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Discovery and validation of sub-threshold genome-wide association study loci using epigenomic signatures.

Wang X, Tucker NR, Rizki G, Mills R, Krijger PH, de Wit E, Subramanian V, Bartell E, Nguyen XX, Ye J, Leyton-Mange J, Dolmatova EV, van der Harst P, de Laat W, Ellinor PT, Newton-Cheh C, Milan DJ, Kellis M, Boyer LA - Elife (2016)

Bottom Line: We apply functional criteria to identify loci associated with QT interval that do not meet genome-wide significance and are missed by existing studies.We experimentally validate the molecular, gene-regulatory, cellular and organismal phenotypes of these sub-threshold loci, demonstrating that most sub-threshold loci have regulatory consequences and that genetic perturbation of nearby genes causes cardiac phenotypes in mouse.Our work provides a general approach for improving the detection of novel loci associated with complex human traits.

View Article: PubMed Central - PubMed

Affiliation: Department of Biology, Massachusetts Institute of Technology, Cambridge, United States.

ABSTRACT
Genetic variants identified by genome-wide association studies explain only a modest proportion of heritability, suggesting that meaningful associations lie 'hidden' below current thresholds. Here, we integrate information from association studies with epigenomic maps to demonstrate that enhancers significantly overlap known loci associated with the cardiac QT interval and QRS duration. We apply functional criteria to identify loci associated with QT interval that do not meet genome-wide significance and are missed by existing studies. We demonstrate that these 'sub-threshold' signals represent novel loci, and that epigenomic maps are effective at discriminating true biological signals from noise. We experimentally validate the molecular, gene-regulatory, cellular and organismal phenotypes of these sub-threshold loci, demonstrating that most sub-threshold loci have regulatory consequences and that genetic perturbation of nearby genes causes cardiac phenotypes in mouse. Our work provides a general approach for improving the detection of novel loci associated with complex human traits.

No MeSH data available.


Related in: MedlinePlus

DOI:http://dx.doi.org/10.7554/eLife.10557.024
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fig7: DOI:http://dx.doi.org/10.7554/eLife.10557.024

Mentions: 3) In the analysis of matched, control SNPs, gene density needs to be accounted for. We thank the reviewers for this suggestion. We now include gene density (within a surrounding +/-500kb window) as a feature to control for in sampling the background distribution of control SNPs. We observe that the same patterns of greater enrichment of QT/QRS GWAS loci overlapping cardiac enhancers persist after account for gene density (Author response image 1 adapted from Figure 1B, but consistent patterns also observed everywhere else control SNPs were sampled for a background distribution).10.7554/eLife.10557.024Author response image 1.


Discovery and validation of sub-threshold genome-wide association study loci using epigenomic signatures.

Wang X, Tucker NR, Rizki G, Mills R, Krijger PH, de Wit E, Subramanian V, Bartell E, Nguyen XX, Ye J, Leyton-Mange J, Dolmatova EV, van der Harst P, de Laat W, Ellinor PT, Newton-Cheh C, Milan DJ, Kellis M, Boyer LA - Elife (2016)

DOI:http://dx.doi.org/10.7554/eLife.10557.024
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4862755&req=5

fig7: DOI:http://dx.doi.org/10.7554/eLife.10557.024
Mentions: 3) In the analysis of matched, control SNPs, gene density needs to be accounted for. We thank the reviewers for this suggestion. We now include gene density (within a surrounding +/-500kb window) as a feature to control for in sampling the background distribution of control SNPs. We observe that the same patterns of greater enrichment of QT/QRS GWAS loci overlapping cardiac enhancers persist after account for gene density (Author response image 1 adapted from Figure 1B, but consistent patterns also observed everywhere else control SNPs were sampled for a background distribution).10.7554/eLife.10557.024Author response image 1.

Bottom Line: We apply functional criteria to identify loci associated with QT interval that do not meet genome-wide significance and are missed by existing studies.We experimentally validate the molecular, gene-regulatory, cellular and organismal phenotypes of these sub-threshold loci, demonstrating that most sub-threshold loci have regulatory consequences and that genetic perturbation of nearby genes causes cardiac phenotypes in mouse.Our work provides a general approach for improving the detection of novel loci associated with complex human traits.

View Article: PubMed Central - PubMed

Affiliation: Department of Biology, Massachusetts Institute of Technology, Cambridge, United States.

ABSTRACT
Genetic variants identified by genome-wide association studies explain only a modest proportion of heritability, suggesting that meaningful associations lie 'hidden' below current thresholds. Here, we integrate information from association studies with epigenomic maps to demonstrate that enhancers significantly overlap known loci associated with the cardiac QT interval and QRS duration. We apply functional criteria to identify loci associated with QT interval that do not meet genome-wide significance and are missed by existing studies. We demonstrate that these 'sub-threshold' signals represent novel loci, and that epigenomic maps are effective at discriminating true biological signals from noise. We experimentally validate the molecular, gene-regulatory, cellular and organismal phenotypes of these sub-threshold loci, demonstrating that most sub-threshold loci have regulatory consequences and that genetic perturbation of nearby genes causes cardiac phenotypes in mouse. Our work provides a general approach for improving the detection of novel loci associated with complex human traits.

No MeSH data available.


Related in: MedlinePlus