MorPhiC: Constructing a Catalog of Cellular Programs to Identify and Annotate Human Disease Genes

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PROJECT SUMMARY Genome-wide studies have now identified hundreds of thousands of associations between genes or genetic loci and human phenotypes, each of which could reveal mechanistic insights about disease biology. Yet, the cell-type specific functions of most of these genes remain unknown, and we currently lack the ability to connect these genes into cellular programs and thereby reveal the pathways important for disease. To address this limitation, our proposed Data Analysis and Validation Center aims to work together with the MorPhiC Consortium to build a Catalog of Cellular Programs — i.e. a map of which genes work together in biological pathways and their corresponding multimodal molecular and cellular phenotypes, in defined cell types or states. Our team brings a diverse set of expertise in computational genomics, methods and technology development, experimental design, interdisciplinary collaboration, consortium organization; and includes new junior investigators who will bring new forward-thinking ideas and tools to MorPhiC. We have developed a wave of innovative methods integrating CRISPR, single-cell, imaging, and human genetics data that will enable building such a Catalog of Cellular Programs and applying this Catalog to understand the genetics of human disease. The goals of our Center are to: (i) Define single-layer phenotypes, by applying a suite of computational state-of-the-art approaches for analysis and modeling of RNA, ATAC, and imaging data; (ii) define a multi-modal representation of molecular and cellular phenotypes, by identifying modules of features that co-vary across perturbations and single cells; (iii) build a Catalog of Cellular Programs that links genes to the molecular and cellular phenotypes they control, by inferring causal gene regulatory networks from perturbation data; (iv) apply the Catalog of Cellular Programs to demonstrate its utility identifying causal genes and programs for human diseases; and (v) participate in Collaborative Activities with MorPhiC, including to guide experimental design and ensure utility, robustness, and interoperability of Phase 1 datasets. Together, these aims will develop novel computational toolkits to infer causal gene regulatory networks from multi-modal perturbation data; construct a Catalog of Cellular Programs as a foundational resource for MorPhiC and the broader community; and demonstrate the utility of this Catalog through application to understand the genetics of human diseases.