Dysregulation of lipid homeostasis is a precipitating event in the pathogenesis and progression of hepatosteatosis and metabolic syndrome. However, defining the molecular mechanisms that underpin lipid dysregulation in humans has proven challenging due to complex gene and environment interactions. Nevertheless, genome-wide association studies (GWAS) have indicated there to be an approximately 30% heritability for hepatosteatosis, however only ~10% has been directly attributable to genetic variants. This highlights a discrepancy that likely exists because most linear GWAS models do not account for features such as structural variation, rare variants and complex epistatic or gene-by-environment interactions. More recently, systems biology approaches utilizing genetic reference panels (GRPs) in model organisms have increased our ability in this regard, because they allow for integration of multiple layers of biological information (trans-omics), and for the control of environmental influence. Accordingly, we undertook a systems genetics analysis of mammalian lipid metabolism. Here we quantify 311 individual lipid species in the liver and plasma of replicate animals from 107 strains of an inbred mouse GRP (>300 individual mice), and integrated these data with matched hepatic proteomics performed on the same set of mice. Subsequent analysis of correlation networks and QTL mapping incorporating strain-specific phenotype and genotype data facilitated the generation of a powerful resource that expands our understanding of mammalian lipid metabolism, identifies bona fide effectors of lipid abundance, and provides several targets of interest for disease intervention.