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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., Author Summary Genome-wide association (GWA) analyses seek to relate variation of phenotype to underlying (and presumably causative) variation in genotype. Recently, many GWA studies have identified candidate genes underlying disease phenotypes such as diabetes, heart disease, and cancer risk. Many groups have also performed GWA using variation in gene expression levels as the input phenotype. These expression QTL (eQTL) studies have provided important clues as to the genetic basis of gene expression regulation. Here, we perform an eQTL study in mouse adipose tissue. We then developed a systematic analysis method to relate these patterns of eQTL associations to biological pathways. Based on this approach, we identified putative roles for thousands of candidate upstream regulators and candidate pathway members in relation to specific biological pathways. Statistical analysis showed that these predictions were highly enriched for true genetic modulators of these pathways. Based on these predictions, we also experimentally validated a role for one particular gene, cyclin H, in the regulation of oxidative phosphorylation. These findings illustrate a new analysis method for relating eQTL studies to biological pathways and identify cyclin H as a novel key regulator of cellular energy metabolism.