Société Française de Bioinformatique

Mots-Clés

Bioinformatics Evolutionary genomics single-cell RNA-seq

Description

Master 2 Internship in Bioinformatics: Genome scrambling and gene expression in Oikopleura dioica
How can genomes undergo extensive rearrangements while maintaining normal gene expression?
Oikopleura dioica, a small marine organism closely related to vertebrates, provides a fascinating model to address this question. Despite having a highly compact genome (~65 Mb), different populations exhibit thousands of chromosomal rearrangements that have profoundly altered gene order, without apparent effects on morphology or development.
We are looking for a motivated Master 2 student in bioinformatics to investigate how this remarkable genome scrambling affects gene expression and to explore its evolutionary origins.

The internship will combine three complementary approaches:
- Single-cell transcriptomics: Analyse scRNA-seq data from different O. dioica populations to identify co-expressed genes and compare their expression profiles.
- Comparative genomics: Investigate whether co-expressed genes maintain their relative genomic positions or undergo extensive rearrangements between populations.
- Genome evolution: Compare newly available genomes from different appendicularian species to investigate the evolutionary history of genome scrambling.
The project will involve computational analyses using Python, gene co-expression network analysis and comparative genomics tools.

Candidate profile: We welcome applications from Master 2 students in bioinformatics, computational biology or related fields. Experience with Python and an interest in evolutionary genomics and gene regulation are particularly desirable.
Host laboratory: Ghavi-Helm team, Institute of Functional Genomics of Lyon (IGFL), ENS de Lyon, France.
Collaboration: This project will be carried out in close collaboration with Charles Plessy at the Okinawa Institute of Science and Technology (OIST), Japan.
This internship offers the opportunity to work at the interface of single-cell transcriptomics, 3D genome organisation and evolutionary genomics, using an emerging model organism and newly generated genomic datasets in an international research environment.