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. 2010 Jul;185(3):983-9.
doi: 10.1534/genetics.110.115915. Epub 2010 May 3.

The rate and spectrum of spontaneous mutations in a plant RNA virus

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The rate and spectrum of spontaneous mutations in a plant RNA virus

Nicolas Tromas et al. Genetics. 2010 Jul.

Abstract

Knowing mutation rates and the molecular spectrum of spontaneous mutations is important to understanding how the genetic composition of viral populations evolves. Previous studies have shown that the rate of spontaneous mutations for RNA viruses widely varies between 0.01 and 2 mutations per genome and generation, with plant RNA viruses always occupying the lower side of this range. However, this peculiarity of plant RNA viruses is based on a very limited number of studies. Here we analyze the spontaneous mutational spectrum and the mutation rate of Tobacco etch potyvirus, a model system of positive sense RNA viruses. Our experimental setup minimizes the action of purifying selection on the mutational spectrum, thus giving a picture of what types of mutations are produced by the viral replicase. As expected for a neutral target, we found that transitions and nonsynonymous (including a few stop codons and small deletions) mutations were the most abundant type. This spectrum was notably different from the one previously described for another plant virus. We have estimated that the spontaneous mutation rate for this virus was in the range 10(-6)-10(-5) mutations per site and generation. Our estimates are in the same biological ballpark that previous values reported for plant RNA viruses. This finding gives further support to the idea that plant RNA viruses may have lower mutation rates than their animal counterparts.

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Figures

F<sc>igure</sc> 1.—
Figure 1.—
Observed frequencies for the different types of nucleotides substitutions. Each column groups mutations rendering complementary pairs and, thus, can occur during the synthesis of the genomic or antigenomic strains. The LaPlace estimator of the frequency has been used to minimize the bias due to small sample size (Agresti and Coull 1998). Error bars represent the 95% confidence interval for the estimator.

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