Méta-programme INRAE DIGIT-BIO Peersim

Coordinators G. Rigaill et E. Delannoy

For the study of multi-stresses in plants, the consensus is that the effect of combined stresses is different from the sum of the effects of single stresses. It seems therefore difficult to predict the effect of the combined stresses knowing only the effect of each single stress. This conclusion was obtained from studies comparing lists of differential genes/metabolites in the response to individual stresses with the same lists in the response to combined stresses. These analyzes are based on a few biological replicates (typically 3 for RNA-Seq). However, even in yeast, 3 RNA-Seq replicates allow the identification of only 20% of the differentially expressed genes. Assuming that these analyzes are independent and have a power of 20%, only 4% (20% x 20%) of the differentially expressed genes can then be detected under two stress conditions.  It may well explain in part the differences between single and multiple stress conditions. We propose to efficiently re-evaluate the prediction of combined stresses responses from single stress responses thanks to an experiment focused on two stresses, CO2 and heat, performed with many replicates (~ 20). Beyond the biological relevance of this dataset in the context of climate change, it will allow us to make progress on 3 points:  (Q1) Quantify the extent to which the effect of combined stresses is different from the sum of the effects of single stresses, and assess whether it is possible to predict the actors of the combined stress response and their interactions. (Q2) Develop and propose powerful experimental designs for studying the response of plants to combined stresses. (Q3) Develop and evaluate recent analyses and integration methodologies for studying the response of plants to combined stresses.

The project is coordinated by Guillem Rigaill (Gnet) and Etienne Delannoy (OGE), and is in collaboration with Axel de Zélicourt and Michael Hodges of MetaboActions, Julien Chiquet (MIA Paris Saclay), Nathalie Vialaneix (MIA-T) and  Pierre Neuvial (Institut Mathématique de Toulouse)

Conditions, replicates and percentage of differential genes
A. Experimental Design : conditions vs replicates. B. Percentage of non-differential genes as a function of the number of replicates (from 2 to 10)

20/01/2022