Domesticated crops experience strong human-mediated selection aimed at developing high-yielding varieties adapted to local conditions. To detect regions of the wheat genome subject to selection during improvement, we developed a high-throughput array to interrogate 9,000 gene-associated single-nucleotide polymorphisms (SNP) in a worldwide sample of 2,994 accessions of hexaploid wheat including landraces and modern cultivars. Using a SNP-based diversity map we characterized the impact of crop improvement on genomic and geographic patterns of genetic diversity. We found evidence of a small population bottleneck and extensive use of ancestral variation often traceable to founders of cultivars from diverse geographic regions. Analyzing genetic differentiation among populations and the extent of haplotype sharing, we identified allelic variants subjected to selection during improvement. Selective sweeps were found around genes involved in the regulation of flowering time and phenology. An introgression of a wild relative-derived gene conferring resistance to a fungal pathogen was detected by haplotype-based analysis. Comparing selective sweeps identified in different populations, we show that selection likely acts on distinct targets or multiple functionally equivalent alleles in different portions of the geographic range of wheat. The majority of the selected alleles were present at low frequency in local populations, suggesting either weak selection pressure or temporal variation in the targets of directional selection during breeding probably associated with changing agricultural practices or environmental conditions. The developed SNP chip and map of genetic variation provide a resource for advancing wheat breeding and supporting future population genomic and genomewide association studies in wheat.SNP genotyping | polyploid wheat | selection scans | wheat improvement | breeding history

New sources of genetic diversity must be incorporated into plant breeding programs if they are to continue increasing grain yield and quality, and tolerance to abiotic and biotic stresses. Germplasm collections provide a source of genetic and phenotypic diversity, but characterization of these resources is required to increase their utility for breeding programs. We used a barley SNP iSelect platform with 7,842 SNPs to genotype 2,417 barley accessions sampled from the USDA National Small Grains Collection of 33,176 accessions. Most of the accessions in this core collection are categorized as landraces or cultivars/breeding lines and were obtained from more than 100 countries. Both STRUCTURE and principal component analysis identified five major subpopulations within the core collection, mainly differentiated by geographical origin and spike row number (an inflorescence architecture trait). Different patterns of linkage disequilibrium (LD) were found across the barley genome and many regions of high LD contained traits involved in domestication and breeding selection. The genotype data were used to define ‘mini-core’ sets of accessions capturing the majority of the allelic diversity present in the core collection. These ‘mini-core’ sets can be used for evaluating traits that are difficult or expensive to score. Genome-wide association studies (GWAS) of ‘hull cover’, ‘spike row number’, and ‘heading date’ demonstrate the utility of the core collection for locating genetic factors determining important phenotypes. The GWAS results were referenced to a new barley consensus map containing 5,665 SNPs. Our results demonstrate that GWAS and high-density SNP genotyping are effective tools for plant breeders interested in accessing genetic diversity in large germplasm collections.

A valuable core collection that is a subset of a whole germplasm collection should capture most of the variation present in the whole collection, while allowing for more efficient evaluation and management due to smaller size. The United States Department of Agriculture (USDA) rice (Oryza sativa L.) core subset (RCS), assembled by stratified random sampling, consists of 1790 entries from 114 countries and represents approximately 10% of the 18412 accessions in the rice whole collection (RWC). Data for this study were obtained from the USDA germplasm system at http://www.ars-grin.gov for the RWC and from an evaluation conducted in 2002 for the RCS. Comparative analysis for frequency distributions of 14 descriptors demonstrated that the RCS was highly correlated with the RWC (r = 0.94, P < 0.0001). Thus, information drawn from the RCS could be effectively used to assess the RWC with 88% certainty. Correlation coefficients between the RCS and the RWC for eight descriptors were ≥ 0.9, indicating that the RCS was highly representative of the RWC. Correlation coefficients for the other six descriptors were lower (0.65–0.88), but still significant.

Two hundred one hexaploid wheat accessions, representing 200 years of selection and breeding history, were sampled from the National Small Grains Collection in Aberdeen, ID, and evaluated for five root traits at the seedling stage. A paper roll-supported hydroponic system was used for seedling growth. Replicated roots samples were analyzed by WinRHIZO. We observed accessions with nearly no branching and accessions with up to 132 cm of branching. Total seminal root length ranged from 70 to 248 cm, a 3.5-fold difference. Next-generation sequencing was used to produce single-nucleotide polymorphism (SNP) markers and genomic libraries that were aligned to the wheat reference genome IWGSCv1 and were called single-nucleotide polymorphism (SNP) markers. After filtering and imputation, a total of 20,881 polymorphic sites were used to perform association mapping in TASSEL. Gene annotations were conducted for identified marker-trait associations (MTAs) with - logP > 3.5 (p value < 0.003). In total, we identified 63 MTAs with seven for seminal axis root length (SAR), 24 for branching (BR), four for total seminal root length (TSR), eight for root dry matter (RDM), and 20 for root diameter (RD). Putative proteins of interest that we identified include chalcone synthase, aquaporin, and chymotrypsin inhibitor for SAR, MYB transcription factor and peroxidase for BR, zinc fingers and amino acid transporters for RDM, and cinnamoyl-CoA reductase for RD. We evaluated the effects of height-reducing Rht alleles and the 1B/1R translocation event on root traits and found presence of the Rht-B1b allele decreased RDM, while presence of the Rht-D1b allele increased TSR and decreased RD.