Feed efficiency (FE) is a key trait in pig production, as improvement in FE has positive economic and environmental impact. FE is a complex phenotype and testing animals for FE is costly. Therefore, there has been a desire to find functionally relevant single nucleotide polymorphisms (SNPs) as biomarkers, to improve our biological understanding of FE as well as accuracy of genomic prediction for FE. We have performed a cis- and trans- eQTL (expression quantitative trait loci) analysis, in a population of Danbred Durocs (N = 11) and Danbred Landrace (N = 27) using both a linear and ANOVA model based on muscle tissue RNA-seq. We analyzed a total of 1425x19179 or 2.7x107 Gene-SNP combinations in eQTL detection models for FE. The 1425 genes were from RNA-Seq based differential gene expression analyses using 25880 genes related to FE and additionally combined with mitochondrial genes. The 19179 SNPs were from applying stringent quality control and linkage disequilibrium filtering on genotype data using a GGP Porcine HD 70k SNP array. We applied 1000 fold bootstrapping and enrichment analysis to further validate and analyze our detected eQTLs. We identified 13 eQTLs with FDR < 0.1, affecting several genes found in previous studies of commercial pig breeds. Examples include MYO19, CPT1B, ACSL1, IER5L, CPT1A, SUCLA2, CSRNP1, PARK7 and MFF. The bootstrapping results showed statistically significant enrichment (p-value<2.2x10-16) of eQTLs with p-value < 0.01 in both cis and trans-eQTLs. Enrichment analysis of top trans-eQTLs revealed high enrichment for gene categories and gene ontologies associated with genomic context and expression regulation. This included transcription factors (p-value = 1.0x10-13), DNA-binding (GO:0003677, p-value = 8.9x10-14), DNA-binding transcription factor activity (GO:0003700,) nucleus gene (GO:0005634, p-value<2.2x10-16), negative regulation of expression (GO:0010629, p-value<2.2x10-16). These results would be useful for future genome assisted breeding of pigs to improve FE, and in the improved understanding of the functional mechanism of trans eQTLs.