NIH Research Festival
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Identifying Cell-Specific Enhancer Loops and Their Impact on Transcription Activities in Donor Pancreas Tissues: Implications for Gene Regulatory Mechanisms and Therapeutics
– Poster session IV
2:30 – 4:00 p.m.
FAES Terrace
NCI
GEN-11
Authors
- W Zhang
- Y Liu
- M Bergman
- H Jang
- R Nussinov
Abstract
This study aims to identify enhancer loops in donor pancreas tissues by performing ATAC-seq and Hi-ChIP on purified major cell types. We transformed these loops into networks, where nodes denote looping regions and edges denote interactions. We further simplified EP networks to a collection of EP trees, each consisting of a root promoter and its associated enhancer nodes. Through annotation of the EP trees with genomic data (accessibility, interaction frequency, transcripts of root promoters), we observed a strong correlation between enhancer accessibility and interaction frequency within EP trees. This relationship provides a comprehensive measure of enhancer activity on the corresponding promoter. Moreover, cell-specific promoters have unique EP trees, indicating that enhancer activities are associated with promoter activities in a cell-type specific manner.
To validate this finding, CRISPR-perturbation and RNA-FISH were performed in donor tissues at PCSK1, a beta cell-specific gene. We targeted two enhancers with beta-specific activities based on EP tree analysis, and observed the effect on PCSK1 promoter specifically in beta cells but not in exocrine cells where PCSK1 is inactive. In our initial simulation analysis, we were able to identify redundant loops that are likely artifact of crosslinking. The redundant loops (~2%) were removed to help simplify EP tree structure and reduce ambiguity in assessing enhancers impact on root promoter. Our study will provide guidance for prioritizing critical enhancers to understand gene regulatory mechanisms controlling pancreatic cell identity and function, which could lead to the development of therapeutics for pancreatic diseases.
Scientific Focus Area: Genetics and Genomics
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