barley Core
NAM populations
Wild barley-introgression
populations
Elite AM panels
Data management
Triticeae Toolbox (T3)
Data analysis
MAS
GWAS
QTL mapping
Nested association
mapping
GS
Barley
improvement
Gene
cloning
Phenotyping
Yield
Disease resistances
NUE, WUE
LTT
Figure 1: Schematic diagram of the TCAP approach to barley breeding. A diverse set of germplasm including the
NSGC Barley Core, NAM populations, wild barley-introgression populations and elite AM panels are being genotyped and phenotyped. SNP genotyping tools include the Illumina OPA, iSelect and custom platforms, and GBS.
Phenotyping is being focused on climate-change-related traits such as yield, disease resistances, nitrogen and
water use efficiency (NUE and WUE), and LTT. All the genotypic and phenotypic data being generated are placed
in the Triticeae Toolbox (T3) database, and can be accessed by all members of the project to conduct GWAS or
other type of QTL mapping. Discoveries are being directed into MAS and GS programs, and are also being used
for gene isolation. Cumulatively, these strategies will lead to the development of improved barley germplasm in a
more efficient manner.
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Mun‹oz-Amatriaín et al.
Figure 2: Morphological variation existing in the NSGC Barley Core. (A) Diversity of grain types from Ethiopian
accessions belonging to the NSGC Core. (B) Examples of variation in spike morphology present in the Core
collection.
number of regulatory regions. In barley, Sutton et al.
[53] demonstrated that an increased copy number
of the boron transporter gene Bot1 confers
boron-toxicity tolerance to a barley landrace from
Algeria. Similarly, Knox et al. [54] found an association between variation in the copy number of CBF
(C-Repeat Binding Factor) genes at the Frost Resistant-2
(FR-2) locus and tolerance to low temperatures.
More recently, a CGH array developed for barley
has provided the tool to estimate the extent of
CNV in the barley genome [28]. This study revealed
that 9.5% of the coding sequences represented on the
CGH array exhibited CNVs. Genes affected by
CNV are enriched for sequences annotated as disease-resistance proteins, predominantly nucleotidebinding site leucine-rich repeat (NBS-LRR) and
other classes of R proteins. Interestingly, this largescale study also identified CNV at the CBF3 gene
between winter and spring cultivars, providing more
evidence that CNV of CBF genes may contribute to
cold tolerance. A substantial loss in CNV diversity as
a consequence of domestication and breeding was
found, as almost half of the exon-affecting variants
were present only in wild barley.
APPLICATION TO BARLEY
IMPROVEMENT
Barley improvement is not possible without genetic
variation. Breeders usually cross elite lines within a
defined germplasm pool expecting to assemble better
allele combinations in the offspring. This is called
advanced cycle breeding [55] and leads to an accumulation of favorable alleles. Elite lines, as a result,
become more alike within a breeding program and
more different from unimproved germplasm [56]. In
most barley programs, the sources of genetic diversity
can be traced back to a small number of foundational
varieties. Advanced cycle breeding reduces this limited genetic diversity even further. Despite this diversity compression, breeders continue to see genetic
gains in yield and many agronomic traits [57].
Without new germplasm infusion, however, there
is an increased risk of genetic vulnerability as a consequence of pathogen population evolution, loss of
resistance genes [58], as well as the appearance of
new abiotic stresses and yield constraints [59]. The
narrow genetic base of breeding programs was quantified by Martin etal. [60] using pedigree information:
seven ancestors contributed 52% of the North
Barley genetic variation
American 6-row germplasm pool and another seven
ancestors contributed 67% of the 2-row pool. More
recently, using genotypic data from the iSelect genotyping platform we found that 10 parents had contributed over 90% of the alleles present in elite
breeding lines of Oregon State University winter
6-row barley breeding program (unpublished data).
These examples illustrate that breeders access only a
small fraction of the overall available diversity in the
barley germplasm pool to release new varieties.
Continued gains from selection will require efficient access to, and introgression of, novel alleles in
wild relatives, exotic germplasm and elite germplasm
from other breeding programs. Advanced back-cross
QTL studies have shown that wild ancestors of
barley may contribute favorable alleles, likely lost
after a domestication bottleneck, for several agronomic traits, including grain yield and agronomic
performance under drought conditions [61], disease
resistance [62, 63] and malt quality [64]. There are
also examples of successful introgression of alleles
from exotic germplasm to address specific needs.
Ethiopian landraces have been a source of favorable
alleles for Barley Yellow Dwarf virus [65]; most of
the powdery mildew resistance genes used commercially have been introgressed from landraces originating in West Asia, Ethiopia and North Africa [66]; the
boron-toxicity tolerance found in many Australian
varieties traces to an Algerian landrace [53]; and
Spanish landraces were the source of a mild vernalization sensitivity allele that improves adaptation to
Mediterranean environments [67].
Introgression of unadapted germplasm into a
breeding program usually combines several cycles
of backcrossing using an elite line as a recurrent
parent and a landrace/wild barley as the donor of
favorable alleles. The use of the new genotyping
and mapping tools can make this process faster and
more efficient, as SNPs used for MAS can be more
closely associated with the desired gene.
Recombinant individuals in a segregating population
can be selected for a smaller introgression size and a
larger percentage of the recurrent parent genome,
thus reducing linkage drag [68]. However, introgression of exotic germplasm is always challenging. Very
often, the favorable alleles in exotic germplasm are
tightly linked with negative alleles determining deleterious or undesirable traits and then linkage drag is
more difficult to solve, even with the increased
marker density. Either because of linkage drag, or
the epistatic effects of genetic background, favorable
347
alleles may not have the same effect when they are
introgressed into a different genetic background. In
these cases, an intermediate step of validation of allele
effects in different genetic backgrounds is recommended [69]. In contrast, if panels of elite materials
are used for GWAS, the QTL detected could be
more directly incorporated into breeding programs
with no need of prebreeding.
The availability of high-density marker data has
driven the emergence of a new breeding approach
called genomic selection (GS). GS attempts to address some of the limitations of MAS by using all
genome-wide SNP data to predict breeding values
(genomic estimated breeding values, GEBVs [70])
for individual lines in a breeding program [71].
The genomic prediction for a trait of interest requires
a ‘training population’ of breeding lines for which
both phenotypic and genotypic data exist. Since individuals can be selected based on all marker information and without phenotypic tests, faster gains for
quantitative traits can be achieved [71]. If GS is
coupled with doubled haploid production, the
breeding cycle can be as short as one generation.
Indeed, GS has been implemented in barley breeding
programs and simulations studies are showing promising results [72–74]. Encouragingly, in the first
empirical study in barley, Lorenz et al. [75] show
that GS approaches can be used to accelerate FHB
resistance breeding.
Regardless of whether breeders are intending to
access ancestral or elite germplasm, or the type of
breeding strategy they are planning to apply, key considerations are access to germplasm, passport information, phenotypic data, genotypic data and
connectivity to the barley gene sequence information.
The development of databases that integrate and analyse the amount of data being generated is key to
providing the accessibility and distribution of genetic
materials to the barley community. In this context, a
new and key resource integrating contemporary genotyping and sequencing data with phenotype data sets
relevant to plant breeders is the Triticeae Toolbox
(T3) (http://triticeaetoolbox.org/). T3 was previously developed by the Barley CAP and known as
The Hordeum Toolbox [76]. T3 serves as the database for the data generated by the TCAP. T3 allows
open access to SNP, phenotypic and pedigree data
from barley (and wheat) germplasm from groups participating in the CAP and from the core collections of
the USDA-NSGC. It also integrates the same information from the Barley CAP. T3 includes analysis and
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Mun‹oz-Amatriaín et al.
visualization tools in a user-friendly environment,
allowing breeders to select specific lines, traits and
trials of interest and obtain marker-trait associations
with GWAS or to make genomic predictions (GEBV
predictions) for a set of lines. This resource connects
the breeding programs from across the country, providing the opportunity for the barley breeding community to collaborate more effectively. T3 is a crucial
component of the TCAP approach to achieve a sustainable nation-wide improvement of the barley crop
(Figure 1).
New genomics and molecular breeding technologies are allowing us to better understand and mine
genetic variation. Cumulatively, the new resources
empower the current generation of barley breeders
and geneticists to continue the tradition of barley
making simultaneous contributions to agriculture
and to science. The great challenges of climate
change and human population growth will require
innovative, insightful, and productive germplasm enhancement and variety development.
2.
3.
4.
5.
6.
7.
8.
9.
10.
Key Points
We are experiencing a revolution in genomics that is allowing
access to barley genetic diversity (SNPs, INDELs and CNVs) on
an unprecedented scale.
High-density genome-wide SNP data are allowing GWAS in
barley, providing information for MAS, GS and gene cloning.
Useful genetic variation for barley breeding can be now connected to the assembled catalog of gene sequences, increasing
the precision and speed of barley improvement.
The Barley CAP and TCAP are successful examples of collaborative approaches to breeding that have resulted in a rapid exploitation of barley genetic resources for crop improvement.
11.
12.
13.
14.
Acknowledgements
We would like to thank Dr Harold Bockelman and Dr Mike
Bonman (USDA-ARS Aberdeen, Idaho) for kindly providing
the picture used in Figure 2A.
15.
16.
FUNDING
This work was supported by the Triticeae Coordinated
Agricultural Project [2011-68002-30029], funded by the
United States Department of Agriculture, National Institute of
Food and Agriculture.
17.
18.
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