How tiny DNA differences change gene control in human cells over time
Defining causal roles of genomic variants on gene regulatory networks with spatiotemporally-resolved single-cell multiomics
This project looks at how small differences in people’s DNA change the way genes are turned on and off in human-derived cells to help people with genetic conditions.
Quick facts
| Grant type | U01 cooperative agreement |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Pennsylvania NIH-funded |
| Lab location | 1 site (Philadelphia, United States) |
| Project ID | NIH-11109638 on NIH RePORTER |
What this research studies
Researchers will use human induced pluripotent stem cells (cells reprogrammed from people’s tissues) and follow individual cells over time while measuring multiple molecular signals to see how DNA differences alter gene control. They will combine time-resolved single-cell multi-omics (measuring RNA, chromatin accessibility, and other layers in single cells) with large-scale targeted perturbations to test cause-effect relationships. Computer models and machine learning will be used to predict how variants change gene regulatory networks, and experiments will validate important predictions. The goal is to create maps linking specific noncoding DNA changes to altered cellular behavior.
Who could benefit from this research
Good fit: People who can donate blood or other tissue samples, especially those with known genetic variants or inherited conditions, would be most relevant for contributing to this work.
Not a fit: Patients seeking immediate symptom relief or direct treatment are unlikely to benefit directly, because this is lab-based research using cells and computer models rather than a clinical therapy.
Why it matters
Potential benefit: If successful, this work could reveal which specific DNA changes drive disease processes and point to new targets for diagnostics or future treatments.
How similar studies have performed: Laboratory studies using single-cell and hiPSC systems have begun mapping gene regulation, but combining time-resolved multi-omics, large-scale variant perturbations, and predictive machine learning at this scale is relatively new.
Where this research is happening
Philadelphia, United States
- University of Pennsylvania — Philadelphia, United States (Active)
Researchers
- Principal investigator: Wu, Hao — University of Pennsylvania
- Study coordinator: Wu, Hao
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.