# Decoding genome function with DNA methylation and human phenome data

> **NIH NIH R01** · VANDERBILT UNIVERSITY · 2022 · $390,221

## Abstract

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.

## Key facts

- **NIH application ID:** 10501273
- **Project number:** 1R01GM147078-01
- **Recipient organization:** VANDERBILT UNIVERSITY
- **Principal Investigator:** Emily Hodges
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $390,221
- **Award type:** 1
- **Project period:** 2022-08-01 → 2027-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10501273

## Citation

> US National Institutes of Health, RePORTER application 10501273, Decoding genome function with DNA methylation and human phenome data (1R01GM147078-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10501273. Licensed CC0.

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