bioRxivGenomicsPreprint
Functional characterization of thousands of type 2 diabetes-associated and chromatin-modulating variants under steady state and endoplasmic reticulum stress
Shubham KhetaniD, Susan KalesiD, Romy KursaweiD, Alexandria Jillette, Steven K. ReillyiD, Duygu UcariD, Ryan TewheyiD, Michael L. StitzeliD
Abstract
A major goal in functional genomics and complex disease genetics is to identify functional cis-regulatory elements (CREs) and single nucleotide polymorphisms (SNPs) altering CRE activity in disease-relevant cell types and environmental conditions. We tested >13,000 sequences containing each allele of 6,628 SNPs associated with altered in vivo chromatin accessibility in human islets and/or type 2 diabetes risk (T2D GWAS SNPs) for transcriptional activity in {beta} cell under steady state and endoplasmic reticulum (ER) stress conditions using the massively parallel reporter assay (MPRA). Approximately 30% (n=1,983) of putative CREs were active in at least one condition. SNP allelic effects on in vitro MPRA activity strongly correlated with their effects on in vivo islet chromatin accessibility (Pearson r=0.52), i.e., alleles associated with increased chromatin accessibility exhibited higher MPRA activity. Importantly, MPRA identified 220/2500 T2D GWAS SNPs, representing 104 distinct association signals, that significantly altered transcriptional activity in {beta} cells. This study has thus identified functional {beta} cell transcription-activating sequences with in vivo relevance, uncovered regulatory features that modulate transcriptional activity in {beta} cells under steady state and ER stress conditions, and substantially expanded the set of putative functional variants that modulate transcriptional activity in {beta} cells from thousands of genetically-linked T2D GWAS SNPs.
- organism: human
- assay: ChIP-seq
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: variant effect prediction
- research focus: benchmarking
- approach: statistical model
- Citations
- 1
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