Decoding genome function with DNA methylation and human phenome data

项目摘要 DNA甲基化是基因组功能的重要介质。但考虑到 尽管DNA甲基化在整个基因组中的位点数量很少，但DNA甲基化究竟如何驱动细胞表型尚不清楚。 虽然哺乳动物基因组高度甲基化，但低甲基化热点分散在整个非甲基化区域。 编码区，并经常与开放的染色质和其他基因调控标志相一致。DNA 甲基化被认为是抑制转录的，基因调控元件被认为需要 去甲基化以促进谱系特异性基因的转录。因此，低甲基化区域（HMR） 分化的细胞聚焦过去或现在转录因子占据的区域，标记关键基因 涉及谱系特化（细胞历史）或细胞类型特异性基因调控的调控元件。最近 我们实验室的工作比较了不同细胞类型的甲基化谱，表明HMR模式是 高度预测细胞表型。此外，我们已经发现，细胞类型特异性HMR被富集， 与特定临床表型相关的遗传变异。这些数据共同表明，HMR提供了重要的 基因组功能的背景信息，当与人类性状数据相结合时，HMR提供了一个强大的 将基因型与表型联系起来。本建议的目的是了解功能 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HMR携带与细胞型相关的遗传变异。 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细胞的身份和功能至关重要。我们将执行 比较不同细胞类型的DNA甲基化谱以鉴定细胞特异性HMR。阐明HMR 功能，我们将采用一种公正的，尖端的遗传方法，使用人类群体遗传学联系 HMR基因型与人类特征的关系记录在电子健康记录（EHR）中， 任何模式生物的表型条件。同时，我们将探讨HMR定义的功能活动， 基因组序列使用一个强大的，多组学的方法开发了我们的实验室分离“驱动”HMR， 特定的细胞背景。最后，我们将使用表观基因组编辑来了解低甲基化的重要性。 基因组调控这种多层次的方法将测试假设，细胞类型和谱系特异性 HMR是将基因组连接到表型组的关键元件。最终，这些研究将建立 这是一种全新的方式来了解DNA甲基化是如何连接基因组和 表型，揭示了重要的基因调控原则，这是必不可少的理解为什么表观遗传 不稳定导致特定的疾病结果。

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.