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Did Genetic Drift Drive Increases in Genome Complexity?

Mechanisms underlying the dramatic patterns of genome size variation across the tree of life remain mysterious. Effective population size (N(e)) has been proposed as a major driver of genome size: selection is expected to efficiently weed out deleterious mutations increasing genome size in lineages...

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Detalles Bibliográficos
Autores principales: Whitney, Kenneth D., Garland, Theodore
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2928810/
https://www.ncbi.nlm.nih.gov/pubmed/20865118
http://dx.doi.org/10.1371/journal.pgen.1001080
Descripción
Sumario:Mechanisms underlying the dramatic patterns of genome size variation across the tree of life remain mysterious. Effective population size (N(e)) has been proposed as a major driver of genome size: selection is expected to efficiently weed out deleterious mutations increasing genome size in lineages with large (but not small) N(e). Strong support for this model was claimed from a comparative analysis of N(e)u and genome size for ≈30 phylogenetically diverse species ranging from bacteria to vertebrates, but analyses at that scale have so far failed to account for phylogenetic nonindependence of species. In our reanalysis, accounting for phylogenetic history substantially altered the perceived strength of the relationship between N(e)u and genomic attributes: there were no statistically significant associations between N(e)u and gene number, intron size, intron number, the half-life of gene duplicates, transposon number, transposons as a fraction of the genome, or overall genome size. We conclude that current datasets do not support the hypothesis of a mechanistic connection between N(e) and these genomic attributes, and we suggest that further progress requires larger datasets, phylogenetic comparative methods, more robust estimators of genetic drift, and a multivariate approach that accounts for correlations between putative explanatory variables.