Descripción del proyecto
La próxima generación de los métodos de secuenciación de «próxima generación» está en el horizonte
La secuencia de nucleótidos del ADN revela información sobre los genes, los cromosomas e incluso sobre todo el genoma. Los métodos de secuenciación de «próxima generación» y de alto rendimiento han permitido que ahora se pueda secuenciar el genoma humano en tan solo un día. Las técnicas, que contribuyen al fulgurante aumento de nuestro nivel de comprensión de la genética y las mutaciones en la salud y la enfermedad, afrontan una limitación importante. Unos científicos financiados con fondos europeos la están abordando con una mejora considerable de la resolución tanto de la localización espacial como de la organización de las secuencias dentro de células individuales de tejidos intactos. La tecnología, combinada con unos análisis más rápidos y detallados y una reducción de costes, podría impulsar una nueva era de descubrimientos.
Objetivo
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.
Ámbito científico
- natural sciencescomputer and information sciencesdata science
- natural sciencesbiological sciencesbiochemistrybiomoleculesnucleic acids
- natural sciencesbiological sciencesgeneticsDNA
- natural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learning
- natural sciencesbiological sciencesgeneticsRNA
Programa(s)
Régimen de financiación
ERC-POC-LS - ERC Proof of Concept Lump Sum PilotInstitución de acogida
75794 Paris
Francia