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Functional bias in molecular evolution rate of Arabidopsis thaliana

BACKGROUND: Characteristics derived from mutation and other mechanisms that are advantageous for survival are often preserved during evolution by natural selection. Some genes are conserved in many organisms because they are responsible for fundamental biological function, others are conserved for t...

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Detalles Bibliográficos
Autores principales: Warren, Andrew S, Anandakrishnan, Ramu, Zhang, Liqing
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2876160/
https://www.ncbi.nlm.nih.gov/pubmed/20433764
http://dx.doi.org/10.1186/1471-2148-10-125
Descripción
Sumario:BACKGROUND: Characteristics derived from mutation and other mechanisms that are advantageous for survival are often preserved during evolution by natural selection. Some genes are conserved in many organisms because they are responsible for fundamental biological function, others are conserved for their unique functional characteristics. Therefore one would expect the rate of molecular evolution for individual genes to be dependent on their biological function. Whether this expectation holds for genes duplicated by whole genome duplication is not known. RESULTS: We empirically demonstrate here, using duplicated genes generated from the Arabidopsis thaliana α-duplication event, that the rate of molecular evolution of genes duplicated in this event depend on biological function. Using functional clustering based on gene ontology annotation of gene pairs, we show that some duplicated genes, such as defense response genes, are under weaker purifying selection or under stronger diversifying selection than other duplicated genes, such as protein translation genes, as measured by the ratio of nonsynonymous to synonymous divergence (dN/dS). CONCLUSIONS: These results provide empirical evidence indicating that molecular evolution rate for genes duplicated in whole genome duplication, as measured by dN/dS, may depend on biological function, which we characterize using gene ontology annotation. Furthermore, the general approach used here provides a framework for comparative analysis of molecular evolution rate for genes based on their biological function.