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      Dissection of Allelic Variation Underlying Floral and Fruit Traits in Flare Tree Peony ( Paeonia rockii) Using Association Mapping

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          Abstract

          Allelic variation in floral quantitative traits, including the elements of flowers and fruits, is caused by extremely complex regulatory processes. In the genetic improvement of flare tree peony ( Paeonia rockii), a unique ornamental and edible oil woody species in the genus Paeonia, a better understanding of the genetic composition of these complex traits related to flowers and fruits is needed. Therefore, we investigated the genetic diversity and population structure of 160 P. rockii accessions and conducted single-marker association analysis for 19 quantitative flower and fruit traits using 81 EST-SSR markers. The results showed that the population had a high phenotypic diversity (coefficients of variation, 11.87–110.64%) and a high level of genetic diversity (mean number of alleles, N A = 6.09). These accessions were divided into three subgroups by STRUCTURE analysis and a neighbor-joining tree. Furthermore, we also found a low level of linkage disequilibrium between these EST-SSRs and, by single-marker association analysis, identified 134 significant associations, including four flower traits with 11 EST-SSRs and 10 fruit traits with 32 EST-SSRs. Finally, based on the sequence alignment of the associated markers, P280, PS2, PS12, PS27, PS118, PS131, and PS145 may be considered potential loci to increase the yield of flare tree peony. These results laid the foundation for further analysis of the genetic structure of some key traits in P. rockii and had an obvious potential application value in marker-assisted selection breeding.

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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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            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/~pritch/home.html.
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                Author and article information

                Contributors
                Journal
                Front Genet
                Front Genet
                Front. Genet.
                Frontiers in Genetics
                Frontiers Media S.A.
                1664-8021
                11 August 2021
                2021
                : 12
                : 664814
                Affiliations
                [1] 1Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University , Beijing, China
                [2] 2Peony International Institute, School of Landscape Architecture, Beijing Forestry University , Beijing, China
                [3] 3Beijing Key Laboratory of Ornamental Plants Germplasm Innovation & Molecular Breeding, Beijing Forestry University , Beijing, China
                [4] 4Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants of Ministry of Education, Beijing Forestry University , Beijing, China
                [5] 5National Engineering Research Center for Floriculture, Beijing Forestry University , Beijing, China
                [6] 6Beijing Guose Peony Technology Co. Ltd. , Beijing, China
                Author notes

                Edited by: Shang-Qian Xie, Hainan University, China

                Reviewed by: Guoan Shi, Henan University of Science and Technology, China; Rakesh Chahota, Chaudhary Sarwan Kumar Himachal Pradesh Krishi Vishvavidyalaya, India

                This article was submitted to Plant Genomics, a section of the journal Frontiers in Genetics

                Article
                10.3389/fgene.2021.664814
                8385368
                7bb8dfd5-3b9d-4904-b254-9341c2c45873
                Copyright © 2021 Guo, He, Cheng, Zhong, Cheng and Tao.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 06 February 2021
                : 29 June 2021
                Page count
                Figures: 3, Tables: 5, Equations: 0, References: 92, Pages: 16, Words: 12058
                Funding
                Funded by: Special Foundation for National Science and Technology Basic Research Program of China
                Award ID: 2019FY100802
                Funded by: National Key Research and Development Program of China 10.13039/501100012166
                Award ID: 2019YFD1001502
                Funded by: Science and Technology Project of Beijing
                Award ID: Z181100002518001
                Categories
                Genetics
                Original Research

                Genetics
                flare tree peony (p. rockii),ssr markers,floral and fruit traits,association mapping,linkage disequilibrium

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