Abstract
Abstract
Although individual parasite species commonly infect many populations across physical space as well as multiple host species, the extent to which parasites traverse physical and phylogenetic distances is unclear. Population genetic analyses of parasite populations can reveal how parasites move across space or between host species, including helping assess whether a parasite is more likely to infect a different host species in the same location or the same host species in a different location. Identifying these transmission barriers could be exploited for effective disease control. Here, we analysed population genetic structuring of the parasite Pasteuria ramosa in daphniid host species from different lakes. Outbreaks occurred most often in the common host species Daphnia dentifera and Daphnia retrocurva. The genetic distance between parasite samples tended to be smaller when samples were collected from the same lake, the same host species and closer in time. Within lakes, the parasite showed structure by host species and sampling date; within a host species, the parasite showed structure by lake and sampling date. However, despite this structuring, we found the same parasite genotype infecting closely related host species, and we sometimes found the same genotype in nearby lakes. Thus, P. ramosa experiences challenges infecting different host species and moving between populations, but doing so is possible. In addition, the structuring by sampling date indicates potential adaptation to or coevolution with host populations and supports prior findings that parasite population structure is dynamic during outbreaks.
Funder
National Science Foundation
Gordon and Betty Moore Foundation
Publisher
Cambridge University Press (CUP)
Reference62 articles.
1. Dispersal, host genotype and environment shape the spatial dynamics of a parasite in the wild
2. hierfstat, a package for r to compute and test hierarchical F-statistics
3. A statistical method for evaluating systematic relationships;Sokal;University of Kansas Science Bulletin,1958
4. R Core Team (2020) R: A Language and Environment for Statistical Computing.