The metabolic syndrome (MetS) is a collection of co-occurring complex disorders including hypertension, obesity, dyslipidemia, and insulin resistance. The Lyon Hypertensive (LH) and Lyon Normotensive (LN) rats are models of MetS sensitivity and resistance, respectively. To identify genetic determinants and mechanisms underlying MetS, rats from an F2 intercross between LH and LN were studied. Multi-dimensional data were obtained including SNP genotypes, physiological traits including blood pressure, plasma lipid and leptin levels, and body weight/adiposity, and more than 150 billion nucleotides of RNA-Seq reads from the livers of F2 (n=36), LH (n=6), and LN (n=6) individuals. We identified 17 pQTLs (physiological quantitative trait loci) and 1200 eQTLs (gene expression quantitative trait loci) at genome-wide p<0.05. Systems biology methods were applied to prioritize candidate MetS genes, including genes previously shown to be MetS-related. We identified an eQTL peak on rat chromosome 17 (RNO17) shared by large number of genes; RNO17 also has pQTL for MetS-related traits. Network analysis in these genes identified two major co-regulation modules involving mitochondria and gene regulation; genes in the two modules causally affect multiple MetS traits. A gene, RGD1562963, closest to the eQTL peak was identified as the eQTL driver gene. It is directly affected by genetic variation between LH and LN rats, affects downstream genes in the eQTL cluster, and is correlated with MetS phenotypes. Our study sheds light on the intricate pathogenesis of MetS and proved that systems biology with high-throughput sequencing is a powerful method to study the etiology of complicated diseases.