Mots-Clés

transcriptomique, single cell, endometriose

Description

Endometriosis, a gynecologic condition affecting up to 10% of women of reproductive age, is associated with pelvic pain and infertility. It is defined by the presence of endometrial tissue (the inner part of the uterus) outside the uterine cavity. The pregnant patients have a higher risk for miscarriage. Current treatments are partially effective against the pain but incompatible with pregnancy. Amongst the pathological mechanisms, an immune dysfunction that prevents the clearance of ectopic endometrial cells is central and could explain the associated reproductive issues.

In our team, we generated severale single nucleus RNAseq datasets from a mouse model with or without endometriosis and human placentas from women affected or not by endometriosis. We now want to analyze more finely how endometriosis influence the uterine environment and maternal-fetal interface. We also have CITE-seq data on immune cells from the mouse maternal fetal interface. And we expect to have new human RNAseq datasets on specific cells important for oocyte maturation from women affected or not with endometriosis.

This project aims at analyzing more finely these datasets (bulk RNAseq, single nuclei RNAseq, CITE-seq), at comparing the data obtained in both species, to understand how EDT influence oocyte maturation and the maternal fetal interface. For this, the master student will interact with scientists with computational knowledge within the team and with other bioinformaticians within a hub at Institut Cochin.

This project will allow to better understand endometriosis physiopathology and pave the way for new treatment approach and more targeted care for women affected by this debilitating disease.

Required experience and skills: the ability to communicate with wet lab biologists and a first experience with analyzing transcriptomic data (bulk or single) are mandatory.