# Omics analysis of three-dimensional transcriptional regulation

> **NIH NIH R01** · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · 2022 · $65,219

## Abstract

Abstract
In this R01 proposal, we plan to use an integrative genomics (Omics) analysis to test two central hypotheses:
1) an environmental or cellular stimulus such as hormones induced distinct chromatin interacting foci such as
enhancer-enhancer looping foci play key roles in regulating cell transformed phenotype; and 2) 3D chromatin
structures play key roles in governing cell identities. The ultimate goal is to dissect the relationship between
chromatin interactions and cell identities or cellular phenotypes. Using a model system of ERα in breast
cancer, we will a) identify distinct types of ERα-regulated chromatin interacting foci including promoter-
enhancer, enhancer-enhancer and enhancer-repressor looping foci; and b) identify 3D-regulated breast cancer
cell identities and sensitive-resistant transition cell subpopulations. The successful completion of our proposed
studies will be of value to the genomics community and biologists in general, which may result in the better
understanding of the contribution of enhancer-enhancer interacting network towards functions of various
biological processes, in particular breast cancer endocrine resistance, and on how 3D chromatin structure
governs the breast cancer sensitive cell subpopulations into resistant cell subpopulations.

## Key facts

- **NIH application ID:** 10317115
- **Project number:** 5R01GM114142-06
- **Recipient organization:** UNIVERSITY OF TEXAS HLTH SCIENCE CENTER
- **Principal Investigator:** Victor Jin
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $65,219
- **Award type:** 5
- **Project period:** 2015-04-13 → 2022-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10317115

## Citation

> US National Institutes of Health, RePORTER application 10317115, Omics analysis of three-dimensional transcriptional regulation (5R01GM114142-06). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10317115. Licensed CC0.

---

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