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      New records of native and introduced fish species in a river basin of Western Ecuador, the Chocó-Darien Ecoregion, using DNA barcoding

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          Abstract

          DNA barcoding, based on mitochondrial markers, is widely applied in species identification and biodiversity studies. The aim of this study was to establish a barcoding reference database of fishes inhabiting the Cube River from Western Ecuador in the Chocó-Darien Global Ecoregion (CGE), a threatened ecoregion with high diversity and endemism, and evaluate the applicability of using barcoding for the identification of fish species. Barcode sequences were obtained from seven orders, 17 families, 23 genera and 26 species, which were validated through phylogenetic analysis, morphological measurements, and literature review. Our results showed that 43% of fish species in this region are endemic, confirmed the presence of known species in the area, and included the addition of three new records of native ( Hoplias microlepis, Rhamdia guatemalensis and Sicydium salvini) and an introduced species ( Xiphophorus maculatus) to Ecuador. In addition, eight species were barcoded for the first time. Species identification based on barcoding and morphology showed discrepancy with species lists from previous studies in the CGE, suggesting that the current baseline of western fishes of Ecuador is still incomplete. Because this study analyzed fishes from a relatively small basin (165 km 2), more molecular-based studies focusing on fish are needed to achieve a robust sequence reference library of species inhabiting Western Ecuador. The new sequences of this study will be useful for future comparisons and biodiversity monitoring, supporting the application of barcoding tools for studying fish diversity in genetically unexplored regions and to develop well-informed conservation programs.

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          Most cited references65

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          Basic local alignment search tool.

          A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straightforward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity.
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            MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform.

            K Katoh (2002)
            A multiple sequence alignment program, MAFFT, has been developed. The CPU time is drastically reduced as compared with existing methods. MAFFT includes two novel techniques. (i) Homo logous regions are rapidly identified by the fast Fourier transform (FFT), in which an amino acid sequence is converted to a sequence composed of volume and polarity values of each amino acid residue. (ii) We propose a simplified scoring system that performs well for reducing CPU time and increasing the accuracy of alignments even for sequences having large insertions or extensions as well as distantly related sequences of similar length. Two different heuristics, the progressive method (FFT-NS-2) and the iterative refinement method (FFT-NS-i), are implemented in MAFFT. The performances of FFT-NS-2 and FFT-NS-i were compared with other methods by computer simulations and benchmark tests; the CPU time of FFT-NS-2 is drastically reduced as compared with CLUSTALW with comparable accuracy. FFT-NS-i is over 100 times faster than T-COFFEE, when the number of input sequences exceeds 60, without sacrificing the accuracy.
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              New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0.

              PhyML is a phylogeny software based on the maximum-likelihood principle. Early PhyML versions used a fast algorithm performing nearest neighbor interchanges to improve a reasonable starting tree topology. Since the original publication (Guindon S., Gascuel O. 2003. A simple, fast and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52:696-704), PhyML has been widely used (>2500 citations in ISI Web of Science) because of its simplicity and a fair compromise between accuracy and speed. In the meantime, research around PhyML has continued, and this article describes the new algorithms and methods implemented in the program. First, we introduce a new algorithm to search the tree space with user-defined intensity using subtree pruning and regrafting topological moves. The parsimony criterion is used here to filter out the least promising topology modifications with respect to the likelihood function. The analysis of a large collection of real nucleotide and amino acid data sets of various sizes demonstrates the good performance of this method. Second, we describe a new test to assess the support of the data for internal branches of a phylogeny. This approach extends the recently proposed approximate likelihood-ratio test and relies on a nonparametric, Shimodaira-Hasegawa-like procedure. A detailed analysis of real alignments sheds light on the links between this new approach and the more classical nonparametric bootstrap method. Overall, our tests show that the last version (3.0) of PhyML is fast, accurate, stable, and ready to use. A Web server and binary files are available from http://www.atgc-montpellier.fr/phyml/.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: InvestigationRole: SoftwareRole: VisualizationRole: Writing – review & editing
                Role: Project administrationRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLOS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                8 March 2024
                2024
                : 19
                : 3
                : e0298970
                Affiliations
                [1 ] Laboratorio de Ecología Acuática, Instituto BIOSFERA, Universidad San Francisco de Quito, Quito, Ecuador
                [2 ] Laboratorio de Biología Evolutiva, Instituto BIOSFERA, Universidad San Francisco de Quito, Quito, Ecuador
                DePaul University, UNITED STATES
                Author notes

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

                Author information
                https://orcid.org/0000-0001-6660-4331
                https://orcid.org/0000-0003-0098-978X
                Article
                PONE-D-23-31485
                10.1371/journal.pone.0298970
                10923491
                38457426
                7dffac74-e419-4489-8c95-6a893aa54750
                © 2024 Escobar Camacho 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
                : 27 September 2023
                : 1 February 2024
                Page count
                Figures: 3, Tables: 2, Pages: 17
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100010654, Universidad San Francisco de Quito;
                Award ID: HUBI-17857
                Award Recipient :
                Funded by: DRYing river networks project (DRYvER)
                Award ID: NO 869226
                Award Recipient :
                Funded by: Instituto Biósfera
                Award Recipient :
                JMG received funding from Universidad San Francisco de Quito ( https://www.usfq.edu.ec/es), grant No. HUBI-17857, ACE received funding from the DRYing river networks project (DRYvER) ( https://www.dryver.eu/), grant No. 869226, and DEC received funding from Instituto Biósfera ( https://instituto-biosfera.org/) of USFQ. Sponsors did not play a role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Vertebrates
                Fish
                Freshwater Fish
                Biology and Life Sciences
                Zoology
                Animals
                Vertebrates
                Fish
                Freshwater Fish
                Research and Analysis Methods
                Database and Informatics Methods
                Bioinformatics
                Sequence Analysis
                Sequence Alignment
                People and places
                Geographical locations
                South America
                Ecuador
                Biology and life sciences
                Molecular biology
                Molecular biology techniques
                DNA barcoding
                Research and analysis methods
                Molecular biology techniques
                DNA barcoding
                Biology and life sciences
                Evolutionary biology
                Evolutionary systematics
                Molecular systematics
                DNA barcoding
                Biology and life sciences
                Taxonomy
                Evolutionary systematics
                Molecular systematics
                DNA barcoding
                Computer and information sciences
                Data management
                Taxonomy
                Evolutionary systematics
                Molecular systematics
                DNA barcoding
                Biology and Life Sciences
                Evolutionary Biology
                Evolutionary Systematics
                Phylogenetics
                Phylogenetic Analysis
                Biology and Life Sciences
                Taxonomy
                Evolutionary Systematics
                Phylogenetics
                Phylogenetic Analysis
                Computer and Information Sciences
                Data Management
                Taxonomy
                Evolutionary Systematics
                Phylogenetics
                Phylogenetic Analysis
                Biology and Life Sciences
                Evolutionary Biology
                Evolutionary Processes
                Speciation
                Cryptic Speciation
                Biology and Life Sciences
                Ecology
                Biodiversity
                Ecology and Environmental Sciences
                Ecology
                Biodiversity
                Earth Sciences
                Marine and Aquatic Sciences
                Bodies of Water
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                Ecology and Environmental Sciences
                Aquatic Environments
                Freshwater Environments
                Rivers
                Earth Sciences
                Marine and Aquatic Sciences
                Aquatic Environments
                Freshwater Environments
                Rivers
                Custom metadata
                All sequences are available from the GenBank database. Accession numbers are within the manuscript and its Supporting Information files.

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