High-density single nucleotide polymorphism (SNP) genotyping arrays are a powerful tool for studying genomic patterns of diversity, inferring ancestral relationships between individuals in populations and studying marker–trait associations in mapping experiments. We developed a genotyping array including about 90 000 gene-associated SNPs and used it to characterize genetic variation in allohexaploid and allotetraploid wheat populations. The array includes a significant fraction of common genome-wide distributed SNPs that are represented in populations of diverse geographical origin. We used density-based spatial clustering algorithms to enable high-throughput genotype calling in complex data sets obtained for polyploid wheat. We show that these model-free clustering algorithms provide accurate genotype calling in the presence of multiple clusters including clusters with low signal intensity resulting from significant sequence divergence at the target SNP site or gene deletions. Assays that detect low-intensity clusters can provide insight into the distribution of presence–absence variation (PAV) in wheat populations. A total of 46 977 SNPs from the wheat 90K array were genetically mapped using a combination of eight mapping populations. The developed array and cluster identification algorithms provide an opportunity to infer detailed haplotype structure in polyploid wheat and will serve as an invaluable resource for diversity studies and investigating the genetic basis of trait variation in wheat.

An annotated reference sequence representing the hexaploid bread wheat genome in 21 pseudomolecules has been analyzed to identify the distribution and genomic context of coding and noncoding elements across the A, B, and D subgenomes. With an estimated coverage of 94% of the genome and containing 107,891 high-confidence gene models, this assembly enabled the discovery of tissue- and developmental stage–related coexpression networks by providing a transcriptome atlas representing major stages of wheat development. Dynamics of complex gene families involved in environmental adaptation and end-use quality were revealed at subgenome resolution and contextualized to known agronomic single-gene or quantitative trait loci. This community resource establishes the foundation for accelerating wheat research and application through improved understanding of wheat biology and genomics-assisted breeding.

The coordinated expression of highly related homoeologous genes in polyploid species underlies the phenotypes of many of the world's major crops. Here we combine extensive gene expression datasets to produce a comprehensive, genome-wide analysis of homoeolog expression patterns in hexaploid bread wheat. Bias in homoeolog expression varies between tissues, with ~30% of wheat homoeologs showing nonbalanced expression. We found expression asymmetries along wheat chromosomes, with homoeologs showing the largest inter-tissue, inter-cultivar, and coding sequence variation, most often located in high-recombination distal ends of chromosomes. These transcriptionally dynamic genes potentially represent the first steps toward neo- or subfunctionalization of wheat homoeologs. Coexpression networks reveal extensive coordination of homoeologs throughout development and, alongside a detailed expression atlas, provide a framework to target candidate genes underpinning agronomic traits in wheat.

Wheat (Triticum spp.) is one of the founder crops that likely drove the Neolithic transition to sedentary agrarian societies in the Fertile Crescent more than 10,000 years ago. Identifying genetic modifications underlying wheat’s domestication requires knowledge about the genome of its allo-tetraploid progenitor, wild emmer (T. turgidum ssp. dicoccoides). We report a 10.1-gigabase assembly of the 14 chromosomes of wild tetraploid wheat, as well as analyses of gene content, genome architecture, and genetic diversity. With this fully assembled polyploid wheat genome, we identified the causal mutations in Brittle Rachis 1 (TtBtr1) genes controlling shattering, a key domestication trait. A study of genomic diversity among wild and domesticated accessions revealed genomic regions bearing the signature of selection under domestication. This reference assembly will serve as a resource for accelerating the genome-assisted improvement of modern wheat varieties.

Advances in genomics have expedited the improvement of several agriculturally important crops but similar efforts in wheat (Triticum spp.) have been more challenging. This is largely owing to the size and complexity of the wheat genome1, and the lack of genome-assembly data for multiple wheat lines2,3. Here we generated ten chromosome pseudomolecule and five scaffold assemblies of hexaploid wheat to explore the genomic diversity among wheat lines from global breeding programs. Comparative analysis revealed extensive structural rearrangements, introgressions from wild relatives and differences in gene content resulting from complex breeding histories aimed at improving adaptation to diverse environments, grain yield and quality, and resistance to stresses4,5. We provide examples outlining the utility of these genomes, including a detailed multi-genome-derived nucleotide-binding leucine-rich repeat protein repertoire involved in disease resistance and the characterization of Sm16, a gene associated with insect resistance. These genome assemblies will provide a basis for functional gene discovery and breeding to deliver the next generation of modern wheat cultivars.