TY - JOUR
T1 - Identification of atrial fibrillation associated genes and functional non-coding variants
AU - van Ouwerkerk, Antoinette F.
AU - Bosada, Fernanda M.
AU - van Duijvenboden, Karel
AU - Hill, Matthew C.
AU - Montefiori, Lindsey E.
AU - Scholman, Koen T.
AU - Liu, Jia
AU - de Vries, Antoine A. F.
AU - Boukens, Bastiaan J.
AU - Ellinor, Patrick T.
AU - Goumans, Marie José T. H.
AU - Efimov, Igor R.
AU - Nobrega, Marcelo A.
AU - Barnett, Phil
AU - Martin, James F.
AU - Christoffels, Vincent M.
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85073561028&origin=inward
UR - https://www.ncbi.nlm.nih.gov/pubmed/31628324
U2 - https://doi.org/10.1038/s41467-019-12721-5
DO - https://doi.org/10.1038/s41467-019-12721-5
M3 - Article
C2 - 31628324
SN - 2041-1723
VL - 10
JO - Nature communications
JF - Nature communications
IS - 1
M1 - 4755
ER -