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

MorPhiC：构建细胞程序目录来识别和注释人类疾病基因

• 批准号: 10733164
• 负责人: JESSE M ENGREITZ
• 金额: $ 49.2万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2028-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10733164
• 关键词: Address; Biological; Biological Assay; Biology; CRISPR interference; Catalogs; Cell Communication; Cells; Cellular Morphology; Chromatin; Clustered Regularly Interspaced Short Palindromic Repeats; Collaborations; Communities; Computer Models; Computing Methodologies; DNA Sequence; Data; Data Analyses; Data Set; Disease; Ensure; Experimental Designs; Gene Expression; Genes; Genetic; Genetic Diseases; Genetic Transcription; Genome; Genomics; Goals; Human; Human Genetics; Image; Kinetics; Learning; Link; Maps; Methods; Modality; Modeling; Molecular; Pathway interactions; Phase; Phenotype; Production; RNA; RNA analysis; Research Design; Research Personnel; Resources; Thinking; Validation; Variant; Work; XCL1 gene; causal variant; cell type; computational suite; computerized tools; data quality; experience; gene network; gene regulatory network; genome-wide analysis; genomic locus; human disease; imaging genetics; improved; innovation; insight; interdisciplinary collaboration; interoperability; method development; multimodality; novel; programs; reconstruction; technology development; tool

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.

项目摘要 全基因组研究现已确定了基因或遗传之间的数十万种关联， 基因座和人类表型，其中每一个都可以揭示疾病生物学的机制见解。然而 大多数这些基因的细胞类型特异性功能仍然未知，我们目前缺乏连接这些基因的能力。 这些基因进入细胞程序，从而揭示疾病的重要途径。为了解决这个 我们建议的数据分析和验证中心旨在与MorPhiC合作， 联盟建立细胞程序目录-即基因在生物学中共同工作的地图 途径及其相应的多模态分子和细胞表型， states. 我们的团队在计算基因组学、方法和技术开发方面拥有丰富的专业知识， 实验设计，跨学科合作，联盟组织;并包括新的初级 研究人员将为MorPhiC带来新的前瞻性想法和工具。我们发展了一波 创新方法整合CRISPR，单细胞，成像和人类遗传学数据， 这样一个细胞程序目录，并应用这个目录来了解人类疾病的遗传学。 我们中心的目标是：（i）定义单层表型，通过应用一套计算 用于RNA、ATAC和成像数据的分析和建模的最新方法;（ii）定义 分子和细胞表型的多模态表示，通过识别 （iii）建立一个细胞程序目录，将基因与细胞程序联系起来。 它们控制的分子和细胞表型，通过从扰动中推断因果基因调控网络 数据;（iv）应用细胞程序目录来证明其识别因果基因的实用性， （v）参与与MorPhiC的合作活动，包括指导 实验设计，并确保第1阶段数据集的实用性，鲁棒性和互操作性。 这些目标将共同开发新型计算工具包，以从基因中推断因果基因调控网络 多模态扰动数据;构建细胞程序目录作为基础资源， MorPhiC和更广泛的社区;并通过应用程序演示此目录的实用性， 了解人类疾病的遗传学。