Previous studies have shown that there is considerable population structure in cultivated barley (Hordeum vulgare L.), with the strongest structure corresponding to differences in row number and growth habit. U.S. barley breeding programs include six‐row and two‐row types and winter and spring types in all combinations. To facilitate mapping of complex traits in breeding germplasm, 1816 barley lines from 10 U.S. breeding programs were scored with 1536 single nucleotide polymorphism (SNP) genotyping assays. The number of SNPs segregating within breeding programs varied from 854 to 1398. Model‐based analysis of population structure showed the expected clustering by row type and growth habit; however, there was additional structure, some of which corresponded to the breeding programs. The model that fit the data best had seven populations: three two‐row spring, two six‐row spring, and two six‐row winter. Average linkage disequilibrium (LD) within populations decayed over a distance of 20 to 30 cM, but some populations showed long‐range LD suggestive of admixture. Genetic distance (allele‐sharing) between populations varied from 0.11 (six‐row spring vs. six‐row spring) to 0.45 (two‐row spring vs. six‐row spring). Analyses of pairwise LD revealed that the phase of allelic associations was not well correlated between populations, particularly when their allele‐sharing distance was >0.2. These results suggest that pooling divergent barley populations for purposes of association mapping may be inadvisable.
A physically anchored consensus map is foundational to modern genomics research; however, construction of such a map in oat (Avena sativa L., 2n = 6x = 42) has been hindered by the size and complexity of the genome, the scarcity of robust molecular markers, and the lack of aneuploid stocks. Resources developed in this study include a modified SNP discovery method for complex genomes, a diverse set of oat SNP markers, and a novel chromosome-deficient SNP anchoring strategy. These resources were applied to build the first complete, physically-anchored consensus map of hexaploid oat. Approximately 11,000 high-confidence in silico SNPs were discovered based on nine million inter-varietal sequence reads of genomic and cDNA origin. GoldenGate genotyping of 3,072 SNP assays yielded 1,311 robust markers, of which 985 were mapped in 390 recombinant-inbred lines from six bi-parental mapping populations ranging in size from 49 to 97 progeny. The consensus map included 985 SNPs and 68 previously-published markers, resolving 21 linkage groups with a total map distance of 1,838.8 cM. Consensus linkage groups were assigned to 21 chromosomes using SNP deletion analysis of chromosome-deficient monosomic hybrid stocks. Alignments with sequenced genomes of rice and Brachypodium provide evidence for extensive conservation of genomic regions, and renewed encouragement for orthology-based genomic discovery in this important hexaploid species. These results also provide a framework for high-resolution genetic analysis in oat, and a model for marker development and map construction in other species with complex genomes and limited resources.
Six hundred thirty five oat (Avena sativa L.) lines and 4561 single-nucleotide polymorphism (SNP) loci were used to evaluate population structure, linkage disequilibrium (LD), and genotypephenotype association with heading date. The first five principal components (PCs) accounted for 25.3% of genetic variation. Neither the eigenvalues of the first 25 PCs nor the cross-validation errors from K = 1 to 20 model-based analyses suggested a structured population. However, the PC and K = 2 model-based analyses supported clustering of lines on spring oat vs. southern United States origin, accounting for 16% of genetic variation (p < 0.0001). Single-locus F-statistic (F ST ) in the highest 1% of the distribution suggested linkage groups that may be differentiated between the two population subgroups. Population structure and kinship-corrected LD of r 2 = 0.10 was observed at an average pairwise distance of 0.44 cM (0.71 and 2.64 cM within spring and southern oat, respectively). On most linkage groups LD decay was slower within southern lines than within the spring lines. A notable exception was found on linkage group Mrg28, where LD decay was substantially slower in the spring subpopulation. It is speculated that this may be caused by a heterogeneous translocation event on this chromosome. Association with heading date was most consistent across location-years on linkage groups Mrg02, Mrg12, Mrg13, and Mrg24. Core Ideas• An oat association-mapping panel contributed by active breeding programs worldwide.• Characterized population structure and found subdivisions related to adaptation• Characterized genome-wide and chromosomespecific linkage disequilibrium• Performed association-mapping and post hoc modeling of heading date• Found several consistently associated 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.
BackgroundGenetic markers are pivotal to modern genomics research; however, discovery and genotyping of molecular markers in oat has been hindered by the size and complexity of the genome, and by a scarcity of sequence data. The purpose of this study was to generate oat expressed sequence tag (EST) information, develop a bioinformatics pipeline for SNP discovery, and establish a method for rapid, cost-effective, and straightforward genotyping of SNP markers in complex polyploid genomes such as oat.ResultsBased on cDNA libraries of four cultivated oat genotypes, approximately 127,000 contigs were assembled from approximately one million Roche 454 sequence reads. Contigs were filtered through a novel bioinformatics pipeline to eliminate ambiguous polymorphism caused by subgenome homology, and 96 in silico SNPs were selected from 9,448 candidate loci for validation using high-resolution melting (HRM) analysis. Of these, 52 (54%) were polymorphic between parents of the Ogle1040 × TAM O-301 (OT) mapping population, with 48 segregating as single Mendelian loci, and 44 being placed on the existing OT linkage map. Ogle and TAM amplicons from 12 primers were sequenced for SNP validation, revealing complex polymorphism in seven amplicons but general sequence conservation within SNP loci. Whole-amplicon interrogation with HRM revealed insertions, deletions, and heterozygotes in secondary oat germplasm pools, generating multiple alleles at some primer targets. To validate marker utility, 36 SNP assays were used to evaluate the genetic diversity of 34 diverse oat genotypes. Dendrogram clusters corresponded generally to known genome composition and genetic ancestry.ConclusionsThe high-throughput SNP discovery pipeline presented here is a rapid and effective method for identification of polymorphic SNP alleles in the oat genome. The current-generation HRM system is a simple and highly-informative platform for SNP genotyping. These techniques provide a model for SNP discovery and genotyping in other species with complex and poorly-characterized genomes.
Amylose and β‐glucan are important components of barley (Hordeum vulgare L.) grain. Factors such as seed yield, test weight, seed plumpness, protein content, field location, and seasonal variation may have an effect on β‐glucan and amylose concentrations, and therefore, require additional study. Twenty‐seven barley cultivars and advanced lines with varying levels of β‐glucan (4–9%) and amylose (6–27%) were grown in 2004 and 2005 in replicated plots at three locations in Idaho to evaluate agronomic traits and genotype × environment interactions. Seed yield, test weight, percentage of plump kernels, β‐glucan percentage, amylose/amylopectin ratio, and protein percentage were measured for seed samples from all plots. Estimates of variance components showed that about 49% of the variability in β‐glucan concentration and about 48% in amylose starch levels can be attributed to year, location, year × location, and their interactions with genotype. Amylose was found to be negatively correlated with protein and β‐glucan content but was positively, though weakly, correlated with seed yield and test weight; β‐glucan was positively correlated with protein and percentage plump kernels but showed a weak negative correlation with seed yield.
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