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      Mitochondrial phylogenomics provides insights into the phylogeny and evolution of spiders (Arthropoda: Araneae)

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          Abstract

          Spiders are among the most varied terrestrial predators, with highly diverse morphology, ecology, and behavior. Morphological and molecular data have greatly contributed to advances in the phylogeny and evolutionary dynamics of spiders. Here, we performed comprehensive mitochondrial phylogenomics analysis on 78 mitochondrial genomes (mitogenomes) representing 29 families; of these, 23 species from eight families were newly generated. Mesothelae retained the same gene arrangement as the arthropod ancestor ( Limulus polyphemus), while Opisthothelae showed extensive rearrangement, with 12 rearrangement types in transfer RNAs (tRNAs) and control region. Most spider tRNAs were extremely truncated and lacked typical dihydrouridine or TΨC arms, showing high tRNA structural diversity; in particular, trnS1 exhibited anticodon diversity across the phylogeny. The evolutionary rates of mitochondrial genes were potentially associated with gene rearrangement or truncated tRNAs. Both mitogenomic sequences and rearrangements possessed phylogenetic characteristics, providing a robust backbone for spider phylogeny, as previously reported. The monophyly of suborder, infraorder, retrolateral tibial apophysis clade, and families (except for Pisauridae) was separately supported, and high-level relationships were resolved as (Mesothelae, (Mygalomorphae, (Entelegynae, (Synspermiata, Hypochilidae)))). The phylogenetic positions of several families were also resolved (e.g., Eresidae, Oecobiidae and Titanoecidae). Two reconstructions of ancestral web type obtained almost identical results, indicating that the common ancestor of spiders likely foraged using a silk-lined burrow. This study, the largest mitochondrial phylogenomics analysis of spiders to date, highlights the usefulness of mitogenomic data not only for providing efficient phylogenetic signals for spider phylogeny, but also for characterizing trait diversification in spider evolution.

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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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              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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                Author and article information

                Contributors
                Journal
                Zool Res
                Zool Res
                ZR
                Zoological Research
                Science Press (16 Donghuangchenggen Beijie, Beijing 100717, China )
                2095-8137
                18 July 2022
                : 43
                : 4
                : 566-584
                Affiliations
                [1 ] State Key Laboratory of Grassland Agro-Ecosystems, Lanzhou University, Lanzhou, Gansu 730020, China
                [2 ] College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou, Gansu 730020, China
                [3 ] National Demonstration Center for Experimental Grassland Science Education, Lanzhou University, Lanzhou, Gansu 730020, China
                [4 ] Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, Yunnan 650500, China
                [5 ] Lanzhou University Second Hospital, Lanzhou University, Lanzhou, Gansu 730030, China
                Author notes

                #Authors contributed equally to this work

                Article
                zr-43-4-566
                10.24272/j.issn.2095-8137.2021.418
                9336457
                35638362
                bb9a3450-5e39-4543-bca7-b85091acabe7
                Editorial Office of Zoological Research, Kunming Institute of Zoology, Chinese Academy of Sciences

                This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 27 February 2022
                : 25 May 2022
                Funding
                This study was supported by the Second Tibetan Plateau Scientific Expedition and Research (STEP) Program (2019QZKK0302), Natural Science Foundation of Gansu Province (20JR5RA252), and Innovation and Entrepreneurship Project of Lanzhou University (20210010020, 20210010002)
                Categories
                Article

                spiders,mitochondrial genome,gene rearrangement,truncated trnas,trait evolution,phylogenomics

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