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      Development of genic SSR marker resources from RNA-seq data in Camellia japonica and their application in the genus Camellia

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          Abstract

          Camellia is a genus of flowering plants in the family Theaceae, and several species in this genus have economic importance. Although a great deal of molecular makers has been developed for molecular assisted breeding in genus Camellia in the past decade, the number of simple sequence repeats (SSRs) publicly available for plants in this genus is insufficient. In this study, a total of 28,854 potential SSRs were identified with a frequency of 4.63 kb. A total of 172 primer pairs were synthesized and preliminarily screened in 10 C. japonica accessions, and of these primer pairs, 111 were found to be polymorphic. Fifty-one polymorphic SSR markers were randomly selected to perform further analysis of the genetic relationships of 89 accessions across the genus Camellia. Cluster analysis revealed major clusters corresponding to those based on taxonomic classification and geographic origin. Furthermore, all the genotypes of C. japonica separated and consistently grouped well in the genetic structure analysis. The results of the present study provide high-quality SSR resources for molecular genetic breeding studies in camellia plants.

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          Most cited references34

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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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            KEGG: kyoto encyclopedia of genes and genomes.

            M Kanehisa (2000)
            KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the GENES database, which is a collection of gene catalogs for all the completely sequenced genomes and some partial genomes with up-to-date annotation of gene functions. The higher order functional information is stored in the PATHWAY database, which contains graphical representations of cellular processes, such as metabolism, membrane transport, signal transduction and cell cycle. The PATHWAY database is supplemented by a set of ortholog group tables for the information about conserved subpathways (pathway motifs), which are often encoded by positionally coupled genes on the chromosome and which are especially useful in predicting gene functions. A third database in KEGG is LIGAND for the information about chemical compounds, enzyme molecules and enzymatic reactions. KEGG provides Java graphics tools for browsing genome maps, comparing two genome maps and manipulating expression maps, as well as computational tools for sequence comparison, graph comparison and path computation. The KEGG databases are daily updated and made freely available (http://www. genome.ad.jp/kegg/).
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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
                gavin1982@163.com
                xulin@wuhanagri.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                10 May 2021
                10 May 2021
                2021
                : 11
                : 9919
                Affiliations
                [1 ]GRID grid.495882.a, Forestry and Fruit Tree Research Institute, , Wuhan Academy of Agricultural Sciences, ; Wuhan, 430075 China
                [2 ]GRID grid.35155.37, ISNI 0000 0004 1790 4137, College of Horticulture and Forestry Sciences, , Huazhong Agricultural University, ; Wuhan, 430070 China
                [3 ]GRID grid.35155.37, ISNI 0000 0004 1790 4137, College of Plant Science and Technology, , Huazhong Agricultural University, ; Wuhan, 430070 China
                Article
                89350
                10.1038/s41598-021-89350-w
                8110538
                33972624
                07b9a043-4fe4-48b3-9f9e-82b561de0ad3
                © The Author(s) 2021

                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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 9 November 2020
                : 26 April 2021
                Funding
                Funded by: National Natural Science Foundation of China
                Award ID: 31701965
                Award Recipient :
                Funded by: Hubei Province Major Projects of Technological Innovation
                Award ID: 2017ABA162
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                genetics,plant sciences
                Uncategorized
                genetics, plant sciences

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