Functional annotation of genomic data with metabolic inference

Metabolomics is an appealing new approach in systems biology aimed at enabling an improved understanding of the dynamic biochemical composition of living systems. Biological systems are remarkably complex. Importantly, metabolites are the end products of cellular regulatory processes, and their concentrations reflect the ultimate response of a biological system to genetic or environmental changes. In this article, we describe the components of lipid metabolomics and then use them to investigate the metabolic basis for increased abdominal adiposity in 2 strains of divergently selected chickens. Lipid metabolomics were chosen due to the availability of well-developed analytical platforms and the pervasive physiological importance of lipids in metabolism. The analysis Suggests that metabolic shifts that result in increased abdominal adiposity are not universal and vary with genetic background. Metabolomics can be used to reverse engineer selection pro-rams through superior metabolic descriptions that can then be associated with specific gene networks and transcriptional profiles.