# Quantifying the genetic diversity of human regulatory element activity

> **NIH NIH R01** · DUKE UNIVERSITY · 2021 · $764,842

## Abstract

Understanding the genetic causes of human disease has immense potential to benefit human
health. The human genetics community has devoted tremendous resources to identifying those
causes, including, most recently, whole genome sequencing of patient cohorts. Those studies
have found genetic variation in non-coding regions of the genome to be most often associated
with diseases and drug responses. Unfortunately, since the effects of genetic variation on gene
regulation remain poorly understood and difficult to study at the genome-wide scale, the full
benefit of most of those studies has yet to be realized. Our long-term goal is to understand how
non-coding genetic variants act through gene regulatory elements to influence phenotypes. The
objective of this proposal, a step towards that long-term goal, is to develop a platform of
empirical and statistical methods to reliably and systematically determine the regulatory
mechanisms underlying human traits and diseases. Specifically, in Aim 1, we will use high-
throughput reporter assays to quantify the effects of millions of human genetic variants on
regulatory element activity. Those variants will represent diverse human ancestries, and will cover
over 60% of all regions associated with a trait or disease via GWAS. The outcome will be the
most extensive catalog of human regulatory variation every created. In Aim 2, we will develop
new technologies to systematically relate those changes in regulatory element activity to changes
in gene expression. That technology will combine our previous work developing CRISPR-Cas9-
based epigenome editing screens with targeted single-cell RNA-seq. In Aim 3 we will develop
statistical analyses to integrate the effects of regulatory variants to infer changes in gene
expression and differences in phenotypes between individuals. The resulting method will be
analogous to gene based association tests, but for the noncoding genome. The expected
outcomes of this project are (i) dramatically improved ability to establish mechanisms underlying
non-coding associations with human traits and diseases; (ii) better understanding of the genetic
architecture of regulatory element activity and gene regulation that will guide the design and
interpretation of future genetic association studies; and (iii) novel reagents, protocols, and
software that other labs can use to complete similar investigations of their own model systems of
interest. Taken together, we expect that this project will be a major step towards fully realizing the
potential of genome wide and whole genome association studies.

## Key facts

- **NIH application ID:** 10150923
- **Project number:** 5R01HG010741-03
- **Recipient organization:** DUKE UNIVERSITY
- **Principal Investigator:** ANDREW S ALLEN
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $764,842
- **Award type:** 5
- **Project period:** 2019-07-29 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10150923

## Citation

> US National Institutes of Health, RePORTER application 10150923, Quantifying the genetic diversity of human regulatory element activity (5R01HG010741-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10150923. Licensed CC0.

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