Description du projet
La nouvelle génération de méthodes de séquençage de «nouvelle génération» se profile à l’horizon
La séquence de nucléotides dans l’ADN révèle des informations sur les gènes, les chromosomes et même un génome entier. Les méthodes de séquençage à haut débit de «nouvelle génération» permettent désormais de séquencer le génome humain en une seule journée. Contribuant au renforcement fulgurant de notre compréhension de la génétique et des mutations dans la santé et la maladie, les techniques sont pourtant fortement entravées. Des scientifiques financés par l’UE les libèrent en améliorant de manière significative la résolution de la localisation spatiale et l’organisation des séquences au sein des cellules uniques dans des tissus intacts. Associée à des analyses plus rapides et plus détaillées et à une réduction des coûts, cette technologie pourrait inaugurer une nouvelle ère de découverte.
Objectif
Next generation sequencing has led to revolutionary discoveries in the fields of genetics, genomics, epigenetics and transcriptional regulation. The main limitation of this technology relies on the loss of spatial information: NGS is unable to retrieve the organization of nucleic acids (DNA/RNA) in the cell or within the more complex structure of the tissue. We have recently developed a novel imaging-based technology, Hi-M, that enables the simultaneous detection of tens of DNA and RNA species in single cells within the context of intact tissues. In NGI, we propose to make major improvements to drastically reduce data acquisition and analysis time, considerably increase throughput and number of independent nucleic-acid species detected, and improve the robustness of acquisition and the user-friendliness of analysis. These objectives will be achieved by implementing, testing and validating a novel combinatorial labeling scheme, parallelized acquisition, improvement of the liquid-handling robot to handle hundreds of independent species, and on-the-fly analysis using deep learning technologies to provide more robust data analysis pipelines and adapt acquisition parameters in real time. These improvements will enable simultaneous detection of thousands of species (DNA, RNA or protein) in single-cells with spatial resolution within the context of complex organisms and tissues. Because of these important advantages over existing technologies, NGI will be key to future discoveries in the fields of genetics, genomics and transcription. Critically, NGI will also have a large impact in other fundamental and applied fields where knowledge of spatial organization of transcription and 3D chromosome organization at the single-cell level are relevant: neuroscience and neurological diseases, diabetes, cancer, etc. Thus, NGI has the potential to become an ubiquitous tool not only in academic science but also at the clinic.
Champ scientifique
- natural sciencescomputer and information sciencesdata science
- natural sciencesbiological sciencesbiochemistrybiomoleculesnucleic acids
- natural sciencesbiological sciencesgeneticsDNA
- natural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learning
- natural sciencesbiological sciencesgeneticsRNA
Programme(s)
Régime de financement
ERC-POC-LS - ERC Proof of Concept Lump Sum PilotInstitution d’accueil
75794 Paris
France