Cancer Regulatory Genomics
The main interest of the group is to understand principles of transcriptional regulation in development and cancer.
In particular, we are studying the contribution of the genetic and epigenetic contribution to gene regulation in order to understand how perturbations in the regulatory network impact the expression of genes in a disease context.
To achieve this, we are developing new tools and methods in order to take advantage of the massive publicly available datasets to contextualize regulatory elements in the genome.
1. Tool development for regulatory analysis
A major focus of the group is sequence analysis, in particular in regulatory regions. We are applying motif discovery or motif enrichment approaches to annotate potential regulatory region and understand the impact of mutations in non-coding region. A particular effort is made towards defining realistic control sets in order to detect enrichments of motifs in regions independently of compositional biases. We also develop background models to test evidence of positive and negative selection in mutational landscapes.
2. (Epi)genotype / phenotype relation
In order to dissociate the relative contributions to gene expression or de-regulation, we employ statistical methods to link germline or somatic mutations to gene expression in order to map potential quantitive trait loci. Similarly, we want to analyze the impact of the genetic background on the epigenomic landscape, in particular the methylome, based on whole genome bisulfite methylation data.