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      The genetic diversity and population structure of two endemic Amazonian quillwort ( Isoetes L.) species

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          Abstract

          Background

          Two endemic lycophyte species Isoetes cangae and Isoetes serracarajensis have been recently described in the State of Pará in the Amazon forest located in northern Brazil. Isoetes L. has survived through three mass extinctions. Plants are considered small-sized, heterosporous, and can display a great diversity of physiological adaptations to different environments. Thus, the current study aimed to estimate the genetic variation of the populations of I. cangae and I. serracarajensis to generate information about their different mechanisms for survival at the same geographical location that could point to different reproductive, adaptative and dispersal strategies and should be considered for effective conservation strategies.

          Methods

          The genetic diversity and population structure of I. cangae and I. serracarajensis were investigated using Inter Simple Sequence Repeat (ISSR) molecular markers. Total genomic DNA was isolated, and the genetic diversity parameters were calculated.

          Results

          The sixteen primers produced 115 reproducible bands, 87% of which were polymorphic. A high level of polymorphic loci (81.74% and 68.48%) and a high Shannon index (Sh = 0.376 and 0.289) were observed for I. cangae and I. serracarajensis, respectively. The coefficient of genetic differentiation between population areas (G ST) showed a higher value in I. serracarajensis (0.5440). Gene flow was higher in I. cangae (1.715) and lower in I. serracarajensis populations (0.419). Overall, the results further show that I. serracarajensis and I. cangae are two species with considerable genetic variation and that these differences may reflect their habitats and modes of reproduction. These results should be considered in the development of effective conservation strategies for both species.

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          Most cited references41

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          MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets.

          We present the latest version of the Molecular Evolutionary Genetics Analysis (Mega) software, which contains many sophisticated methods and tools for phylogenomics and phylomedicine. In this major upgrade, Mega has been optimized for use on 64-bit computing systems for analyzing larger datasets. Researchers can now explore and analyze tens of thousands of sequences in Mega The new version also provides an advanced wizard for building timetrees and includes a new functionality to automatically predict gene duplication events in gene family trees. The 64-bit Mega is made available in two interfaces: graphical and command line. The graphical user interface (GUI) is a native Microsoft Windows application that can also be used on Mac OS X. The command line Mega is available as native applications for Windows, Linux, and Mac OS X. They are intended for use in high-throughput and scripted analysis. Both versions are available from www.megasoftware.net free of charge.
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            GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research—an update

            Summary: GenAlEx: Genetic Analysis in Excel is a cross-platform package for population genetic analyses that runs within Microsoft Excel. GenAlEx offers analysis of diploid codominant, haploid and binary genetic loci and DNA sequences. Both frequency-based (F-statistics, heterozygosity, HWE, population assignment, relatedness) and distance-based (AMOVA, PCoA, Mantel tests, multivariate spatial autocorrelation) analyses are provided. New features include calculation of new estimators of population structure: G′ST, G′′ST, Jost’s D est and F′ST through AMOVA, Shannon Information analysis, linkage disequilibrium analysis for biallelic data and novel heterogeneity tests for spatial autocorrelation analysis. Export to more than 30 other data formats is provided. Teaching tutorials and expanded step-by-step output options are included. The comprehensive guide has been fully revised. Availability and implementation: GenAlEx is written in VBA and provided as a Microsoft Excel Add-in (compatible with Excel 2003, 2007, 2010 on PC; Excel 2004, 2011 on Macintosh). GenAlEx, and supporting documentation and tutorials are freely available at: http://biology.anu.edu.au/GenAlEx. Contact: rod.peakall@anu.edu.au
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              The detection of disease clustering and a generalized regression approach.

              N Mantel (1967)
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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                peerj
                peerj
                PeerJ
                PeerJ Inc. (San Diego, USA )
                2167-8359
                9 November 2020
                2020
                : 8
                : e10274
                Affiliations
                [1 ]Instituto de Sustentabilidade e Biodiversidade, Universidade Federal do Rio de Janeiro , Macaé, Rio de Janeiro, Brazil
                [2 ]Laboratório de Melhoramento Genético Vegetal, Universidade Estadual do Norte Fluminense , Campos dos Goytacazes, Rio de Janeiro, Brazil
                [3 ]Environmental Studies Office, Vale , Belo Horizonte, Minas Gerais, Brazil
                [4 ]Instituto Tecnológico Vale , Belém, Pará, Brazil
                Article
                10274
                10.7717/peerj.10274
                7659625
                66c92270-bafb-4975-b3c3-238d29e3abec
                ©2020 Santos et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                History
                : 13 May 2020
                : 8 October 2020
                Funding
                Funded by: Fundacao Coppetec
                Award ID: 20734
                This work was supported by Fundacao Coppetec (no. 20734). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Conservation Biology
                Genetics
                Plant Science
                Natural Resource Management

                isoetes cangae,isoetes serracarajensis,issr,lycophyte,gene flow,mating system

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