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      An unexpected genetic diversity pattern and a complex demographic history of a rare medicinal herb, Chinese asparagus ( Asparagus cochinchinensis) in Korea

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          Abstract

          Range-wide population studies of wide spread species are often associated with complex diversity patterns resulting from genetically divergent evolutionary significant units (ESUs). The compound evolutionary history creating such a pattern of diversity can be inferred through molecular analyses. Asparagus cochinchinensis, a medicinally important perennial herb, is in decline due to overharvesting in Korea. Eight A. cochinchinensis populations in Korea and three populations from neighboring countries (China, Japan and Taiwan) were examined using nine nuclear microsatellite loci and three chloroplast microsatellite loci to characterize molecular diversity patterns. The average within-population diversity was limited likely due to long-term bottlenecks observed in all eight populations. High pairwise F ST values indicated that the populations have largely diverged, but the divergences were not correlated with geographic distances. Clustering analyses revealed a highly complex spatial structure pattern associated with two ESUs. Approximate Bayesian Computation (ABC) suggests that the two ESUs split about 21,000 BP were independently introduced to Korea approximately 1,800 years ago, and admixed in secondary contact zones. The two ESUs found in our study may have different habitat preferences and growth conditions, implying that the two genetically divergent groups should be considered not only for conservation and management but also for breeding programs in agricultural areas.

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          Detection of reduction in population size using data from microsatellite loci.

          We demonstrate that the mean ratio of the number of alleles to the range in allele size, which we term M, calculated from a population sample of microsatellite loci, can be used to detect reductions in population size. Using simulations, we show that, for a general class of mutation models, the value of M decreases when a population is reduced in size. The magnitude of the decrease is positively correlated with the severity and duration of the reduction in size. We also find that the rate of recovery of M following a reduction in size is positively correlated with post-reduction population size, but that recovery occurs in both small and large populations. This indicates that M can distinguish between populations that have been recently reduced in size and those which have been small for a long time. We employ M to develop a statistical test for recent reductions in population size that can detect such changes for more than 100 generations with the post-reduction demographic scenarios we examine. We also compute M for a variety of populations and species using microsatellite data collected from the literature. We find that the value of M consistently predicts the reported demographic history for these populations. This method, and others like it, promises to be an important tool for the conservation and management of populations that are in need of intervention or recovery.
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            Comparison of different nuclear DNA markers for estimating intraspecific genetic diversity in plants.

            A compilation was made of 307 studies using nuclear DNA markers for evaluating among- and within-population diversity in wild angiosperms and gymnosperms. Estimates derived by the dominantly inherited markers (RAPD, AFLP, ISSR) are very similar and may be directly comparable. STMS analysis yields almost three times higher values for within-population diversity whereas among-population diversity estimates are similar to those derived by the dominantly inherited markers. Number of sampled plants per population and number of scored microsatellite DNA alleles are correlated with some of the population genetics parameters. In addition, maximum geographical distance between sampled populations has a strong positive effect on among-population diversity. As previously verified with allozyme data, RAPD- and STMS-based analyses show that long-lived, outcrossing, late successional taxa retain most of their genetic variability within populations. By contrast, annual, selfing and/or early successional taxa allocate most of the genetic variability among populations. Estimates for among- and within-population diversity, respectively, were negatively correlated. The only major discrepancy between allozymes and STMS on the one hand, and RAPD on the other hand, concerns geographical range; within-population diversity was strongly affected when the former methods were used but not so in the RAPD-based studies. Direct comparisons between the different methods, when applied to the same plant material, indicate large similarities between the dominant markers and somewhat lower similarity with the STMS-based data, presumably due to insufficient number of analysed microsatellite DNA loci in many studies.
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              Inferring population history with DIY ABC: a user-friendly approach to approximate Bayesian computation

              Summary: Genetic data obtained on population samples convey information about their evolutionary history. Inference methods can extract part of this information but they require sophisticated statistical techniques that have been made available to the biologist community (through computer programs) only for simple and standard situations typically involving a small number of samples. We propose here a computer program (DIY ABC) for inference based on approximate Bayesian computation (ABC), in which scenarios can be customized by the user to fit many complex situations involving any number of populations and samples. Such scenarios involve any combination of population divergences, admixtures and population size changes. DIY ABC can be used to compare competing scenarios, estimate parameters for one or more scenarios and compute bias and precision measures for a given scenario and known values of parameters (the current version applies to unlinked microsatellite data). This article describes key methods used in the program and provides its main features. The analysis of one simulated and one real dataset, both with complex evolutionary scenarios, illustrates the main possibilities of DIY ABC. Availability: The software DIY ABC is freely available at http://www.montpellier.inra.fr/CBGP/diyabc. Contact: j.cornuet@imperial.ac.uk Supplementary information: Supplementary data are also available at http://www.montpellier.inra.fr/CBGP/diyabc
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                Author and article information

                Contributors
                ydkim@hallym.ac.kr
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                5 July 2019
                5 July 2019
                2019
                : 9
                : 9757
                Affiliations
                [1 ]ISNI 0000 0004 0470 5964, GRID grid.256753.0, Multidisciplinary Genome Institute, , Hallym University, ; Chuncheon, 24252 South Korea
                [2 ]ISNI 0000 0004 0470 5964, GRID grid.256753.0, Department of Life Sciences, , Hallym University, ; Chuncheon, 24252 South Korea
                [3 ]ISNI 0000 0004 0400 5474, GRID grid.419519.1, National Institute of Biological Resources, ; Incheon, 22689 South Korea
                [4 ]ISNI 0000 0001 2360 039X, GRID grid.12981.33, State Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, , Sun Yat-sen University, ; Guangzhou, 510275 China
                [5 ]ISNI 0000 0004 0404 0958, GRID grid.463419.d, USDA-ARS, 1500 North Central Avenue, ; Sidney, Montana 59270 USA
                Author information
                http://orcid.org/0000-0003-0277-4926
                Article
                46275
                10.1038/s41598-019-46275-9
                6611897
                31278330
                d4979f78-70f5-4d6e-8398-48b0c3f90ddd
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 26 June 2018
                : 25 June 2019
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100005880, MOE | National Institute of Biological Resources (NIBR);
                Award ID: NIBR201403202
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2019

                Uncategorized
                molecular evolution,genetic variation,genotype,plant evolution
                Uncategorized
                molecular evolution, genetic variation, genotype, plant evolution

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