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      DNA barcoding of Scomberomorus (Scombridae, Actinopterygii) reveals cryptic diversity and misidentifications

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          Abstract

          The genus Scomberomorus is economically important; however, the taxonomic status and phylogenetic relationships in this genus are not clearly resolved, making it difficult to effectively protect and exploit fish resources. To clarify the taxonomic status of Scomberomorus species, mitochondrial cytochrome c oxidase I (COI) gene sequences of 150 samples were analyzed. The average genetic distance among 14 species was approximately 11 times greater than the distances within species, in accordance with the ‘10× rule’ of species identification. Five of the 14 species did not form monophyletic clades based on a Bayesian inference gene tree. The application of four DNA-based species delimitation methods (automatic barcode gap discovery, barcode index numbers, Poisson tree process, and the K/θ method) yielded several key results. (1) Cryptic species were detected within Scomberomorus commerson . (2) A Scomberomorus queenslandicus sample from Australia was misidentified as S. commerson in the Barcode of Life Data System (BOLD). (3) Specimens originally identified as Scomberomorus guttatus was differentiated into four OTUs or species, two in the Yellow, South China, and Java seas, and two in geographically distant areas, one each in the Arabian Sea and the Bay of Bengal. (4) Six specimens from South Africa originally identified as S. plurilineatus most likely do not belong to the species. (5) Specimens identified as S. maculatus and S. regalis were conspecific; however, introgression cannot be ruled out. Our findings revealed cryptic diversity and difficulties in morphological identification of species in the genus Scomberomorus . This study provides scientifically based support for the conservation of germplasm resources of the genus Scomberomorus .

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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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            MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space

            Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site d N /d S rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software.
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              ModelFinder: Fast Model Selection for Accurate Phylogenetic Estimates

              Model-based molecular phylogenetics plays an important role in comparisons of genomic data, and model selection is a key step in all such analyses. We present ModelFinder, a fast model-selection method that greatly improves the accuracy of phylogenetic estimates. The improvement is achieved by incorporating a model of rate-heterogeneity across sites not previously considered in this context, and by allowing concurrent searches of model-space and tree-space.
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                Author and article information

                Contributors
                Role: Data curationRole: MethodologyRole: SoftwareRole: Writing - original draft
                Role: Data curationRole: MethodologyRole: Writing - review and editing
                Role: Formal analysis
                Role: Formal analysis
                Role: Methodology
                Role: Methodology
                Role: Funding acquisitionRole: Writing - review and editing
                Journal
                Zookeys
                Zookeys
                2
                urn:lsid:arphahub.com:pub:45048D35-BB1D-5CE8-9668-537E44BD4C7E
                urn:lsid:zoobank.org:pub:91BD42D4-90F1-4B45-9350-EEF175B1727A
                ZooKeys
                Pensoft Publishers
                1313-2989
                1313-2970
                2022
                14 December 2022
                : 1135
                : 157-170
                Affiliations
                [1 ] Department of Ecology and Institute of Hydrobiology, Jinan University, Guangzhou 510632, China Jinan University Guangzhou China
                [2 ] Chinese Sturgeon Research Institute, China Three Gorges Corporation, Yichang 443100, Hubei, China Chinese Sturgeon Research Institute, China Three Gorges Corporation Yichang China
                [3 ] Hubei Key Laboratory of Three Gorges Project for Conservation of Fishes, Yichang 443100, Hubei, China Hubei Key Laboratory of Three Gorges Project for Conservation of Fishes Yichang China
                Author notes
                Corresponding author: Qun Zhang (tqzhang@jnu.edu.cn)

                Academic editor: Nina Bogutskaya

                Author information
                https://orcid.org/0000-0002-3352-2249
                https://orcid.org/0000-0002-0650-5443
                Article
                93631
                10.3897/zookeys.1135.93631
                9836712
                36761794
                ab112b85-3a0b-403f-8eba-1beef1142aa0
                Xiao-Shu Zeng, Cheng-He Sun, Xiao-Ying Huang, Ye-Ling Lao, Jin-Long Huang, Sha Li, Qun Zhang

                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
                : 18 August 2022
                : 15 November 2022
                Funding
                Funded by: National Key Research and Development Program of China 501100012166 http://doi.org/10.13039/501100012166
                The present study was supported by the National Key R&D Program of China (Grant number 2018YFD0900802); Fishery resources survey of Guangxi Zhuang Autonomous Region (GXZC2022-G3-001062-ZHZB); Director’s Fund of the Hubei Key Laboratory of Three Gorges Project for Conservation of Fishes, China Three Gorges Corporation (0704157) and the Outstanding Innovative Talents Cultivation Funded Programs for Doctoral Students of Jinan University (Project number 2021CXB022).
                Categories
                Research Article
                Scombridae
                Conservation Biology
                Evolutionary biology
                Molecular genetics
                Molecular systematics
                Taxonomy
                Cenozoic
                World

                Animal science & Zoology
                coi,conservation,cryptic species,dna-based species delimitation,mackerel,phylogeny

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