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Finding potential cis-regulatory loci using allele-specific chromatin accessibility as weights in a kernel-based variance component test.
Peralta, Juan Manuel; Almeida, Marcio; Abraham, Lawrence J; Moses, Eric; Blangero, John.
Affiliation
  • Peralta JM; South Texas Diabetes and Obesity Institute, University of Texas at the Rio Grande Valley, One West University Blvd., Brownsville, TX 78520 USA.
  • Almeida M; South Texas Diabetes and Obesity Institute, University of Texas at the Rio Grande Valley, One West University Blvd., Brownsville, TX 78520 USA.
  • Abraham LJ; Centre for Genetic Origins of Health and Disease, University of Western Australia, 35 Stirling Hwy, Crawley, WA 6009 Australia.
  • Moses E; Centre for Genetic Origins of Health and Disease, University of Western Australia, 35 Stirling Hwy, Crawley, WA 6009 Australia.
  • Blangero J; South Texas Diabetes and Obesity Institute, University of Texas at the Rio Grande Valley, One West University Blvd., Brownsville, TX 78520 USA ; South Texas Diabetes and Obesity Institute, University of Texas Health Science Center, 7703 Floyd Curl Drive, San Antonio, TX 78229 USA.
BMC Proc ; 10(Suppl 7): 103-108, 2016.
Article in En | MEDLINE | ID: mdl-27980619
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.

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Diagnostic_studies Language: En Journal: BMC Proc Year: 2016 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Diagnostic_studies Language: En Journal: BMC Proc Year: 2016 Document type: Article
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