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      Amphidromous but endemic: Population connectivity of Rhinogobius gigas (Teleostei: Gobioidei)

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          Abstract

          Rhinogobius gigas is an amphidromous fish endemic to eastern Taiwan. Fishes with the diadromous behavior are expected to have a broader distribution range and higher genetic homogeneity despite that some amphidromous fishes with limited distribution are observed and R. gigas is an additional exception with a limited distribution range. Rhinogobius gigas has been documented to be retained inshore near the river plume with a short pelagic larval duration of 30–40 days, which may account for the endemism of this species. The short marine larval stage of R. gigas may imply a population genetic structure and the aim of the present study is to test whether the population genetic structure is present in R. gigas. To test the population genetic structure, fragments of mitochondrial displacement loop and cytochrome c oxidase subunit I were sequenced to provide molecular inference for genetic structure among populations. Sixty-nine haplotypes were identified among 191 R. gigas from 10 populations of eastern Taiwan and the mean haplotype and nucleotide diversities for all samples were 0.956 and 0.0024, respectively, implying a bottleneck followed by a recent population expansion further supported by Fu’s Fs (-26.6; p < 0.001) and Tajima’s D (-1.5; p = 0.037) values. The phylogenetic analysis revealed lack of genetic structure and the bush-like median joining network without commonly shared haplotypes supports the same scenario. The genetic homogeneity is probably due to the amphidromous life history providing the opportunity for passive larval transportation among the rivers through coastal currents in eastern Taiwan. The endemism to eastern Taiwan may be a consequence of complicated interactions among short pelagic larval duration, interspecific competition and coastal currents.

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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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            Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7

            Abstract Bayesian inference of phylogeny using Markov chain Monte Carlo (MCMC) plays a central role in understanding evolutionary history from molecular sequence data. Visualizing and analyzing the MCMC-generated samples from the posterior distribution is a key step in any non-trivial Bayesian inference. We present the software package Tracer (version 1.7) for visualizing and analyzing the MCMC trace files generated through Bayesian phylogenetic inference. Tracer provides kernel density estimation, multivariate visualization, demographic trajectory reconstruction, conditional posterior distribution summary, and more. Tracer is open-source and available at http://beast.community/tracer.
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              CONFIDENCE LIMITS ON PHYLOGENIES: AN APPROACH USING THE BOOTSTRAP.

              The recently-developed statistical method known as the "bootstrap" can be used to place confidence intervals on phylogenies. It involves resampling points from one's own data, with replacement, to create a series of bootstrap samples of the same size as the original data. Each of these is analyzed, and the variation among the resulting estimates taken to indicate the size of the error involved in making estimates from the original data. In the case of phylogenies, it is argued that the proper method of resampling is to keep all of the original species while sampling characters with replacement, under the assumption that the characters have been independently drawn by the systematist and have evolved independently. Majority-rule consensus trees can be used to construct a phylogeny showing all of the inferred monophyletic groups that occurred in a majority of the bootstrap samples. If a group shows up 95% of the time or more, the evidence for it is taken to be statistically significant. Existing computer programs can be used to analyze different bootstrap samples by using weights on the characters, the weight of a character being how many times it was drawn in bootstrap sampling. When all characters are perfectly compatible, as envisioned by Hennig, bootstrap sampling becomes unnecessary; the bootstrap method would show significant evidence for a group if it is defined by three or more characters.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: Writing – original draft
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: Writing – original draft
                Role: Data curationRole: Formal analysisRole: InvestigationRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: Writing – review & editing
                Role: Writing – original draft
                Role: Formal analysisRole: Writing – review & editing
                Role: InvestigationRole: Writing – review & editing
                Role: InvestigationRole: Writing – review & editing
                Role: Formal analysisRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                11 February 2021
                2021
                : 16
                : 2
                : e0246406
                Affiliations
                [1 ] Department of Oceanography, National Sun Yat-sen University, Kaohsiung, Taiwan
                [2 ] Department of Life Science, National Taitung University, Taitung, Taiwan
                [3 ] Doctoral Degree Program in Marine Biotechnology, National Sun Yat-sen University, Kaohsiung, Taiwan
                [4 ] Doctoral Degree Program in Marine Biotechnology, Academia Sinica, Taipei, Taiwan
                [5 ] Institute of Oceanography, National Taiwan University, Taipei, Taiwan
                [6 ] Affiliated School of National Tainan First Senior High School, Tainan, Taiwan
                Southwest University, CHINA
                Author notes

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

                Author information
                https://orcid.org/0000-0001-7588-200X
                https://orcid.org/0000-0002-9482-8188
                Article
                PONE-D-20-30110
                10.1371/journal.pone.0246406
                7877787
                33571236
                6f97b184-193a-4b87-90a3-b0e084e34963
                © 2021 Liao et al

                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
                : 2 October 2020
                : 19 January 2021
                Page count
                Figures: 5, Tables: 1, Pages: 14
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100004663, Ministry of Science and Technology, Taiwan;
                Award ID: 106-2923-B-110 -002 -MY3
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100004663, Ministry of Science and Technology, Taiwan;
                Award ID: 107-2311-B-143-001
                Award Recipient :
                This study was supported by grants from the NSYSU-NTTU 2019 academic cooperation project and Ministry of Science and Technology to T.Y.L. (106-2923-B-110 -002 -MY3) and P.L.L. (107-2311-B-143-001). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
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                Evolutionary Biology
                Population Genetics
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