Prédiction et compréhension des interactions génotypes x environnements par des approches d’intégration multi-omique chez le maïs

Soutenance de thèse
 12/12/2024
 09:30:00
 Baber ALI, GQE-Le Moulon
 IDEEV - Salle Rosalind Franklin

Abstract: Maize hybrids are generally evaluated in multi-environmental conditions where a large proportion of the phenotypic variation is due to genotype by environment (GxE) interactions. Classical genomic prediction models act as black boxes due to their inherent constraints and fail to account for underlying biological processes that occur in response to the environmental conditions. As genes respond differently to the growth conditions, marker prioritization and multi-omics information can be useful to account for these interactions in prediction models. Therefore, by using some novel statistical approaches, we have integrated gene ontology (GO) information and multi-omics (transcriptomics and proteomics) in prediction of platform eco-physiological and field productivity traits. The results of this research indicate that both systematically integrated GO terms as well as multi-omics information can be useful for improving predictive abilities. We also proved that this information can be used to increase detection power and resolution of association studies. Conclusions of this research work open several frontiers for future research.

La soutenance se déroulera en anglais, et aura lieu en mode hybride avec une connexion zoom possible au lien suivant