Bioinformatics dissection of aberrant developmental progression during tumorigenesis using a single-cell multi-omics approach
We are proposing a PhD position to investigate, at the single cell level, the gene regulatory regions controlling brain development and tumorigenesis in Drosophila. For this purpose, we will use a single-cell multi-omics approach (RNA-seq and ATAC-seq).
Details of the project can be found http://www.adum.fr/as/ed/voirproposition.pl?matricule_prop=40900&langue=en
This PhD project is part of the PhD Programme of the Doctoral School ED62. The deadline of application is: May 15, 2022 and the application procedure is explained here: http://ecole-doctorale-62.univ-amu.fr/fr/financements-concours-ed/concours-lecole-doctorale
Recent single-cell transcriptomics data have shown that brain cancers in children are driven by aberrantly redeployed developmental programs. However, it is still unclear how these developmental programs are coopted and regulated in the tumorigenic context. Brain development is understood in unmatched details in Drosophila where we have recently generated a model of brain tumors that recapitulates childhood tumors. New technologies now allow the simultaneous analysis of the transcriptome and regulome (regulatory regions) in single-cells. This project aims to generate and analyze single-cell data from neural progenitors isolated from the developing brain and tumors in Drosophila. The student will prepare tissues for high-throughput sequencing (HTS). He will then carry out a bioinformatics analysis to identify gene regulatory regions and infer gene regulatory networks involved during normal brain development and brain tumorigenesis. This project will shed light on how developmental programs can be coopted to promote tumorigenesis in children.
The PhD candidate should have a Master's degree in an area related to Bioinformatics, Biophysics, or Computer Science with a strong interest in data analysis. Previous experimental experience is not required but the student should be motivated to embark on a substantial amount of experimental work in order to generate the single-cell data to be analyzed.
Thank you for sharing this offer with motivated candidates.
Cédric Maurange, Aitor González
