Genomic selection - the prediction of breeding values using DNA polymorphisms - is a disruptive method that has widely been adopted by animal and plant breeders to increase productivity. It was recently shown that other sources of molecular variations such as those resulting from transcripts or metabolites could be used to accurately predict complex traits. These endophenotypes have the advantage of capturing the expressed genotypes and consequently the complex regulatory networks that occur in the different layers between the genome and the phenotype. However, obtaining such omics data at very large scales, such as those typically experienced in breeding, remains challenging. As an alternative, we proposed using near-infrared spectroscopy (NIRS) as a high-throughput, low cost and non-destructive tool to indirectly capture endophenotypic variants and compute relationship matrices for predicting complex traits, and coined this new approach "phenomic selection" (PS). We tested PS on two species of economic interest (Triticum aestivum L. and Populus nigra L.) using NIRS on various tissues (grains, leaves, wood). We showed that one could reach predictions as accurate as with molecular markers, for developmental, tolerance and productivity traits, even in environments radically different from the one in which NIRS were collected. Our work constitutes a proof of concept and provides new perspectives for the breeding community, as PS is theoretically applicable to any organism at low cost and does not require any molecular information.

Because of their abundance and their amenability to high-throughput genotyping techniques, Single Nucleotide Polymorphisms (SNPs) are powerful tools for efficient genetics and genomics studies, including characterization of genetic resources, genome-wide association studies and genomic selection. In wheat, most of the previous SNP discovery initiatives targeted the coding fraction, leaving almost 98% of the wheat genome largely unexploited. Here we report on the use of whole-genome resequencing data from eight wheat lines to mine for SNPs in the genic, the repetitive and non-repetitive intergenic fractions of the wheat genome. Eventually, we identified 3.3 million SNPs, 49% being located on the B-genome, 41% on the A-genome and 10% on the D-genome. We also describe the development of the TaBW280K high-throughput genotyping array containing 280,226 SNPs. Performance of this chip was examined by genotyping a set of 96 wheat accessions representing the worldwide diversity. Sixty-nine percent of the SNPs can be efficiently scored, half of them showing a diploid-like clustering. The TaBW280K was proven to be a very efficient tool for diversity analyses, as well as for breeding as it can discriminate between closely related elite varieties. Finally, the TaBW280K array was used to genotype a population derived from a cross between Chinese Spring and Renan, leading to the construction a dense genetic map comprising 83,721 markers. The results described here will provide the wheat community with powerful tools for both basic and applied research.

A phylogeographical study reveals the reshuffling of wheat genetic diversity through time, in relation to human history.

The sequencing of the wheat (Triticum aestivum) genome has been a methodological challenge for many years owing to its large size (15.5 Gb), repeat content, and hexaploidy. Many initiatives aiming at obtaining a reference genome of cultivar Chinese Spring have been launched in the past years and it was achieved in 2018 as the result of a huge effort to combine short-read sequencing with many other resources. Reference-quality genome assemblies were then produced for other accessions, but the rapid evolution of sequencing technologies offers opportunities to reach high-quality standards at lower cost. Here, we report on an optimized procedure based on long reads produced on the Oxford Nanopore Technology PromethION device to assemble the genome of the French bread wheat cultivar Renan. We provide the most contiguous chromosome-scale assembly of a bread wheat genome to date. Coupled with an annotation based on RNA-sequencing data, this resource will be valuable for the crop community and will facilitate the rapid selection of agronomically important traits. We also provide a framework to generate high-quality assemblies of complex genomes using ONT.

Bread wheat is an allohexaploid species originating from two successive and recent rounds of hybridization between three diploid species that were very similar in terms of chromosome number, genome size, TE content, gene content and synteny. As a result, it has long been considered that most of the genes were in three pairs of homoeologous copies. However, these so‐called triads represent only one half of wheat genes, while the remaining half belong to homoeologous groups with various number of copies across subgenomes. In this study, we examined and compared the distribution, conservation, function, expression and epigenetic profiles of triads with homoeologous groups having undergone a deletion (dyads) or a duplication (tetrads) in one subgenome. We show that dyads and tetrads are mostly located in distal regions and have lower expression level and breadth than triads. Moreover, they are enriched in functions related to adaptation and more associated with the repressive H3K27me3 modification. Altogether, these results suggest that triads mainly correspond to housekeeping genes and are part of the core genome, while dyads and tetrads belong to the Triticeae dispensable genome. In addition, by comparing the different categories of dyads and tetrads, we hypothesize that, unlike most of the allopolyploid species, subgenome dominance and biased fractionation are absent in hexaploid wheat. Differences observed between the three subgenomes are more likely related to two successive and ongoing waves of post‐polyploid diploidization, that had impacted A and B more significantly than D, as a result of the evolutionary history of hexaploid wheat.

There is currently a strong societal demand for sustainability, quality, and safety in bread wheat production. To address these challenges, new and innovative knowledge, resources, tools, and methods to facilitate breeding are needed. This starts with the development of high throughput genomic tools including single nucleotide polymorphism (SNP) arrays, high density molecular marker maps, and full genome sequences. Such powerful tools are essential to perform genome-wide association studies (GWAS), to implement genomic and phenomic selection, and to characterize the worldwide diversity. This is also useful to breeders to broaden the genetic basis of elite varieties through the introduction of novel sources of genetic diversity. Improvement in varieties particularly relies on the detection of genomic regions involved in agronomical traits including tolerance to biotic (diseases and pests) and abiotic (drought, nutrient deficiency, high temperature) stresses. When enough resolution is achieved, this can result in the identification of candidate genes that could further be characterized to identify relevant alleles. Breeding must also now be approached through in silico modeling to simulate plant development, investigate genotype × environment interactions, and introduce marker–trait linkage information in the models to better implement genomic selection. Breeders must be aware of new developments and the information must be made available to the world wheat community to develop new high-yielding varieties that can meet the challenge of higher wheat production in a sustainable and fluctuating agricultural context. In this review, we compiled all knowledge and tools produced during the BREEDWHEAT project to show how they may contribute to face this challenge in the coming years.