Journal Article

Reduced Efficacy of Natural Selection on Codon Usage Bias in Selfing <i>Arabidopsis</i> and <i>Capsella</i> Species

Suo Qiu, Kai Zeng, Tanja Slotte, Stephen Wright and Deborah Charlesworth

in Genome Biology and Evolution

Published on behalf of Society for Molecular Biology and Evolution

Volume 3, issue , pages 868-880
Published in print January 2011 |
Published online August 2011 | e-ISSN: 1759-6653 | DOI: http://dx.doi.org/10.1093/gbe/evr085

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Population genetic theory predicts that the efficacy of natural selection in a self-fertilizing species should be lower than its outcrossing relatives because of the reduction in the effective population size (Ne) in the former brought about by inbreeding. However, previous analyses comparing Arabidopsis thaliana (selfer) with A. lyrata (outcrosser) have not found conclusive support for this prediction. In this study, we addressed this issue by examining silent site polymorphisms (synonymous and intronic), which are expected to be informative about changes in Ne. Two comparisons were made: A. thaliana versus A. lyrata and Capsella rubella (selfer) versus C. grandiflora (outcrosser). Extensive polymorphism data sets were obtained by compiling published data from the literature and by sequencing 354 exon loci in C. rubella and 89 additional loci in C. grandiflora. To extract information from the data effectively for studying these questions, we extended two recently developed models in order to investigate detailed selective differences between synonymous codons, mutational biases, and biased gene conversion (BGC), taking into account the effects of recent changes in population size. We found evidence that selection on synonymous codons is significantly weaker in the selfers compared with the outcrossers and that this difference cannot be fully accounted for by mutational biases or BGC.

Keywords: Arabidopsis; Capsella; natural selection; inbreeding; codon usage bias

Journal Article.  9306 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology ; Evolutionary Biology ; Genetics and Genomics

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