Using transcriptomic signatures to diagnose rare neuromuscular diseases
ABG-129186 | Thesis topic | |
2025-03-06 | Public funding alone (i.e. government, region, European, international organization research grant) |
- Psychology, neurosciences
- Biology
- Health, human and veterinary medicine
Topic description
The NeuroSchool PhD Program of Aix-Marseille University (France) has launched its annual calls for PhD contracts for students with a master's degree in a non-French university and for international co-supervised PhDs.
This project is one of the proposed projects. Not all proposed projects will be funded, check our website for details.
State of the art: Major changes in the level of gene expression (number of mRNA molecules or transcripts produced by the gene) and in the gene splicing patterns can be observed during normal development of nerve and muscle tissues as well as during neuromuscular disease. While many studies focused on changes in the gene expression level, the modifications in splicing patterns remain poorly explored. Different neuromuscular diseases are likely to have distinct molecular changes in the nerve and muscle tissues that might alter splicing in different ways. Our hypothesis is that these splicing patterns can be used to establish transcriptomic signatures that can be then used to study the normal function of muscle and nerves as well as to identify abnormal processes during neuromuscular disease.
Methods: Muscle and nerve biopsies from patients affected with rare neuromuscular disorders will be used to perform transcriptomic analysis (total RNA sequencing). The RNAseq data for control individuals will be obtained from GTEX project. Several bioinformatic tools will then be used to identify all splice junctions present in the transcriptomic data. Different subsets of splice junctions will be tested to identify the transcriptomic signatures that could distinguish patient samples from the controls.
Objectives: The two objectives of our project are:
1. Establish novel transcriptomic signatures using RNA sequencing of nerve and muscle biopsies from patients and controls
2. Use the newly developed transcriptomic signatures to establish diagnosis in previously undiagnosed patients affected by rare neuromuscular diseases
Expected results: We expect to observe differences in transcriptomic signatures between patients and controls, thus establishing a digital biomarker for future clinical studies. We also expect to see differences between different subtypes of neuromuscular diseases, thus helping to identify the underlying molecular processes.
Feasibility: We have recently started a clinical study (ARNseq-Musc, CPP# 2024-A01079-38) that will provide transcriptomic data for patients affected with neuromuscular diseases. Our “Translational Neuromyology” team as well as the Genomic and Bioinformatics platform (GBiM) of the Marseille Medical Genetics institute have all necessary equipment and infrastructure to accomplish the proposed research project.
Starting date
Funding category
Funding further details
Presentation of host institution and host laboratory
Within Aix Marseille Université, NeuroMarseille brings together 8 research laboratories and NeuroSchool, a graduate school in neuroscience, to increase the attractiveness of the university, international collaborations, interdisciplinarity, links with the clinical and industrial worlds and the integration of students into professional life.
Launched in July 2018, NeuroSchool unifies and harmonizes the training of the third year of the Bachelor of Life Sciences (Neuroscience track), the Master's and the PhD in Neuroscience.
PhD title
Country where you obtained your PhD
Institution awarding doctoral degree
Graduate school
Candidate's profile
- Master's degree from a non-French university in neuroscience or related field
- Fluent in English
We are looking for a curious and motivated candidate with a solid fundamental background in molecular biology, neuroscience and genomics. In addition, the candidate must have experience in bioinformatics and data analysis. Previous experience in transcriptomic analysis would also be a plus.
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