Mots-Clés

Transcriptomics gene networks neuroscience psychiatry

Description

Chronic pain is a major risk factor for the emergence of emotional dysfunction, in particular anxiety and depressive disorders. Understanding molecular mechanisms that contribute to this relationship is therefore a public health issue. Over the last few years, our group has developed a robust mouse model in which the induction of a sustained neuropathic pain leads to anxiodepressive-like behaviours. Building on this model, we now seek to better characterize the brain-wide molecular changes that mediate these behaviours.

To do so, we opted for a massive next-generation sequencing strategy, whereby gene expression changes that occur following the induction of chronic pain have been systematically characterized in 6 brain regions known to process nociceptive information and regulate emotions. Importantly, we characterized the kinetics of these changes by analysing 3 successive time-points (TP), defined by the presence of pain only (TP1), pain and related emotional dysfunction (TP2), or emotional dysfunction only (TP3). Data were generated using 3’ RNA-Sequencing, are immediately available, and were already pre-processed by our group (QC, alignment, counting).

The goal of the internship will to be acquire hands-on experience with bioinformatic approaches and tools necessary to integrate large gene expression datasets. This will notably include a variety of strategies to: i) conduct threshold-free Gene Ontology analyses (GSEA), ii) compare genome-wide changes in expression within (differential expression, DESeq2) or across brain regions or time-points (e.g. Rank-Rank Hypergeometric Overlay, RRHO2), as well as iii) construct gene networks and characterize their disorganization by chronic pain (MEGENA, WGCNA).

Overall, the internship is expected to provide deeper understanding of the molecular mechanisms that differentially contribute to pain and its emotional consequences.