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.

Comprehensive reverse genetic resources, which have been key to understanding gene function in diploid model organisms, are missing in many polyploid crops. Young polyploid species such as wheat, which was domesticated less than 10,000 y ago, have high levels of sequence identity among subgenomes that mask the effects of recessive alleles. Such redundancy reduces the probability of selection of favorable mutations during natural or human selection, but also allows wheat to tolerate high densities of induced mutations. Here we exploited this property to sequence and catalog more than 10 million mutations in the protein-coding regions of 2,735 mutant lines of tetraploid and hexaploid wheat. We detected, on average, 2,705 and 5,351 mutations per tetraploid and hexaploid line, respectively, which resulted in 35-40 mutations per kb in each population. With these mutation densities, we identified an average of 23-24 missense and truncation alleles per gene, with at least one truncation or deleterious missense mutation in more than 90% of the captured wheat genes per population. This public collection of mutant seed stocks and sequence data enables rapid identification of mutations in the different copies of the wheat genes, which can be combined to uncover previously hidden variation. Polyploidy is a central phenomenon in plant evolution, and many crop species have undergone recent genome duplication events. Therefore, the general strategy and methods developed herein can benefit other polyploid crops.wheat | polyploidy | mutations | reverse genetics | exome capture S ince the dawn of agriculture, wheat has been a major dietary source of calories and protein for humans. The cultivated wheat species Triticum turgidum (tetraploid, AABB genome) and Triticum aestivum (hexaploid, AABBDD genome) originated via recent polyploidization events followed by domestication.

The majority of transcriptome sequencing (RNA-seq) expression studies in plants remain underutilized and inaccessible due to the use of disparate transcriptome references and the lack of skills and resources to analyze and visualize these data. We have developed expVIP, an expression visualization and integration platform, which allows easy analysis of RNA-seq data combined with an intuitive and interactive interface. Users can analyze public and user-specified data sets with minimal bioinformatics knowledge using the expVIP virtual machine. This generates a custom Web browser to visualize, sort, and filter the RNA-seq data and provides outputs for differential gene expression analysis. We demonstrate expVIP's suitability for polyploid crops and evaluate its performance across a range of biologically relevant scenarios. To exemplify its use in crop research, we developed a flexible wheat (Triticum aestivum) expression browser (www.wheat-expression.com) that can be expanded with user-generated data in a local virtual machine environment. The open-access expVIP platform will facilitate the analysis of gene expression data from a wide variety of species by enabling the easy integration, visualization, and comparison of RNA-seq data across experiments.The global demand for staple crops is predicted to double by 2050 (FAO, 2009;Tilman et al., 2011), which will require an annual increase in yield of approximately 2.4% (Ray et al., 2013). However, currently, yields of the major crops maize (Zea mays), rice (Oryza sativa), wheat (Triticum aestivum), and soybean (Glycine max) are increasing only at 1.6%, 1%, 0.9%, and 1.3% per year, respectively (Ray et al., 2013). The advent of the genomics era represents a great opportunity to accelerate the pace of yield increase in staple crops, for example, by facilitating novel breeding strategies (Heffner et al., 2009) and providing unprecedented numbers of genetic markers (Bevan and Uauy, 2013). In particular, transcriptome sequencing (RNA-seq) is a widely adopted genomics approach in crops due to its relatively low cost (Wang et al., 2009), its suitability for nonmodel organisms (Ekblom and Galindo, 2011), and the multiple downstream applications of the data generated. These features have driven the generation of a wealth of expression data with over 9,000 RNAseq samples currently available at public repositories, such as the National Center for Biotechnology Information (NCBI)/ENA for the major agricultural crops (Table I).Although several public databases containing gene expression data for plant species exist (Lawrence et al., 2007;Ouyang et al., 2007;Dash et al., 2012), these resources do not make full use of the expression data available in SRAs, frequently relying on a subset of experiments or microarray data. Similarly, pipelines have been proposed to allow the reanalysis of expression data that provide useful functionality but limit the number of samples that can be analyzed (D'Antonio et al., 2015), have limited visualization outputs (Fonseca et al., 2014), or require t...

Advances in genome sequencing and assembly technologies are generating many high-quality genome sequences, but assemblies of large, repeat-rich polyploid genomes, such as that of bread wheat, remain fragmented and incomplete. We have generated a new wheat whole-genome shotgun sequence assembly using a combination of optimized data types and an assembly algorithm designed to deal with large and complex genomes. The new assembly represents >78% of the genome with a scaffold N50 of 88.8 kb that has a high fidelity to the input data. Our new annotation combines strand-specific Illumina RNA-seq and Pacific Biosciences (PacBio) full-length cDNAs to identify 104,091 high-confidence protein-coding genes and 10,156 noncoding RNA genes. We confirmed three known and identified one novel genome rearrangements. Our approach enables the rapid and scalable assembly of wheat genomes, the identification of structural variants, and the definition of complete gene models, all powerful resources for trait analysis and breeding of this key global crop.

Photosynthetic starch reserves that accumulate in Arabidopsis leaves during the day decrease approximately linearly with time at night to support metabolism and growth. We find that the rate of decrease is adjusted to accommodate variation in the time of onset of darkness and starch content, such that reserves last almost precisely until dawn. Generation of these dynamics therefore requires an arithmetic division computation between the starch content and expected time to dawn. We introduce two novel chemical kinetic models capable of implementing analog arithmetic division. Predictions from the models are successfully tested in plants perturbed by a night-time light period or by mutations in starch degradation pathways. Our experiments indicate which components of the starch degradation apparatus may be important for appropriate arithmetic division. Our results are potentially relevant for any biological system dependent on a food reserve for survival over a predictable time period.DOI: http://dx.doi.org/10.7554/eLife.00669.001

BackgroundTransposable elements (TEs) are major components of large plant genomes and main drivers of genome evolution. The most recent assembly of hexaploid bread wheat recovered the highly repetitive TE space in an almost complete chromosomal context and enabled a detailed view into the dynamics of TEs in the A, B, and D subgenomes.ResultsThe overall TE content is very similar between the A, B, and D subgenomes, although we find no evidence for bursts of TE amplification after the polyploidization events. Despite the near-complete turnover of TEs since the subgenome lineages diverged from a common ancestor, 76% of TE families are still present in similar proportions in each subgenome. Moreover, spacing between syntenic genes is also conserved, even though syntenic TEs have been replaced by new insertions over time, suggesting that distances between genes, but not sequences, are under evolutionary constraints. The TE composition of the immediate gene vicinity differs from the core intergenic regions. We find the same TE families to be enriched or depleted near genes in all three subgenomes. Evaluations at the subfamily level of timed long terminal repeat-retrotransposon insertions highlight the independent evolution of the diploid A, B, and D lineages before polyploidization and cases of concerted proliferation in the AB tetraploid.ConclusionsEven though the intergenic space is changed by the TE turnover, an unexpected preservation is observed between the A, B, and D subgenomes for features like TE family proportions, gene spacing, and TE enrichment near genes.Electronic supplementary materialThe online version of this article (10.1186/s13059-018-1479-0) contains supplementary material, which is available to authorized users.

Wheat, like many other staple cereals, contains low levels of the essential micronutrients iron and zinc. Up to two billion people worldwide suffer from iron and zinc deficiencies, particularly in regions with predominantly cereal-based diets. Although wheat flour is commonly fortified during processing, an attractive and more sustainable solution is biofortification, which requires developing new varieties of wheat with inherently higher iron and zinc content in their grains. Until now most studies aimed at increasing iron and zinc content in wheat grains have focused on discovering natural variation in progenitor or related species. However, recent developments in genomics and transformation have led to a step change in targeted research on wheat at a molecular level. We discuss promising approaches to improve iron and zinc content in wheat using knowledge gained in model grasses. We explore how the latest resources developed in wheat, including sequenced genomes and mutant populations, can be exploited for biofortification. We also highlight the key research and practical challenges that remain in improving iron and zinc content in wheat.