VISION: ValIdated Systematic IntegratiON of epigenomic data

项目总结愿景：已验证的造血表观基因组系统整合 技术进步使大量丰富的、全基因组的、基于序列的 数据集改变了生物学。然而，对于大多数调查人员来说，数据量是压倒性的。另外， 我们不知道绝大多数表观遗传特征调节正常的机制 分化或导致疾病中的功能异常。我们已经组建了一个跨学科、协作的团队 以解决如何有效利用海量表观遗传学数据的问题 既用于基础研究，也用于精确医学。在这一点上，获取数据不再是主要障碍 了解正常组织和病理组织发育过程中的基因调控机制。这个 主要挑战是如何：(1)以可访问和可理解的方式整合表观遗传数据 广泛的研究人员社区，(Ii)建立有效的量化模型，解释基因动力学如何 表达与表观遗传特征有关，以及(Iii)将信息从小鼠模型有效地翻译到 在人类健康方面的潜在应用。建议的经验证的系统解决了这些需求 整合(VISION)表观遗传数据以分析小鼠和人类的造血，这是一个易于处理的系统，具有 明确NIDDK的临床意义和重要性。通过追求以下具体目标， 跨学科协作将提供全面的CI监管模块(CRM)目录、广泛的 染色质相互作用图和推导出的调控结构域，验证了基因调控的定量模型， 以及一本指导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 交付成果将在易于访问的基于网络的平台上提供给社区，包括定制的 基因组浏览器、具有便捷查询界面的数据库和数据驱动的在线工具。具体地说， 目标1中的拟议工作将建立全面、综合的造血CRM目录和 通过编辑和确定信息性表观遗传学特征和转录本水平 造血干细胞和造血祖细胞以及成熟细胞。将使用新的想法来预测CRM (综合和判别性表观基因组注释系统)方法。目标2中提议的工作将建立和 验证由染色质相互作用图和表观遗传学数据提供信息的基因调控的定量模型。 汇编和确定染色体相互作用频率将预测CRM可能的靶基因。基因 将建立预测CRM和特定蛋白质对被调控的贡献的调控模型 这些模型将通过在10个参考基因座进行基因组编辑的广泛测试来验证。 最后，AIM 3的工作将为研究人员提供一份指南，将老鼠模型的洞察力转化为人类 临床研究。这一努力将包括根据保守性对同源的老鼠和人类基因进行分类。 相对于表达模式的差异，将CRM分配给表观基因组进化的信息类别， 并通过基因组编辑对物种间功能图谱进行实验性测试。

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.