My research is focused on understanding the regulation of the expression of polygenic traits at the molecular level, and their evolution. I recently received a Marie Skłodowska Curie Individual Fellowship to study polygenic adaptation targeting gene expression regulation using eQTL Networks.
PhD in Population Genomics and Epigenomics, 2015
Institut Pasteur / Université Pierre et Marie Curie
Master in Biosciences, 2011
École normale supérieure de Lyon
Licence in Fundamental biology, 2009
École normale supérieure de Lyon
Genome-wide association studies (GWASes) have identified many noncoding germline single-nucleotide polymorphisms (SNPs) that are associated with an increased risk of developing cancer. However, how these SNPs affect cancer risk is still largely unknown.
Characterizing the collective regulatory impact of genetic variants on complex phenotypes is a major challenge in developing a genotype to phenotype map. Using expression quantitative trait locus (eQTL) analyses, we constructed bipartite networks in which edges represent significant associations between genetic variants and gene expression levels and found that the network structure informs regulatory function. We show, in 13 tissues, that these eQTL networks are organized into dense, highly modular communities grouping genes often involved in coherent biological processes. We find communities representing shared processes across tissues, as well as communities associated with tissue-specific processes that coalesce around variants in tissue-specific active chromatin regions. Node centrality is also highly informative, with the global and community hubs differing in regulatory potential and likelihood of being disease associated.
The genetic history of African populations is increasingly well documented, yet their patterns of epigenomic variation remain uncharacterized. Moreover, the relative impacts of DNA sequence variation and temporal changes in lifestyle and habitat on the human epigenome remain unknown. Here we generate genome-wide genotype and DNA methylation profiles for 362 rainforest hunter-gatherers and sedentary farmers. We find that the current habitat and historical lifestyle of a population have similarly critical impacts on the methylome, but the biological functions affected strongly differ. Specifically, methylation variation associated with recent changes in habitat mostly concerns immune and cellular functions, whereas that associated with historical lifestyle affects developmental processes. Furthermore, methylation variation[mdash]particularly that correlated with historical lifestyle[mdash]shows strong associations with nearby genetic variants that, moreover, are enriched in signals of natural selection. Our work provides new insight into the genetic and environmental factors affecting the epigenomic landscape of human populations over time.
Genome-wide scans for selection have identified multiple regions of the human genome as being targeted by positive selection. However, only a small proportion has been replicated across studies, and the prevalence of positive selection as a mechanism of adaptive change in humans remains controversial. Here we explore the power of two haplotype-based statistics–the integrated haplotype score (iHS) and the Derived Intraallelic Nucleotide Diversity (DIND) test–in the context of next-generation sequencing data, and evaluate their robustness to demography and other selection modes. We show that these statistics are both powerful for the detection of recent positive selection, regardless of population history, and robust to variation in coverage, with DIND being insensitive to very low coverage. We apply these statistics to whole-genome sequence data sets from the 1000 Genomes Project and Complete Genomics. We found that putative targets of selection were highly significantly enriched in genic and nonsynonymous single nucleotide polymorphisms, and that DIND was more powerful than iHS in the context of small sample sizes, low-quality genotype calling, or poor coverage. As we excluded genomic confounders and alternative selection models, such as background selection, the observed enrichment attests to the action of recent, strong positive selection. Further support to the adaptive significance of these genomic regions came from their enrichment in functional variants detected by genome-wide association studies, informing the relationship between past selection and current benign and disease-related phenotypic variation. Our results indicate that hard sweeps targeting low-frequency standing variation have played a moderate, albeit significant, role in recent human evolution.