Constructing High-Resolution Ensemble Models of 3D Single-Cell Chromatin Conformations of eQTL Loci from Integrated Analysis of 4DN-GTEx Data towards Structural Basis of Differential Gene Expression

从 4DN-GTEx 数据的集成分析构建 eQTL 位点 3D 单细胞染色质构象的高分辨率整体模型,以构建差异基因表达的结构基础

基本信息

  • 批准号:
    10357063
  • 负责人:
  • 金额:
    $ 30.94万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-09-22 至 2023-09-21
  • 项目状态:
    已结题

项目摘要

Program Director/Principal Investigator (Liang, Jie): PROJECT SUMMARY/ABSTRACT To enhance the utility of the common fund supported 4D Nucleome (4DN) database and Genotype- Tissue Expression (GTEx) database, we will develop novel computational tools for infering the spatial organizations of genomic elements to elucidate how eQTLs can regulate the expression of their target genes. Our tools will integrate 4DN and GTEx data and overcome the limit of the 2D nature of Hi-C frequency heatmaps, enabling construction of large 3D ensembles of high-resolution models of single-cell chromatin conformations for loci containing tissue-specific genetic variants associated with differential expression. By accounting for 3D polymer effects of random collision between genomic elements due to nuclear volume confinement, our tools will identify chromatin interactions that are statistically significant and likely biologically important. With the ensemble model of single-cell 3D chromatin conformations, our tools will further identify participating genes, promoters, enhancers, and other elements, and elucidate how they are physically arranged in space around genetic variants associated differential gene expression, including how units of higher order many-body interaction for gene regulation may form. In addition, our tools will quantify the presence of heterogeneous subpopulation of cells with different chromatin 3D configurations, allowing probabilistic understanding of the heterogeneous physical interactions around eQTLs. With planned comparative analysis of 3D chromatin conformations from different tissues, different spatial pattern of arrangement of genes and elements important for gene expression will be uncovered, resulting better understanding of genome structure and function relationship. Overall, we will demonstrate significant added-power of integrating two important Common Fund data resources and will provide tools to facilitate understanding the relationship between genome topology and gene expression. Our work will enable highly specific and compelling testable hypothesis on mechanisms of gene regulation to be formulated based on the reconstructed 3D spatial genome topology at loci that harbor variants and eGenes. Validation or refutation of these hypotheses will lead to new insight into the relationship of genome structure and genome function important for improving human health. 0925-0001 (Rev. 03/16) Page Continuation Format Page
项目负责人/主要研究者(梁杰): 项目总结/摘要 为了提高共同基金支持的4D Nucleome(4DN)数据库和基因型的实用性, 组织表达(GTEx)数据库,我们将开发新的计算工具,推断空间 基因组元件的组织,以阐明eQTL如何调控其靶基因的表达, 基因.我们的工具将集成4DN和GTEx数据,并克服Hi-C的2D特性限制 频率热图,能够构建高分辨率模型的大型3D集合, 单细胞染色质构象的基因座含有组织特异性遗传变异相关 差异表达通过考虑基因组之间随机碰撞的3D聚合物效应, 由于核体积限制,我们的工具将识别染色质相互作用, 具有统计学显著性和可能的生物学重要性。利用单细胞3D的整体模型 染色质构象,我们的工具将进一步确定参与基因,启动子,增强子, 其他元素,并阐明它们如何在遗传变异周围的空间中物理排列 相关的差异基因表达,包括如何单位的高阶多体相互作用, 基因调控可能形成。此外,我们的工具将量化异质性的存在, 具有不同染色质3D构型的细胞亚群,允许概率理解 eQTL周围的异质物理相互作用。通过计划的3D对比分析 不同组织的染色质构象,基因排列的不同空间模式, 基因表达的重要元件将被发现,从而更好地了解基因组 结构和功能关系。总的来说,我们将展示 整合两个重要的共同基金数据资源,并将提供工具, 了解基因组拓扑结构和基因表达之间的关系。我们的工作将使 关于基因调控机制的高度特异性和令人信服的可检验假设, 基于在含有变体的基因座处的重建的3D空间基因组拓扑来制定, 基因。对这些假说的验证或反驳将导致对 基因组结构和基因组功能对改善人类健康很重要。 0925 - 0001(修订版03/16)页续格式页

项目成果

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Jie Liang其他文献

Jie Liang的其他文献

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{{ truncateString('Jie Liang', 18)}}的其他基金

Predicting 3D physical gene-enhancer interactions through integration of GTEx and 4DN data
通过整合 GTEx 和 4DN 数据预测 3D 物理基因增强子相互作用
  • 批准号:
    10776871
  • 财政年份:
    2023
  • 资助金额:
    $ 30.94万
  • 项目类别:
Models and Algorithms for Beta-Barrel Membrane Proteins and Stochastic Networks
β-桶膜蛋白和随机网络的模型和算法
  • 批准号:
    9923024
  • 财政年份:
    2018
  • 资助金额:
    $ 30.94万
  • 项目类别:
Models and Algorithms for Beta-Barrel Membrane Proteins and Stochastic Networks
β-桶膜蛋白和随机网络的模型和算法
  • 批准号:
    10395949
  • 财政年份:
    2018
  • 资助金额:
    $ 30.94万
  • 项目类别:
Constructing Ensembles of 3D Structures of Igh Locus and Predicting Novel Chromosomal Interactions
构建 Igh 基因座 3D 结构的集合并预测新的染色体相互作用
  • 批准号:
    9317936
  • 财政年份:
    2017
  • 资助金额:
    $ 30.94万
  • 项目类别:
Computational Assembly of Beta Barrel Membrane Protein
β 桶膜蛋白的计算组装
  • 批准号:
    8546506
  • 财政年份:
    2007
  • 资助金额:
    $ 30.94万
  • 项目类别:
Computational Assembly of Beta Barrel Membrane Protein
β 桶膜蛋白的计算组装
  • 批准号:
    7586266
  • 财政年份:
    2007
  • 资助金额:
    $ 30.94万
  • 项目类别:
Computational Assembly of Beta Barrel Membrane Protein
β 桶膜蛋白的计算组装
  • 批准号:
    7213136
  • 财政年份:
    2007
  • 资助金额:
    $ 30.94万
  • 项目类别:
Computational Assembly of Beta Barrel Membrane Protein
β 桶膜蛋白的计算组装
  • 批准号:
    8918774
  • 财政年份:
    2007
  • 资助金额:
    $ 30.94万
  • 项目类别:
Computational Assembly of Beta Barrel Membrane Protein
β 桶膜蛋白的计算组装
  • 批准号:
    7356031
  • 财政年份:
    2007
  • 资助金额:
    $ 30.94万
  • 项目类别:
Computational Assembly of Beta Barrel Membrane Protein
β 桶膜蛋白的计算组装
  • 批准号:
    8034791
  • 财政年份:
    2007
  • 资助金额:
    $ 30.94万
  • 项目类别:

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