Multiscale Analyses of 4D Nucleome Structure and Function by Comprehensive Multimodal Data Integration

通过综合多模态数据集成对 4D 核组结构和功能进行多尺度分析

• 批准号: 10704567
• 负责人: Frank Alber
• 金额: $ 207.54万
• 依托单位: CARNEGIE-MELLON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-22 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10704567
• 关键词: Address; Architecture; Binding; Biochemical; Cell Cycle; Cell Nucleus; Cell physiology; Cells; Chromatin; Chromatin Loop; Chromatin Structure; Chromosome Mapping; Chromosome Structures; Chromosomes; Collaborations; Communities; Complement; Computing Methodologies; Cytology; DNA Replication Timing; Data; Data Set; Development; Disease; Formulation; Gene Expression; Genetic; Genetic Transcription; Genome; Genomics; Goals; Health; Human; Image; Interphase Chromosome; Intuition; Knowledge; Link; Maps; Measurement; Measures; Methods; Microscopy; Mission; Modality; Modeling; Molecular; Multimodal Imaging; Nuclear; Nuclear Lamina; Nuclear Structure; Organelles; Outcome; Output; Phase; Population; Production; Public Health; Research; Research Personnel; Resolution; Role; Structure; Technology; Three-Dimensional Imaging; United States National Institutes of Health; Validation; Variant; Visualization; Work; cell fixing; cell type; computer framework; computerized tools; data exploration; data integration; data tools; empowerment; experimental study; genome-wide; genomic data; histone modification; imaging modality; improved; insight; machine learning algorithm; multi-scale atlas; multimodal data; multimodality; multiple data types; multiscale data; predictive modeling; response; spatiotemporal; superresolution microscopy; tool; transcription factor; transcriptome sequencing; user-friendly; whole genome

PROJECT SUMMARY The cell nucleus is a heterogeneous organelle that consists of nuclear bodies such as nuclear lamina, speckles, nucleoli and PML bodies. These structures continuously tether and tug chromatin at the small and large scales to synergistically orchestrate dynamic functions in distinct spatio-temporal compartments. A major obstacle to the production of navigable 4D reference maps and relating structure to function in the nucleus remains understanding how these different scales of organization influence each other. In particular, we have a poor understanding of the large-scale genome organization. Growing evidence suggests that such nuclear compartmentalization is causally connected with vital genome functions in human health and disease. However, the principles of this nuclear compartmentalization, its dynamics during changes in cell conditions, and its functional relevance are poorly understood. One lesson from Phase 1 4DN was the huge gap in throughput between imaging methods, that directly measure large-scale multi-landmark relationships, and genomic methods, that aim for whole genome high-resolution maps but are indirect measurements and provide limited information about large-scale compartments. For this 4DN UM1 Center application, we propose to meet these needs through the following Aims: (1) Generate multi-modal imaging and genomic datasets to reveal the structure, dynamics, and function of nuclear compartmentalization; (2) Develop and apply computational tools for data-driven genome structure modeling and integrative analysis of nuclear compartmentalization; (3) Develop an integrative analysis and visualization platform with navigable 4D reference maps of nuclear organization. The combined datasets and results of our proposed approaches will advance our understanding of nuclear compartmentalization, the interwoven connections among different nuclear components, and their functional significance. Our new integrative analysis tools and data-driven predictive models will produce more complete nuclear organization reference maps that integrate large-scale chromosome structure data from live and super-resolution microscopy with multi-modal genomic data including smaller scale chromatin interaction maps and predict functional relationships and dynamic responses. Our navigable reference maps will be publicly accessible through an analysis platform that provides interactive visualization of multiple data types, thus enabling investigators with diverse expertise to simultaneously explore their own data and related datasets/tools and promoting collaborations that will open new horizons into the role of the 4D nucleome in human health and disease.

项目总结 细胞核是由核板等核体组成的异质细胞器， 斑点、核仁和PML小体。这些结构不断地在小的和 大规模协同协调不同时空隔间中的动态功能。一位少校 制作可导航的4D参考图和将结构与核内功能联系起来的障碍 了解这些不同规模的组织是如何相互影响的。特别是，我们有一个 对大规模基因组组织的认识不足。越来越多的证据表明，这种核能 区划与人类健康和疾病中至关重要的基因组功能有因果关系。 然而，这种核分区的原理，它在细胞条件变化期间的动态， 以及它的功能相关性还知之甚少。从第1阶段4DN中得到的一个教训是 直接测量大规模多里程碑关系的成像方法之间的吞吐量，以及 基因组方法，目标是全基因组高分辨率图谱，但是间接测量和提供 关于大型隔间的有限信息。对于此4DN UM1中心应用，我们建议满足 这些需求通过以下目标实现：(1)生成多模式成像和基因组数据集以揭示 核分区的结构、动力学和功能；(2)开发和应用计算工具 用于数据驱动的基因组结构建模和核分区的综合分析；(3) 开发可导航的核4D参考图综合分析和可视化平台 组织。我们提出的方法的组合数据集和结果将促进我们的理解 不同核成分之间相互交织的联系，以及它们 功能意义。我们新的综合分析工具和数据驱动的预测模型将产生更多 完整的核组织参考图，集成来自LIVE的大规模染色体结构数据 以及具有包括较小规模染色质相互作用的多模式基因组数据的超分辨率显微镜 映射和预测功能关系和动态响应。我们的导航参考地图将是 通过提供多种数据类型的交互可视化的分析平台可公开访问， 从而使具有不同专业知识的调查人员能够同时探索他们自己的数据和相关 数据集/工具，并促进合作，这将打开4D核基因组在 人类的健康和疾病。