The genetic regulatory signature of type 2 diabetes in human skeletal muscle View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2016-06-29

AUTHORS

Laura J. Scott, Michael R. Erdos, Jeroen R. Huyghe, Ryan P. Welch, Andrew T. Beck, Brooke N. Wolford, Peter S. Chines, John P. Didion, Narisu Narisu, Heather M. Stringham, D. Leland Taylor, Anne U. Jackson, Swarooparani Vadlamudi, Lori L. Bonnycastle, Leena Kinnunen, Jouko Saramies, Jouko Sundvall, Ricardo D'Oliveira Albanus, Anna Kiseleva, John Hensley, Gregory E. Crawford, Hui Jiang, Xiaoquan Wen, Richard M. Watanabe, Timo A. Lakka, Karen L. Mohlke, Markku Laakso, Jaakko Tuomilehto, Heikki A. Koistinen, Michael Boehnke, Francis S. Collins, Stephen C. J. Parker

ABSTRACT

Type 2 diabetes (T2D) results from the combined effects of genetic and environmental factors on multiple tissues over time. Of the >100 variants associated with T2D and related traits in genome-wide association studies (GWAS), >90% occur in non-coding regions, suggesting a strong regulatory component to T2D risk. Here to understand how T2D status, metabolic traits and genetic variation influence gene expression, we analyse skeletal muscle biopsies from 271 well-phenotyped Finnish participants with glucose tolerance ranging from normal to newly diagnosed T2D. We perform high-depth strand-specific mRNA-sequencing and dense genotyping. Computational integration of these data with epigenome data, including ATAC-seq on skeletal muscle, and transcriptome data across diverse tissues reveals that the tissue-specific genetic regulatory architecture of skeletal muscle is highly enriched in muscle stretch/super enhancers, including some that overlap T2D GWAS variants. In one such example, T2D risk alleles residing in a muscle stretch/super enhancer are linked to increased expression and alternative splicing of muscle-specific isoforms of ANK1. More... »

PAGES

11764

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/ncomms11764

DOI

http://dx.doi.org/10.1038/ncomms11764

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1025776703

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/27353450


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curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/ncomms11764'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/ncomms11764'


 

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