Article: article from journal or magazin.
Stronger transferability but lower variability in transcriptomic- than in anonymous microsatellites: evidence from Hylid frogs.
Molecular Ecology Resources
A simple way to quickly optimize microsatellites in nonmodel organisms is to reuse loci available in closely related taxa; however, this approach can be limited by the stochastic and low cross-amplification success experienced in some groups (e.g. amphibians). An efficient alternative is to develop loci from transcriptome sequences. Transcriptomic microsatellites have been found to vary in their levels of cross-species amplification and variability, but this has to date never been tested in amphibians. Here, we compare the patterns of cross-amplification and levels of polymorphism of 18 published anonymous microsatellites isolated from genomic DNA vs. 17 loci derived from a transcriptome, across nine species of tree frogs (Hyla arborea and Hyla cinerea group). We established a clear negative relationship between divergence time and amplification success, which was much steeper for anonymous than transcriptomic markers, with half-lives (time at which 50% of the markers still amplify) of 1.1 and 37 My, respectively. Transcriptomic markers are significantly less polymorphic than anonymous loci, but remain variable across diverged taxa. We conclude that the exploitation of amphibian transcriptomes for developing microsatellites seems an optimal approach for multispecies surveys (e.g. analyses of hybrid zones, comparative linkage mapping), whereas anonymous microsatellites may be more informative for fine-scale analyses of intraspecific variation. Moreover, our results confirm the pattern that microsatellite cross-amplification is greatly variable among amphibians and should be assessed independently within target lineages. Finally, we provide a bank of microsatellites for Palaearctic tree frogs (so far only available for H. arborea), which will be useful for conservation and evolutionary studies in this radiation.
amphibian, EST, Hyla, population genetics, transcriptome
Web of science
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