Background: Single nucleotide polymorphisms (SNPs) are ideally suited for the construction of high-resolution genetic maps, studying population evolutionary history and performing genome-wide association mapping experiments. Here, we used a genome-wide set of 1536 SNPs to study linkage disequilibrium (LD) and population structure in a panel of 478 spring and winter wheat cultivars (Triticum aestivum) from 17 populations across the United States and Mexico.Results: Most of the wheat oligo pool assay (OPA) SNPs that were polymorphic within the complete set of 478 cultivars were also polymorphic in all subpopulations. Higher levels of genetic differentiation were observed among wheat lines within populations than among populations. A total of nine genetically distinct clusters were identified, suggesting that some of the pre-defined populations shared significant proportion of genetic ancestry. Estimates of population structure (F_ST) at individual loci showed a high level of heterogeneity across the genome. In addition, seven genomic regions with elevated F_STwere detected between the spring and winter wheat populations. Some of these regions overlapped with previously mapped flowering time QTL. Across all populations, the highest extent of significant LD was observed in the wheat D-genome, followed by lower LD in the A- and B-genomes. The differences in the extent of LD among populations and genomes were mostly driven by differences in long-range LD ( > 10 cM).Conclusions: Genome- and population-specific patterns of genetic differentiation and LD were discovered in the populations of wheat cultivars from different geographic regions. Our study demonstrated that the estimates of population structure between spring and winter wheat lines can identify genomic regions harboring candidate genes involved in the regulation of growth habit. Variation in LD suggests that breeding and selection had a different impact on each wheat genome both within and among populations. The higher extent of LD in the wheat D-genome versus the A- and B-genomes likely reflects the episodes of recent introgression and population bottleneck accompanying the origin of hexaploid wheat. The assessment of LD and population structure in this assembled panel of diverse lines provides critical information for the development of genetic resources for genome-wide association mapping of agronomically important traits in wheat.

Existing algorithms and methods for forming diverse core subsets currently address either allele representativeness (breeder's preference) or allele richness (taxonomist's preference). The main objective of this paper is to propose a powerful yet flexible algorithm capable of selecting core subsets that have high average genetic distance between accessions, or rich genetic diversity overall, or a combination of both.

Climate change during the last 40 years has had a serious impact on agriculture and threatens global food and nutritional security. From over half a million plant species, cereals and legumes are the most important for food and nutritional security. Although systematic plant breeding has a relatively short history, conventional breeding coupled with advances in technology and crop management strategies has increased crop yields by 56 % globally between 1965-85, referred to as the Green Revolution. Nevertheless, increased demand for food, feed, fiber, and fuel necessitates the need to break existing yield barriers in many crop plants. In the first decade of the 21st century we witnessed rapid discovery, transformative technological development and declining costs of genomics technologies. In the second decade, the field turned towards making sense of the vast amount of genomic information and subsequently moved towards accurately predicting gene-to-phenotype associations and tailoring plants for climate resilience and global food security. In this review we focus on genomic resources, genome and germplasm sequencing, sequencing-based trait mapping, and genomics-assisted breeding approaches aimed at developing biotic stress resistant, abiotic stress tolerant and high nutrition varieties in six major cereals (rice, maize, wheat, barley, sorghum and pearl millet), and six major legumes (soybean, groundnut, cowpea, common bean, chickpea and pigeonpea). We further provide a perspective and way forward to use genomic breeding approaches including marker-assisted selection, marker-assisted backcrossing, haplotype based breeding and genomic prediction approaches coupled with machine learning and artificial intelligence, to speed breeding approaches. The overall goal is to accelerate genetic gains and deliver climate resilient and high nutrition crop varieties for sustainable agriculture.

Wheat is an important staple that acts as a primary source of dietary energy, protein, and essential micronutrients such as iron (Fe) and zinc (Zn) for the world’s population. Approximately two billion people suffer from micronutrient deficiency, thus breeders have crossed high Zn progenitors such as synthetic hexaploid wheat, T. dicoccum, T. spelta, and landraces to generate wheat varieties with competitive yield and enhanced grain Zn that are being adopted by farmers in South Asia. Here we report a genome-wide association study (GWAS) using the wheat Illumina iSelect 90 K Infinitum SNP array to characterize grain Zn concentrations in 330 bread wheat lines. Grain Zn phenotype of this HarvestPlus Association Mapping (HPAM) panel was evaluated across a range of environments in India and Mexico. GWAS analysis revealed 39 marker-trait associations for grain Zn. Two larger effect QTL regions were found on chromosomes 2 and 7. Candidate genes (among them zinc finger motif of transcription-factors and metal-ion binding genes) were associated with the QTL. The linked markers and associated candidate genes identified in this study are being validated in new biparental mapping populations for marker-assisted breeding.

Key message: Here, we provide an updated set of guidelines for naming genes in wheat that has been endorsed by the wheat research community. The last decade has seen a proliferation in genomic resources for wheat, including reference- and pan-genome assemblies with gene annotations, which provide new opportunities to detect, characterise, and describe genes that influence traits of interest. The expansion of genetic information has supported growth of the wheat research community and catalysed strong interest in the genes that control agronomically important traits, such as yield, pathogen resistance, grain quality, and abiotic stress tolerance. To accommodate these developments, we present an updated set of guidelines for gene nomenclature in wheat. These guidelines can be used to describe loci identified based on morphological or phenotypic features or to name genes based on sequence information, such as similarity to genes characterised in other species or the biochemical properties of the encoded protein. The updated guidelines provide a flexible system that is not overly prescriptive but provides structure and a common framework for naming genes in wheat, which may be extended to related cereal species. We propose these guidelines be used henceforth by the wheat research community to facilitate integration of data from independent studies and allow broader and more efficient use of text and data mining approaches, which will ultimately help further accelerate wheat research and breeding.