Elucidation of the organizing principles of the regulatory genome through large-scale data integration

通过大规模数据整合阐明调控基因组的组织原理

• 批准号: 10251060
• 负责人: Wouter Meuleman
• 金额: $ 36.98万
• 依托单位: ALTIUS INSTITUTE FOR BIOMEDICAL SCIENCES
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10251060
• 关键词: Area; Cells; Chromatin; Communities; Data; Data Analyses; Data Set; Disease; Elements; Gene Expression; Genes; Genetic Variation; Genome; Genomics; Health; Human; Human Genome; Individual; Instruction; Light; Methods; Open Reading Frames; Pattern; Play; Process; Regulator Genes; Regulatory Element; Research; Resources; Role; Structure; System; Systems Biology; Untranslated RNA; Variant; Work; annotation system; base; cell type; data integration; design; functional genomics; genome annotation; genome wide association study; human disease; insight; large scale data; lens; synthetic biology; trait

PROJECT SUMMARY The human genome contains the structural and operational instructions for living cells, yet exactly what these instructions are and how they are utilized and encoded in the primary genomic sequence is poorly understood. Arguably the only well-understood portions of the genome are protein-coding regions, which make up less than 2% of the genome. It has become increasingly clear that the non-coding genome encodes vast numbers of regulatory elements important for controlling gene expression levels in a cell type specific manner. Moreover, the overwhelming majority of disease- and trait-associated variants identified by genome-wide association studies (GWAS) lie in non-coding regions of the genome, and are strongly enriched in regulatory elements. Despite this clear relevance, we still lack a complete understanding of the global organizing principles of the regulatory genome, such as how regulatory elements are distributed across the genome, what their occurrence patterns are across cell types, and how they are encoded in the genomic sequence. We hypothesize that the main reason for our limited understanding is not lack of data, but that most data sets are generated and ultimately analyzed in isolation, limiting their full potential. To further our understanding of the organizing principles of the regulatory genome, it is therefore essential to take an ​en masse approach to data analysis, exploiting the dynamics across large numbers of observations. In this project, we will use this notion to develop methods for defining the first comprehensive and pragmatically useful human regulatory genome annotation based on the coordinated occurrence patterns of regulatory elements across hundreds of cell types and states. Beyond individual elements, we will define multi-kilobase domains of shared regulatory activity, which will shed light on the regulatory landscapes around genes and higher-order regulatory domains. In addition, we will integrate regulatory annotations with orthogonal information based on functional genomics chromatin state data to arrive at a rich composite view of the regulatory genome. Lastly, we will develop the first fully data-driven system for designing and validating context-specific synthetic regulatory elements. We anticipate that our results will provide a new lens on the human regulatory genome, which will open up new research avenues in the areas of systems and synthetic biology, ultimately contributing to the understanding and treatment of human disease. We are determined to provide the genomics community with pragmatically useful regulatory genome annotations and tools to utilize these resources.

项目摘要 人类基因组包含活细胞的结构和操作指令，但这些指令是什么？ 指令是什么以及它们如何在初级基因组序列中被利用和编码，人们知之甚少。 可以说，基因组中唯一被很好理解的部分是蛋白质编码区，它占不到 基因组的2%。越来越清楚的是，非编码基因组编码大量的 对于以细胞类型特异性方式控制基因表达水平重要的调节元件。此外，委员会认为， 通过全基因组关联鉴定的绝大多数疾病和性状相关变异 研究（GWAS）位于基因组的非编码区，并且强烈富集调节元件。 尽管有这种明显的相关性，但我们仍然缺乏对联合国全球组织原则的全面了解。 调控基因组，如调控元件如何分布在基因组中，它们的出现 模式是跨细胞类型的，以及它们如何在基因组序列中编码。我们假设 我们理解有限的主要原因不是缺乏数据，而是大多数数据集都是生成的， 最终被孤立地分析，限制了它们的全部潜力。为了进一步了解组织 根据调控基因组的原则，因此必须采取全面的方法进行数据分析， 利用大量观测数据的动态性。在这个项目中，我们将使用这个概念来 开发定义第一个全面和实用的人类调控基因组的方法 基于数百种细胞类型中调控元件的协调出现模式的注释 和国家。除了个别元素，我们将定义共享的调节活性的多个酶域， 这将揭示基因和高阶调控域周围的调控景观。在 此外，我们将整合调控注释与正交信息的基础上功能基因组学 染色质状态数据，以达到丰富的复合视图的调控基因组。最后，我们将开发 第一个完全数据驱动的系统，用于设计和验证特定环境的合成调控元件。我们 我预计我们的研究结果将为人类调控基因组提供一个新的透镜，这将开辟新的 系统和合成生物学领域的研究途径，最终有助于理解 治疗人类疾病。我们决心以务实的方式为基因组学界提供 有用的调控基因组注释和工具来利用这些资源。