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      Comparative mitogenomic analysis of subterranean and surface amphipods (Crustacea, Amphipoda) with special reference to the family Crangonyctidae

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          Abstract

          Mitochondrial genomes play important roles in studying genome evolution, phylogenetic analyses, and species identification. Amphipods (Class Malacostraca, Order Amphipoda) are one of the most ecologically diverse crustacean groups occurring in a diverse array of aquatic and terrestrial environments globally, from freshwater streams and lakes to groundwater aquifers and the deep sea, but we have a limited understanding of how habitat influences the molecular evolution of mitochondrial energy metabolism. Subterranean amphipods likely experience different evolutionary pressures on energy management compared to surface-dwelling taxa that generally encounter higher levels of predation and energy resources and live in more variable environments. In this study, we compared the mitogenomes, including the 13 protein-coding genes involved in the oxidative phosphorylation (OXPHOS) pathway, of surface and subterranean amphipods to uncover potentially different molecular signals of energy metabolism between surface and subterranean environments in this diverse crustacean group. We compared base composition, codon usage, gene order rearrangement, conducted comparative mitogenomic and phylogenomic analyses, and examined evolutionary signals of 35 amphipod mitogenomes representing 13 families, with an emphasis on Crangonyctidae. Mitogenome size, AT content, GC-skew, gene order, uncommon start codons, location of putative control region (CR), length of rrnL and intergenic spacers differed between surface and subterranean amphipods. Among crangonyctid amphipods, the spring-dwelling Crangonyx forbesi exhibited a unique gene order, a long nad5 locus, longer rrnL and rrnS loci, and unconventional start codons. Evidence of directional selection was detected in several protein-encoding genes of the OXPHOS pathway in the mitogenomes of surface amphipods, while a signal of purifying selection was more prominent in subterranean species, which is consistent with the hypothesis that the mitogenome of surface-adapted species has evolved in response to a more energy demanding environment compared to subterranean amphipods. Overall, gene order, locations of non-coding regions, and base-substitution rates points to habitat as an important factor influencing the evolution of amphipod mitogenomes.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12864-024-10111-w.

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          Trimmomatic: a flexible trimmer for Illumina sequence data

          Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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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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              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
                matthew.niemiller@uah.edu
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                20 March 2024
                20 March 2024
                2024
                : 25
                : 298
                Affiliations
                [1 ]Department of Biological Sciences, The University of Alabama in Huntsville, ( https://ror.org/02zsxwr40) Huntsville, AL 35899 USA
                [2 ]School of Life Sciences, University of Hawai’i at Mānoa, ( https://ror.org/01wspgy28) Honolulu, HI 96822 USA
                Article
                10111
                10.1186/s12864-024-10111-w
                10956265
                38509489
                9969fa2c-c8dd-43dc-b2bc-80e3aeb93de4
                © 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/. 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
                : 20 June 2023
                : 9 February 2024
                Funding
                Funded by: Friends of the Capital Crescent Trail
                Funded by: The town of Chevy Chase
                Funded by: FundRef http://dx.doi.org/10.13039/100016825, Illinois Natural History Survey;
                Funded by: The University of Alabama in Huntsville
                Categories
                Research
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2024

                Genetics
                cave,crustaceans,mitogenomes,oxphos,selection,stygobromus
                Genetics
                cave, crustaceans, mitogenomes, oxphos, selection, stygobromus

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