The Pattern of Evolution of Smaller-Scale Gene Duplicates in Mammalian Genomes is More Consistent with Neo- than Subfunctionalisation
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Gene duplication and the accompanying release of negative selective pressure on the duplicate pair is thought to be the key process that makes functional change in the coding and regulatory regions of genomes possible. However, the nature of these changes remains unresolved. There are a number of models for the fate of gene duplicates, the two most prominent of which are neofunctionalisation and subfunctionalisation, but it is still unclear which is the dominant fate. Using a dataset consisting of smaller-scale (tandem and segmental) duplications identified from the genomes of four fully sequenced mammalian genomes, we characterise two key features of smaller-scale duplicate evolution: the rate of pseudogenisation and the rate of accumulation of replacement substitutions in the coding sequence. We show that the best fitting model for gene duplicate survival is a Weibull function with a downward sloping convex hazard function which implies that the rate of pseudogenisation of a gene declines rapidly with time since duplication. Our analysis of the accumulation of replacement substitutions per replacement site shows that they accumulate on average at 64% of the neutral expectation immediately following duplication and as high as 73% in the human lineage. Although this rate declines with time since duplication, it takes several tens of millions of years before it has declined to half its initial value. We show that the properties of the gene death rate and of the accumulation of replacement substitutions are more consistent with neofunctionalisation (or subfunctionalisation followed by neofunctionalisation) than they are with subfunctionalisation alone or any of the other alternative modes of evolution of smaller-scale duplicates.
KeywordsGene duplication Chordata Pseudogenisation Neofunctionalisation Subfunctionalisation Positive selection Nonsynonymous substitution
We are grateful to Alex Buerkle and Snehalata Huzurbazar for helpful discussion and to Annie Bouvier for help with the nls2 package. The work has been funded by FUGE, the functional genomics platform of the Norwegian research council.
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