VISION: ValIdated Systematic IntegratiON of epigenomic data

项目概要VISION：造血表观基因组的有效系统整合 技术进步使得能够产生大量丰富的、全基因组的、基于序列的 数据集已经改变了生物学。然而，数据量对大多数调查人员来说是压倒性的。还有， 我们不知道绝大多数表观遗传特征调节正常发育的机制， 分化或导致疾病中的异常功能。我们组建了一个跨学科的协作团队 如何有效利用大量的表观遗传学数据， 无论是基础研究还是精准医疗。在这一点上，获取数据不再是主要障碍 了解正常和病理组织发育过程中的基因调控机制。的 主要的挑战是如何：（i）将表观遗传数据以一种可获得和可理解的方式纳入， 广泛的研究人员社区，（ii）建立有效的定量模型，解释基因的动态如何 表达与表观遗传特征有关，以及（iii）将来自小鼠模型的信息有效地翻译为 在人类健康方面的潜在应用。这些需求通过拟议的经验证的系统解决 IntegratiON（VISION）的表观遗传数据分析小鼠和人类造血，一个易于处理的系统， 明确临床意义和对NIDDK的重要性。通过追求以下具体目标， 跨学科合作将提供全面的顺式调控模块（CRM）目录，广泛的 染色质相互作用图谱和推导的调控结构域，用于基因调控的经验证的定量模型， 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 将通过易于访问的基于网络的平台向社区提供可交付的成果，包括定制的 基因组浏览器、具有简易查询界面的数据库和数据驱动的在线工具。具体而言是 目标1中提出的工作将建立全面的、综合的造血CRM目录， 转录组通过编译和确定信息表观遗传特征和转录水平， 造血干细胞和祖细胞以及成熟细胞。标准物质将使用新的IDEAS预测 （综合和区分表观基因组注释系统）方法。目标2中提出的工作将建立和 通过染色质相互作用图谱和表观遗传学数据验证基因调控的定量模型。 编译和确定染色体相互作用频率将预测CRM可能的靶基因。基因 将建立调控模型，预测CRM和特定蛋白质对调控的贡献。 这些模型将通过在十个参考基因座中使用基因组编辑的广泛测试来验证。 最后，Aim3的工作将为研究人员提供一个指南，将小鼠模型的见解转化为人类模型。 临床研究。这项工作将包括按保守性对小鼠和人类基因进行分类 与表达模式的分歧，分配标准物质的表观基因组进化的信息类别， 并通过基因组编辑实验性地测试物种间功能图。

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.