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      The efficacy of DNA barcoding in the classification, genetic differentiation, and biodiversity assessment of benthic macroinvertebrates

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          Abstract

          Macroinvertebrates have been recognized as key ecological indicators of aquatic environment and are the most commonly used approaches for water quality assessment. However, species identification of macroinvertebrates (especially of aquatic insects) proves to be very difficult due to the lack of taxonomic expertise in some regions and can become time‐consuming. In this study, we evaluated the feasibility of DNA barcoding for the classification of benthic macroinvertebrates and investigated the genetic differentiation in seven orders (Insecta: Ephemeroptera, Plecoptera, Trichoptera, Diptera, Hemiptera, Coleoptera, and Odonata) from four large transboundary rivers of northwest China and further explored its potential application to biodiversity assessment. A total of 1,144 COI sequences, belonging to 176 species, 112 genera, and 53 families were obtained and analyzed. The barcoding gap analysis showed that COI gene fragment yielded significant intra‐ and interspecific divergences and obvious barcoding gaps. NJ phylogenetic trees showed that all species group into monophyletic species clusters whether from the same population or not, except two species ( Polypedilum. laetum and Polypedilum. bullum). The distance‐based (ABGD) and tree‐based (PTP and MPTP) methods were utilized for grouping specimens into Operational Taxonomic Units (OTUs) and delimiting species. The ABGD, PTP, and MPTP analysis were divided into 177 ( p = .0599), 197, and 195 OTUs, respectively. The BIN analysis generated 186 different BINs. Overall, our study showed that DNA barcoding offers an effective framework for macroinvertebrate species identification and sheds new light on the biodiversity assessment of local macroinvertebrates. Also, the construction of DNA barcode reference library of benthic macroinvertebrates in Eurasian transboundary rivers provides a solid backup for bioassessment studies of freshwater habitats using modern high‐throughput technologies in the near future.

          Abstract

          We evaluated the feasibility of DNA barcoding for the classification of benthic macroinvertebrates from four large transboundary rivers of northwest China. Our study shows that DNA barcoding can be used to clarify species boundaries and improve the reliability of environmental and biodiversity assessment in rivers.

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          MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

          We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.
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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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              RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies

              Motivation: Phylogenies are increasingly used in all fields of medical and biological research. Moreover, because of the next-generation sequencing revolution, datasets used for conducting phylogenetic analyses grow at an unprecedented pace. RAxML (Randomized Axelerated Maximum Likelihood) is a popular program for phylogenetic analyses of large datasets under maximum likelihood. Since the last RAxML paper in 2006, it has been continuously maintained and extended to accommodate the increasingly growing input datasets and to serve the needs of the user community. Results: I present some of the most notable new features and extensions of RAxML, such as a substantial extension of substitution models and supported data types, the introduction of SSE3, AVX and AVX2 vector intrinsics, techniques for reducing the memory requirements of the code and a plethora of operations for conducting post-analyses on sets of trees. In addition, an up-to-date 50-page user manual covering all new RAxML options is available. Availability and implementation: The code is available under GNU GPL at https://github.com/stamatak/standard-RAxML. Contact: alexandros.stamatakis@h-its.org Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Contributors
                hainan@mail.hzau.edu.cn
                Journal
                Ecol Evol
                Ecol Evol
                10.1002/(ISSN)2045-7758
                ECE3
                Ecology and Evolution
                John Wiley and Sons Inc. (Hoboken )
                2045-7758
                04 April 2021
                May 2021
                : 11
                : 10 ( doiID: 10.1002/ece3.v11.10 )
                : 5669-5681
                Affiliations
                [ 1 ] Key Laboratory of Freshwater Animal Breeding Ministry of Agriculture and Rural Affair/Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction Ministry of Education College of Fisheries Huazhong Agricultural University Wuhan China
                [ 2 ] Engineering Research Center of Green Development for Conventional Aquatic Biological Industry in the Yangtze River Economic Belt Ministry of Education Wuhan China
                [ 3 ] The Key Laboratory of Aquatic Biodiversity and Conservation Institute of Hydrobiology Chinese Academy of Sciences Wuhan China
                Author notes
                [*] [* ] Correspondence

                Qiong Zhou, College of Fisheries, Huazhong Agricultural University, Wuhan 430070, China.

                Email: hainan@ 123456mail.hzau.edu.cn

                Author information
                https://orcid.org/0000-0003-2481-1409
                https://orcid.org/0000-0003-3262-9834
                https://orcid.org/0000-0001-5118-6683
                Article
                ECE37470
                10.1002/ece3.7470
                8131818
                e14f5744-5c1b-433c-bb05-d72cb5fc87d8
                © 2021 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 26 February 2021
                : 21 May 2020
                : 05 March 2021
                Page count
                Figures: 6, Tables: 0, Pages: 13, Words: 8737
                Funding
                Funded by: Special Funds for the Foundation Work of Science and Technology
                Award ID: 2012FY112700
                Funded by: Finance Special Fund of the Ministry of Agriculture and Rural Affairs (Fisheries Resources and Environment Survey in the Key Water Areas of Northwest China)
                Categories
                Original Research
                Original Research
                Custom metadata
                2.0
                May 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.0.2 mode:remove_FC converted:19.05.2021

                Evolutionary Biology
                benthic macroinvertebrates,biodiversity assessment,dna barcoding,species identification

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