[Show abstract][Hide abstract] ABSTRACT: Glucocorticoids (GCs) are key mediators of stress response and are widely used as pharmacological agents to treat immune diseases, such as asthma and inflammatory bowel disease, and certain types of cancer. GCs act mainly by activating the GC receptor (GR), which interacts with other transcription factors to regulate gene expression. Here, we combined different functional genomics approaches to gain molecular insights into the mechanisms of action of GC. By profiling the transcriptional response to GC over time in 4 Yoruba (YRI) and 4 Tuscans (TSI) lymphoblastoid cell lines (LCLs), we suggest that the transcriptional response to GC is variable not only in time, but also in direction (positive or negative) depending on the presence of specific interacting transcription factors. Accordingly, when we performed ChIP-seq for GR and NF-κB in two YRI LCLs treated with GC or with vehicle control, we observed that features of GR binding sites differ for up- and down-regulated genes. Finally, we show that eQTLs that affect expression patterns only in the presence of GC are 1.9-fold more likely to occur in GR binding sites, compared to eQTLs that affect expression only in its absence. Our results indicate that genetic variation at GR and interacting transcription factors binding sites influences variability in gene expression, and attest to the power of combining different functional genomic approaches.
PLoS ONE 04/2013; 8(4):e61654. DOI:10.1371/journal.pone.0061654 · 3.23 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Author Summary
Glucocorticoids (GCs) are steroid hormones produced by the human body in response to environmental stressors. Despite their key role as physiological regulators and widely administered pharmaceuticals, little is known about the genetic basis of inter-individual and inter-ethnic variation in GC response. As GC action is mediated by the regulation of gene expression, we profiled transcript abundance and protein secretion in EBV-transformed B lymphocytes from a panel of 114 individuals, including those of both African and European ancestry. Combining these molecular traits with genome-wide genetic data, we found that genotype-treatment interactions at polymorphisms near genes affected GC regulation of expression for 26 genes and of secretion for IL6. A novel statistical approach revealed that these interactions could be distinguished into distinct types, with some showing genotypic effects only in GC-treated samples and others showing genotypic effects only in control-treated samples, with differing phenotypic and molecular interpretations. The insights into the genetic basis of variation in GC response and the statistical tools for identifying gene-treatment interactions that we provide will aid future efforts to identify genetic predictors of response to this and other treatments.