Decoding genome function with DNA methylation and human phenome data

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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.