Quantitative trait locus (QTL) and QTL x environment (E) interaction effects for agronomic and malting quality traits were measured using a 123-point linkage map and multi-environment phenotype data from an F1-derived doubled haploid population of barley (Hordeum vulgare). The QTL × E interactions were due to differences in magnitude of QTL effects. Highly significant QTL effects were found for all traits at multiple sites in the genome. Yield QTL peaks and support intervals often coincided with plant height and lodging QTL peaks and support intervals. QTL were detected in the vicinity of a previously mapped Mendelian maturity locus and known function probes forα- andβ-amylase genes. The average map density (9.6 cM) should be adequate for molecular marker-assisted selection, particularly since there were few cases of alternative favorable alleles for different traits mapping to the same or adjacent intervals.

Quantitative trait locus (QTL) main effects and QTL by environment (QTL × E) interactions for seven agronomic traits (grain yield, days to heading, days to maturity, plant height, lodging severity, kernel weight, and test weight) were investigated in a two-row barley (Hordeura vulgare L.) cross, Harrington/TR306. A 127-point base map was constructed from markers (mostly RFLP) scored in 146 random double-haploid (DH) lines from the Harrington/TR306 cross. Field experiments involving the two parents and 145 random DH lines were grown in 1992 and/or 1993 at 17 locations in North America. Analysis of QTL was based on simple and composite interval mapping. Primary QTL were declared at positions where both methods gave evidence for QTL. The number of primary QTL ranged from three to six per trait, collectively explaining 34 to 52% of the genetic variance. None of these primary QTL showed major effects, but many showed effects that were consistent across environments. The addition of secondary QTL gave models that explained 39 to 80% of the genetic variance. The QTL were dispersed throughout the barley genome and some were detected in regions where QTL have been found in previous studies. Eight chromosome regions contained pleiotropic loci and/or linked clusters of loci that affected multiple traits. One region on chromosome 7 affected all traits except days to heading. This study was an intensive effort to evaluate QTL in a narrow-base population grown in a large set of environments. The results reveal the types and distributions of QTL effects manipulated by plant breeders and provide opportunities for future testing of marker-assisted selection. M OLECULAR MAPS of plant genomes, used in conjunction with phenotypic measurements, can provide information about chromosome regions that affect quantitative traits. Although knowing whether such regions represent individual quantitative trait loci (QTL)

We report malt quality QTLs relevant to breeding with greater precision than previous mapping studies. The distribution of favorable alleles suggests strategies for marker-assisted breeding and germplasm exchange. This study leverages the breeding data of 1,862 barley breeding lines evaluated in 97 field trials for genome-wide association study of malting quality traits in barley. The mapping panel consisted of six-row and two-row advanced breeding lines from eight breeding populations established at six public breeding programs across the United States. A total of 4,976 grain samples were subjected to micro-malting analysis and mapping of nine quality traits was conducted with 3,072 SNP markers distributed throughout the genome. Association mapping was performed for individual breeding populations and for combined six-row and two-row populations. Only 16% of the QTL we report here had been detected in prior bi-parental mapping studies. Comparison of the analyses of the combined two-row and six-row panels identified only two QTL regions that were common to both. In total, 108 and 107 significant marker-trait associations were identified in all six-row and all two-row breeding programs, respectively. A total of 102 and 65 marker-trait associations were specific to individual six-row and two-row breeding programs, respectively indicating that most marker-trait associations were breeding population specific. Combining datasets from different breeding program resulted in both the loss of some QTL that were apparent in the analyses of individual programs and the discovery of new QTL not identified in individual programs. This suggests that simply increasing sample size by pooling samples with different breeding history does not necessarily increase the power to detect associations. The genetic architecture of malting quality and the distribution of favorable alleles suggest strategies for marker-assisted selection and germplasm exchange.

The use of genome-wide association studies (GWAS) to detect quantitative trait loci (QTL) controlling complex traits has become a popular approach for studying key traits in crop plants. The goal of this study was to identify the genomic regions of barley (Hordeum vulgare L.) that impact five agronomic and one quality trait in U.S. elite barley breeding lines, as well as to identify markers tightly linked with these loci for further use in barley improvement. Advanced recombinant inbred lines submitted to the U.S. Barley Coordinated Agricultural Project (CAP) were genotyped using a platform of 3072 single nucleotide polymorphism (SNP) markers from the barley oligonucleotide pool assays (BOPAs) 1 and 2. In each of 4 yr, approximately 770 lines were evaluated in a replicated, randomized complete block design under both irrigated and dryland conditions. This gave an overall population size of >3000 lines, which we analyzed in a hierarchical fashion, including analyzing the lines in aggregate using a mixed model to account for population structure and relatedness among the lines. We identified 41 significant marker-trait associations, of which 31 had been previously reported as QTL using biparental mapping techniques; 10 novel marker-trait associations were identified. The results of this work show that genes with major effects are still segregating in U.S. barley germplasm and demonstrate the utility of GWAS in barley breeding populations.

The ability to access alleles from unadapted germplasm collections is a long-standing problem for geneticists and breeders. Here we developed, characterized, and demonstrated the utility of a wild barley advanced backcross-nested association mapping (AB-NAM) population. We developed this population by backcrossing 25 wild barley accessions to the six-rowed malting barley cultivar Rasmusson. The 25 wild barley parents were selected from the 318 accession Wild Barley Diversity Collection (WBDC) to maximize allelic diversity. The resulting 796 BC 2 F 4:6 lines were genotyped with 384 SNP markers, and an additional 4022 SNPs and 263,531 sequence variants were imputed onto the population using 9K iSelect SNP genotypes and exome capture sequence of the parents, respectively. On average, 96% of each wild parent was introgressed into the Rasmusson background, and the population exhibited low population structure. While linkage disequilibrium (LD) decay (r 2 = 0.2) was lowest in the WBDC (0.36 cM), the AB-NAM (9.2 cM) exhibited more rapid LD decay than comparable advanced backcross (28.6 cM) and recombinant inbred line (32.3 cM) populations. Three qualitative traits: glossy spike, glossy sheath, and black hull color were mapped with high resolution to loci corresponding to known barley mutants for these traits. Additionally, a total of 10 QTL were identified for grain protein content. The combination of low LD, negligible population structure, and high diversity in an adapted background make the AB-NAM an important tool for highresolution gene mapping and discovery of novel allelic variation using wild barley germplasm.KEYWORDS wild barley; advanced backcross; nested association mapping population; association mapping; plant genetic resources; Multiparent Advanced Generation Inter-Cross (MAGIC); multiparental populations; MPP D IVERSE germplasm collections are valuable resources for crop improvement. However, breeders often neglect these resources due to the time and effort required to identify and deploy beneficial exotic alleles. Breeding for complex traits requires balancing the introduction of genetic diversity with maintaining the selective progress obtained over many cycles of breeding (Bernardo 2002). Due to the malting quality requirements imposed by North American malting and brewing industries, barley (Hordeum vulgare subsp. vulgare) breeding has been restricted to a narrow germplasm base and focused on elite-by-elite crosses (Rasmusson and Phillips 1997). Over many cycles of breeding, extensive genome-wide linkage disequilibrium (LD) can develop in closed breeding populations (Fang et al. 2013), and the genetic diversity of these populations becomes reduced (Condón et al. 2008;Fu and Somers 2009;Muñoz-Amatriaín et al. 2010;Poets et al. 2015). The need to expand the genetic diversity of the breeding pool has become evident as breeders face disease and environmental pressures which are threatening crop production. Today, genomics technologies are advancing our ability to understand the genetic basis of ...

GrainGenes (http://wheat.pw.usda.gov) is an international database for genetic and genomic information about Triticeae species (wheat [Triticum aestivum], barley [Hordeum vulgare], rye [Secale cereale], and their wild relatives) and oat (Avena sativa) and its wild relatives. A major strength of the GrainGenes project is the interaction of the curators with database users in the research community, placing GrainGenes as both a data repository and information hub. The primary intensively curated data classes are genetic and physical maps, probes used for mapping, classical genes, quantitative trait loci, and contact information for Triticeae and oat scientists. Curation of these classes involves important contributions from the GrainGenes community, both as primary data sources and reviewers of published data. Other partially automated data classes include literature references, sequences, and links to other databases. Beyond the GrainGenes database per se, the Web site incorporates other more specific databases, informational topics, and downloadable files. For example, unique BLAST datasets of sequences applicable to Triticeae research include mapped wheat expressed sequence tags, expressed sequence tag-derived simple sequence repeats, and repetitive sequences. In 2004, the GrainGenes project migrated from the AceDB database and separate Web site to an integrated relational database and Internet resource, a major step forward in database delivery. The process of this migration and its impacts on database curation and maintenance are described, and a perspective on how a genomic database can expedite research and crop improvement is provided. ) and oat (Avena sativa) crops to plant breeders, pathologists, geneticists, and molecular biologists (Matthews et al., 2003). Originally conceived as a stand-alone database, GrainGenes now encompasses an integrated database and Web site, working intensively with the smallgrains research community to provide an Internet portal for numerous ancillary projects for Triticeae genetics and contributing to the development of informatics tools to support small-grains research. Like many other organism-focused databases, GrainGenes concentrates on genomic aspects; however, it is also an important repository for information concerning genetic resources, pathology, and colleagues.The GrainGenes Database initially was operated using AceDB (http://www.acedb.org), a platform adopted by many early genome projects. AceDB served the GrainGenes project's needs very well with powerful schema, query languages, graphical displays, and the simplicity to be operated completely by a single biologist. The object-like data structures of AceDB worked well for handling the diverse underlying data, enabling straightforward connections between all data types and allowing the schema to be changed easily to accommodate new kinds of data. The AceDB software continued to develop and improve for several years and still has an active user community, providing an excellent resource for biological database deve...

Crop improvement relies on the ability to utilize novel genetic variation. Six‐rowed malting barley (Hordeum vulgare L. subsp. vulgare) developed in the US Midwest has an especially narrow genetic base. Therefore, developing strategies to widen the genetic base in barley is important for continued crop improvement. A wild barley [Hordeum vulgare L. subsp. spontaneum (K. Koch) Thell.] advanced backcross–nested association mapping (AB‐NAM) population was developed to assess wild‐barley‐derived alleles in an elite spring six‐rowed malting barley background. The 796 BC2F4:6 lines in the AB‐NAM were derived from 25 wild barley accessions backcrossed to the cultivar Rasmusson. Because the AB‐NAM design minimizes the deleterious and unadapted traits of the wild barley parents, the population was screened in five field environments for the agronomic traits: days to heading, height, productive tiller number (PTN), test weight, and yield. The number of loci identified ranged from two (PTN, the trait with the lowest heritability) to 19 (height). Domestication‐related genes were identified for each trait, particularly the photoperiod gene Ppd‐H1 for days to heading, height, and PTN and the nonbrittle Btr1/Btr2 loci for test weight and yield. Only a single variant showed beneficial variation for yield from a wild barley allele, but positive effects were identified for the other traits examined, including positive variants for test weight on chromosomes 1H and 3H. The AB‐NAM population is a novel resource to map agronomically important traits associated with wild barley alleles.

The polymerase chain reaction (PCR) is an attractive technique for many genome mapping and characterization projects. One PCR approach which has been evaluated involves the use of randomly amplified polymorphic DNA (RAPD). An alternative to RAPDs is the sequence-tagged-site (STS) approach, whereby PCR primers are designed from mapped low-copy-number sequences. In this study, we sequenced and designed primers from 22 wheat RFLP clones in addition to testing 15 primer sets that had been previously used to amplify DNA sequences in the barley genome. Our results indicated that most of the primers amplified sequences that mapped to the expected chromosomes in wheat. Additionally, 9 of 16 primer sets tested revealed polymorphisms among 20 hexaploid wheat genotypes when PCR products were digested with restriction enzymes. These results suggest that the STS-based PCR analysis will be useful for generation of informative molecular markers in hexaploid wheat.