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系统整合 技术进步使得能够生产大量丰富的、全基因组的、基于序列的 数据集改变了生物学。然而，对于大多数研究人员来说，数据量是巨大的。还， 我们不知道绝大多数表观遗传特征调节正常的机制 分化或导致疾病功能异常。我们组建了一支跨学科的协作团队 研究人员需要解决如何有效利用海量表观遗传数据的问题 无论是基础研究还是精准医学。此时，数据获取不再是主要障碍 了解正常和病理组织发育过程中的基因调控机制。这 主要挑战是如何：（i）以人们可以访问和理解的方式整合表观遗传数据。 广泛的研究人员群体，（ii）建立经过验证的定量模型，解释基因的动态变化 表达与表观遗传特征有关，并且（iii）有效地将信息从小鼠模型转化为 在人类健康方面的潜在应用。这些需求由拟议的验证系统解决 整合表观遗传数据来分析小鼠和人类造血作用，这是一个易于处理的系统 对 NIDDK 具有明确的临床意义和重要性。通过追求以下具体目标， 跨学科合作将提供全面的顺式监管模块（CRM）目录，广泛 染色质相互作用图谱和推断的调控域，验证基因调控的定量模型， 以及研究人员将小鼠模型的见解转化为人类临床研究的指南。这些 可交付成果将通过易于访问的网络平台向社区提供，包括定制的 基因组浏览器、具有简便查询界面的数据库以及数据驱动的在线工具。具体来说， 目标 1 中拟议的工作将建立全面、综合的造血 CRM 目录和 通过编译和确定信息表观遗传特征和转录水平来构建转录组 造血干细胞和祖细胞以及成熟细胞。将使用新颖的 IDEAS 来预测 CRM （综合和判别表观基因组注释系统）方法。目标 2 中提出的工作将建立和 验证由染色质相互作用图和表观遗传数据提供的基因调控定量模型。 编译和确定染色体相互作用频率将预测 CRM 的可能目标基因。基因 将建立监管模型来预测 CRM 和特定蛋白质对监管的贡献 表达;这些模型将通过在十个参考基因座中使用基因组编辑进行广泛测试来验证。 最后，Aim 3 的工作将为研究人员提供一份指南，将小鼠模型的见解转化为人类模型 临床研究。这项工作将包括通过保护对直系同源小鼠和人类基因进行分类 与表达模式的分歧相比，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功能图谱。