# Statistical and high-throughput models of enhancer function and evolution

> **NIH NIH R01** · HARVARD UNIVERSITY · 2022 · $555,652

## Abstract

PROJECT SUMMARY
Enhancers are an important class of noncoding loci regulating gene expression and play important roles in
modulating diverse phenotypes and disease states. However, our understanding of the role of enhancers in
phenotypic evolution is limited and we lack a detailed understanding of the relationship between sequence
change within and between species, epigenetic states and variation in enhancer function. Moreover, we have
few statistical models that allow researchers to connect evolutionary changes in enhancer sequences within
and between species to phenotypic variation, and we often cannot unambiguously determine the causes of
observed changes in evolutionary rate of enhancers along lineages. Finally, most studies of enhancer
evolution thus far have studied only small numbers of enhancers and genome-wide assays of enhancer
variation and function are rare. Here we propose to develop statistical models linking phylogenetic patterns of
enhancer evolution with phenotypic variation between species, and to leverage within-species variation across
multiple species – “comparative population genomics” – to disentangle the sources of rate changes observed
in enhancers across species. We will also functionally test diverse enhancers on a large-scale, using the
developing fore- and hindlimb of volant and flightless birds as a model of development and gene expression.
Specifically, in Aim 1 we will extend a recently developed Bayesian phylogenetic model for detecting rate
changes in noncoding DNA, phyloAcc, to improve its biological realism by incorporating stochastic gene tree
heterogeneity and the ability to associate sequence change with both binary and continuous traits. Building on
a novel data set of comparative gene expression and chromatin states across multiple species and
developmental stages, we will also develop methods to associate genome-wide variation in chromatin states
between species with binary and continuous traits. In Aim 2 we will develop additional statistical models to
leverage information from sequence variation within species to better understand the evolutionary forces
contributing to rate variation in noncoding DNA observed between species. The models developed in Aims 1
and 2 will be refined and made available to the broader community in a user-friendly format for use on diverse
systems and species. In Aim 3 we will functionally validate large numbers of candidate enhancers identified in
Aims 1 and 2 as having evolved new functions or found in altered chromatin states in the developing fore- and
hindlimb of volant and flightless birds. Using high-throughput assays in chicken, emu and other birds we will
study the relationship between within- and between-species sequence variation of enhancers and their ability
to drive gene expression. Together these aims will provide a number of tools that will benefit the community of
researchers using comparative genomics to understand links between genotype and phenotype, and wi...

## Key facts

- **NIH application ID:** 10357741
- **Project number:** 5R01HG011485-02
- **Recipient organization:** HARVARD UNIVERSITY
- **Principal Investigator:** SCOTT V. EDWARDS
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $555,652
- **Award type:** 5
- **Project period:** 2021-02-22 → 2025-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10357741

## Citation

> US National Institutes of Health, RePORTER application 10357741, Statistical and high-throughput models of enhancer function and evolution (5R01HG011485-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10357741. Licensed CC0.

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