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      Highlighting Astyanax Species Diversity through DNA Barcoding

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          Abstract

          DNA barcoding has been used extensively to solve taxonomic questions and identify new species. Neotropical fishes are found in a wide variety of shapes and sizes, with a large number of species yet to be described, many of which are very difficult to identify. Characidae is the most species-rich family of the Characiformes, and many of its genera are affected by taxonomic uncertainties, including the widely-distributed, species-rich genus Astyanax. In this study, we present an extensive analysis of Astyanax covering almost its entire area of occurrence, based on DNA barcoding. The use of different approaches (ABGD, GMYC and BIN) to the clustering of the sequences revealed ample consistency in the results obtained by the initial cutoff value of 2% divergence for putative species in the Neighbor-Joining analysis using the Kimura-2-parameter model. The results indicate the existence of five Astyanax lineages. Some groups, such as that composed by the trans-Andean forms, are mostly composed of well-defined species, and in others a number of nominal species are clustered together, hampering the delimitation of species, which in many cases proved impossible. The results confirm the extreme complexity of the systematics of the genus Astyanax and show that DNA barcoding can be an useful tool to address these complexes questions.

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          The promise of DNA barcoding for taxonomy.

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            Sequence-based species delimitation for the DNA taxonomy of undescribed insects.

            Cataloging the very large number of undescribed species of insects could be greatly accelerated by automated DNA based approaches, but procedures for large-scale species discovery from sequence data are currently lacking. Here, we use mitochondrial DNA variation to delimit species in a poorly known beetle radiation in the genus Rivacindela from arid Australia. Among 468 individuals sampled from 65 sites and multiple morphologically distinguishable types, sequence variation in three mtDNA genes (cytochrome oxidase subunit 1, cytochrome b, 16S ribosomal RNA) was strongly partitioned between 46 or 47 putative species identified with quantitative methods of species recognition based on fixed unique ("diagnostic") characters. The boundaries between groups were also recognizable from a striking increase in branching rate in clock-constrained calibrated trees. Models of stochastic lineage growth (Yule models) were combined with coalescence theory to develop a new likelihood method that determines the point of transition from species-level (speciation and extinction) to population-level (coalescence) evolutionary processes. Fitting the location of the switches from speciation to coalescent nodes on the ultrametric tree of Rivacindela produced a transition in branching rate occurring at 0.43 Mya, leading to an estimate of 48 putative species (confidence interval for the threshold ranging from 47 to 51 clusters within 2 logL units). Entities delimited in this way exhibited biological properties of traditionally defined species, showing coherence of geographic ranges, broad congruence with morphologically recognized species, and levels of sequence divergence typical for closely related species of insects. The finding of discontinuous evolutionary groupings that are readily apparent in patterns of sequence variation permits largely automated species delineation from DNA surveys of local communities as a scaffold for taxonomy in this poorly known insect group.
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              Identifying Canadian Freshwater Fishes through DNA Barcodes

              Background DNA barcoding aims to provide an efficient method for species-level identifications using an array of species specific molecular tags derived from the 5′ region of the mitochondrial cytochrome c oxidase I (COI) gene. The efficiency of the method hinges on the degree of sequence divergence among species and species-level identifications are relatively straightforward when the average genetic distance among individuals within a species does not exceed the average genetic distance between sister species. Fishes constitute a highly diverse group of vertebrates that exhibit deep phenotypic changes during development. In this context, the identification of fish species is challenging and DNA barcoding provide new perspectives in ecology and systematics of fishes. Here we examined the degree to which DNA barcoding discriminate freshwater fish species from the well-known Canadian fauna, which currently encompasses nearly 200 species, some which are of high economic value like salmons and sturgeons. Methodology/Principal Findings We bi-directionally sequenced the standard 652 bp “barcode” region of COI for 1360 individuals belonging to 190 of the 203 Canadian freshwater fish species (95%). Most species were represented by multiple individuals (7.6 on average), the majority of which were retained as voucher specimens. The average genetic distance was 27 fold higher between species than within species, as K2P distance estimates averaged 8.3% among congeners and only 0.3% among concpecifics. However, shared polymorphism between sister-species was detected in 15 species (8% of the cases). The distribution of K2P distance between individuals and species overlapped and identifications were only possible to species group using DNA barcodes in these cases. Conversely, deep hidden genetic divergence was revealed within two species, suggesting the presence of cryptic species. Conclusions/Significance The present study evidenced that freshwater fish species can be efficiently identified through the use of DNA barcoding, especially the species complex of small-sized species, and that the present COI library can be used for subsequent applications in ecology and systematics.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                19 December 2016
                2016
                : 11
                : 12
                : e0167203
                Affiliations
                [1 ]Laboratório de Biologia e Genética de Peixes, Departamento de Morfologia, UNESP—Universidade Estadual Paulista, Botucatu, São Paulo, Brazil
                [2 ]Instituto de Biotecnologia da UNESP, UNESP—Universidade Estadual Paulista, Botucatu, São Paulo, Brazil
                [3 ]Universidade Estadual de Maringá, Programa de Pós-Graduação em Ecologia de Ambientes Aquáticos Continentais, Maringá, Paraná, Brazil
                [4 ]Universidade Estadual do Piauí, Campus Alexandre Alves de Oliveira, Parnaíba, Piauí, Brazil
                [5 ]Museu de Ciências Naturais, Fundação Zoobotânica do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
                [6 ]Grupo de Biotaxonomía Morfológica y Molecular de Peces, Instituto de Investigaciones Marinas y Costeras, Universidad Nacional de Mar del Plata. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina
                Centre National de la Recherche Scientifique, FRANCE
                Author notes

                Competing Interests: We don't have competing interests.

                • Conceptualization: BCR CO FF.

                • Data curation: BCR CO FF VAB FAGM CAMO JMDA JJR.

                • Formal analysis: BCR CO FF VAB FAGM CAMO JMDA JJR.

                • Funding acquisition: BCR CO JJR JMDA.

                • Investigation: BCR CO VAB FAGM CAMO JMDA JJR.

                • Methodology: BCR CO FF.

                • Project administration: BCR CO FF.

                • Resources: BCR CO FF JMDA JJR.

                • Supervision: CO FF.

                • Validation: BCR CO FF VAB FAGM CAMO JMDA JJR.

                • Visualization: BCR CO.

                • Writing – original draft: BCR CO.

                • Writing – review & editing: BCR CO FF VAB FAGM CAMO JMDA JJR.

                Author information
                http://orcid.org/0000-0002-5685-9610
                Article
                PONE-D-16-18288
                10.1371/journal.pone.0167203
                5167228
                27992537
                cb387812-7e1f-402d-915c-c26c3294f84c
                © 2016 Rossini 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
                : 5 May 2016
                : 10 November 2016
                Page count
                Figures: 6, Tables: 2, Pages: 20
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100001807, Fundação de Amparo à Pesquisa do Estado de São Paulo;
                Award ID: 00264-2/2011
                Award Recipient :
                Funded by: Fundação de Amparo à Pesquisa do Estado de São Paulo (BR)
                Award ID: 2010/17009-2
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100003593, Conselho Nacional de Desenvolvimento Científico e Tecnológico;
                Award ID: 303854/2009-0
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100002923, Consejo Nacional de Investigaciones Científicas y Técnicas;
                Award ID: D1009
                Award Recipient :
                This investigation was supported by Fundacao de Amparo a Pesquisa do Estado de Sao Paulo ( www.fapesp.br; grant number 00264-2/2011 for BCR and 2010/17009-2 for CO), Consejo Nacional de Investigaciones Cientificas y Tecnicas ( http://www.conicet.gov.ar/; grant number D1009 for JMDA), Conselho Nacional de Desenvolvimento Cientifico e Tecnologico ( http://cnpq.br/; grant number 303854/2009-0 for CO) and Coordenadoria de Aperfeicoamento do Ensino Superior ( https://www.capes.gov.br/).
                Categories
                Research Article
                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
                Organisms
                Animals
                Vertebrates
                Fishes
                Biology and Life Sciences
                Evolutionary Biology
                Evolutionary Processes
                Speciation
                Species Delimitation
                Biology and Life Sciences
                Taxonomy
                Computer and Information Sciences
                Data Management
                Taxonomy
                Biology and Life Sciences
                Molecular Biology
                Molecular Biology Techniques
                Molecular Biology Assays and Analysis Techniques
                Phylogenetic Analysis
                Research and Analysis Methods
                Molecular Biology Techniques
                Molecular Biology Assays and Analysis Techniques
                Phylogenetic Analysis
                Research and Analysis Methods
                Database and Informatics Methods
                Bioinformatics
                Sequence Analysis
                Research and analysis methods
                Database and informatics methods
                Bioinformatics
                Sequence analysis
                DNA sequence analysis
                Research and Analysis Methods
                Database and Informatics Methods
                Biological Databases
                Sequence Databases
                Research and Analysis Methods
                Database and Informatics Methods
                Bioinformatics
                Sequence Analysis
                Sequence Databases
                Custom metadata
                Data are available in the Barcode of Life Database (BOLD): dx.doi.org/10.5883/DS-ABARCODE. The sequences are also available in GenBank, submission BankIt1972027: accessions KY266982—KY268290.

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