A system genetics approach including genomic, transcriptomic and metabolomic data to unravel the genetic control of complex quantitative traits in poplar
Résumé
The causative factors underlying complex quantitative trait variations have been debated and modeled for over a century. Today, the availability of high throughput -omic technologies enables the genome wide profiling of various sources of DNA variations, together with the screening of higher levels of biological data, such as gene expression and metabolite content, within the same individuals of large populations. The integration of multi-omic datasets allows a more comprehensive analysis of the genetic control of quantitative trait regulation through the interactions of multiple components within a system. In our project, we are using long-read sequencing, to characterize the diversity of SNPs, structural variations and DNA methylation in 750 individuals of a wild population of Populus nigra that has been collected along the main river basins of Europe. We have optimized a high molecular weight DNA extraction protocol and developed a long-read sequencing strategy fitting our large number of samples. So far we have sequenced and de novo assembled the genomes of more than 150 poplars, together with the assembly of a reference P. nigra genome that will be at the base of the variant calling, including SNP and structural variation, and methylation profiling. In this same population, we will profile individual gene expression levels and metabolite content, and provide a network representation of how each level of biological information impact tree quantitative traits. We hope to bring new insights into the biology of this long-lived model species.
Domaines
Sciences du Vivant [q-bio]| Origine | Fichiers produits par l'(les) auteur(s) |
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