Co-regulatory expression quantitative trait loci mapping: method and application to endometrial cancer.
paper
Cited
Public
- Authors
- Kompass, Kenneth S; Witte, John S
- Year
- 2011
- Journal
- BMC medical genomics
- PMID
- 21226949
- DOI
- 10.1186/1755-8794-4-6
- PMCID
- PMC3032645
BACKGROUND: Expression quantitative trait loci (eQTL) studies have helped identify the genetic determinants of gene expression. Understanding the potential interacting mechanisms underlying such findings, however, is challenging. METHODS: We describe a method to identify the trans-acting drivers of multiple gene co-expression, which reflects the action of regulatory molecules. This method-termed co-regulatory expression quantitative trait locus (creQTL) mapping-allows for evaluation of a more focused set of phenotypes within a clear biological context than conventional eQTL mapping. RESULTS: Applying this method to a study of endometrial cancer revealed regulatory mechanisms supported by the literature: a creQTL between a locus upstream of STARD13/DLC2 and a group of seven IFNΞ²-induced genes. This suggests that the Rho-GTPase encoded by STARD13 regulates IFNΞ²-induced genes and the DNA damage response. CONCLUSIONS: Because of the importance of IFNΞ² in cancer, our results suggest that creQTL may provide a finer picture of gene regulation and may reveal additional molecular targets for intervention. An open source R implementation of the method is available at http://sites.google.com/site/kenkompass/.
Overview of analysis.
Histogram of gene cluster sizes identified from the EC gene expression data.
creQTL1 (left panel) and creQTL2 (right panel) from Table 1, with SNP IDs rs9315220 and rs2296697, respectively. For each association, co-regulation of a given cluster and a SNP is shown. The 52 endometrial carcinoma samples are color coded by genotype on the x-axis (upper panel), with every third sample labeled beneath the axis. On the y-axis (upper panel), normalized gene cluster expression values are plotted. The median, 25th/75th quantiles, minimum, and maximum gene values across all genes in the cluster are shown for each sample. The bottom panel of each figure shows the Z2E(j) statistic for each sample and the given cluster.
Genewise genomic locations of SNP q-values. After assigning 68,523 SNPs to 8,398 genes based on the minimum association q-value within 5 MB of the nearest gene's coding sequence, q-values were binned into categories based on their relative position to the nearest gene. Note that the q-values do not reach the bottom of the plot as they were chosen as the minimum value within 5 MB of the nearest gene.
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