title: Genome-scale network analysis of imprinted human metabolic genes.
abstract: System analysis of metabolic network reconstructions can be used to calculate functional states or phenotypes. This provides tools to study the metabolic effects of genetic and epigenetic properties, such as dosage sensitivity. We used the genome-scale reconstruction of human metabolism (Recon 1) to analyze the effect of nine known or predicted imprinted genes on metabolic phenotypes. Simulations of maternal deletion of ATP10A indicated an anabolic metabolism consistent with the known clinical phenotypes of obesity. The abnormal expression of the other genes affected fewer subsections of metabolism consistent with a lack of established clinical phenotypes. We found that four of nine genes had metabolic effect as predicted by the Haig's parental conflict theory.
authors.affiliation: Department of Biochemistry and Molecular Biology, University of Iceland, Reykjavik, Iceland.
authors.forename: Martin I
authors.initials: MI
authors.lastname: Sigurdsson
authors.forename: Neema
authors.initials: N
authors.lastname: Jamshidi
authors.forename: Jon J
authors.initials: JJ
authors.lastname: Jonsson
authors.forename: Bernhard O
authors.initials: BO
authors.lastname: Palsson
mesh_terms: D019295:Computational Biology / Q000379:methods; D003198:Computer Simulation; D030541:Databases, Genetic; D044127:Epigenesis, Genetic; D017353:Gene Deletion; D018628:Gene Dosage; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D016678:Genome; D015894:Genome, Human; D018392:Genomic Imprinting; D006801:Humans; D053858:Metabolic Networks and Pathways / Q000235:genetics; D008957:Models, Genetic; D010641:Phenotype