title: Bayesian integration of genetics and epigenetics detects causal regulatory SNPs underlying expression variability.
abstract: The standard expression quantitative trait loci (eQTL) detects polymorphisms associated with gene expression without revealing causality. We introduce a coupled Bayesian regression approach--eQTeL, which leverages epigenetic data to estimate regulatory and gene interaction potential, and identifies combination of regulatory single-nucleotide polymorphisms (SNPs) that explain the gene expression variance. On human heart data, eQTeL not only explains a significantly greater proportion of expression variance but also predicts gene expression more accurately than other methods. Based on realistic simulated data, we demonstrate that eQTeL accurately detects causal regulatory SNPs, including those with small effect sizes. Using various functional data, we show that SNPs detected by eQTeL are enriched for allele-specific protein binding and histone modifications, which potentially disrupt binding of core cardiac transcription factors and are spatially proximal to their target. eQTeL SNPs capture a substantial proportion of genetic determinants of expression variance and we estimate that 58% of these SNPs are putatively causal.
authors.affiliation: Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland 20742, USA.
authors.forename: Avinash
authors.identifier: http://orcid.org/0000-0002-2193-6276
authors.initials: A
authors.lastname: Das
authors.affiliation: Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104-5159, USA.
authors.forename: Michael
authors.initials: M
authors.lastname: Morley
authors.affiliation: Department of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, Cleveland, Ohio 44195, USA.
authors.forename: Christine S
authors.initials: CS
authors.lastname: Moravec
authors.affiliation: Department of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, Cleveland, Ohio 44195, USA.
authors.forename: W H W
authors.initials: WH
authors.lastname: Tang
authors.affiliation: The Childrens Hospital of Philadelphia, Philadelphia, Pennsylvania 19104-5159, USA.
authors.forename: Hakon
authors.initials: H
authors.lastname: Hakonarson
authors.affiliation: Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104-5159, USA.
authors.forename: Kenneth B
authors.initials: KB
authors.lastname: Margulies
authors.affiliation: Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104-5159, USA.
authors.forename: Thomas P
authors.initials: TP
authors.lastname: Cappola
authors.affiliation: The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104-6340, USA.
authors.forename: Shane
authors.initials: S
authors.lastname: Jensen
authors.affiliation: Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland 20742, USA.
authors.forename: Sridhar
authors.initials: S
authors.lastname: Hannenhalli
mesh_terms: D001499:Bayes Theorem; D003851:Deoxyribonucleases / Q000378:metabolism; D057890:Epigenomics; D015870:Gene Expression; D006801:Humans; D008957:Models, Genetic; D009206:Myocardium / Q000378:metabolism; D020641:Polymorphism, Single Nucleotide; D040641:Quantitative Trait Loci; D014157:Transcription Factors / Q000378:metabolism
chemical_list: D014157:Transcription Factors; D003851:Deoxyribonucleases