Next Generation Imaging

ended

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.