Abstract
Genome-wide gene expression profiling has been extensively used to generate biological hypotheses based on differential expression. Recently, many studies have used microarrays to measure gene expression levels across genetic mapping populations. These gene expression phenotypes have been used for genome-wide association analyses, an analysis referred to as expression QTL (eQTL) mapping. Here, eQTL analysis was performed in adipose tissue from 28 inbred strains of mice. We focused our analysis on “trans-eQTL bands”, defined as instances in which the expression patterns of many genes were all associated to a common genetic locus. Genes comprising trans-eQTL bands were screened for enrichments in functional gene sets representing known biological pathways, and genes located at associated trans-eQTL band loci were considered candidate transcriptional modulators. We demonstrate that these patterns were enriched for previously characterized relationships between known upstream transcriptional regulators and their downstream target genes. Moreover, we used this strategy to identify both novel regulators and novel members of known pathways. Finally, based on a putative regulatory relationship identified in our analysis, we identified and validated a previously uncharacterized role for cyclin H in the regulation of oxidative phosphorylation. We believe that the specific molecular hypotheses generated in this study will reveal many additional pathway members and regulators, and that the analysis approaches described herein will be broadly applicable to other eQTL data sets.
Highlights
Traditional studies for mapping quantitative trait loci (QTL) have focused on identifying the causative genomic loci for individual disease-related phenotypes, such as body weight and glucose levels
We perform an expression QTL (eQTL) study in mouse adipose tissue
We developed a systematic analysis method to relate these patterns of eQTL associations to biological pathways
Summary
Traditional studies for mapping quantitative trait loci (QTL) have focused on identifying the causative genomic loci for individual disease-related phenotypes, such as body weight and glucose levels. Microarray technologies have enabled the measurement of gene expression levels for thousands of genes in parallel, and these traits have been used as phenotypes in genetic association studies These expression QTL (‘‘eQTL’’) experiments have been conducted in a wide variety of organisms and cell types, including yeast, mouse (hematopoietic stem cells, brain and liver), rat (kidney and adipose), and human (lymphoblastoid cell lines) (for example, [1,2,3,4,5,6,7,8]). Several other groups have used trans-eQTLs to study the relationships between up-stream regulators and both transcriptional targets and phenotypic readouts [9,10,11] These individual trans-eQTLs organize into ‘‘trans-eQTL bands’’, wherein the expression of multiple genes is associated with a single, common genetic locus. Functional relationship between trans-eQTL band and biological pathways was studied in limited set of human trans-eQTL bands [12]
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