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      Molecular phylogeny reveals Varroa mites are not a separate family but a subfamily of Laelapidae

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          Abstract

          Varroa mites, notorious for parasitizing honeybees, are generally classified as Varroidae. Their extremely modified morphologies and behaviors have led to debates regarding their phylogenetic position and classification as an independent family. In this study, two different datasets were employed to reconstruct the phylogenies of Varroa mites and related Laelapidae species: (1) 9257 bp from the whole 13 mitochondrial protein-coding genes of 24 taxa, (2) 3158 bp from 113 taxa using Sanger sequencing of four nuclear loci. Both mitochondrial and nuclear analyses consistently place Varroa mites within the Laelapidae. Here we propose to place Varroa mites in the subfamily Varroinae stat. nov., which represents a highly morphologically adapted group within the Laelapidae. Ancestral state reconstructions reveal that bee-associated lifestyles evolved independently at least three times within Laelapidae, with most phoretic traits originating from free-living ancestors. Our revised classification and evolutionary analyses will provide new insight into understanding the Varroa mites.

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          MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

          We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.
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            IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

            Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%.
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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
                seung@snu.ac.kr
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                18 June 2024
                18 June 2024
                2024
                : 14
                : 13994
                Affiliations
                [1 ]Insect Biosystematics Laboratory, Department of Agricultural Biotechnology, Seoul National University, ( https://ror.org/04h9pn542) 1, Gwanak-ro, Gwanak-gu, Seoul, Republic of Korea
                [2 ]Research Institute of Agriculture and Life Sciences, Seoul National University, ( https://ror.org/04h9pn542) Seoul, Republic of Korea
                [3 ]Department of Life Sciences, Natural History Museum, ( https://ror.org/039zvsn29) London, UK
                [4 ]Division of Environmental Science and Ecological Engineering, Korea University, ( https://ror.org/047dqcg40) Seoul, South Korea
                [5 ]Anatis Bioprotection Inc., Saint-Jacques-de-Mineur, Québec, J0J 1Z0 Canada
                [6 ]All-Russian Institute of Plant Protections, ( https://ror.org/01e69j385) St. Petersburg, Russia
                [7 ]Agriculture Science and Technology Institute, Andong National University, ( https://ror.org/04wd10e19) Andong, Republic of Korea
                [8 ]Lab. of Insect Phylogenetics and Evolution, Department of Plant Protection & Quarantine, Jeonbuk National University, ( https://ror.org/05q92br09) Jeonju, 54896 Republic of Korea
                [9 ]Department of Agricultural Convergence Technology, Jeonbuk National University, ( https://ror.org/05q92br09) Jeonju, 54896 Republic of Korea
                Article
                63991
                10.1038/s41598-024-63991-z
                11183080
                38886408
                ebebd8a2-8d00-4a4c-91e8-ace03fe57b6c
                © 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
                : 2 April 2024
                : 4 June 2024
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100003725, National Research Foundation of Korea;
                Award ID: NRF2020R1I1A2069484
                Funded by: Russian Science Foundation
                Award ID: 24–46–00024
                Award Recipient :
                Categories
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                © Springer Nature Limited 2024

                Uncategorized
                multi-locus phylogeny,mitochondrial genome,varroinae,laelapidae,taxonomic change,host evolution,evolution,zoology

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