Mots-Clés
Genotype-environment interactions
transcriptomics
gene expression regulation
RNA-seq pipeline
evolution
Description
Missions
To determine how random mutations contribute to gene regulatory evolution, our team has developed two complementary tools: i) a high-throughput transcriptomic approach (microcolony RNA-seq) to quantify mRNA levels of thousand of yeast genotypes (S. cerevisiae) in different environments ; ii) a package in R (HTRfit: https://gitbio.ens-lyon.fr/LBMC/yvertlab/vortex/plasticity_mutation/HTRfit) to simulate and to analyze large RNA-seq datasets using mixed-effects models.
Your main missions will be:
1. To implement new functionalities in HTRfit to compare genotype-environment interactions for different transcripts (functionalities specific to our research project, while the current functionalities have more general applications).
2. To develop a Nextflow pipeline for analyzing microcolony RNA-seq data (demultiplexing, indexing, normalization, quality controls, read alignments and quantifications of transcript levels).
3. To analyze available data from pilot microcolony RNA-seq experiments and to contribute to the conception and analyses of complementary experiments performed by another scientist in the team.
You will have a central role in the eGRIDE research project aiming at understanding general mechanisms that drive the evolution of gene expression depending on the environment. The goal of this project is to determine how regulatory evolution depends on one hand on the effects of random mutations – “What can possibly happen?”, and on the other hand on the selection regime – “What benefits and costs of regulation?”. This knowledge will allow us to better predict regulatory evolution, which is involved in fundamental processes such as adaptation of species to their dynamically changing natural environments or evolving pathologies such as cancers.
Activities
You will :
• Develop, implement and use computer codes assembled in « pipelines » to analyze high-throughut sequencing data generated with an original approach (microcolony RNA-seq).
• Identify, conceive, and develop statistical methods adapted to our scientific questions and to the nature of our experimental data.
• Ensure the portability, traceability and durability of the computer codes concerned.
• Participate to the design of experiments by providing advices on the structure of data produced.
• Diffuse and promote the results and tools developed via online documentations, scientific publications or oral presentations.
Skills
• Computer programing and biostatistical knowledge (R, bash, python).
• Strong understanding of NGS approaches, in particular RNA-seq.
• Basic knowledge in genomics, evolutionary biology, genetics and regulation of gene expression.
• Previous experience in NGS data analysis highly regarded.
• Proficiency working with Unix/Linux environments.
• Proficiency using tools for version tracking and collaborative development of computer code (Git).
• Knowledge of tools for code portability highly regarded (Docker containers, Singularity or other).
• Ability to implement Nextflow pipelines highly regarded.
• Ability to work and interact with experimental biologists, biocomputational scientists and biostatisticians.
• Excellet team-working ability to carry-out collectively an ambitious research project.
• Proficiency with scientific English (writing, reading and speaking).
Context
You will work under the scientific supervision of Fabien Duveau (researcher) in the team « Genetic complexity of living system » (http://www.ens-lyon.fr/LBMC/gisv/index.php/fr/) in the Laboratory of Biology and Modeling of the Cell (UMR5239) at ENS Lyon. The team is currently composed of two researchers, two engineers, one PhD student and one Licence intern. This job offer is funded by the ERC project eGRIDE starting in September 2024. You will therefore join a growing team at the beginning of an ambitious research project.
The LBMC is a cutting-edge research institute dedicated to the study of fundamental mechanisms of living cells. We combine experimental approaches in molecular cell biology and genetics with mathematical modeling and computational biology to understand complex processes regulating cellular functions. Located on the Monod campus of ENS Lyon, the LBMC is composed of 115 scientists distributed among 17 research teams. You will benefit from the highly interdisciplinary environment of our team and laboratory. More specifically, you will interact with the LBMC biocomputational hub led by permanent scientists who offer training, resources (sharing of code and pipelines) and advices for statistical analyses of sequencing data.
Additional information
Little extras :
• An interdisciplinary work environment in contact with diverse research staff.
• Professional support including access to various training.
• Partial telework possible.
• Access to a company restaurant with healthy lunch at an attractive price.
• Partial reimbursement of transportation costs (75%) or sustainable mobility package up to 300€/year (for cyclists)
• A site easily accessible with public transport (Métro + Tram T1 + T4 + bus) and bicycles
• 44 days paid vacation / RTT per year