# Elucidating human beta cell transcriptional regulome with low-input genomic technologies

> **NIH NIH R01** · CASE WESTERN RESERVE UNIVERSITY · 2021 · $442,685

## Abstract

Genetic studies have revealed numerous non-coding sequence variants associated with diabetes
or obesity risk. Generating reference 3D epigenome data in in key metabolic cell or tissue types, such as
human pancreatic β cell, is therefore very important for the understanding of disease etiology.
Conventional genomic methods to study transcriptional regulation include RNA-seq and ChIP-seq, for
the mapping of transcriptome and epigenome, respectively. These technologies typically require ~1
million cells per assay. Hi-C is currently the most popular method to map the 3D genome organization in
an unbiased fashion, but tens of millions cells are required to achieve kilobase resolution 3D genome
analysis. On the other hand, the β cell research community is relying on islet samples from deceased
donors, which are precious and very expensive. Low-input technologies are therefore essential for β cell
genomic studies. The overall goal of this project is to combine several state-of-art single-cell and low-
input genomic technologies to systematically characterize the β cell 3D enhancer regulome from a cohort
of 40 fresh human islet samples; some key technologies are the original inventions from the laboratories
of our team. In aim 1, we will use a massively parallel single cell RNA-seq method (Drop-seq) to generate
a comprehensive dataset of single islet cell transcriptome, and simultaneously use a low-input
ChIPmentation method to map enhancers and promoters from a cohort of 40 human islet donors. This
will lead to the identification of diabetes and obesity signature genes and variable enhancer loci (VELs)
correlated with disease status. In aim 2, we will map the human β cell 3D genome at kilobase resolution
using a highly efficient easy Hi-C (eHi-C) method. The map will reveal all the interactions between
individual enhancers and promoters. In aim 3, we will for the first time perform an in-depth study of the
3D regulome at the human INS locus, and quantify the activity of all enhancers near INS using a
haplotype-resolved human cell line. We will also test a hypothesis that MAU2-NIPBL cohesin loading
complex may regulate insulin gene expressions through mediating enhancer-promoter DNA looping at
this locus. Finally, we will use a novel high-throughput Mosaic-seq method to validation the in vivo activity
of dozens of β cell enhancers at single cell level. This comprehensive 3D regulome data will provide a
key resource for the understanding of the functions of non-coding genome in T2D or obesity.

## Key facts

- **NIH application ID:** 10159254
- **Project number:** 5R01DK113185-04
- **Recipient organization:** CASE WESTERN RESERVE UNIVERSITY
- **Principal Investigator:** Yan Li
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $442,685
- **Award type:** 5
- **Project period:** 2018-07-01 → 2023-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10159254

## Citation

> US National Institutes of Health, RePORTER application 10159254, Elucidating human beta cell transcriptional regulome with low-input genomic technologies (5R01DK113185-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10159254. Licensed CC0.

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