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Finding potential cis-regulatory loci using allele-specific chromatin accessibility as weights in a kernel-based variance component test

Overview of attention for article published in BMC Proceedings, October 2016
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Title
Finding potential cis-regulatory loci using allele-specific chromatin accessibility as weights in a kernel-based variance component test
Published in
BMC Proceedings, October 2016
DOI 10.1186/s12919-016-0013-1
Pubmed ID
Authors

Juan Manuel Peralta, Marcio Almeida, Lawrence J. Abraham, Eric Moses, John Blangero

Abstract

We present a novel approach to detect potential cis-acting regulatory loci that combines the functional potential, an empirical DNase-seq based estimate of the allele-specificity of DNase-I hypersensitivity sites, with kernel-based variance component association analyses against expression phenotypes. To test our method we used public ENCODE whole genome DNase-I sequencing data, from a single sample, to estimate the functional potentials of the subset of 10,552 noncoding heterozygous single-nucleotide polymorphisms (SNPs) that were also present in the Genetic Analysis Workshop 19 (GAW19) family-based data set. We then built two covariance kernels, one nonweighted and one weighted by the functional potentials, and conducted kernel-based variance component association analyses against the 20,527 transcript expression phenotypes in the GAW19 family-based data set. We found signals of potential cis-regulatory effects, that surpassed the Bonferroni significance threshold, for ten transcripts. Stepwise removal of the cis-located SNPs from the weighted kernel lead to the disappearance of the association signal from our top transcript hit. We found compelling evidence of allele-specific cis-regulation for four transcripts using both kernels, and our results agree with previous research that suggests the involvement of specific cis-located variants in the regulation of their neighboring gene.

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Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 40%
Professor 1 20%
Student > Ph. D. Student 1 20%
Student > Master 1 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 3 60%
Nursing and Health Professions 1 20%
Unknown 1 20%