# The Evolution of Gene Regulation and Human Disease

> **NIH NIH R35** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2022 · $402,136

## Abstract

PROJECT SUMMARY
Genetic variants that disrupt the functionality of regulatory sequences, and thereby alter gene expression
levels, are major contributors to both evolutionary divergence between species and differences in risk for
complex disease among humans. However, due to the complexity of the gene regulatory programs encoded in
mammalian genomes and their rapid turnover between species, evaluating the function of non-protein-coding
mutations is challenging. This is a major roadblock to tracing the evolution of human-specific biology. In
addition, since the majority of disease-associated variants are non-coding, it impairs our ability to map the
genetics of complex disease.
 The long-term mission of my lab is to interpret the complex gene regulatory programs encoded in the
human genome and accurately model the effects of genetic mutations to these elements on phenotypes
relevant to disease and human evolution. We work toward these goals by integrating cutting-edge machine
learning, statistical modeling of evolution, and the analysis of genotypes and phenotypes from large-scale
clinical biobanks. In particular, my lab is uniquely well positioned to build on our previous work to address the
following fundamental questions:
 1. How have evolutionary transitions on the human-lineage modified the genome—in particular gene
 regulatory programs—to produce human-specific biology? And how do these modifications relate to
 human-specific disease risk?
 2. What are the combinatorial rules underlying how TF binding patterns specify precise control of gene
 regulation? And how do these gene regulatory “programs” evolve between species?
 3. How do genetic and epigenetic mechanisms interact to specify the dynamic gene regulatory programs
 that drive cellular development? And how are these programs perturbed in disease?
 4. How can we interpret non-protein-coding mutations identified in patient genomes to inform treatment
 and preventative care?
Our work will produce much-needed methods for understanding the effects of mutations to gene regulatory
regions and identify mutations responsible for differences in disease risk between human populations.

## Key facts

- **NIH application ID:** 10460911
- **Project number:** 5R35GM127087-06
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** John Anthony Capra
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $402,136
- **Award type:** 5
- **Project period:** 2018-04-01 → 2024-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10460911

## Citation

> US National Institutes of Health, RePORTER application 10460911, The Evolution of Gene Regulation and Human Disease (5R35GM127087-06). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10460911. Licensed CC0.

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