Expression level, cellular compartment and metabolic network position all influence the average selective constraint on mammalian enzymes

BMC Evolutionary Biology

Research Article

Corey M Hudson¹  Gavin C Conant² 

[1] Informatics Institute, University of Missouri, Columbia, MO, USA;Informatics Institute, University of Missouri, Columbia, MO, USA;Division of Animal Sciences, University of Missouri, Columbia, MO, USA;

关键词: Metabolic Network;    Node Degree;    Metabolic Gene;    Betweenness Centrality;    Protein Interaction Network;   

DOI  :  10.1186/1471-2148-11-89

 received in 2010-11-12, accepted in 2011-04-06,  发布年份 2011

来源: Springer

【 摘 要 】

BackgroundA gene's position in regulatory, protein interaction or metabolic networks can be predictive of the strength of purifying selection acting on it, but these relationships are neither universal nor invariably strong. Following work in bacteria, fungi and invertebrate animals, we explore the relationship between selective constraint and metabolic function in mammals.ResultsWe measure the association between selective constraint, estimated by the ratio of nonsynonymous (Ka) to synonymous (Ks) substitutions, and several, primarily metabolic, measures of gene function. We find significant differences between the selective constraints acting on enzyme-coding genes from different cellular compartments, with the nucleus showing higher constraint than genes from either the cytoplasm or the mitochondria. Among metabolic genes, the centrality of an enzyme in the metabolic network is significantly correlated with Ka/Ks. In contrast to yeasts, gene expression magnitude does not appear to be the primary predictor of selective constraint in these organisms.ConclusionsOur results imply that the relationship between selective constraint and enzyme centrality is complex: the strength of selective constraint acting on mammalian genes is quite variable and does not appear to exclusively follow patterns seen in other organisms.

【 授权许可】

CC BY   
© Hudson and Conant; licensee BioMed Central Ltd. 2011