# Investigating human cis-regulatory evolution with hybrid iPS cells

> **NIH NIH R01** · STANFORD UNIVERSITY · 2022 · $760,624

## Abstract

Project Summary
Despite a great deal of research, we have discovered surprisingly little about the genetic
basis of uniquely human traits—largely due to the ethical and practical considerations that
severely limit comparisons between humans and other primates. To advance this field, we
have integrated two effective approaches for studying evolution: induced pluripotent stem
(iPS) cells, and interspecific hybrids. iPS cells can be differentiated into a wide range of
cell types in vitro, circumventing many limitations of primate research, while measurement
of allele-specific gene expression in hybrids allows cis-regulatory divergence and gene
expression adaptations to be mapped genome-wide. To combine these approaches, we
have recently generated human/chimpanzee hybrid iPS cells. We propose to characterize
this powerful resource with RNA-seq and cellular phenotyping in diverse cell types,
including cardiomyocytes, motor neurons, hepatocytes, pancreatic progenitors, skeletal muscle,
retinal pigmented epithelium, and skin organoids that include dermis/epidermis, adipose,
cartilage, hair follicles, and more. Our goal is to discover and experimentally validate genes and
genetic variants that have contributed to the evolutionary origin of our species.

## Key facts

- **NIH application ID:** 10342219
- **Project number:** 1R01HG012285-01
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Hunter B Fraser
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $760,624
- **Award type:** 1
- **Project period:** 2022-05-25 → 2026-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10342219

## Citation

> US National Institutes of Health, RePORTER application 10342219, Investigating human cis-regulatory evolution with hybrid iPS cells (1R01HG012285-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10342219. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*