VISION: ValIdated Systematic IntegratiON of epigenomic data

愿景：经过验证的表观基因组数据的系统整合

• 批准号: 9183143
• 负责人: DAVID M. BODINE
• 金额: $ 132.49万
• 依托单位: PENNSYLVANIA STATE UNIVERSITY, THE
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-18 至 2021-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9183143
• 关键词: Accounting; Address; Area; Back; Base Sequence; Basic Science; Binding Proteins; Biology; Blood; Blood Cells; Cataloging; Catalogs; Categories; Cells; Chromatin; Chromosomes; Clinical Research; Collaborations; Communities; DNA; DNA Sequence; Data; Data Set; Databases; Development; Disease; Elements; Engineering; Epigenetic Process; Erythroid Cells; Evolution; Experimental Models; Frequencies; Gene Expression; Gene Expression Regulation; Gene Targeting; Genetic; Genetic Transcription; Genome; Health; Heart; Hematopoiesis; Hematopoietic; Human; Human Resources; Knock-out; Lead; Learning; Machine Learning; Maps; Measurement; Methods; Modeling; Modification; Monitor; Monoclonal Antibody R24; Mus; National Institute of Diabetes and Digestive and Kidney Diseases; Online Systems; Output; Pattern; Positioning Attribute; Production; Proteins; Publications; Publishing; Recording of previous events; Regulator Genes; Research; Research Personnel; Resources; Science; Staging; Stem cells; System; Technology; Testing; Tissues; Training; Transcript; Translating; Vision; Work; cell injury; cell type; chromosome conformation capture; clinically significant; data acquisition; epigenome; epigenomics; falls; feeding; gene conservation; genome browser; genome editing; genome-wide; improved; insight; interdisciplinary collaboration; loss of function; mouse model; novel; precision medicine; prototype; research study; response; stem; tool; transcriptome

Project Summary VISION: ValIdated Systematic IntegratiON of hematopoietic epigenomes Technological advances enabling the production of large numbers of rich, genome-wide, sequence-based datasets have transformed biology. However, the volume of data is overwhelming for most investigators. Also, we do not know the mechanisms by which the vast majority of epigenetic features regulate normal differentiation or lead to aberrant function in disease. We have formed an interdisciplinary, collaborative team of investigators to address the problem of how to effectively utilize the enormous amount of epigenetic data both for basic research and precision medicine. At this point, acquisition of data is no longer the major barrier to understanding mechanisms of gene regulation during normal and pathological tissue development. The chief challenges are how to: (i) integrate epigenetic data in terms that are accessible and understandable to a broad community of researchers, (ii) build validated quantitative models explaining how the dynamics of gene expression relates to epigenetic features, and (iii) translate information effectively from mouse models to potential applications in human health. These needs are addressed by the proposed ValIdated Systematic IntegratiON (VISION) of epigenetic data to analyze mouse and human hematopoiesis, a tractable system with clear clinical significance and importance to NIDDK. By pursuing the following Specific Aims, the interdisciplinary collaboration will deliver comprehensive catalogs of cis regulatory modules (CRMs), extensive chromatin interaction maps and deduced regulatory domains, validated quantitative models for gene regulation, and a guide for investigators to translate insights from mouse models to human clinical studies. These deliverables will be provided to the community in readily accessible, web-based platforms including customized genome browsers, databases with facile query interfaces, and data-driven on-line tools. Specifically, the proposed work in Aim 1 will build comprehensive, integrative catalogs of hematopoietic CRMs and transcriptomes by compiling and determining informative epigenetic features and transcript levels in hematopoietic stem and progenitor cells and in mature cells. CRMs will be predicted using the novel IDEAS (Integrative and Discriminative Epigenome Annotation System) method. Work proposed in Aim 2 will build and validate quantitative models for gene regulation informed by chromatin interaction maps and epigenetic data. Compiling and determining chromosome interaction frequencies will predict likely target genes for CRMs. Gene regulatory models will be built that predict the contributions of CRMs and specific proteins to regulated expression; these models will be validated by extensive testing using genome-editing in ten reference loci. Finally, work in Aim 3 will produce a guide for investigators to translate insights from mouse models to human clinical studies. This effort will include categorizing orthologous mouse and human genes by conservation versus divergence of expression patterns, assigning CRMs to informative categories of epigenomic evolution, and testing the interspecies functional maps experimentally by genome-editing.

项目摘要愿景：经过验证的造血表观基因组的系统整合 技术进步，能够产生大量富含基因组，基于序列的大量 数据集改变了生物学。但是，对于大多数研究人员来说，数据量是压倒性的。还， 我们不知道绝大多数表观遗传特征正常的机制 分化或导致疾病异常功能。我们组成了一个跨学科的协作团队 研究人员解决了如何有效利用大量表观遗传数据的问题 用于基础研究和精确医学。此时，数据的获取不再是主要障碍 了解正常和病理组织发育过程中基因调节的机制。这 主要挑战是：（i）以可访问和可理解的术语整合表观遗传数据 广泛的研究人员社区，（ii）构建经过验证的定量模型，解释了基因动态如何 表达与表观遗传特征有关，（iii）将信息有效地从鼠标模型转换为 人类健康中的潜在应用。这些需求由拟议的经过验证的系统解决 表观遗传数据的整合（视觉）分析小鼠和人类造血，这是一种可拖动的系统 对NIDDK的明确临床意义和重要性。通过追求以下特定目标， 跨学科合作将提供CIS监管模块（CRMS）的全面目录，广泛 染色质相互作用图和推导的调节域，验证了基因调节的定量模型， 以及研究人员的指南，将洞察力从小鼠模型转化为人类的临床研究。这些 将以易于访问的，基于网络的平台（包括自定义）提供可交付成果 基因组浏览器，具有简便查询接口的数据库以及数据驱动的在线工具。具体来说， AIM 1中的拟议工作将建立造血CRM和 通过编译和确定信息性表观遗传特征和转录水平的转录组 造血干细胞和成熟细胞中的造血干细胞。将使用新颖的想法预测CRM （综合和歧视性基因组注释系统）方法。 AIM 2中提出的工作将建立，并且 验证通过染色质相互作用图和表观遗传数据告知的基因调节的定量模型。 编译和确定染色体相互作用频率将预测CRM的靶基因。基因 将建立监管模型，以预测CRM和特定蛋白质对调节的贡献 表达;这些模型将通过十个参考基因座中的基因组编辑进行广泛的测试来验证。 最后，在AIM 3中的工作将为调查人员提供指南，以将洞察力从鼠标模型转化为人类 临床研究。这项工作将包括通过保护对直系同源的小鼠和人类基因进行分类 表达模式的差异与差异，将CRM分配给表观基因组进化的信息类别， 并通过基因组编辑实验测试种间函数图。