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      The complete mitochondrial genome of the intertidal spider ( Desis jiaxiangi) provides novel insights into the adaptive evolution of the mitogenome and the evolution of spiders

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          Abstract

          Background

          Although almost all extant spider species live in terrestrial environments, a few species live fully submerged in freshwater or seawater. The intertidal spiders (genus Desis) built silk nests within coral crevices can survive submerged in high tides. The diving bell spider, Argyroneta aquatica, resides in a similar dynamic environment but exclusively in freshwater. Given the pivotal role played by mitochondria in supplying most energy for physiological activity via oxidative phosphorylation and the environment, herein we sequenced the complete mitogenome of Desis jiaxiangi to investigate the adaptive evolution of the aquatic spider mitogenomes and the evolution of spiders.

          Results

          We assembled a complete mitogenome of the intertidal spider Desis jiaxiangi and performed comparative mitochondrial analyses of data set comprising of Desis jiaxiangi and other 45 previously published spider mitogenome sequences, including that of Argyroneta aquatica. We found a unique transposition of trnL2 and trnN genes in Desis jiaxiangi. Our robust phylogenetic topology clearly deciphered the evolutionary relationships between Desis jiaxiangi and Argyroneta aquatica as well as other spiders. We dated the divergence of Desis jiaxiangi and Argyroneta aquatica to the late Cretaceous at ~ 98 Ma. Our selection analyses detected a positive selection signal in the nd4 gene of the aquatic branch comprising both Desis jiaxiangi and Argyroneta aquatica. Surprisingly, Pirata subpiraticus, Hypochilus thorelli, and Argyroneta aquatica each had a higher Ka/Ks value in the 13 PCGs dataset among 46 taxa with complete mitogenomes, and these three species also showed positive selection signal in the nd6 gene.

          Conclusions

          Our finding of the unique transposition of trnL2 and trnN genes indicates that these genes may have experienced rearrangements in the history of intertidal spider evolution. The positive selection signals in the nd4 and nd6 genes might enable a better understanding of the spider metabolic adaptations in relation to different environments. Our construction of a novel mitogenome for the intertidal spider thus sheds light on the evolutionary history of spiders and their mitogenomes.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12862-021-01803-y.

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          Most cited references48

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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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              New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0.

              PhyML is a phylogeny software based on the maximum-likelihood principle. Early PhyML versions used a fast algorithm performing nearest neighbor interchanges to improve a reasonable starting tree topology. Since the original publication (Guindon S., Gascuel O. 2003. A simple, fast and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52:696-704), PhyML has been widely used (>2500 citations in ISI Web of Science) because of its simplicity and a fair compromise between accuracy and speed. In the meantime, research around PhyML has continued, and this article describes the new algorithms and methods implemented in the program. First, we introduce a new algorithm to search the tree space with user-defined intensity using subtree pruning and regrafting topological moves. The parsimony criterion is used here to filter out the least promising topology modifications with respect to the likelihood function. The analysis of a large collection of real nucleotide and amino acid data sets of various sizes demonstrates the good performance of this method. Second, we describe a new test to assess the support of the data for internal branches of a phylogeny. This approach extends the recently proposed approximate likelihood-ratio test and relies on a nonparametric, Shimodaira-Hasegawa-like procedure. A detailed analysis of real alignments sheds light on the links between this new approach and the more classical nonparametric bootstrap method. Overall, our tests show that the last version (3.0) of PhyML is fast, accurate, stable, and ready to use. A Web server and binary files are available from http://www.atgc-montpellier.fr/phyml/.
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                Author and article information

                Contributors
                lifan@genomics.cn
                lvyunyun@njtc.edu.cn
                wenzhengyong@genomics.cn
                bianchao@genomics.cn
                zhangxinhui@genomics.cn
                guoshengtao@genomics.cn
                shiqiong@genomics.cn
                dbslidq@nus.edu.sg
                Journal
                BMC Ecol Evol
                BMC Ecol Evol
                BMC Ecology and Evolution
                BioMed Central (London )
                2730-7182
                30 April 2021
                30 April 2021
                2021
                : 21
                : 72
                Affiliations
                [1 ]GRID grid.410726.6, ISNI 0000 0004 1797 8419, College of Life Sciences, , University of Chinese Academy of Sciences, ; Beijing, 100049 China
                [2 ]GRID grid.21155.32, ISNI 0000 0001 2034 1839, Shenzhen Key Lab of Marine Genomics, Guangdong Provincial Key Lab of Molecular Breeding in Marine Economic Animals, , BGI Academy of Marine Sciences, BGI Marine, BGI, ; Shenzhen, 518083 China
                [3 ]GRID grid.34418.3a, ISNI 0000 0001 0727 9022, Centre for Behavioural Ecology and Evolution, School of Life Sciences, , Hubei University, ; Wuhan, 430062 Hubei China
                [4 ]GRID grid.464376.4, ISNI 0000 0004 1759 6007, Key Laboratory of Sichuan Province for Fishes Conservation and Utilization in the Upper Reaches of the Yangtze River, College of Life Sciences, , Neijiang Normal University, ; Neijiang, 641100 China
                [5 ]GRID grid.4280.e, ISNI 0000 0001 2180 6431, Department of Biological Sciences, , National University of Singapore, ; Singapore, 117543 Singapore
                Author information
                http://orcid.org/0000-0001-5449-6812
                Article
                1803
                10.1186/s12862-021-01803-y
                8086345
                33931054
                0e07e173-6aa1-4a6a-a7e0-24b8e6456ed9
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 9 November 2020
                : 22 April 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: NSFC-31872229
                Award Recipient :
                Funded by: Singapore Ministry of Education AcRF Tier 1 grant
                Award ID: R-154-000-A52-114
                Award ID: R-154-000-B72-114
                Award Recipient :
                Funded by: Grant Plan for Demonstration City Project for Marine Economic Development in Shenzhen
                Award ID: 86
                Funded by: FundRef http://dx.doi.org/10.13039/501100004543, China Scholarship Council;
                Award ID: CSC202004910573
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2021

                mitogenome,phylogeny,evolution,positive selection,desis jiaxiangi,argyroneta aquatica

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