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      Landscape Genetics of Schistocephalus solidus Parasites in Threespine Stickleback ( Gasterosteus aculeatus) from Alaska

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          Abstract

          The nature of gene flow in parasites with complex life cycles is poorly understood, particularly when intermediate and definitive hosts have contrasting movement potential. We examined whether the fine-scale population genetic structure of the diphyllobothriidean cestode Schistocephalus solidus reflects the habits of intermediate threespine stickleback hosts or those of its definitive hosts, semi-aquatic piscivorous birds, to better understand complex host-parasite interactions. Seventeen lakes in the Cook Inlet region of south-central Alaska were sampled, including ten in the Matanuska-Susitna Valley, five on the Kenai Peninsula, and two in the Bristol Bay drainage. We analyzed sequence variation across a 759 bp region of the mitochondrial DNA (mtDNA) cytochrome oxidase I region for 1,026 S. solidus individuals sampled from 2009-2012. We also analyzed allelic variation at 8 microsatellite loci for 1,243 individuals. Analysis of mtDNA haplotype and microsatellite genotype variation recovered evidence of significant population genetic structure within S. solidus. Host, location, and year were factors in structuring observed genetic variation. Pairwise measures revealed significant differentiation among lakes, including a pattern of isolation-by-distance. Bayesian analysis identified three distinct genotypic clusters in the study region, little admixture within hosts and lakes, and a shift in genotype frequencies over time. Evidence of fine-scale population structure in S. solidus indicates that movement of its vagile, definitive avian hosts has less influence on gene flow than expected based solely on movement potential. Observed patterns of genetic variation may reflect genetic drift, behaviors of definitive hosts that constrain dispersal, life history of intermediate hosts, and adaptive specificity of S. solidus to intermediate host genotype.

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          Most cited references 26

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          Gene flow and the geographic structure of natural populations.

           M Slatkin (1987)
          There is abundant geographic variation in both morphology and gene frequency in most species. The extent of geographic variation results from a balance of forces tending to produce local genetic differentiation and forces tending to produce genetic homogeneity. Mutation, genetic drift due to finite population size, and natural selection favoring adaptations to local environmental conditions will all lead to the genetic differentiation of local populations, and the movement of gametes, individuals, and even entire populations--collectively called gene flow--will oppose that differentiation. Gene flow may either constrain evolution by preventing adaptation to local conditions or promote evolution by spreading new genes and combinations of genes throughout a species' range. Several methods are available for estimating the amount of gene flow. Direct methods monitor ongoing gene flow, and indirect methods use spatial distributions of gene frequencies to infer past gene flow. Applications of these methods show that species differ widely in the gene flow that they experience. Of particular interest are those species for which direct methods indicate little current gene flow but indirect methods indicate much higher levels of gene flow in the recent past. Such species probably have undergone large-scale demographic changes relatively frequently.
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            A synthesis of experimental work on parasite local adaptation.

            The study of parasite local adaptation, whereby parasites perform better on sympatric hosts than on allopatric hosts and/or better on their own host population than do other parasites, is of great importance to both basic and applied biology. Theoretical examination of host-parasite coevolution predicts that parasite migration rate, generation time and virulence all contribute to the pattern of parasite local adaptation, such that parasites with greater dispersal ability, more frequent reproduction and/or high virulence ought to exhibit increased infectivity on local hosts. Here, we present a meta-analysis of experimental work from 57 host-parasite systems across 54 local adaptation studies to directly test theoretical predictions concerning the effect of each attribute on parasite adaptation. As expected, we find that studies of parasites with higher migration rates than their hosts report local adaptation, as measured by infection success, significantly more often than studies of parasites with relatively low migration rates. Furthermore, this synthesis serves to identify biases in the current body of work and highlight areas with the greatest need for further study. We emphasize the importance of unifying the field with regard to experimental methods, local adaptation definitions and reported statistics for cross-infection studies.
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              Life history determines genetic structure and evolutionary potential of host-parasite interactions.

              Measures of population genetic structure and diversity of disease-causing organisms are commonly used to draw inferences regarding their evolutionary history and potential to generate new variation in traits that determine interactions with their hosts. Parasite species exhibit a range of population structures and life-history strategies, including different transmission modes, life-cycle complexity, off-host survival mechanisms and dispersal ability. These are important determinants of the frequency and predictability of interactions with host species. Yet the complex causal relationships between spatial structure, life history and the evolutionary dynamics of parasite populations are not well understood. We demonstrate that a clear picture of the evolutionary potential of parasitic organisms and their demographic and evolutionary histories can only come from understanding the role of life history and spatial structure in influencing population dynamics and epidemiological patterns.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                13 April 2015
                2015
                : 10
                : 4
                Affiliations
                [1 ]Department of Ecology and Evolutionary Biology, Tulane University, New Orleans, LA, 70118, United States of America
                [2 ]Tulane-Xavier Center for Bioenvironmental Research, Tulane University, New Orleans, LA, 70118, United States of America
                [3 ]School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA, 98195, United States of America
                Bournemouth University, UNITED KINGDOM
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: CGS MB DH. Performed the experiments: CGS. Analyzed the data: CGS. Contributed reagents/materials/analysis tools: MB DH TQ. Wrote the paper: CGS MB TQ DH. Obtained specimens: DH TQ.

                Article
                PONE-D-14-40993
                10.1371/journal.pone.0122307
                4395347
                25874710

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

                Page count
                Figures: 2, Tables: 3, Pages: 17
                Product
                Funding
                Laboratory funding was provided by the Newcomb College Institute at Tulane University ( http://tulane.edu/newcomb/).
                Categories
                Research Article
                Custom metadata
                All relevant data are within the paper and its Supporting Information files. Sequences have been uploaded to Genbank with the following accession numbers: KP864727 - KP865752.

                Uncategorized

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