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      Parasites specific to centipedes form a new major lineage of terrestrial gregarines

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          Abstract

          Gregarines from the families Dactylophoridae and Trichorhynchidae parasitize exclusively centipedes and have a distinct morphology among other terrestrial eugregarines, but their evolutionary relationships have not yet been studied with molecular methods. Here we obtain rDNA operon sequences for the dactylophorids and trichorhynchids. We describe a new species Trichorhynchus efeykini sp. n. from a scutigeromorph Thereuopoda longicornis from Vietnam. Phylogenetic analyses with combined SSU, 5.8S and LSU rDNA dataset support the previously proposed separation of Trichorhynchus to the Trichorhynchidae based on morphology and recover the dactylophorids and trichorhynchids as sister groups in a monophyletic clade. This clade appears sister to the clade of the Actinocephaloidea and Stylocephaloidea, and represents a new major lineage of terrestrial gregarines that we designate as a new superfamily Dactylophoroidea.

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          Fast gapped-read alignment with Bowtie 2.

          As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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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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              IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era

              Abstract IQ-TREE (http://www.iqtree.org, last accessed February 6, 2020) is a user-friendly and widely used software package for phylogenetic inference using maximum likelihood. Since the release of version 1 in 2014, we have continuously expanded IQ-TREE to integrate a plethora of new models of sequence evolution and efficient computational approaches of phylogenetic inference to deal with genomic data. Here, we describe notable features of IQ-TREE version 2 and highlight the key advantages over other software.

                Author and article information

                Contributors
                provorosenok@gmail.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                2 January 2025
                2 January 2025
                2025
                : 15
                : 192
                Affiliations
                [1 ]Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, ( https://ror.org/05qrfxd25) Leninsky Ave. 33, Moscow, Russian Federation 119071
                [2 ]Joint Vietnam-Russia Tropical Science and Technology Research Center, Hanoi, Vietnam
                [3 ]Belozersky Institute for Physico-Chemical Biology, Lomonosov Moscow State University, ( https://ror.org/010pmpe69) Leninskiye Gory 1, bldg. 40, Moscow, Russian Federation 119991
                [4 ]Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences, ( https://ror.org/05qrfxd25) Bolshoy Karetny Ln. 19, bldg. 1, Moscow, Russian Federation 127051
                [5 ]Faculty of Biology, Lomonosov Moscow State University, ( https://ror.org/010pmpe69) Leninskiye Gory 1, bldg. 12, Moscow, Russian Federation 119234
                Article
                83990
                10.1038/s41598-024-83990-4
                11695991
                39747254
                aa7bd823-53f6-4940-b532-bdc8b8d2125b
                © The Author(s) 2024

                Open Access This 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/.

                History
                : 19 April 2024
                : 18 December 2024
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100006769, Russian Science Foundation;
                Award ID: 24-24-00560
                Award ID: 24-24-00560
                Award Recipient :
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                © Springer Nature Limited 2025

                Uncategorized
                phylogenetics,taxonomy
                Uncategorized
                phylogenetics, taxonomy

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