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      Phylogeography of Yersinia ruckeri reveals effects of past evolutionary events on the current strain distribution and explains variations in the global transmission of enteric redmouth (ERM) disease

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          Abstract

          Phylogeographic patterns and population genetic structure of Yersinia ruckeri, the pathological agent of enteric redmouth disease (ERM) in salmonids, were investigated on the basis of concatenated multiloci sequences from isolates of different phenotypes obtained between 1965 and 2009 from diverse areas and hosts. Sequence analyses revealed genetic differentiation among subpopulations with the largest genetic distance occurring between subpopulations of Europe and Canada and/or South America. Bayesian analysis indicated the presence of three ancestral population clusters. Mismatch distribution displayed signatures characteristic of changes in size due to demographic and spatial expansions in the overall Y. ruckeri population, and also in the geographically separate subpopulations. Furthermore, a weak signal of isolation by distance was determined. A significant positive correlation between genetic and geographical distances was observed. These results revealed that the population of Y. ruckeri has undergone both ancient and recent population changes that were probably induced by biogeography forces in the past and, much more recently, by adaptive processes forced by aquaculture expansion. These findings have important implications for future studies on Y. ruckeri population dynamics, on the potential role of genetic structure to explain variations in ERM transmission, and on the effect of past evolutionary events on current estimations of gene flow.

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          Signature of ancient population growth in a low-resolution mitochondrial DNA mismatch distribution.

          A mismatch distribution is a tabulation of the number of pairwise differences among all DNA sequences in a sample. In a population that has been stationary for a long time these distributions from nonrecombinant DNA sequences become ragged and erratic, whereas a population that has been growing generates mismatch distributions that are smooth and have a peak. The position of the peak reflects the time of the population growth. The signature of an ancient population expansion is apparent even in the low-resolution mtDNA typings described by Merriwether et al. (1991). The smoothness of the mismatch distribution, an indicator of population expansion, is hardly affected by population structure, whereas mean sequence divergence increases in a pooled sample from highly isolated subpopulations.
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            Pairwise comparisons of mitochondrial DNA sequences in stable and exponentially growing populations.

            We consider the distribution of pairwise sequence differences of mitochondrial DNA or of other nonrecombining portions of the genome in a population that has been of constant size and in a population that has been growing in size exponentially for a long time. We show that, in a population of constant size, the sample distribution of pairwise differences will typically deviate substantially from the geometric distribution expected, because the history of coalescent events in a single sample of genes imposes a substantial correlation on pairwise differences. Consequently, a goodness-of-fit test of observed pairwise differences to the geometric distribution, which assumes that each pairwise comparison is independent, is not a valid test of the hypothesis that the genes were sampled from a panmictic population of constant size. In an exponentially growing population in which the product of the current population size and the growth rate is substantially larger than one, our analytical and simulation results show that most coalescent events occur relatively early and in a restricted range of times. Hence, the "gene tree" will be nearly a "star phylogeny" and the distribution of pairwise differences will be nearly a Poisson distribution. In that case, it is possible to estimate r, the population growth rate, if the mutation rate, mu, and current population size, N0, are assumed known. The estimate of r is the solution to ri/mu = ln(N0r) - gamma, where i is the average pairwise difference and gamma approximately 0.577 is Euler's constant.
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              Isolation by distance, web service

              Background The population genetic pattern known as "isolation by distance" results from spatially limited gene flow and is a commonly observed phenomenon in natural populations. However, few software programs exist for estimating the degree of isolation by distance among populations, and they tend not to be user-friendly. Results We have created Isolation by Distance Web Service (IBDWS) a user-friendly web interface for determining patterns of isolation by distance. Using this site, population geneticists can perform a variety of powerful statistical tests including Mantel tests, Reduced Major Axis (RMA) regression analysis, as well as calculate F ST between all pairs of populations and perform basic summary statistics (e.g., heterozygosity). All statistical results, including publication-quality scatter plots in Postscript format, are returned rapidly to the user and can be easily downloaded. Conclusion IBDWS population genetics analysis software is hosted at and documentation is available at . The source code has been made available on Source Forge at .
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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                29 October 2015
                2015
                : 6
                : 1198
                Affiliations
                [1] 1Departamento de Microbiología y Parasitología, CIBUS, Universidad de Santiago de Compostela Santiago de Compostela, Spain
                [2] 2Estación de Investigaciones Hidrobiológicas de Guayana, Fundación La Salle de Ciencias Naturales San Félix, Venezuela
                Author notes

                Edited by: Eric Altermann, AgResearch Ltd., New Zealand

                Reviewed by: Michel Drancourt, Université de la Méditerranée, France; Andrey P. Anisimov, State Research Center for Applied Microbiology and Biotechnology, Russia; Ping Li, China University of Geosciences, China

                *Correspondence: Jesús L. Romalde jesus.romalde@ 123456usc.es

                This article was submitted to Evolutionary and Genomic Microbiology, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2015.01198
                4625090
                9daffd3f-b755-4fe0-afe0-cceadb558daa
                Copyright © 2015 Bastardo, Ravelo and Romalde.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 23 July 2015
                : 15 October 2015
                Page count
                Figures: 5, Tables: 4, Equations: 0, References: 57, Pages: 11, Words: 7992
                Funding
                Funded by: Ministerio de Ciencia e Innovación 10.13039/501100004837
                Award ID: AGL2010-18438
                Award ID: AGL2013-42628-R
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                phylogeography,yersinia ruckeri,genetic structure,population changes,aquaculture,bayesian analysis

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