Biology subjects

Paux, E.

Publications and source records attributed to Paux, E..

3 recordsLinked to original sources

bioRxiv2018

Impact of transposable elements on genome structure and evolution in bread wheat

BackgroundTransposable elements (TEs) are ubiquitous components of genomes and they are the main contributors to genome evolution. The reference sequence of the hexaploid bread wheat (Triticum aestivum L.) genome enabled for the first time a comprehensive genome-wide view of the dynamics of TEs that have massively proliferated in the A, B, and D subgenomes.\n\nResultsTEs represent 85% of the genome. We traced back TE amplification dynamics in the evolutionary history of wheat and did not find large bursts in the wake of either the tetra- or the hexaploidization. Despite the massive turnover of TEs since A, B, and D diverged, 76% of TE families are present in similar proportions in the three subgenomes. Moreover, spacing between homeologous genes was also conserved. TE content around genes is very different from the TE space comprising large intergenic regions and families that are enriched or depleted from gene promoters are the same in the three subgenomes.\n\nConclusionsThe chromosome-scale assembly of the wheat genome provided an unprecedented genome-wide view of the organization and impact of TEs in such a complex genome. Our results suggest that TEs play a role at the structural level and that the overall chromatin structure is likely under selection pressure.

genomics↗

bioRxiv2018

Linking the International Wheat Genome Sequencing Consortium bread wheat reference genome sequence to wheat genetic and phenomic data

The Wheat@URGI portal (https://wheat-urgi.versailles.inra.fr) has been developed to provide the international community of researchers and breeders with access to the bread wheat reference genome sequence produced by the International Wheat Genome Sequencing Consortium. Genome browsers, BLAST, and InterMine tools have been established for in depth exploration of the genome sequence together with additional linked datasets including physical maps, sequence variations, gene expression, and genetic and phenomic data from other international collaborative projects already stored in the GnpIS information system. The portal provides enhanced search and browser features that will facilitate the deployment of the latest genomics resources in wheat improvement.

bioinformatics↗

bioRxiv2018

Phenomic selection: a low-cost and high-throughput alternative to genomic selection

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.\n\nARTICLE SUMMARYDespite its widely adopted interest in breeding, genomic selection - the prediction of breeding values using DNA polymorphisms - remains difficult to implement for many species because of genotyping costs. As an alternative or complement depending on the context, we propose \"phenomic selection\" (PS) as the use of low-cost and high-throughput phenotypic records to reconstruct similarities between genotypes and predict their performances. As a proof of concept of PS, we made use of near infrared spectroscopy applied to different tissues in poplar and wheat to predict various key traits and showed that PS could reach predictions as accurate as with molecular markers.

genetics↗