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      Genetic diversity and structure of Saussurea polylepis (Asteraceae) on continental islands of Korea: Implications for conservation strategies and management

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          Abstract

          Saussurea polylepis Nakai is an herbaceous perennial endemic to Korea and is highly restricted to several continental islands in the southwestern part of the Korean Peninsula. Given its very narrow geographical distribution, it is more vulnerable to anthropogenic activities and global climate changes than more widely distributed species. Despite the need for comprehensive genetic information for conservation and management, no such population genetic studies of S. polylepis have been conducted. In this study, genetic diversity and population structure were evaluated for 97 individuals from 5 populations (Gwanmaedo, Gageodo, Hongdo, Heusando, and Uido) using 19 polymorphic microsatellites. The populations were separated by a distance of 20–90 km. We found moderate levels of genetic diversity in S. polylepis ( Ho = 0.42, He = 0.43). This may be due to long lifespans, outcrossing, and gene flow, despite its narrow range. High levels of gene flow ( Nm = 1.76, mean Fst = 0.09), especially from wind-dispersed seeds, would contribute to low levels of genetic differentiation among populations. However, the small population size and reduced number of individuals in the reproductive phase of S. polylepis can be a major threat leading to inbreeding depression and genetic diversity loss. Bayesian cluster analysis revealed three significant structures at K = 3, consistent with DAPC and UPGMA. It is thought that sea level rise after the last glacial maximum may have acted as a geographical barrier, limiting the gene flow that would lead to distinct population structures. We proposed the Heuksando population, which is the largest island inhabited by S. polylepis, as a source population because of its large population size and high genetic diversity. Four management units (Gwanmaedo, Gageodo, Hongdo-Heuksando, and Uido) were suggested for conservation considering population size, genetic diversity, population structure, unique alleles, and geographical location (e.g., proximity).

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          MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms.

          The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation of Mega to enable cross-platform use on Microsoft Windows and Linux operating systems. Mega X does not require virtualization or emulation software and provides a uniform user experience across platforms. Mega X has additionally been upgraded to use multiple computing cores for many molecular evolutionary analyses. Mega X is available in two interfaces (graphical and command line) and can be downloaded from www.megasoftware.net free of charge.
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            Detecting the number of clusters of individuals using the software structure: a simulation study

            The identification of genetically homogeneous groups of individuals is a long standing issue in population genetics. A recent Bayesian algorithm implemented in the software STRUCTURE allows the identification of such groups. However, the ability of this algorithm to detect the true number of clusters (K) in a sample of individuals when patterns of dispersal among populations are not homogeneous has not been tested. The goal of this study is to carry out such tests, using various dispersal scenarios from data generated with an individual-based model. We found that in most cases the estimated 'log probability of data' does not provide a correct estimation of the number of clusters, K. However, using an ad hoc statistic DeltaK based on the rate of change in the log probability of data between successive K values, we found that STRUCTURE accurately detects the uppermost hierarchical level of structure for the scenarios we tested. As might be expected, the results are sensitive to the type of genetic marker used (AFLP vs. microsatellite), the number of loci scored, the number of populations sampled, and the number of individuals typed in each sample.
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              Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows.

              We present here a new version of the Arlequin program available under three different forms: a Windows graphical version (Winarl35), a console version of Arlequin (arlecore), and a specific console version to compute summary statistics (arlsumstat). The command-line versions run under both Linux and Windows. The main innovations of the new version include enhanced outputs in XML format, the possibility to embed graphics displaying computation results directly into output files, and the implementation of a new method to detect loci under selection from genome scans. Command-line versions are designed to handle large series of files, and arlsumstat can be used to generate summary statistics from simulated data sets within an Approximate Bayesian Computation framework. © 2010 Blackwell Publishing Ltd.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Writing – original draft
                Role: ConceptualizationRole: Funding acquisitionRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                8 April 2021
                2021
                : 16
                : 4
                : e0249752
                Affiliations
                [001]Department of Biological Sciences, Sungkyunkwan University, Suwon, Gyeonggi-do, Korea
                University of Massachusetts, UNITED STATES
                Author notes

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

                Author information
                https://orcid.org/0000-0003-0559-6782
                Article
                PONE-D-20-14749
                10.1371/journal.pone.0249752
                8031399
                33831066
                0c34553f-b4b0-420f-aee9-3e94256a3b9a
                © 2021 Yun, Kim

                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.

                History
                : 17 May 2020
                : 24 March 2021
                Page count
                Figures: 5, Tables: 4, Pages: 19
                Funding
                Funded by: National Research Foundation of Korea
                Award ID: NRF-2019R1A2C2009841
                Award Recipient :
                This research was supported in part by the National Research Foundation of Korea (NRF-2019R1A2C2009841) and there was no additional external funding received for this study.
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                Biology and Life Sciences
                Evolutionary Biology
                Population Genetics
                Biology and Life Sciences
                Genetics
                Population Genetics
                Biology and Life Sciences
                Population Biology
                Population Genetics
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                Conservation Biology
                Conservation Genetics
                Ecology and Environmental Sciences
                Conservation Science
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                Ecological Metrics
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                Gene Flow
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                Earth Sciences
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                Population Biology
                Population Genetics
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