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Development of Highly Informative Genome-Wide Single Sequence Repeat Markers for Breeding Applications in Sesame and Construction of a Web Resource: SisatBase

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      Abstract

      The sequencing of the full nuclear genome of sesame ( Sesamum indicum L.) provides the platform for functional analyses of genome components and their application in breeding programs. Although the importance of microsatellites markers or simple sequence repeats (SSR) in crop genotyping, genetics, and breeding applications is well established, only a little information exist concerning SSRs at the whole genome level in sesame. In addition, SSRs represent a suitable marker type for sesame molecular breeding in developing countries where it is mainly grown. In this study, we identified 138,194 genome-wide SSRs of which 76.5% were physically mapped onto the 13 pseudo-chromosomes. Among these SSRs, up to three primers pairs were supplied for 101,930 SSRs and used to in silico amplify the reference genome together with two newly sequenced sesame accessions. A total of 79,957 SSRs (78%) were polymorphic between the three genomes thereby suggesting their promising use in different genomics-assisted breeding applications. From these polymorphic SSRs, 23 were selected and validated to have high polymorphic potential in 48 sesame accessions from different growing areas of Africa. Furthermore, we have developed an online user-friendly database, SisatBase ( http://www.sesame-bioinfo.org/SisatBase/), which provides free access to SSRs data as well as an integrated platform for functional analyses. Altogether, the reference SSR and SisatBase would serve as useful resources for genetic assessment, genomic studies, and breeding advancement in sesame, especially in developing countries.

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      Most cited references 65

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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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          We created a visualization tool called Circos to facilitate the identification and analysis of similarities and differences arising from comparisons of genomes. Our tool is effective in displaying variation in genome structure and, generally, any other kind of positional relationships between genomic intervals. Such data are routinely produced by sequence alignments, hybridization arrays, genome mapping, and genotyping studies. Circos uses a circular ideogram layout to facilitate the display of relationships between pairs of positions by the use of ribbons, which encode the position, size, and orientation of related genomic elements. Circos is capable of displaying data as scatter, line, and histogram plots, heat maps, tiles, connectors, and text. Bitmap or vector images can be created from GFF-style data inputs and hierarchical configuration files, which can be easily generated by automated tools, making Circos suitable for rapid deployment in data analysis and reporting pipelines.
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            Author and article information

            Affiliations
            1Key Laboratory of Biology and Genetic Improvement of Oil Crops, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture Wuhan, China
            2Centre d’Etudes Régional pour l’Amélioration de l’Adaptation à la Sécheresse Thiès, Senegal
            Author notes

            Edited by: Mariela Torres, Instituto Nacional de Tecnología Agropecuaria (INTA), Argentina

            Reviewed by: Harsh Raman, NSW Department of Primary Industries, Australia; Ioannis Ganopoulos, Institute of Plant Breeding and Genetic Resources-ELGO DEMETER, Greece

            *Correspondence: Xiurong Zhang, zhangxr@ 123456oilcrops.cn Ndiaga Cisse, cissendiaga02@ 123456hotmail.com

            These authors have contributed equally to this work.

            This article was submitted to Crop Science and Horticulture, a section of the journal Frontiers in Plant Science

            Contributors
            Journal
            Front Plant Sci
            Front Plant Sci
            Front. Plant Sci.
            Frontiers in Plant Science
            Frontiers Media S.A.
            1664-462X
            22 August 2017
            2017
            : 8
            5572293 10.3389/fpls.2017.01470
            Copyright © 2017 Dossa, Yu, Liao, Cisse and Zhang.

            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) or licensor 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.

            Counts
            Figures: 5, Tables: 3, Equations: 0, References: 65, Pages: 10, Words: 0
            Categories
            Plant Science
            Original Research

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