School of Medicine Publications and Presentations
Document Type
Conference Proceeding
Publication Date
10-18-2016
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.
Recommended Citation
Peralta, J.M., Almeida, M., Abraham, L.J. et al. Finding potential cis-regulatory loci using allele-specific chromatin accessibility as weights in a kernel-based variance component test. BMC Proc 10 (Suppl 7), 50 (2016). https://doi.org/10.1186/s12919-016-0013-1
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Publication Title
BMC Proc
DOI
10.1186/s12919-016-0013-1
Academic Level
faculty
Mentor/PI Department
Office of Human Genetics
Comments
Copyright © 2016, The Author(s).