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Comparative genomics and the study of evolution by natural selection

期刊

MOLECULAR ECOLOGY
卷 17, 期 21, 页码 4586-4596

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WILEY-BLACKWELL
DOI: 10.1111/j.1365-294X.2008.03954.x

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adaptive evolution; gene ontology; genome sequencing; nearly neutral theory

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Genomics profoundly affects most areas of biology, including ecology and evolutionary biology. By examining genome sequences from multiple species, comparative genomics offers new insight into genome evolution and the way natural selection moulds DNA sequence evolution. Functional divergence, as manifested in the accumulation of nonsynonymous substitutions in protein-coding genes, differs among lineages in a manner seemingly related to population size. For example, the ratio of nonsynonymous to synonymous substitution (d(N)/d(S)) is higher in apes than in rodents, compatible with Ohta's nearly neutral theory of molecular evolution, which suggests that the fixation of slightly deleterious mutations contributes to protein evolution at an extent negatively correlated with effective population size. While this supports the idea that functional evolution is not necessarily adaptive, comparative genomics is uncovering a role for positive Darwinian selection in 10-40% of all genes in different lineages, estimates that are likely to increase when the addition of more genomes gives increased power. Again, population size seems to matter also in this context, with a higher proportion of fixed amino acid changes representing advantageous mutations in large populations. Genes that are particularly prone to be driven by positive selection include those involved with reproduction, immune response, sensory perception and apoptosis. Genetic innovations are also frequently obtained by the gain or loss of complete gene sequences. Moreover, it is increasingly realized, from comparative genomics, that purifying selection conserves much more than just the protein-coding part of the genome, and this points at an important role for regulatory elements in trait evolution. Finally, genome sequencing using outbred or multiple individuals has provided a wealth of polymorphism data that gives information on population history, demography and marker evolution.

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