Orthogonal CRISPR GEMMs

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PROJECT SUMMARY The heart of this proposal is to overturn the existing one-gene-at-a-time paradigm for studying human genes in organismal model studies, and to push the envelope for studying genetic interactions in vivo. We have developed a technology to study gene interactions in mouse models using a high-throughput CRISPR technology suitable for interrogating specific genes implicated in a given pathway or disease. An in vivo high-throughput targeted multi-mutation approach has never been accomplished in any organismal model and this will revolutionize the study of complex gene interaction in physiologically relevant organismal model systems. Our preliminary data have addressed the major feasibility gaps but we need to further develop the platform and apply rigor/reproducibility. Multimer technology will help bridge the gap between the enormous volumes of data generated by genome sequencing studies and the ability to use these data for the understanding of biology and disease. Our end goal is to benchmark the proposed technology, illustrating its application in a use-case setting—targeting a set of CD antigens with orthogonal gene activation and gene editing CRISPR machinery to reveal underlying genetic interactions and pathway directionality. Our general strategy is to take advantage of novel tools and methodologies that we have developed during the past two years– using innovative high throughput CRISPR screening methods. Our end goal is to develop a modular toolset that advances functional genomics approaches. All this will be done in vivo in an animal model. Our goal is to pilot an orthogonal Multimer platform to investigate up to 900 combinations of perturbations in vivo in a single animal. We will benchmark our technology using CD antigens as reporter genes that are easy to quantitate using commercially available monoclonal antibodies. Targeted edits and transcript abundance will be analyzed by flow cytometry and via single-cell sequencing on subpopulations of B and T cells. The future for bioinformatically dissecting mechanisms of complex diseases is promising but challenging. Multiple large-scale reference data sets of human sequences are rapidly becoming available and are expected to increase over the coming decades. Millions of human genome sequencing data sets will constitute an incredible resource for interpretation of DNA mutations. Unfortunately, there are no feasible approaches for interrogating the thousands of combinations of genes in animal models. This proposal aims to further a new technology that would advance complex genetics problems relevant to organismal biology and human disease and will showcase promising new technologies for studying genetic interaction in vivo.