Data from: Spatial population genetic structure of a bacterial parasite in close coevolution with its host
Cite this dataset
Andras, Jason P.; Fields, Peter D.; Ebert, Dieter (2018). Data from: Spatial population genetic structure of a bacterial parasite in close coevolution with its host [Dataset]. Dryad. https://doi.org/10.5061/dryad.67r06s0
Knowledge of a species’ population genetic structure can provide insight into fundamental ecological and evolutionary processes including gene flow, genetic drift, and adaptive evolution. Such inference is of particular importance for parasites, as an understanding of their population structure can illuminate epidemiological and coevolutionary dynamics. Here we describe the population genetic structure of the bacterium Pasteuria ramosa, a parasite that infects planktonic crustaceans of the genus Daphnia. This system has become a model for investigations of host-parasite interactions and represents an example of coevolution via negative frequency-dependent selection (a.k.a. ‘Red Queen’ dynamics). To sample P. ramosa, we experimentally infected a panel of Daphnia hosts with natural spore banks from the sediments of 25 ponds throughout much of the species range in Europe and Western Asia. Using 12 polymorphic VNTR loci, we identified substantial genetic diversity both within and among localities that was structured geographically among ponds. Genetic diversity was also structured among host genotypes within ponds, though this pattern varied by locality, with P. ramosa at some localities partitioned into distinct host-specific lineages, and other localities where recombination had shuffled genetic variation among different infection phenotypes. Across the sample range, there was a pattern of isolation-by-distance, and principal components analysis coupled with Procrustes rotation identified congruence between patterns of genetic variation and geography. Our findings support the hypothesis that Pasteuria is an endemic parasite coevolving closely with its host. These results provide important context for previous studies of this model system and inform hypotheses for future research.