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      The InBIO barcoding initiative database: DNA barcodes of Iberian Trichoptera, documenting biodiversity for freshwater biomonitoring in a Mediterranean hotspot

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          Abstract

          Background

          The Trichoptera are an important component of freshwater ecosystems. In the Iberian Peninsula, 380 taxa of caddisflies are known, with nearly 1/3 of the total species being endemic in the region. A reference collection of morphologically identified Trichoptera specimens, representing 142 Iberian taxa, was constructed. The InBIO Barcoding Initiative (IBI) Trichoptera 01 dataset contains records of 438 sequenced specimens. The species of this dataset correspond to about 37% of Iberian Trichoptera species diversity. Specimens were collected between 1975 and 2018 and are deposited in the IBI collection at the CIBIO (Research Center in Biodiversity and Genetic Resources, Portugal) or in the collection Marcos A. González at the University of Santiago de Compostela (Spain).

          New information

          Twenty-nine species, from nine different families, were new additions to the Barcode of Life Data System (BOLD). A success identification rate of over 80% was achieved when comparing morphological identifications and DNA barcodes for the species analysed. This encouraging step advances incorporation of informed Environmental DNA tools in biomonitoring schemes, given the shortcomings of morphological identifications of larvae and adult Caddisflies in such studies. DNA barcoding was not successful in identifying species in six Trichoptera genera: Hydropsyche ( Hydropsychidae ), Athripsodes ( Leptoceridae ), Wormaldia ( Philopotamidae ), Polycentropus ( Polycentropodidae ) Rhyacophila ( Rhyacophilidae ) and Sericostoma ( Sericostomatidae ). The high levels of intraspecific genetic variability found, combined with a lack of a barcode gap and a challenging morphological identification, rendered these species as needing additional studies to resolve their taxonomy.

          Related collections

          Most cited references56

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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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            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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              Biological identifications through DNA barcodes.

              Although much biological research depends upon species diagnoses, taxonomic expertise is collapsing. We are convinced that the sole prospect for a sustainable identification capability lies in the construction of systems that employ DNA sequences as taxon 'barcodes'. We establish that the mitochondrial gene cytochrome c oxidase I (COI) can serve as the core of a global bioidentification system for animals. First, we demonstrate that COI profiles, derived from the low-density sampling of higher taxonomic categories, ordinarily assign newly analysed taxa to the appropriate phylum or order. Second, we demonstrate that species-level assignments can be obtained by creating comprehensive COI profiles. A model COI profile, based upon the analysis of a single individual from each of 200 closely allied species of lepidopterans, was 100% successful in correctly identifying subsequent specimens. When fully developed, a COI identification system will provide a reliable, cost-effective and accessible solution to the current problem of species identification. Its assembly will also generate important new insights into the diversification of life and the rules of molecular evolution.
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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
                2023
                19 January 2023
                : 11
                : e97484
                Affiliations
                [1 ] BIOPOLIS Program in Genomics, Biodiversity and Land Planning, CIBIO, Campus de Vairão, 4485-661 Vairão, Vila do Conde, Portugal BIOPOLIS Program in Genomics, Biodiversity and Land Planning, CIBIO, Campus de Vairão, 4485-661 Vairão Vila do Conde Portugal
                [2 ] European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge, United Kingdom European Molecular Biology Laboratory, European Bioinformatics Institute Hinxton, Cambridge United Kingdom
                [3 ] CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, Universidade do Porto, 4485-661 Vairão, Vila do Conde, Portugal CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, Universidade do Porto, 4485-661 Vairão Vila do Conde Portugal
                [4 ] Departamento de Zoología, Genética y Antropología Física, Facultad de Biología. Universidad de Santiago de Compostela, Santiago de Compostela, Spain Departamento de Zoología, Genética y Antropología Física, Facultad de Biología. Universidad de Santiago de Compostela Santiago de Compostela Spain
                [5 ] Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, 4169-007, Porto, Portugal Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, 4169-007 Porto Portugal
                [6 ] Marshall University, Department of Biological Sciences, Huntington, United States of America Marshall University, Department of Biological Sciences Huntington United States of America
                [7 ] Museu de História Natural e da Ciência da Universidade do Porto, Porto, Portugal Museu de História Natural e da Ciência da Universidade do Porto Porto Portugal
                [8 ] CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Instituto Superior de Agronomia, Universidade de Lisboa, Lisboa, Portugal CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Instituto Superior de Agronomia, Universidade de Lisboa Lisboa Portugal
                [9 ] EBM, Estação Biológica de Mértola, Praça Luís de Camões, Mértola, Portugal EBM, Estação Biológica de Mértola, Praça Luís de Camões Mértola Portugal
                Author notes
                Corresponding author: Sónia Ferreira ( hiporame@ 123456gmail.com ).

                Academic editor: Henrique Paprocki

                Author information
                https://orcid.org/0000-0003-2569-0768
                https://orcid.org/0000-0003-4191-5031
                https://orcid.org/0000-0002-5038-0238
                https://orcid.org/0000-0002-0979-5896
                https://orcid.org/0000-0003-0353-7885
                https://orcid.org/0000-0002-1094-0771
                https://orcid.org/0000-0002-9703-0171
                https://orcid.org/0000-0002-6868-7035
                https://orcid.org/0000-0002-5859-9656
                https://orcid.org/0000-0003-4832-578X
                https://orcid.org/0000-0001-8164-0760
                https://orcid.org/0000-0002-6884-3966
                Article
                97484 21190
                10.3897/BDJ.11.e97484
                10848855
                38327295
                e89456a7-ef83-4afd-8531-0e325f931426
                Joana Pauperio, Luis Martin Gonzalez, Jesus Martinez, Marcos A González, Filipa MS Martins, Joana Veríssimo, Pamela Puppo, Joana Pinto, Cátia Chaves, Catarina J. Pinho, José Manuel Grosso-Silva, Lorenzo Quaglietta, Teresa Luísa L Silva, Pedro Sousa, Paulo Celio Alves, Nuno Fonseca, Pedro Beja, Sónia Ferreira

                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
                : 12 November 2022
                : 28 December 2022
                Page count
                Figures: 2, Tables: 1, References: 50
                Categories
                Data Paper (Biosciences)
                Invertebrata
                Arthropoda
                Insecta
                Trichoptera
                Molecular biology
                Systematics
                Aquatic biology
                Zoology & Animal Biology
                Genetics
                Biodiversity & Conservation
                Europe
                Southern Europe and Mediterranean
                Iberian Peninsula

                trichoptera,occurrence records,species distributions,continental portugal,continental spain,dna barcode,cytochrome c oxidase subunit i (coi)

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