Stage de Master 1 en transcritomique

SFBI; Illkirch-Graffenstaden; Vor Ort; EUR 6.700 - 8.900; Vollzeit

Zusammenfassung

SFBI is offering an internship focused on RNA-seq analysis of iPSC neuronal differentiation and rare diseases. The project aims to compare transcriptomic profiles across stages, genotypes, and iPSC clones to uncover maturation programs and variant impacts.

The role emphasizes reproducible bioinformatic workflows and high-dimensional data interpretation, with an English-friendly environment. The internship can start between November 2026 and February 2027, with hands-on experience in QC,

Qualifikationen

• Sound basis in bioinformatics; ability to analyze raw RNA-seq data.
• Good level of English is required.
• Experience with transcriptomic data analysis is a plus.

Aufgaben

• Perform complete RNA-seq analyses from raw data and compare transcriptomic profiles across differentiation stages and genetic backgrounds.
• Include quality control, statistical analysis, and visualization of results.
• Conduct differential expression analyses and functional enrichment to interpret high-dimensional data.

Kenntnisse

Bioinformatics

RNA-seq analysis

English (good level)

Ausbildung

Biology-related Bachelor's or Master’s

Tools

R

Python

Git

Bioconductor

Jobbeschreibung

RNAseq iPSC neuronal differentiation rare diseases neurodevelopment neurodegeneration

Description

Human induced pluripotent stem cells (iPSCs) provide a powerful model to study human neuronal development and disease mechanisms. The differentiation of iPSCs into medium spiny neurons (MSNs), the principal neuronal population affected in several neurodegenerative disorders, offers an opportunity to investigate molecular alterations resulting from disease-causing genetic variants. However, the capacity to reproducibly generate MSNs from iPSCs in high quantity remains a limiting factor.
A newly established protocol for the differentiation of human iPSCs towards MSNs overcomes this limitation and provides a valuable experimental model to characterize the molecular changes occurring during neuronal differentiation. In this project, transcriptomic data generated at several stages of the differentiation process will be analyzed to define the transcriptional programs associated with neuronal maturation and to investigate the potential impact of a rare variant in the retinoic acid receptor beta (RARb), associated with MCOPS12 (microphthalmia syndromic 12) a rare disease with sever neurological symptoms.
The main objective of the internship will be to perform complete RNAseq analyses starting from raw bioinformatic sequencing data and compare transcriptomic profiles across differentiation stages, genetic backgrounds and independent iPSC clones.
The analyses will include three main variables: (1) Genotype: patient cells carrying rare variant of RARb to be compared with control cells, in order to identify transcriptomic alterations potentially associated with the disease-causing variant; (2) Differentiation stage: samples collected at different developmental stages, including undifferentiated iPSCs, neural stem cells (NSCs), and several time points following induction of neuronal differentiation will be compared to identify transcriptional changes associated with progression towards the MSN phenotype; (3) Cellular clone: comparison of independent iPSC clones to evaluate biological variability and distinguish clone-specific effects from reproducible effects associated with the genetic variant or differentiation process.
Temporal changes in gene expression will be investigated to characterize transcriptional trajectories during differentiation and identify genes whose expression is altered specifically at particular developmental stages. Functional enrichment analyses will be used to identify biological processes, molecular pathways and neuronal programs associated with the observed changes.

Skills expected

The candidate should have sound basis in bioinformatics and optimally be able to perform analyses of raw RNAseq data. Good level of English is required.

Skills Developed

The student will gain practical experience in transcriptomic data analysis, quality control, statistical analysis, visualization, differential expression, pathway enrichment and interpretation of high-dimensional biological data, as well as reproducible bioinformatic workflows using appropriate computational tools.

The beginnig of the internship is possible between November 2026 and Fenruary 2027.