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      Using DNA barcoding to improve invasive pest identification at U.S. ports-of-entry

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          Abstract

          Interception of potential invasive species at ports-of-entry is essential for effective biosecurity and biosurveillance programs. However, taxonomic assessment of the immature stages of most arthropods is challenging; characters for identification are often dependent on adult morphology and reproductive structures. This study aims to strengthen the identification of such specimens through DNA barcoding, with a focus on microlepidoptera. A sample of 241 primarily immature microlepidoptera specimens intercepted at U.S. ports-of-entry from 2007 to 2011 were selected for analysis. From this sample, 201 COI-5P sequences were generated and analyzed for concordance between morphology-based and DNA-based identifications. The retrospective analysis of the data over 10 years (2009 to 2019) using the Barcode of Life Data (BOLD) system demonstrates the importance of establishing and growing DNA barcode reference libraries for use in specimen identification. Additionally, analysis of specimen identification using public data (43.3% specimens identified) vs. non-public data (78.6% specimens identified) highlights the need to encourage researchers to make data publicly accessible. DNA barcoding surpassed morphological identification with 42.3% (public) and 66.7% (non-public) of the sampled specimens achieving a species-level identification, compared to 38.3% species-level identification by morphology. Whilst DNA barcoding was not able to identify all specimens in our dataset, its incorporation into border security programs as an adjunct to morphological identification can provide secondary lines of evidence and lower taxonomic resolution in many cases. Furthermore, with increased globalization, database records need to be clearly annotated for suspected specimen origin versus interception location.

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          Most cited references 49

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          DNA barcodes distinguish species of tropical Lepidoptera.

          Although central to much biological research, the identification of species is often difficult. The use of DNA barcodes, short DNA sequences from a standardized region of the genome, has recently been proposed as a tool to facilitate species identification and discovery. However, the effectiveness of DNA barcoding for identifying specimens in species-rich tropical biotas is unknown. Here we show that cytochrome c oxidase I DNA barcodes effectively discriminate among species in three Lepidoptera families from Area de Conservación Guanacaste in northwestern Costa Rica. We found that 97.9% of the 521 species recognized by prior taxonomic work possess distinctive cytochrome c oxidase I barcodes and that the few instances of interspecific sequence overlap involve very similar species. We also found two or more barcode clusters within each of 13 supposedly single species. Covariation between these clusters and morphological and/or ecological traits indicates overlooked species complexes. If these results are general, DNA barcoding will significantly aid species identification and discovery in tropical settings.
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            GenBank

            GenBank® is a comprehensive database that contains publicly available DNA sequences for more than 165 000 named organisms, obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects. Most submissions are made using the web-based BankIt or standalone Sequin programs and accession numbers are assigned by GenBank staff upon receipt. Daily data exchange with the EMBL Data Library in the UK and the DNA Data Bank of Japan helps to ensure worldwide coverage. GenBank is accessible through NCBI's retrieval system, Entrez, which integrates data from the major DNA and protein sequence databases along with taxonomy, genome, mapping, protein structure and domain information, and the biomedical journal literature via PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of the GenBank database are available by FTP. To access GenBank and its related retrieval and analysis services, go to the NCBI Homepage at http://www.ncbi.nlm.nih.gov.
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              Does the DNA barcoding gap exist? – a case study in blue butterflies (Lepidoptera: Lycaenidae)

              Background DNA barcoding, i.e. the use of a 648 bp section of the mitochondrial gene cytochrome c oxidase I, has recently been promoted as useful for the rapid identification and discovery of species. Its success is dependent either on the strength of the claim that interspecific variation exceeds intraspecific variation by one order of magnitude, thus establishing a "barcoding gap", or on the reciprocal monophyly of species. Results We present an analysis of intra- and interspecific variation in the butterfly family Lycaenidae which includes a well-sampled clade (genus Agrodiaetus) with a peculiar characteristic: most of its members are karyologically differentiated from each other which facilitates the recognition of species as reproductively isolated units even in allopatric populations. The analysis shows that there is an 18% overlap in the range of intra- and interspecific COI sequence divergence due to low interspecific divergence between many closely related species. In a Neighbour-Joining tree profile approach which does not depend on a barcoding gap, but on comprehensive sampling of taxa and the reciprocal monophyly of species, at least 16% of specimens with conspecific sequences in the profile were misidentified. This is due to paraphyly or polyphyly of conspecific DNA sequences probably caused by incomplete lineage sorting. Conclusion Our results indicate that the "barcoding gap" is an artifact of insufficient sampling across taxa. Although DNA barcodes can help to identify and distinguish species, we advocate using them in combination with other data, since otherwise there would be a high probability that sequences are misidentified. Although high differences in DNA sequences can help to identify cryptic species, a high percentage of well-differentiated species has similar or even identical COI sequences and would be overlooked in an isolated DNA barcoding approach.
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                Author and article information

                Contributors
                Role: Data curationRole: Formal analysisRole: InvestigationRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: MethodologyRole: ResourcesRole: ValidationRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: MethodologyRole: ValidationRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                17 September 2019
                2019
                : 14
                : 9
                Affiliations
                [1 ] Department of Integrated Biology, University of Guelph, Guelph, Ontario, Canada
                [2 ] Entomology Department, National Museum of Natural History, Smithsonian Institution, Washington, D.C., United States of America
                Universita degli Studi di Milano-Bicocca, ITALY
                Author notes

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

                Article
                PONE-D-19-14651
                10.1371/journal.pone.0222291
                6748562
                31527883

                This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

                Page count
                Figures: 2, Tables: 0, Pages: 15
                Product
                Funding
                This project was funded in part through Growing Forward, a federal provincial-territorial initiative with funding awarded to RH. The Agricultural Adaptation Council assists in the delivery of Growing Forward programs in Ontario. Additional funding was provided by Flowers Canada (Ontario) Inc. and the Ontario Ministry of Agriculture and Food, and Rural Affairs (OMAFRA) to RH. The sponsors did not play a role in the study design, data collection and analysis, decision to publish, or preparation of this manuscript.
                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
                Taxonomy
                Computer and Information Sciences
                Data Management
                Taxonomy
                Ecology and Environmental Sciences
                Species Colonization
                Invasive Species
                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
                Computer and Information Sciences
                Data Management
                Metadata
                Biology and life sciences
                Genetics
                DNA
                DNA libraries
                Biology and life sciences
                Biochemistry
                Nucleic acids
                DNA
                DNA libraries
                Research and Analysis Methods
                Storage and Handling
                Specimen Storage
                Research and Analysis Methods
                Database and Informatics Methods
                Bioinformatics
                Sequence Analysis
                Custom metadata
                Data are currently available on the BOLD system under the dataset DS-ITLP. The DOI for this data is doi.org/10.5883/DS-ITLP.

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