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Computational Analysis of Next Generation Sequencing Data Predicts Potential Sources of Phenotypic Variation in Human Glucocorticoid Signaling
Author(s) -
Ryan Sean M.,
Forst Thomas M.,
Martz Flora G.,
Murphy Patrick J. M.
Publication year - 2016
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.30.1_supplement.818.2
Subject(s) - nonsynonymous substitution , biology , phenotype , genetics , single nucleotide polymorphism , gene , glucocorticoid receptor , candidate gene , glucocorticoid , copy number variation , genetic variation , computational biology , genotype , genome , immunology
Genetic differences and the complexity of protein‐protein interactions affecting intracellular hsp90‐mediated glucocorticoid receptor (GR) signaling cause substantial phenotypic variation and impact an individual's response to glucocorticoids. The goal of this study was to identify candidate causal variants and single nucleotide polymorphisms (SNPs) correlated with a previously observed phenotypic variation in in glucocorticoid response. A newly developed computer program was used to analyze whole exome sequencing data from leukocytes of participants with similar demographic profiles yet distinct glucocorticoid response phenotypes. Utilizing user‐defined arguments, identified mutations were filtered to homozygous nonsynonymous SNPs, reducing the total number of candidate casual variants to <2% of the initial total mutation count of 384,889 unique variants. From this number of variants detected among all participants, <500 (<0.15%) were nonsynonymous mutations shared exclusively among those identified as possessing the negative glucocorticoid response phenotype. A subset of these gene mutations were clustered, resulting in translated products with known protein‐protein interactions and identified using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. These data indicate a select group of candidate causal gene variants (<200) could be detected and provide a quantitative approach to reduction in preliminary loci examination for causal variance of glucocorticoid phenotypic response.