GC-biased gene conversion conceals the prediction of the nearly neutral theory in avian genomes

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ID: 44988
2019
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Abstract
Abstract Background The nearly neutral theory of molecular evolution predicts that the efficacy of natural selection increases with the effective population size. This prediction has been verified by independent observations in diverse taxa, which show that life-history traits are strongly correlated with measures of the efficacy of selection, such as the d N /d S ratio. Surprisingly, avian taxa are an exception to this theory because correlations between life-history traits and d N /d S are apparently absent. Here we explore the role of GC-biased gene conversion on estimates of substitution rates as a potential driver of these unexpected observations. Results We analyze the relationship between d N /d S estimated from alignments of 47 avian genomes and several proxies for effective population size. To distinguish the impact of GC-biased gene conversion from selection, we use an approach that accounts for non-stationary base composition and estimate d N /d S separately for changes affected or unaffected by GC-biased gene conversion. This analysis shows that the impact of GC-biased gene conversion on substitution rates can explain the lack of correlations between life-history traits and d N /d S . Strong correlations between life-history traits and d N /d S are recovered after accounting for GC-biased gene conversion. The correlations are robust to variation in base composition and genomic location. Conclusions Our study shows that gene sequence evolution across a wide range of avian lineages meets the prediction of the nearly neutral theory, the efficacy of selection increases with effective population size. Moreover, our study illustrates that accounting for GC-biased gene conversion is important to correctly estimate the strength of selection.
Reference Key
bolvar2019gcbiasedgenome Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Bolívar, Paulina;Guéguen, Laurent;Duret, Laurent;Ellegren, Hans;Mugal, Carina F.;
Journal Genome biology
Year 2019
DOI
DOI not found
URL
http://link.springer.com/article/10.1186/s13059-018-1613-z
Keywords
Biology (General) Technology business economics as a science commerce management. industrial management telecommunication genetics commercial geography. economic geography accounting. bookkeeping

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