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      Genetic variation and genetic structure within metapopulations of two closely related selfing and outcrossing Zingiber species (Zingiberaceae)

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          Abstract

          Habitat fragmentation strongly affects the genetic diversity of plant populations, and this has always attracted much research interest. Although numerous studies have investigated the effects of habitat fragmentation on the genetic diversity of plant populations, fewer studies have compared species with contrasting breeding systems while accounting for phylogenetic distance. Here, we compare the levels of genetic diversity and differentiation within and among subpopulations in metapopulations (at fine-scale level) of two closely related Zingiber species, selfing Zingiber corallinum and outcrossing Zingiber nudicarpum. Comparisons of the genetic structure of species from unrelated taxa may be confounded by the effects of correlated ecological traits or/and phylogeny. Thus, we possibly reveal the differences in genetic diversity and spatial distribution of genetic variation within metapopulations that relate to mating systems. Compared to outcrossing Z. nudicarpum, the subpopulation genetic diversity in selfing Z. corallinum was significantly lower, but the metapopulation genetic diversity was not different. Most genetic variation resided among subpopulations in selfing Z. corallinum metapopulations, while a significant portion of variation resided either within or among subpopulations in outcrossing Z. nudicarpum, depending on whether the degree of subpopulation isolation surpasses the dispersal ability of pollen and seed. A stronger spatial genetic structure appeared within subpopulations of selfing Z. corallinum potentially due to restricted pollen flow and seed dispersal. In contrast, a weaker genetic structure was apparent in subpopulations of outcrossing Z. nudicarpum most likely caused by extensive pollen movement. Our study shows that high genetic variation can be maintained within metapopulations of selfing Zingiber species, due to increased genetic differentiation intensified primarily by the stochastic force of genetic drift among subpopulations. Therefore, maintenance of natural variability among subpopulations in fragmented areas is key to conserve the full range of genetic diversity of selfing Zingiber species. For outcrossing Zingiber species, maintenance of large populations is an important factor to enhance genetic diversity.

          Compared to outcrossing Z. nudicarpum, the subpopulation genetic diversity in selfing Z. corallinum was significantly lower, but the metapopulation genetic diversity did not differ. Most genetic variation resided among subpopulations in selfing Z. corallinum metapopulations, while a significant portion of variation resided either within or among subpopulations in outcrossing Z. nudicarpum, depending on whether the degree of subpopulation isolation surpasses the dispersal ability of pollen and seed. Our study shows that selfing Z. corallinum could maintain high genetic diversity through differentiation intensified primarily by the stochastic force of genetic drift among subpopulations at fine-scale level, but not local adaptation.

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          Most cited references 81

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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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            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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              Spatial patterns of seed dispersal, their determinants and consequences for recruitment.

              Growing interest in spatial ecology is promoting new approaches to the study of seed dispersal, one of the key processes determining the spatial structure of plant populations. Seed-dispersion patterns vary among plant species, populations and individuals, at different distances from parents, different microsites and different times. Recent field studies have made progress in elucidating the mechanisms behind these patterns and the implications of these patterns for recruitment success. Together with the development and refinement of mathematical models, this promises a deeper, more mechanistic understanding of dispersal processes and their consequences.
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                Author and article information

                Contributors
                Role: Associate Editor
                Journal
                AoB Plants
                AoB Plants
                aobpla
                AoB Plants
                Oxford University Press (US )
                2041-2851
                February 2021
                02 December 2020
                02 December 2020
                : 13
                : 1
                Affiliations
                [1 ] Guangdong Provincial Key Laboratory of Biotechnology for Plant Development, School of Life Sciences, South China Normal University , Guangzhou, China
                [2 ] Guangzhou Key Laboratory of Subtropical Biodiversity and Biomonitoring, School of Life Sciences, South China Normal University , Guangzhou, China
                Author notes
                Corresponding author’s e-mail address: wangyq@ 123456scnu.edu.cn
                Article
                plaa065
                10.1093/aobpla/plaa065
                7788390
                © The Author(s) 2020. Published by Oxford University Press on behalf of the Annals of Botany Company.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                Page count
                Pages: 15
                Product
                Funding
                Funded by: Join Fund of National Natural Science Foundation of China;
                Funded by: Guangdong Provincial Government;
                Award ID: U1301213
                Funded by: National Natural Science Foundation of China, DOI 10.13039/501100001809;
                Award ID: 30770376
                Categories
                Studies
                AcademicSubjects/SCI01210
                Aobpla/1006
                Aobpla/1009
                Aobpla/1011
                Aobpla/1001

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