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Microsatellite evolutionary rate and pattern in Schistocerca gregaria inferred from direct observation of germline mutations
Authors:M‐P Chapuis  C Plantamp  R Streiff  L Blondin  C Piou
Institution:1. CIRAD, UMR CBGP, Montpellier, France;2. Laboratoire de Biométrie et Biologie Evolutive, CNRS, UMR 5558, Université Lyon 1, Villeurbanne, France;3. INRA, UMR CBGP, Montpellier, France;4. INRA, UMR DGIMI, Montpellier, France;5. CIRAD, UPR B‐AMR, Montpellier, France
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.
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