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      Molecular diversity within the genus Laeonereis (Annelida, Nereididae) along the west Atlantic coast: paving the way for integrative taxonomy

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          Abstract

          The polychaete genus Laeonereis (Annelida, Nereididae) occurs over a broad geographic range and extends nearly across the entire Atlantic coast of America, from the USA to Uruguay. Despite the research efforts to clarify its diversity and systematics, mostly by morphological and ecological evidence, there is still uncertainty, mainly concerning the species Laeonereis culveri, which constitutes an old and notorious case of taxonomic ambiguity. Here, we revised the molecular diversity and distribution of Laeonereis species based on a multi-locus approach, including DNA sequence analyses of partial segments of the cytochrome c oxidase subunit I (COI), 16S rRNA, and 28S rRNA genes. We examined Laeonereis specimens collected from 26 sites along the American Atlantic coast from Massachusetts (USA) to Mar del Plata (Argentina). Although no comprehensive morphological examination was performed between different populations, the COI barcodes revealed seven highly divergent MOTUs, with a mean K2P genetic distance of 16.9% (from 6.8% to 21.9%), which was confirmed through four clustering algorithms. All MOTUs were geographically segregated, except for MOTUs 6 and 7 from southeastern Brazil, which presented partially overlapping ranges between Rio de Janeiro and São Paulo coast. Sequence data obtained from 16S rRNA and 28S rRNA markers supported the same MOTU delimitation and geographic segregation as those of COI, providing further evidence for the existence of seven deeply divergent lineages within the genus. The extent of genetic divergence between MOTUs observed in our study fits comfortably within the range reported for species of polychaetes, including Nereididae, thus providing a strong indication that they might constitute separate species. These results may therefore pave the way for integrative taxonomic studies, aiming to clarify the taxonomic status of the Laeonereis MOTUs herein reported.

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          MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets.

          We present the latest version of the Molecular Evolutionary Genetics Analysis (Mega) software, which contains many sophisticated methods and tools for phylogenomics and phylomedicine. In this major upgrade, Mega has been optimized for use on 64-bit computing systems for analyzing larger datasets. Researchers can now explore and analyze tens of thousands of sequences in Mega The new version also provides an advanced wizard for building timetrees and includes a new functionality to automatically predict gene duplication events in gene family trees. The 64-bit Mega is made available in two interfaces: graphical and command line. The graphical user interface (GUI) is a native Microsoft Windows application that can also be used on Mac OS X. The command line Mega is available as native applications for Windows, Linux, and Mac OS X. They are intended for use in high-throughput and scripted analysis. Both versions are available from www.megasoftware.net free of charge.
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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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              jModelTest 2: more models, new heuristics and parallel computing.

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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ Inc. (San Diego, USA )
                2167-8359
                27 May 2021
                2021
                : 9
                : e11364
                Affiliations
                [1 ]Centro de Biologia Molecular e Ambiental, Universidade do Minho , Braga, Portugal
                [2 ]Museu de Zoologia, Universidade Estadual de Campinas , Campinas, São Paulo, Brazil
                [3 ]Institute of Science and Innovation for Bio-Sustainability (IB-S), Universidade do Minho , Braga, Portugal
                [4 ]Programa de Pós-Graduação em Ecologia, Instituto de Biologia, Universidade Federal do Rio de Janeiro , Rio de Janeiro, Brazil
                [5 ]Laboratório de Biodiversidade e Conservação Marinha, Universidade Federal de Santa Catarina , Florianopólis, Santa Catarina, Brazil
                [6 ]Departamento de Biologia Animal, Universidade Estadual de Campinas , Campinas, São Paulo, Brazil
                Author information
                http://orcid.org/0000-0002-1675-1090
                http://orcid.org/0000-0003-4880-3323
                http://orcid.org/0000-0002-2228-2673
                http://orcid.org/0000-0002-2067-9490
                http://orcid.org/0000-0002-3303-1351
                http://orcid.org/0000-0001-5398-3942
                Article
                11364
                10.7717/peerj.11364
                8164838
                147a85d6-4183-4ef0-8222-455236b39b23
                © 2021 Sampieri et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                History
                : 6 August 2020
                : 7 April 2021
                Funding
                Funded by: FAPESP
                Award ID: 2011/50317-5, 2015/25623-6, 2017/06167-5, 2018/10313-0
                Funded by: CNPq
                Award ID: 301551/2019-7
                Funded by: FCT
                Award ID: SFRH/BD/131527/2017
                Funded by: Post-Doctoral Fellowships
                Award ID: BPD1/next-sea/2018, NORTE-01-0145-FEDER-000032
                Funded by: University of Minho’s
                Award ID: UID/BIA/04050/2013 POCI-01-0145-FEDER-007569
                Funded by: CAPES-PNPD
                Award ID: 88882.316714/2019-01
                This work was supported by the FAPESP (Grants n° 2011/50317-5, 2015/25623-6, 2017/06167-5, 2018/10313-0) and CNPq through a productivity grant to A.C.Z.A (301551/2019-7). Marcos AL Teixeira was supported by a PhD fellowship (SFRH/BD/131527/2017) from FCT. Pedro Vieira was supported by a Post-Doctoral Fellowships (BPD1/next-sea/2018, NORTE-01-0145-FEDER-000032). Filipe Costa and the University of Minho’s contribution was supported by the strategic program UID/BIA/04050/2013 POCI-01-0145-FEDER-007569. Victor C Seixas was supported by a Post-Doctoral Fellowship sponsored by CAPES-PNPD (88882.316714/2019-01). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Biodiversity
                Biogeography
                Marine Biology
                Molecular Biology

                polychaeta,multi-locus,dna barcode,molecular identification

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