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      Narrow genetic diversity in germplasm from the Guinean and Sudano-Guinean zones in Benin indicates the need to broaden the genetic base of sweet fig banana ( Musa acuminata cv Sotoumon)

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          Abstract

          Sweet fig ( M. acuminata cv. Sotoumon) is an economically important dessert banana in Benin, with high nutritional, medicinal, and cultural values. Nevertheless, its productivity and yield are threatened by biotic and abiotic stresses. Relevant knowledge of the genetic diversity of this economically important crop is essential for germplasm conservation and the development of breeding programs. However, very little is known about the genetic makeup of this cultivar in Benin. To advance the understanding of genetic diversity in sweet fig banana germplasm, a Genotype-By-Sequencing (GBS) was performed on a panel of 273 accessions collected in different phytogeographical zones of Benin. GBS generated 8,457 quality SNPs, of which 1992 were used for analysis after filtering. The results revealed a low diversity in the studied germplasm (He = 0.0162). Genetic differentiation was overall very low in the collection as suggested by the negative differentiation index (Fstg = -0.003). The Analysis of Molecular Variance (AMOVA) indicated that the variation between accessions within populations accounted for 83.8% of the total variation observed (P < 0.001). The analysis of population structure and neighbor-joining tree partitioned the germplasm into three clusters out of which a predominant major one contained 98.1% of all accessions. These findings demonstrate that current sweet fig banana genotypes shared a common genetic background, which made them vulnerable to biotic and abiotic stress. Therefore, broadening the genetic base of the crop while maintaining its quality attributes and improving yield performance is of paramount importance. Moreover, the large genetic group constitutes an asset for future genomic selection studies in the crop and can guide the profiling of its conservation strategies.

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          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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            Interactive Tree Of Life (iTOL) v5: an online tool for phylogenetic tree display and annotation

            The Interactive Tree Of Life ( https://itol.embl.de ) is an online tool for the display, manipulation and annotation of phylogenetic and other trees. It is freely available and open to everyone. iTOL version 5 introduces a completely new tree display engine, together with numerous new features. For example, a new dataset type has been added (MEME motifs), while annotation options have been expanded for several existing ones. Node metadata display options have been extended and now also support non-numerical categorical values, as well as multiple values per node. Direct manual annotation is now available, providing a set of basic drawing and labeling tools, allowing users to draw shapes, labels and other features by hand directly onto the trees. Support for tree and dataset scales has been extended, providing fine control over line and label styles. Unrooted tree displays can now use the equal-daylight algorithm, proving a much greater display clarity. The user account system has been streamlined and expanded with new navigation options and currently handles >1 million trees from >70 000 individual users. Graphical Abstract iTOL: an online tool for the tree display and annotation.
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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
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: VisualizationRole: Writing – original draft
                Role: Formal analysisRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: ValidationRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: Project administrationRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLOS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                16 November 2023
                2023
                : 18
                : 11
                : e0294315
                Affiliations
                [001] Genetics, Biotechnology and Seed Science Unit (GBioS), Laboratory of Crop Production, Physiology and Plant Breeding (PAGEV), Faculty of Agricultural Sciences (FSA), University of Abomey-Calavi, Abomey-Calavi, Republic of Benin
                International Institute of Tropical Agriculture, KENYA
                Author notes

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

                Author information
                https://orcid.org/0009-0008-3855-7636
                https://orcid.org/0000-0002-1285-245X
                Article
                PONE-D-23-29467
                10.1371/journal.pone.0294315
                10653437
                37972084
                5a632591-0095-4819-94a5-eefd9288d291
                © 2023 Capo-Chichi 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.

                History
                : 11 September 2023
                : 31 October 2023
                Page count
                Figures: 6, Tables: 3, Pages: 21
                Funding
                The author(s) received no specific funding for this work.
                Categories
                Research Article
                Biology and Life Sciences
                Organisms
                Eukaryota
                Plants
                Fruits
                Bananas
                Biology and Life Sciences
                Evolutionary Biology
                Population Genetics
                Biology and Life Sciences
                Genetics
                Population Genetics
                Biology and Life Sciences
                Population Biology
                Population Genetics
                Biology and Life Sciences
                Conservation Biology
                Conservation Genetics
                Ecology and Environmental Sciences
                Conservation Science
                Conservation Biology
                Conservation Genetics
                Biology and Life Sciences
                Genetics
                Conservation Genetics
                Biology and Life Sciences
                Agriculture
                Agronomy
                Plant Breeding
                Biology and Life Sciences
                Biogeography
                Phylogeography
                Ecology and Environmental Sciences
                Biogeography
                Phylogeography
                Earth Sciences
                Geography
                Biogeography
                Phylogeography
                Biology and Life Sciences
                Evolutionary Biology
                Population Genetics
                Phylogeography
                Biology and Life Sciences
                Genetics
                Population Genetics
                Phylogeography
                Biology and Life Sciences
                Population Biology
                Population Genetics
                Phylogeography
                Biology and Life Sciences
                Genetics
                Single Nucleotide Polymorphisms
                Biology and Life Sciences
                Genetics
                Plant Genetics
                Crop Genetics
                Biology and Life Sciences
                Plant Science
                Plant Genetics
                Crop Genetics
                People and Places
                Geographical Locations
                Africa
                Benin
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

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