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Genome Biol Evol. 2014 Apr;6(4):754-62. doi: 10.1093/gbe/evu051.

Gene family level comparative analysis of gene expression in mammals validates the ortholog conjecture.

Author information

1
National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland.

Abstract

The ortholog conjecture (OC), which is central to functional annotation of genomes, posits that orthologous genes are functionally more similar than paralogous genes at the same level of sequence divergence. However, a recent study challenged the OC by reporting a greater functional similarity, in terms of Gene Ontology (GO) annotations and expression profiles, among within-species paralogs compared with orthologs. These findings were taken to indicate that functional similarity of homologous genes is primarily determined by the cellular context of the genes, rather than evolutionary history. However, several subsequent studies suggest that GO annotations and microarray data could artificially inflate functional similarity between paralogs from the same organism. We sought to test the OC using approaches distinct from those used in previous studies. Analysis of a large RNAseq data set from multiple human and mouse tissues shows that expression similarity (correlations coefficients, rank's, or Z-scores) between orthologs is substantially greater than that for between-species paralogs with the same sequence divergence, in agreement with the OC and the results of recent detailed analyses. These findings are further corroborated by a fine-grain analysis in which expression profiles of orthologs and paralogs were compared separately for individual gene families. Expression profiles of within-species paralogs are more strongly correlated than profiles of orthologs but it is shown that this is caused by high background noise, that is, correlation between profiles of unrelated genes in the same organism. Z-scores and rank scores show a nonmonotonic dependence of expression profile similarity on sequence divergence. This complexity of gene expression evolution after duplication might be at least partially caused by selection for protein dosage rebalancing following gene duplication.

KEYWORDS:

duplicated genes; duplication–degeneration–complementation model; neofunctionalization model; neutral evolution; rebalancing dosage effect model; selection; subfunctionalization model

PMID:
24610837
PMCID:
PMC4007545
DOI:
10.1093/gbe/evu051
[Indexed for MEDLINE]
Free PMC Article

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