Identification of atrial fibrillation associated genes and functional non-coding variants

Antoinette F. Ouwerkerk, Fernanda M. Bosada, Karel Duijvenboden, Matthew C. Hill, Lindsey E. Montefiori, Koen T. Scholman, Jia Liu, Antoine A. F. Vries, Bastiaan J. Boukens, Patrick T. Ellinor, Marie José T. H. Goumans, Igor R. Efimov, Marcelo A. Nobrega, Phil Barnett, James F. Martin and Vincent M. Christoffels ()
Additional contact information
Antoinette F. Ouwerkerk: Amsterdam University Medical Centers, Academic Medical Center
Fernanda M. Bosada: Amsterdam University Medical Centers, Academic Medical Center
Karel Duijvenboden: Amsterdam University Medical Centers, Academic Medical Center
Matthew C. Hill: Program in Developmental Biology, Baylor College of Medicine
Lindsey E. Montefiori: The University of Chicago
Koen T. Scholman: Amsterdam University Medical Centers, Academic Medical Center
Jia Liu: Leiden University Medical Center, Albinusdreef 2
Antoine A. F. Vries: Leiden University Medical Center, Albinusdreef 2
Bastiaan J. Boukens: Amsterdam University Medical Centers, Academic Medical Center
Patrick T. Ellinor: Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard
Marie José T. H. Goumans: Department of Cell and Chemical Biology, Leiden University Medical Center
Igor R. Efimov: George Washington University
Marcelo A. Nobrega: The University of Chicago
Phil Barnett: Amsterdam University Medical Centers, Academic Medical Center
James F. Martin: Program in Developmental Biology, Baylor College of Medicine
Vincent M. Christoffels: Amsterdam University Medical Centers, Academic Medical Center

Nature Communications, 2019, vol. 10, issue 1, 1-14

Abstract: Abstract Disease-associated genetic variants that lie in non-coding regions found by genome-wide association studies are thought to alter the functionality of transcription regulatory elements and target gene expression. To uncover causal genetic variants, variant regulatory elements and their target genes, here we cross-reference human transcriptomic, epigenomic and chromatin conformation datasets. Of 104 genetic variant regions associated with atrial fibrillation candidate target genes are prioritized. We optimize EMERGE enhancer prediction and use accessible chromatin profiles of human atrial cardiomyocytes to more accurately predict cardiac regulatory elements and identify hundreds of sub-threshold variants that co-localize with regulatory elements. Removal of mouse homologues of atrial fibrillation-associated regions in vivo uncovers a distal regulatory region involved in Gja1 (Cx43) expression. Our analyses provide a shortlist of genes likely affected by atrial fibrillation-associated variants and provide variant regulatory elements in each region that link genetic variation and target gene regulation, helping to focus future investigations.

Date: 2019
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DOI: 10.1038/s41467-019-12721-5

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