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.

Association mapping is usually performed by testing the correlation between a single marker and phenotypes. However, because patterns of variation within genomes are inherited as blocks, clustering markers into haplotypes for genome-wide scans could be a worthwhile approach to improve statistical power to detect associations. The availability of high-density molecular data allows the possibility to assess the potential of both approaches to identify marker-trait associations in durum wheat. In the present study, we used single marker- and haplotype-based approaches to identify loci associated with semolina and pasta colour in durum wheat, the main objective being to evaluate the potential benefits of haplotype-based analysis for identifying quantitative trait loci. One hundred sixty-nine durum lines were genotyped using the Illumina 90K Infinium iSelect assay, and 12,234 polymorphic single nucleotide polymorphism (SNP) markers were generated and used to assess the population structure and the linkage disequilibrium (LD) patterns. A total of 8,581 SNPs previously localized to a high-density consensus map were clustered into 406 haplotype blocks based on the average LD distance of 5.3 cM. Combining multiple SNPs into haplotype blocks increased the average polymorphism information content (PIC) from 0.27 per SNP to 0.50 per haplotype. The haplotype-based analysis identified 12 loci associated with grain pigment colour traits, including the five loci identified by the single marker-based analysis. Furthermore, the haplotype-based analysis resulted in an increase of the phenotypic variance explained (50.4% on average) and the allelic effect (33.7% on average) when compared to single marker analysis. The presence of multiple allelic combinations within each haplotype locus offers potential for screening the most favorable haplotype series and may facilitate marker-assisted selection of grain pigment colour in durum wheat. These results suggest a benefit of haplotype-based analysis over single marker analysis to detect loci associated with colour traits in durum wheat.

Breeding for solid-stemmed durum (Triticum turgidum L. var durum) and common wheat (Triticum aestivum L.) cultivars is one strategy to minimize yield losses caused by the wheat stem sawfly (Cephus cinctus Norton). Major stem-solidness QTL have been localized to the long arm of chromosome 3B in both wheat species, but it is unclear if these QTL span a common genetic interval. In this study, we have improved the resolution of the QTL on chromosome 3B in a durum (Kofa/W9262-260D3) and common wheat (Lillian/Vesper) mapping population. Coincident QTL (LOD = 94–127, R2 = 78–92%) were localized near the telomere of chromosome 3BL in both mapping populations, which we designate SSt1. We further examined the SSt1 interval by using available consensus maps for durum and common wheat and compared genetic to physical intervals by anchoring markers to the current version of the wild emmer wheat (WEW) reference sequence. These results suggest that the SSt1 interval spans a physical distance of 1.6 Mb in WEW (positions 833.4–835.0 Mb). In addition, minor QTL were identified on chromosomes 2A, 2D, 4A, and 5A that were found to synergistically enhance expression of SSt1 to increase stem-solidness. These results suggest that developing new wheat cultivars with improved stem-solidness is possible by combining SSt1 with favorable alleles at minor loci within both wheat species.

In dairy cows, there is evidence that failure to respond to superovulation protocols is a heritable trait. In women, genotyping for the p.N680S single nucleotide polymorphism (SNP) in the follicle-stimulating hormone receptor (FSHR) gene may help identify poor responders before ovarian stimulation is initiated. Our objectives were to identify SNPs in the coding region of the bovine FSHR gene and to investigate the effect of FSHR genotypes on superovulatory response in Holstein cattle. Sequencing of FSHR exons 1-10 revealed seven SNPs. Three were non-synonymous mutations (c.337C>G, c.871A>G and c.1973C>G). SNP c.337C>G encodes for a proline-to-alanine (p.Pro113Ala) amino acid replacement in the extracellular ligand-binding domain of the receptor. PCR-RFLP analyses showed that homozygous GG Holstein cows present a higher percentage of viable embryos, whereas GG and CG animals have less unfertilised oocytes. SNP c.871A>G results in an isoleucine-to-valine (p.Ile291Val) modification, and homozygous AA animals present lower embryo yield after superovulatory treatments. SNP c.1973C>G corresponds to a threonine-to-serine (p.The658Ser) modification in the intracellular carboxyl-terminal domain of the FSHR protein, and homozygous GG Holstein cows were associated with a lower embryo yield and a higher percentage of unfertilised oocytes. Our results suggest that specific alleles of the bovine FSHR gene are associated with variations in embryo yield and in the number of unfertilised oocytes.