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      Mitogenomic Characterization of South African Leopards and the Effect of Past Climatic Events

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          Abstract

          Revealing phylogeographic structure is important for accurate subspecies delineation and understanding a species’ evolutionary history. In leopards (Panthera pardus), there are currently nine subspecies recognized. On the African continent, only one subspecies occurs (P. p. pardus), although mitochondrial DNA from historical samples suggests the presence of three putative continental clades: (1) West Africa (WA), (2) Central Africa (CA), and (3) Southern Africa (SA). So far, whole genome data did not recover this phylogeographic structure, although leopards in the southern periphery of their distribution range in Africa have not yet been investigated in detail. The Mpumalanga province of South Africa is of particular interest, as here, the CA and the SA clade possibly meet. The aim of this study was to characterize the first mitogenomes of African leopards from Mpumalanga, to help clarifying how South African leopards fit into continental patterns of genetic differentiation. Complete mitogenomes from nine leopards, including a strawberry leopard, were assembled de novo and included in phylogenetic analysis, in combination with 32 publicly available mitogenomes. Bayesian inference and maximum likelihood analyses identified two deeply diverged putative clades within South Africa, which were more genetically distinct than two subspecies in Asia. The clades dated back to 0.76-0.86 million years ago, indicating that they originated during the climatically unstable Mid-Pleistocene, as seen in other large mammals. The Pleistocene refuge theory states that the maintenance of savanna refugia in East and Southern Africa promoted the divergence between populations. As such, leopards may reflect the unique climatic history of southern Africa, which has resulted in eminent and endemic genetic diversity.

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          Trimmomatic: a flexible trimmer for Illumina sequence data

          Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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            MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

            We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.
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              MEGA11: Molecular Evolutionary Genetics Analysis Version 11

              The Molecular Evolutionary Genetics Analysis (MEGA) software has matured to contain a large collection of methods and tools of computational molecular evolution. Here, we describe new additions that make MEGA a more comprehensive tool for building timetrees of species, pathogens, and gene families using rapid relaxed-clock methods. Methods for estimating divergence times and confidence intervals are implemented to use probability densities for calibration constraints for node-dating and sequence sampling dates for tip-dating analyses. They are supported by new options for tagging sequences with spatiotemporal sampling information, an expanded interactive Node Calibrations Editor , and an extended Tree Explorer to display timetrees. Also added is a Bayesian method for estimating neutral evolutionary probabilities of alleles in a species using multispecies sequence alignments and a machine learning method to test for the autocorrelation of evolutionary rates in phylogenies. The computer memory requirements for the maximum likelihood analysis are reduced significantly through reprogramming, and the graphical user interface has been made more responsive and interactive for very big data sets. These enhancements will improve the user experience, quality of results, and the pace of biological discovery. Natively compiled graphical user interface and command-line versions of MEGA11 are available for Microsoft Windows, Linux, and macOS from www.megasoftware.net .
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                Author and article information

                Contributors
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                Journal
                Journal of Zoological Systematics and Evolutionary Research
                Journal of Zoological Systematics and Evolutionary Research
                Hindawi Limited
                1439-0469
                0947-5745
                May 4 2024
                May 4 2024
                : 2024
                : 1-14
                Affiliations
                [1 ]Institute for Integrated Natural Sciences, Department of Biology, Koblenz University, Koblenz, Germany
                [2 ]Department of Zoology, University of Johannesburg, Johannesburg, South Africa
                [3 ]Department of Biology, Faculty of Science, University of Copenhagen, Copenhagen, Denmark
                [4 ]Institute for Wildlife Management and Nature Conservation, Gödöllő 2100, Hungary
                [5 ]Independent Researcher, Lydenburg, South Africa
                [6 ]Department of Biological Sciences, Faculty of Science, Engineering and Agriculture, University of Venda, Thohoyandou, South Africa
                Article
                10.1155/2024/2174469
                cf945e0b-3777-481c-9847-cfe43fc62206
                © 2024

                https://creativecommons.org/licenses/by/4.0/

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