Cultivated oat (Avena sativa L.) is an allohexaploid (AACCDD, 2n = 6x = 42) thought to have been domesticated more than 3,000 years ago while growing as a weed in wheat, emmer and barley fields in Anatolia^1,2. Oat has a low carbon footprint, substantial health benefits and the potential to replace animal-based food products. However, the lack of a fully annotated reference genome has hampered efforts to deconvolute its complex evolutionary history and functional gene dynamics. Here we present a high-quality reference genome of A. sativa and close relatives of its diploid (Avena longiglumis, AA, 2n = 14) and tetraploid (Avena insularis, CCDD, 2n = 4x = 28) progenitors. We reveal the mosaic structure of the oat genome, trace large-scale genomic reorganizations in the polyploidization history of oat and illustrate a breeding barrier associated with the genome architecture of oat. We showcase detailed analyses of gene families implicated in human health and nutrition, which adds to the evidence supporting oat safety in gluten-free diets, and we perform mapping-by-sequencing of an agronomic trait related to water-use efficiency. This resource for the Avena genus will help to leverage knowledge from other cereal genomes, improve understanding of basic oat biology and accelerate genomics-assisted breeding and reanalysis of quantitative trait studies.

Advances in next-generation sequencing offer high-throughput and cost-effective genotyping alternatives, including genotyping-by-sequencing (GBS). Results have shown that this methodology is efficient for genotyping a variety of species, including those with complex genomes. To assess the utility of GBS in cultivated hexaploid oat (Avena sativa L.), seven bi-parental mapping populations and diverse inbred lines from breeding programs around the world were studied. We examined technical factors that influence GBS SNP calls, established a workflow that combines two bioinformatics pipelines for GBS SNP calling, and provided a nomenclature for oat GBS loci. The high-throughput GBS system enabled us to place 45,117 loci on an oat consensus map, thus establishing a positional reference for further genomic studies. Using the diversity lines, we estimated that a minimum density of one marker per 2 to 2.8 cM would be required for genome-wide association studies (GWAS), and GBS markers met this density requirement in most chromosome regions. We also demonstrated the utility of GBS in additional diagnostic applications related to oat breeding. We conclude that GBS is a powerful and useful approach, which will have many additional applications in oat breeding and genomic studies.

Genomic discovery in oat and its application to oat improvement have been hindered by a lack of genetic markers common to different genetic maps, and by the difficulty of conducting whole-genome analysis using high-throughput markers. This study was intended to develop, characterize, and apply a large set of oat genetic markers based on Diversity Array Technology (DArT).

Summary: In a de novo genotyping‐by‐sequencing (GBS) analysis of short, 64‐base tag‐level haplotypes in 4657 accessions of cultivated oat, we discovered 164741 tag‐level (TL) genetic variants containing 241224 SNPs. From this, the marker density of an oat consensus map was increased by the addition of more than 70000 loci. The mapped TL genotypes of a 635‐line diversity panel were used to infer chromosome‐level (CL) haplotype maps. These maps revealed differences in the number and size of haplotype blocks, as well as differences in haplotype diversity between chromosomes and subsets of the diversity panel. We then explored potential benefits of SNP vs. TL vs. CL GBS variants for mapping, high‐resolution genome analysis and genomic selection in oats. A combined genome‐wide association study (GWAS) of heading date from multiple locations using both TL haplotypes and individual SNP markers identified 184 significant associations. A comparative GWAS using TL haplotypes, CL haplotype blocks and their combinations demonstrated the superiority of using TL haplotype markers. Using a principal component‐based genome‐wide scan, genomic regions containing signatures of selection were identified. These regions may contain genes that are responsible for the local adaptation of oats to Northern American conditions. Genomic selection for heading date using TL haplotypes or SNP markers gave comparable and promising prediction accuracies of up to r = 0.74. Genomic selection carried out in an independent calibration and test population for heading date gave promising prediction accuracies that ranged between r = 0.42 and 0.67. In conclusion, TL haplotype GBS‐derived markers facilitate genome analysis and genomic selection in oat.

Hexaploid oat ( Avena sativa L., 2 n = 6 x = 42) is a member of the Poaceae family and has a large genome (∼12.5 Gb) containing 21 chromosome pairs from three ancestral genomes. Physical rearrangements among parental genomes have hindered the development of linkage maps in this species. The objective of this work was to develop a single high‐density consensus linkage map that is representative of the majority of commonly grown oat varieties. Data from a cDNA‐derived single‐nucleotide polymorphism (SNP) array and genotyping‐by‐sequencing (GBS) were collected from the progeny of 12 biparental recombinant inbred line populations derived from 19 parents representing oat germplasm cultivated primarily in North America. Linkage groups from all mapping populations were compared to identify 21 clusters of conserved collinearity. Linkage groups within each cluster were then merged into 21 consensus chromosomes, generating a framework consensus map of 7202 markers spanning 2843 cM. An additional 9678 markers were placed on this map with a lower degree of certainty. Assignment to physical chromosomes with high confidence was made for nine chromosomes. Comparison of homeologous regions among oat chromosomes and matches to orthologous regions of rice ( Oryza sativa L.) reveal that the hexaploid oat genome has been highly rearranged relative to its ancestral diploid genomes as a result of frequent translocations among chromosomes. Heterogeneous chromosome rearrangements among populations were also evident, probably accounting for the failure of some linkage groups to match the consensus. This work contributes to a further understanding of the organization and evolution of hexaploid grass genomes.

Background: Genetic 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. Results: Based 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. Conclusions: The 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.