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Functional Annotation of Genomic Data with Metabolic Inference^1,2

R. L. Walzem^*,3, R. A. Baillie, M. Wiest, R. Davis, S. M. Watkins, T. E. Porter, J. Simon and L. A. Cogburn^||

^* Department of Poultry Science, Texas A&M University, College Station 77843; Lipomic Technologies Inc., West Sacramento, CA 95691; Department of Animal and Avian Sciences, University of Maryland, College Park 20742; Station de Recherches Avicoles, Institut National de la Recherche Agronomique, 37380 Nouzilly, France; and ^|| Department of Animal and Food Sciences, University of Delaware, Newark 19176

³ Corresponding author: rwalzem{at}poultry.tamu.edu

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 programs through superior metabolic descriptions that can then be associated with specific gene networks and transcriptional profiles.

Key Words: genetic selection • adipose • metabolomics • chicken lipid

¹ Disclosure: Potential financial conflicts are listed at the end of the manuscript. This study was supported by National Space Biomedical Research Institute grant number NPFR00204 (R. L. Walzem), National Cancer Institute number 5R25CA090301-05 (R. L. Walzem), Texas Agricultural Experiment Station project number 8738 (R. L. Walzem), and USDA Initiative for Future Agricultural and Food Systems number 00-52100-9614 (L. A. Cogburn, T. E. Porter, and J. Simon).

² Presented as part of the Ancillary Scientists Symposium, Functional Genomics: Building the Bridge between the Genome and Phenome, Poultry Science Association Annual Meeting, Sunday, July 16, 2006.

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