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      Primitive Genepools of Asian Pears and Their Complex Hybrid Origins Inferred from Fluorescent Sequence-Specific Amplification Polymorphism (SSAP) Markers Based on LTR Retrotransposons

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          Abstract

          Recent evidence indicated that interspecific hybridization was the major mode of evolution in Pyrus. The genetic relationships and origins of the Asian pear are still unclear because of frequent hybrid events, fast radial evolution, and lack of informative data. Here, we developed fluorescent sequence-specific amplification polymorphism (SSAP) markers with lots of informative sites and high polymorphism to analyze the population structure among 93 pear accessions, including nearly all species native to Asia. Results of a population structure analysis indicated that nearly all Asian pear species experienced hybridization, and originated from five primitive genepools. Four genepools corresponded to four primary Asian species: P. betulaefolia, P. pashia, P. pyrifolia, and P. ussuriensis. However, cultivars of P. ussuriensis were not monophyletic and introgression occurred from P. pyrifolia. The specific genepool detected in putative hybrids between occidental and oriental pears might be from occidental pears. The remaining species, including P. calleryana, P. xerophila, P. sinkiangensis, P. phaeocarpa, P. hondoensis, and P. hopeiensis in Asia, were inferred to be of hybrid origins and their possible genepools were identified. This study will be of great help for understanding the origin and evolution of Asian pears.

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          Most cited references 25

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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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            Inference of population structure using multilocus genotype data.

            We describe a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations. We assume a model in which there are K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned (probabilistically) to populations, or jointly to two or more populations if their genotypes indicate that they are admixed. Our model does not assume a particular mutation process, and it can be applied to most of the commonly used genetic markers, provided that they are not closely linked. Applications of our method include demonstrating the presence of population structure, assigning individuals to populations, studying hybrid zones, and identifying migrants and admixed individuals. We show that the method can produce highly accurate assignments using modest numbers of loci-e.g. , seven microsatellite loci in an example using genotype data from an endangered bird species. The software used for this article is available from http://www.stats.ox.ac.uk/ approximately pritch/home. html.
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              CLUMPP: a cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure.

              Clustering of individuals into populations on the basis of multilocus genotypes is informative in a variety of settings. In population-genetic clustering algorithms, such as BAPS, STRUCTURE and TESS, individual multilocus genotypes are partitioned over a set of clusters, often using unsupervised approaches that involve stochastic simulation. As a result, replicate cluster analyses of the same data may produce several distinct solutions for estimated cluster membership coefficients, even though the same initial conditions were used. Major differences among clustering solutions have two main sources: (1) 'label switching' of clusters across replicates, caused by the arbitrary way in which clusters in an unsupervised analysis are labeled, and (2) 'genuine multimodality,' truly distinct solutions across replicates. To facilitate the interpretation of population-genetic clustering results, we describe three algorithms for aligning multiple replicate analyses of the same data set. We have implemented these algorithms in the computer program CLUMPP (CLUster Matching and Permutation Program). We illustrate the use of CLUMPP by aligning the cluster membership coefficients from 100 replicate cluster analyses of 600 chickens from 20 different breeds. CLUMPP is freely available at http://rosenberglab.bioinformatics.med.umich.edu/clumpp.html.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                12 February 2016
                2016
                : 11
                : 2
                Affiliations
                [1 ]Department of Horticulture, The State Agricultural Ministry Key Laboratory of Horticultural Plant Growth, Development and Quality Improvement, Zhejiang University, Hangzhou, Zhejiang 310058, China
                [2 ]Forest & Fruit Tree Institute, Shanghai Academy of Agricultural Sciences, Shanghai, 201403, China
                [3 ]Institute of Horticulture and Landscape, College of Ecology, Lishui University, Lishui, Zhejiang 323000, China
                [4 ]Department of Biotechnology, Mirpur University of Science and Technology (MUST), Main Allama Iqbal Road, Mirpur, Azad Kashmir-10250, Pakistan
                [5 ]Institute of Horticulture, Zhejiang Academy of Agricultural Sciences, Hangzhou, Zhejiang Province, China
                NARO Institute of Fruit Tree Science, JAPAN
                Author notes

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

                Conceived and designed the experiments: SJ YT DC. Performed the experiments: SJ PY MA. Analyzed the data: SJ XZ XY. Wrote the paper: SJ YT DC.

                Article
                PONE-D-15-53195
                10.1371/journal.pone.0149192
                4752223
                26871452
                © 2016 Jiang 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.

                Page count
                Figures: 4, Tables: 3, Pages: 17
                Product
                Funding
                This research was funded by a Grant from the National Natural Science Foundation of China (No. 31201592, http://www.nsfc.gov.cn/) awarded to DC, and a Specialized Research Fund for the Doctoral Program of Higher Education (20110101110091, http://www.cutech.edu.cn/cn/index.htm) and a Grant for Innovative Research Team of Zhejiang Province of China (2013TD05, http://www.zjnsf.gov.cn/) awarded to YT. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Agriculture
                Crop Science
                Crops
                Fruits
                Pears
                Biology and Life Sciences
                Organisms
                Plants
                Fruits
                Pears
                Biology and Life Sciences
                Genetics
                Genetic Elements
                Mobile Genetic Elements
                Transposable Elements
                Retrotransposons
                Biology and Life Sciences
                Genetics
                Genomics
                Mobile Genetic Elements
                Transposable Elements
                Retrotransposons
                People and Places
                Geographical Locations
                Asia
                China
                Biology and Life Sciences
                Genetics
                Genomics
                Plant Genomics
                Biology and Life Sciences
                Biotechnology
                Plant Biotechnology
                Plant Genomics
                Biology and Life Sciences
                Plant Science
                Plant Biotechnology
                Plant Genomics
                Biology and Life Sciences
                Genetics
                Plant Genetics
                Plant Genomics
                Biology and Life Sciences
                Plant Science
                Plant Genetics
                Plant Genomics
                Biology and Life Sciences
                Evolutionary Biology
                Evolutionary Genetics
                Biology and Life Sciences
                Evolutionary Biology
                Evolutionary Processes
                Hybridization
                Biology and life sciences
                Molecular biology
                Molecular biology techniques
                Sequencing techniques
                Sequence analysis
                DNA sequence analysis
                Research and analysis methods
                Molecular biology techniques
                Sequencing techniques
                Sequence analysis
                DNA sequence analysis
                Biology and Life Sciences
                Evolutionary Biology
                Evolutionary Processes
                Introgression
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

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