High-throughput functional dissection of noncoding SNPs with biased allelic enhancer activity for insulin resistance-relevant phenotypes

  • Yuan Yuan Duan
  • , Xiao Feng Chen
  • , Ren Jie Zhu
  • , Ying Ying Jia
  • , Xiao Ting Huang
  • , Meng Zhang
  • , Ning Yang
  • , Shan Shan Dong
  • , Mengqi Zeng
  • , Zhihui Feng
  • , Dong Li Zhu
  • , Hao Wu
  • , Feng Jiang
  • , Wei Shi
  • , Wei Xin Hu
  • , Xin Ke
  • , Hao Chen
  • , Yunlong Liu
  • , Rui Hua Jing
  • , Yan Guo
  • Meng Li, Tie Lin Yang

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Most of the single-nucleotide polymorphisms (SNPs) associated with insulin resistance (IR)-relevant phenotypes by genome-wide association studies (GWASs) are located in noncoding regions, complicating their functional interpretation. Here, we utilized an adapted STARR-seq to evaluate the regulatory activities of 5,987 noncoding SNPs associated with IR-relevant phenotypes. We identified 876 SNPs with biased allelic enhancer activity effects (baaSNPs) across 133 loci in three IR-relevant cell lines (HepG2, preadipocyte, and A673), which showed pervasive cell specificity and significant enrichment for cell-specific open chromatin regions or enhancer-indicative markers (H3K4me1, H3K27ac). Further functional characterization suggested several transcription factors (TFs) with preferential allelic binding to baaSNPs. We also incorporated multi-omics data to prioritize 102 candidate regulatory target genes for baaSNPs and revealed prevalent long-range regulatory effects and cell-specific IR-relevant biological functional enrichment on them. Specifically, we experimentally verified the distal regulatory mechanism at IRS1 locus, in which rs952227-A reinforces IRS1 expression by long-range chromatin interaction and preferential binding to the transcription factor HOXC6 to augment the enhancer activity. Finally, based on our STARR-seq screening data, we predicted the enhancer activity of 227,343 noncoding SNPs associated with IR-relevant phenotypes (fasting insulin adjusted for BMI, HDL cholesterol, and triglycerides) from the largest available GWAS summary statistics. We further provided an open resource (http://www.bigc.online/fnSNP-IR) for better understanding genetic regulatory mechanisms of IR-relevant phenotypes.

Original languageEnglish
Pages (from-to)1266-1288
Number of pages23
JournalAmerican Journal of Human Genetics
Volume110
Issue number8
DOIs
StatePublished - 3 Aug 2023
Externally publishedYes

Keywords

  • GWAS
  • IRS1
  • STARR-seq
  • biased allelic enhancer activity effect
  • genetic regulatory mechanisms
  • insulin resistance
  • noncoding SNPs
  • rs952227

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