Title of the PhD thesis:
Improved knowledge and pan-genomic prediction of complex phenotypes using a multi-omic integrative approach in black poplar
Plants are fixed organisms, with continuous development, no pre-established germline, and highly varied life cycles ranging up to hundreds of years in trees. Thus, they are relevant biological models for studying the relationship between development and adaptation to the environment (Mladenov et al., 2021). The woody species Populus nigra, the black poplar, constitutes a reference model where so-called “omics” resources such as phenomics, transcriptomics, genomics and epigenomics have been accumulated for more than 20 years in collaboration between BioForA and the LBLGC.
Genome-wide evaluation is an innovation in the way genetic progress is managed and generated in breeding programs. However, like traditional genetic evaluation, it relies on very little consideration of the underlying genetic architecture of traits of interest. However, new resources from omics approaches are bridging the gap between the phenotypes studied and the DNA sequence, paving the way for systems approaches to integrative biology. Recently, systems biology approaches allow, through the integration of different types of data (genomic, transcriptomic), to better understand the interaction of functional factors that condition the expression of phenotypes (Chateigner et al 2020).
Epigenetics is involved in phenotypic plasticity (Maury et al., 2019), stress memory, and even transgenerational transmission and is of interest in plant breeding (Kakoulidou et al., 2021). Epigenomic data thus offer a new and innovative perspective for improving phenotypic predictions through the integration of information from heterogeneous omics data. The challenge will therefore be to decipher the complexity of quantitative traits of interest using explicit predictive models, while maintaining the predictive qualities necessary for operational selection.
This thesis project is thus placed at the interface between 2 teams (LBLGC and BioForA) for which it reinforces the synergies by developing an integrative and ambitious subject.