Decoding genome function with DNA methylation and human phenome data

项目总结 DNA甲基化是基因组功能的重要中介。但考虑到流行和分布 在整个基因组的甲基化位点中，DNA甲基化究竟是如何驱动细胞表型的尚不清楚。 尽管哺乳动物基因组高度甲基化，但低甲基化热点散布在非 编码区，并经常与开放染色质和其他基因调控标志重合。脱氧核糖核酸 甲基化被认为是对转录的抑制，基因调控元件被认为需要 去甲基化促进谱系特定基因的转录。因此，低甲基化区域(HMR) 分化细胞聚焦过去或现在转录因子占据的区域，标记关键基因 涉及谱系指定(细胞历史)或细胞类型特定基因调控的调控元件。近期 我们实验室的工作比较了不同细胞类型的甲基化情况，表明HMR模式是 对细胞表型的高度预测性。此外，我们还发现细胞类型的特异性HMR被富集化 寻找与特定临床表型相关的遗传变异。总而言之，这些数据表明HMR提供了重要的 基因组功能的上下文信息，当与人类特征数据相结合时，HMR提供了强大的 将基因类型与表型联系起来的手段。本建议的目标是了解功能 细胞类型和谱系特异性HMR的意义及其与基因和细胞的因果关系 表型。我们认为细胞型必需的HMR含有与细胞类型相关的遗传变异。 表型。我们进一步提出，通过理解这种关系，我们将发现新的低甲基化- 依赖的基因调控关系，对正常的细胞身份和功能至关重要。我们将表演 不同细胞类型的比较DNA甲基化图谱以识别细胞特异性HMR。澄清HMR 功能，我们将应用一种无偏见的、尖端的遗传方法，它利用人类群体遗传学将 记录在电子健康记录(EHR)中的HMR基因类型与人类特征的关系，这是 任何模式生物的表型条件。同时，我们将探索HMR定义的功能活动 使用我们实验室开发的一种强大的多组学方法来分离驱动HMR的基因组序列 特定的单元格上下文。最后，我们将使用表观基因组编辑来理解低甲基化的重要性 关于当地的基因组调控。这种多层次的方法将检验细胞类型和谱系特异性的假设 HMRs是连接基因组和物候组的关键元件。最终，这些研究将建立一个 理解DNA甲基化如何连接基因组和 揭示了重要的基因调控原则，这些原则对于理解为什么表观遗传是必不可少的 不稳定会导致特定的疾病后果。

PROJECT SUMMARY DNA methylation is an essential mediator of genome function. But considering the prevalence and distribution of sites of methylation across the genome, exactly how DNA methylation drives cellular phenotype is unclear. Although mammalian genomes are highly methylated, hypomethylated hotspots are scattered throughout non- coding regions and frequently coincide with open chromatin and other gene regulatory landmarks. DNA methylation is considered repressive to transcription, and gene regulatory elements are thought to require demethylation to promote transcription of lineage-specifying genes. Thus, hypomethylated regions (HMRs) of differentiated cells spotlight regions of past or present transcription factor occupancy, flagging key gene regulatory elements involved in lineage specification (cell history) or cell-type specific gene regulation. Recent work from our lab comparing methylation profiles across diverse cell-types demonstrates that HMR patterns are highly predictive of cellular phenotypes. Moreover, we have discovered that cell-type specific HMRs are enriched for genetic variants linked to specific clinical phenotypes. Together these data suggest HMRs provide important contextual information for genome function, and when combined with human trait data, HMRs provide a powerful means to connect genotypes to phenotypes. The objective of this proposal is to understand the functional significance of cell-type and lineage specific HMRs and their causal relationship with genes and cellular phenotypes. We propose that cell-type essential HMRs harbor genetic variants linked to cell-type-related phenotypes. We further propose that, by understanding this relationship, we will uncover new hypomethylation- dependent gene regulatory relationships that are critical for normal cell identity and function. We will perform comparative DNA methylation profiling of diverse cell types to identify cell specific HMRs. To elucidate HMR function, we will apply an unbiased, cutting-edge genetic approach that uses human population genetics to link HMR genotypes to human traits recorded in the electronic health record (EHR), the most extensive repository of phenotypic conditions of any model organism. In parallel we will probe the functional activities of HMR-defined genomic sequences using a powerful, multi-omic approach developed by our lab to isolate “driver” HMRs in specific cell contexts. Finally, we will use epigenome editing to understand the importance of hypomethylation on local genome regulation. This multi-level approach will test the hypothesis that cell-type and lineage specific HMRs are critical elements bridging genomes to phenomes. Ultimately, these studies will establish a fundamentally new way to understand how DNA methylation bridges the connection between genomes and phenomes, revealing important gene regulatory principles that are essential to understanding why epigenetic instability leads to specific disease outcomes.