Author
Listed:
- 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
Shenzhen University, Nanhai Ave
Netherlands Heart Institute, Holland Heart House)
- Antoine A. F. Vries
(Leiden University Medical Center, Albinusdreef 2
Netherlands Heart Institute, Holland Heart House)
- Bastiaan J. Boukens
(Amsterdam University Medical Centers, Academic Medical Center)
- Patrick T. Ellinor
(Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard
Cardiovasular Research Center, Massachusetts General Hospital
Cardiac Arrhythmia Service, Massachusetts General Hospital)
- 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
Baylor College of Medicine
Texas Heart Institute
Cardiovascular Research Institute, Baylor College of Medicine)
- Vincent M. Christoffels
(Amsterdam University Medical Centers, Academic Medical Center)
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.
Suggested Citation
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. Ellino, 2019.
"Identification of atrial fibrillation associated genes and functional non-coding variants,"
Nature Communications, Nature, vol. 10(1), pages 1-14, December.
Handle:
RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-12721-5
DOI: 10.1038/s41467-019-12721-5
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