NETWITS

Climate change is already responsible for massive loss of crop yield worldwide. Adapting varieties to future climatic conditions is thus a timely challenge. However, models used in genomic selection are not yet accurate enough to identify the most adapted genotypes to specific environment, because they lack prior biological knowledge on the molecular bases of crops response to environment. At the molecular level, crops’ tolerance to an environmental constraint is highly polygenic, and is determined by complex gene regulatory networks regulating the expression of several biological processes. It is thus likely that tolerance to a constraint can be reached by leveraging distinct networks depending on the genotype. Distal cis-regulatory elements (dCREs) are likely to play a key role in articulating these networks. But the diversity of dCRE-articulated gene regulatory networks underlying tolerance to a constraint, and its impact on the selection process, remains an open question. Using maize response to water deficit as a model, I will aim to (i) assess the diversity of gene regulatory network wiring underlying maize WD-tolerance; (ii) determine how network topology and its variations may constrain or facilitate selection; and (iii) integrate these novel information into a predictive model of maize response to WD. In NETWITS, I will uncover biological information on regulatory networks underlying WD tolerance in maize by integrating genomic and transcriptomic data already available in the lab using cutting-edge approaches in plant systems biology and population genetics. I will then use this biological knowledge to develop a more accurate model to predict maize phenotype in response to WD. NETWITS will bring an important breakthrough in our understanding of the role of dCRE variations and those of the gene regulatory networks they articulate in determining WD tolerance. This will be key to preserve yield while retaining some genetic diversity among cultivated crops.