Mots-Clés
Data analysis from Epigenomics and Transcriptomics
data analysis (Long reads and WGBS)
integrative statistical analysis and modelling
Description
The P2E laboratory (Physiology of Trees and Forest Ecosystems, INRAE–Université d’Orléans) investigates ecological and evolutionary mechanisms involved in insect biological invasions and tree–insect interactions in the context of global change. In parallel, we are developing epigenetic approaches to study plant and insect responses to climate stress, integrating ecophysiology, biochemistry, genetics, and genomics. The lab collaborates closely with the EPGV sequencing platform (Evry) to implement long-read sequencing technologies for epigenomic analyses.
We offer a Master 2 internship focusing on integrative bioinformatics and statistical modelling of multi-omics data generated in the HOLOSTRESS collaborative project with the IRBI (CNRS, Tours). Holostress investigates how insect holobionts (hosts and their
microbial symbionts) respond to combined environmental stresses such as heatwaves and pesticide exposure. Using the pea aphid Acyrthosiphon pisum as a model, it explores how symbionts influence host thermoregulation, pesticide sensitivity, and thermal tolerance. A central aspect of Task 3 is the analysis of thermal acclimation and the role of facultative endosymbionts across life stages and generations, with a pioneering focus on DNA methylation (methylome profiling) as a potential epigenetic mechanism of thermal plasticity.
The intern will:
•Develop and optimize a bioinformatics pipeline for long-read methylome data (Oxford Nanopore Technology, ONT), using ONT recommendations and state-of-the-art tools for differential methylation analysis.
•Perform multi-omics integration (methylome, RNA-seq from IRBI, and phenotypic data) using the R package mixOmics.
•Compare newly identified candidate genes with those from an existing methylome pipeline developed at P2E, and carry out additional analyses such as GO enrichment and gene network inference to provide biological insights in relation to phenotyping data.
•Build reproducible pipelines in Snakemake/Nextflow, Python, Perl, etc., for implementation on HPC platforms, and produce publication-ready statistical analyses and visualizations in R.
The internship will be based at EPGV (Evry) or shared between EPGV and P2E (Orléans), depending on candidate preference.
Profile sought: Master 2 student with interests in genomics, bioinformatics, and multi-omics analyses, motivated by pipeline development, programming (Snakemake/Nextflow, Python, or Perl), and exploratory data analysis. Strong interest in host-microbiome interactions and evolutionary ecology under environmental and climate stress, with the aim of integrating genomic and ecological data to better understand insect-microbiota dynamics.