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Wiley, Molecular Ecology, 24(24), p. 6107-6119, 2015

DOI: 10.1111/mec.13465

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Microsatellite evolutionary rate and pattern inSchistocerca gregariainferred from direct observation of germline mutations

Journal article published in 2015 by M.-P. Chapuis, C. Plantamp ORCID, R. Streiff, L. Blondin, C. Piou
This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

Unravelling variation among taxonomic orders regarding the rate of evolution in microsatellites is crucial for evolutionary biology and population genetics research. The mean mutation rate of microsatellites tends to be lower in arthropods than in vertebrates, but data are scarce and mostly concern accumulation of mutations in model species. Based on parent–offspring segregations and a hierarchical Bayesian model, the mean rate of mutation in the orthopteran insect Schistocerca gregaria was estimated at 2.1e−4 per generation per untranscribed dinucleotide locus. This is close to vertebrate estimates and one order of magnitude higher than estimates from species of other arthropod orders, such as Drosophila melanogaster and Daphnia pulex. We also found evidence of a directional bias towards expansions even for long alleles and exceptionally large ranges of allele sizes. Finally, at transcribed microsatellites, the mean rate of mutation was half the rate found at untranscribed loci and the mutational model deviated from that usually considered, with most mutations involving multistep changes that avoid disrupting the reading frame. Our direct estimates of mutation rate were discussed in the light of peculiar biological and genomic features of S. gregaria, including specificities in mismatch repair and the dependence of its activity to allele length. Shedding new light on the mutational dynamics of grasshopper microsatellites is of critical importance for a number of research fields. As an illustration, we showed how our findings improve microsatellite application in population genetics, by obtaining a more precise estimation of S. gregaria effective population size from a published data set based on the same microsatellites.