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
基本信息
- 批准号:10733164
- 负责人:
- 金额:$ 49.2万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 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:
- 关键词:AddressBiologicalBiological AssayBiologyCRISPR interferenceCatalogsCell CommunicationCellsCellular MorphologyChromatinClustered Regularly Interspaced Short Palindromic RepeatsCollaborationsCommunitiesComputer ModelsComputing MethodologiesDNA SequenceDataData AnalysesData SetDiseaseEnsureExperimental DesignsGene ExpressionGenesGeneticGenetic DiseasesGenetic TranscriptionGenomeGenomicsGoalsHumanHuman GeneticsImageKineticsLearningLinkMapsMethodsModalityModelingMolecularPathway interactionsPhasePhenotypeProductionRNARNA analysisResearch DesignResearch PersonnelResourcesThinkingValidationVariantWorkXCL1 genecausal variantcell typecomputational suitecomputerized toolsdata qualityexperiencegene networkgene regulatory networkgenome-wide analysisgenomic locushuman diseaseimaging geneticsimprovedinnovationinsightinterdisciplinary collaborationinteroperabilitymethod developmentmultimodalitynovelprogramsreconstructiontechnology developmenttool
项目摘要
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.
项目总结
全基因组研究现在已经确定了数十万个基因或基因之间的关联
基因座和人类表型,其中每一个都可以揭示关于疾病生物学的机械性见解。然而,
其中大多数基因的细胞类型特定功能仍不清楚,我们目前缺乏联系的能力
这些基因进入细胞程序,从而揭示了疾病的重要途径。要解决这个问题
限制,我们建议的数据分析和验证中心旨在与Moric
一个联盟将建立一个细胞程序目录--即哪些基因在生物中协同工作的图谱
通路及其相应的多模式分子和细胞表型,在定义的细胞类型或
各州。
我们的团队带来了计算基因组学、方法和技术开发方面的各种专业知识,
实验设计、跨学科协作、联合体组织;包括新手
将为Moric带来新的前瞻性思维想法和工具的研究人员。我们已经形成了一波
集成CRISPR、单细胞、成像和人类遗传学数据的创新方法,将使
这样一个细胞程序目录,并应用这个目录来理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
对RNA、ATAC和成像数据进行分析和建模的最先进方法;(Ii)定义
分子和细胞表型的多模式表示,通过识别以下特征模块
在扰动和单细胞之间变化;(Iii)建立一个细胞程序目录,将基因与
他们通过从扰动中推断因果基因调控网络来控制分子和细胞表型
数据;(4)应用细胞程序目录以演示其识别致病基因和
人类疾病方案;以及(V)参与与Moric的合作活动,包括指导
实验设计并确保第一阶段数据集的实用性、健壮性和互操作性。
这些目标将共同开发新的计算工具包,以推断因果基因调控网络
多模式摄动数据;构建细胞程序目录作为基础资源
Moric和更广泛的社区;并通过应用于
了解人类疾病的遗传学。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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{{ truncateString('JESSE M ENGREITZ', 18)}}的其他基金
High-throughput cellular genetics to connect noncoding variants to coronary artery disease genes
高通量细胞遗传学将非编码变异与冠状动脉疾病基因连接起来
- 批准号:
10659996 - 财政年份:2023
- 资助金额:
$ 49.2万 - 项目类别:
Mapping, modeling, and manipulating 3D contacts in vascular cells to connect risk variants to disease genes
绘制、建模和操作血管细胞中的 3D 接触,将风险变异与疾病基因联系起来
- 批准号:
10446856 - 财政年份:2022
- 资助金额:
$ 49.2万 - 项目类别:
Mapping, modeling, and manipulating 3D contacts in vascular cells to connect risk variants to disease genes
绘制、建模和操作血管细胞中的 3D 接触,将风险变异与疾病基因联系起来
- 批准号:
10591585 - 财政年份:2022
- 资助金额:
$ 49.2万 - 项目类别:
Systematic mapping and prediction of gene-enhancer connections
基因增强子连接的系统绘图和预测
- 批准号:
10318508 - 财政年份:2021
- 资助金额:
$ 49.2万 - 项目类别:
Stanford Center for Connecting DNA Variants to Function and Phenotype
斯坦福大学 DNA 变异与功能和表型关联中心
- 批准号:
10633286 - 财政年份:2021
- 资助金额:
$ 49.2万 - 项目类别:
Stanford Center for Connecting DNA Variants to Function and Phenotype
斯坦福大学 DNA 变异与功能和表型关联中心
- 批准号:
10480918 - 财政年份:2021
- 资助金额:
$ 49.2万 - 项目类别:
Stanford Center for Connecting DNA Variants to Function and Phenotype
斯坦福大学 DNA 变异与功能和表型关联中心
- 批准号:
10295739 - 财政年份:2021
- 资助金额:
$ 49.2万 - 项目类别:
Mapping enhancer-gene regulation in single cells to connect genetic variants to target genes and cell types
绘制单细胞中的增强子基因调控图谱,将遗传变异与目标基因和细胞类型联系起来
- 批准号:
10434907 - 财政年份:2020
- 资助金额:
$ 49.2万 - 项目类别:
Systematic mapping and prediction of gene-enhancer connections
基因增强子连接的系统绘图和预测
- 批准号:
10153858 - 财政年份:2020
- 资助金额:
$ 49.2万 - 项目类别:
Systematic mapping and prediction of gene-enhancer connections
基因增强子连接的系统绘图和预测
- 批准号:
10365988 - 财政年份:2020
- 资助金额:
$ 49.2万 - 项目类别:
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