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Proc Natl Acad Sci U S A. 2017 Feb 28;114(9):2301-2306. doi: 10.1073/pnas.1621192114. Epub 2017 Feb 13.

Genetic regulatory signatures underlying islet gene expression and type 2 diabetes.

Author information

1
Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109.
2
Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109.
3
National Human Genome Research Institute, NIH, Bethesda, MD 20892.
4
Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI 48109.
5
The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032.
6
Department of Genetics, University of North Carolina, Chapel Hill, NC 27599.
7
European Molecular Biology Laboratory, Wellcome Trust Genome Campus, European Bioinformatics Institute, Hinxton, Cambridgeshire CB10 1SD, United Kingdom.
8
Department of Preventive Medicine, University of Southern California Keck School of Medicine, Los Angeles, CA 90089.
9
Department of Physiology and Biophysics, University of Southern California Keck School of Medicine, Los Angeles, CA 90089.
10
National Human Genome Research Institute, NIH, Bethesda, MD 20892; collinsf@od.nih.gov scjp@umich.edu.
11
Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109; collinsf@od.nih.gov scjp@umich.edu.

Abstract

Genome-wide association studies (GWAS) have identified >100 independent SNPs that modulate the risk of type 2 diabetes (T2D) and related traits. However, the pathogenic mechanisms of most of these SNPs remain elusive. Here, we examined genomic, epigenomic, and transcriptomic profiles in human pancreatic islets to understand the links between genetic variation, chromatin landscape, and gene expression in the context of T2D. We first integrated genome and transcriptome variation across 112 islet samples to produce dense cis-expression quantitative trait loci (cis-eQTL) maps. Additional integration with chromatin-state maps for islets and other diverse tissue types revealed that cis-eQTLs for islet-specific genes are specifically and significantly enriched in islet stretch enhancers. High-resolution chromatin accessibility profiling using assay for transposase-accessible chromatin sequencing (ATAC-seq) in two islet samples enabled us to identify specific transcription factor (TF) footprints embedded in active regulatory elements, which are highly enriched for islet cis-eQTL. Aggregate allelic bias signatures in TF footprints enabled us de novo to reconstruct TF binding affinities genetically, which support the high-quality nature of the TF footprint predictions. Interestingly, we found that T2D GWAS loci were strikingly and specifically enriched in islet Regulatory Factor X (RFX) footprints. Remarkably, within and across independent loci, T2D risk alleles that overlap with RFX footprints uniformly disrupt the RFX motifs at high-information content positions. Together, these results suggest that common regulatory variations have shaped islet TF footprints and the transcriptome and that a confluent RFX regulatory grammar plays a significant role in the genetic component of T2D predisposition.

KEYWORDS:

chromatin; diabetes; eQTL; epigenome; footprint

PMID:
28193859
PMCID:
PMC5338551
DOI:
10.1073/pnas.1621192114
[Indexed for MEDLINE]
Free PMC Article

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