PATTERNS (2020 - 2021)

This picture represent an eQTL network linking regulatory mutations to gene expression level.  A complete regulatory network is represented corresponding to the skin tissue in the Genome Tissue Expression project An eQTL network corresponding to the skin tissue

Polygenic adaptation, in which small changes in allele frequencies co-occur at multiple variants, has been proposed to be a major adaptive mechanism for complex phenotypes. Most approaches to detect polygenic adaptation consist in combining signatures of positive selection across functionally homogenous sets of genes or variants. However, few studies have looked at regulatory variants and none has accounted for the tissue specificity of gene expression. Here, we propose to combine network biology and population genetics methods in order to detect polygenic adaptation acting on complex phenotypes through gene expression regulation. First, we will identify communities of regulatory variants that coregulate various groups of genes, by representing both cis- and trans-expression quantitative trait loci (eQTLs) as bipartite graphs. We will then search for communities enriched for signatures of weak positive selection to identify regulatory variants under polygenic adaptation. After evaluating the power of our approach by means of simulations, we will apply it to data from several tissues of the Genotype-Tissue Expression (GTEx) project. This will allow us to identify and characterize biological functions that evolve under polygenic adaptation, taking into account the tissue-specificity of their expression. We thus hope to better understand the extent to which polygenic adaptation has been shaping the human genetic diversity and susceptibility to complex diseases.


This project is funded by a Marie Skłodowska-Curie Individual Fellowship Marie Skłodowska-Curie Individual Fellowship.

Maud Fagny
Maud Fagny

I aim at understanding plants response to environment at the molecular level.