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      Towards retrieving the Promethean treasure: a first molecular assessment of the freshwater fish diversity of Georgia

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          Abstract

          In this study, we provide a first estimation of the molecular diversity of the freshwater fishes of Georgia. In addition to field collections, we integrated DNA barcode data obtained from recent works and public databases (BOLD and NCBI GenBank). Currently, the DNA barcode reference library for freshwater fishes of Georgia comprises 352 DNA barcodes for 50 species, 36 genera and 15 families (52% of total Georgian freshwater fish diversity), from which 162 DNA barcodes belonging to 41 species were newly generated as part of this study. A total of 22 species are reported from the Caspian Sea basin and 31 from the Black Sea basin. Amongst the studied taxa, seven species were found with large interspecific divergences (> 2%) while 11 species were found to share DNA barcodes within our dataset. In the course of the study, we found the first evidence of the existence of Gymnocephalus cernua (Linnaeus, 1758) and also confirm the second occurrence of invasive Rhinogobius lindbergi (Berg, 1933) in Georgia. Based on the evaluation of currently-available barcode data for Georgian fishes, we highlighted major gaps and research needs to further progress DNA-based biodiversity studies in Georgia. Though this study lays a solid base for DNA, based biodiversity assessment and monitoring approaches, further efforts within the recently started CaBOL (Caucasus Barcode Of Life) project are needed to obtain reference data for the species still lacking DNA barcodes.

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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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            MUSCLE: multiple sequence alignment with high accuracy and high throughput.

            We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
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              Biodiversity hotspots for conservation priorities.

              Conservationists are far from able to assist all species under threat, if only for lack of funding. This places a premium on priorities: how can we support the most species at the least cost? One way is to identify 'biodiversity hotspots' where exceptional concentrations of endemic species are undergoing exceptional loss of habitat. As many as 44% of all species of vascular plants and 35% of all species in four vertebrate groups are confined to 25 hotspots comprising only 1.4% of the land surface of the Earth. This opens the way for a 'silver bullet' strategy on the part of conservation planners, focusing on these hotspots in proportion to their share of the world's species at risk.
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                Author and article information

                Contributors
                Journal
                Biodivers Data J
                Biodivers Data J
                1
                urn:lsid:arphahub.com:pub:F9B2E808-C883-5F47-B276-6D62129E4FF4
                urn:lsid:zoobank.org:pub:245B00E9-BFE5-4B4F-B76E-15C30BA74C02
                Biodiversity Data Journal
                Pensoft Publishers
                1314-2836
                1314-2828
                2020
                23 October 2020
                : 8
                : e57862
                Affiliations
                [1 ] Institute of Zoology, Ilia State University, Tbilisi, Georgia Institute of Zoology, Ilia State University Tbilisi Georgia
                [2 ] Zoological Research Museum A. Koenig, Bonn, Germany Zoological Research Museum A. Koenig Bonn Germany
                Author notes
                Corresponding author: Levan Mumladze ( lmumladze@ 123456gmail.com ).

                Academic editor: Rupert Collins

                Author information
                https://orcid.org/0000-0003-2403-0805
                https://orcid.org/0000-0003-1961-1162
                https://orcid.org/0000-0002-2172-6973
                Article
                57862 14492
                10.3897/BDJ.8.e57862
                7599205
                4e542aea-9e5c-4fa1-8cef-8b04f0b47caa
                Giorgi Epitashvili, Matthias Geiger, Jonas J Astrin, Fabian Herder, Bella Japoshvili, Levan Mumladze

                This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 21 August 2020
                : 24 September 2020
                Page count
                Figures: 5, Tables: 1, References: 48
                Funding
                Funded by: Bundesministerium für Bildung und Forschung 501100002347 http://doi.org/10.13039/501100002347
                Categories
                Research Article

                dna barcoding,coi,molecular assessment,caucasus
                dna barcoding, coi, molecular assessment, caucasus

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