Genetic regulatory signatures underlying islet gene expression and type 2 diabetes

Arushi Varshney(University of Michigan), Laura J. Scott(University of Michigan), Ryan Welch(University of Michigan), Michael R. Erdos(National Human Genome Research Institute), Peter S. Chines(National Human Genome Research Institute), Narisu Narisu(National Human Genome Research Institute), Ricardo D’Oliveira Albanus(University of Michigan), Peter Orchard(University of Michigan), Brooke N. Wolford(University of Michigan), Romy Kursawe(Jackson Laboratory), Swarooparani Vadlamudi(University of North Carolina at Chapel Hill), Maren E. Cannon(University of North Carolina at Chapel Hill), John P. Didion(National Human Genome Research Institute), John Hensley(University of Michigan), Anthony Kirilusha(National Human Genome Research Institute), NISC Comparative Sequencing Program(National Human Genome Research Institute), Lori L. Bonnycastle(European Bioinformatics Institute), D. Leland Taylor(University of Southern California), Richard M. Watanabe(University of North Carolina at Chapel Hill), Karen L. Mohlke(University of North Carolina at Chapel Hill), Michael Boehnke(University of Michigan), Francis S. Collins(University of Michigan), Stephen C.J. Parker(University of Michigan), Michael L. Stitzel(Jackson Laboratory), Beatrice B. Barnabas, Gerard G. Bouffard, Shelise Brooks, Holly Coleman, Lyudmila Dekhtyar, Xiaobin Guan, Joel Han, Shi-ling Ho, Richelle Legaspi, Quino Maduro, Catherine A. Masiello, Jennifer C. McDowell, Casandra Montemayor, James C. Mullikin, Morgan Park, Nancy L. Riebow, Jessica D. Rosarda, Karen Schandler, Brian J. Schmidt, Christina Sison, Raymond Arthur Smith, Sirintorn Stantripop, James W. Thomas, Pamela J. Thomas, Meghana Vemulapalli, Alice Young
Proceedings of the National Academy of Sciences
February 13, 2017
10.1073/pnas.1621192114
Cited by 244Open Access
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Abstract

-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.

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