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Data from: Microsatellite loci for dreissenid mussels (Mollusca: Bivalvia: Dreissenidae) and relatives: markers for assessing exotic and native populations

Cite this dataset

Feldheim, Kevin A.; Brown, Joshua E.; Murphy, Douglas J.; Stepien, Carol A. (2011). Data from: Microsatellite loci for dreissenid mussels (Mollusca: Bivalvia: Dreissenidae) and relatives: markers for assessing exotic and native populations [Dataset]. Dryad. https://doi.org/10.5061/dryad.8621

Abstract

We developed and tested 14 new polymorphic microsatellite loci for dreissenid mussels, including the two species that have invaded many freshwater habitats in Eurasia and North America, where they cause serious industrial fouling damage and ecological alterations. These new loci will aid our understanding of their genetic patterns in invasive populations as well as throughout their native Ponto-Caspian distributions. Eight new loci for the zebra mussel Dreissena polymorpha and six for the quagga mussel D. rostriformis bugensis were compared with new results from six previously published loci to generate a robust molecular toolkit for dreissenid mussels and their relatives. Taxa tested include D. polymorpha , D. r. bugensis , D. r. grimmi , D. stankovici , the “living fossil” Congeria kusceri , and the dark false mussel Mytilopsis leucophaeata (the latter also is invasive). Overall, most of the 24 zebra mussel (N=583) and 13 quagga mussel (N=269) population samples conformed to Hardy-Weinberg equilibrium expectations for the new loci following Bonferroni correction. The 11 loci (eight new, three previously published) evaluated for D. polymorpha averaged 35.1 alleles and 0.72 mean observed heterozygosity per locus, and 25.3 and 0.75 for the nine loci (six new, three previously published) developed for D. r. bugensis . All but three of these loci successfully amplified the other species of Dreissena , and all but one also amplified Congeria and Mytilopsis . All species and populations tested were significantly divergent using the microsatellite data, with neighbor-joining trees reflecting their evolutionary relationships; our results reveal broad utility for resolving their biogeographic, evolutionary, population, and ecological patterns.

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