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      Revisiting mitogenome evolution in Medusozoa with eight new mitochondrial genomes

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          Summary

          Mitogenomics has improved our understanding of medusozoan phylogeny. However, sequenced medusozoan mitogenomes remain scarce, and Medusozoa phylogeny studies often analyze mitogenomic sequences without incorporating mitogenome rearrangements. To better understand medusozoan evolution, we analyzed Medusozoa mitogenome phylogeny by sequencing and assembling eight mitogenomes from three classes (Cubozoa, Hydrozoa, and Scyphozoa). We reconstructed the mitogenome phylogeny using these mitogenomes and 84 other existing cnidarian mitogenomes to study mitochondrial gene rearrangements. All reconstructed mitogenomes had 13 mitochondrial protein-coding genes and two ribosomal genes typical for Medusozoa. Non-cubozoan mitogenomes were all linear and had typical gene orders, while arrangement of genes in the fragmented Cubozoa ( Morbakka sp.) mitogenome differed from other Cubozoa mitogenomes. Gene order comparisons and ancestral state reconstruction suggest minimal rearrangements within medusozoan classes except for Hydrozoa. Our findings support a staurozoan ancestral medusozoan gene order, expand the pool of available medusozoan mitogenomes, and enhance our understanding of medusozoan phylogenetic relationships.

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          Highlights

          • Mitogenomes of two Hydrozoa, five Scyphozoa, and one Cubozoa sequenced

          • Hydrozoa, Staurozoa, and Cubozoa are monophyletic; Scyphozoa is paraphyletic

          • Medusozoan gene orders highly conserved, except in Hydrozoa

          • Staurozoa gene order inferred as ancestral to rest of Medusozoa

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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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            SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing.

            The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.
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              fastp: an ultra-fast all-in-one FASTQ preprocessor

              Abstract Motivation Quality control and preprocessing of FASTQ files are essential to providing clean data for downstream analysis. Traditionally, a different tool is used for each operation, such as quality control, adapter trimming and quality filtering. These tools are often insufficiently fast as most are developed using high-level programming languages (e.g. Python and Java) and provide limited multi-threading support. Reading and loading data multiple times also renders preprocessing slow and I/O inefficient. Results We developed fastp as an ultra-fast FASTQ preprocessor with useful quality control and data-filtering features. It can perform quality control, adapter trimming, quality filtering, per-read quality pruning and many other operations with a single scan of the FASTQ data. This tool is developed in C++ and has multi-threading support. Based on our evaluation, fastp is 2–5 times faster than other FASTQ preprocessing tools such as Trimmomatic or Cutadapt despite performing far more operations than similar tools. Availability and implementation The open-source code and corresponding instructions are available at https://github.com/OpenGene/fastp.
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                Author and article information

                Contributors
                Journal
                iScience
                iScience
                iScience
                Elsevier
                2589-0042
                18 October 2023
                17 November 2023
                18 October 2023
                : 26
                : 11
                : 108252
                Affiliations
                [1 ]Department of Biological Sciences, National University of Singapore, 16 Science Drive 4, Singapore 117558, Singapore
                [2 ]Tropical Marine Science Institute, National University of Singapore, 18 Kent Ridge Road, Singapore 119227, Singapore
                [3 ]St. John’s Island National Marine Laboratory, c/o Tropical Marine Science Institute, National University of Singapore, 18 Kent Ridge Road, Singapore 119227, Singapore
                [4 ]Lee Kong Chian Natural History Museum, National University of Singapore, 2 Conservatory Drive, Singapore 117377, Singapore
                [5 ]Yale-NUS College, National University of Singapore, Singapore 138527, Singapore
                Author notes
                []Corresponding author minkangling@ 123456u.nus.edu
                [∗∗ ]Corresponding author randolphquek@ 123456u.nus.edu
                [6]

                Lead contact

                Article
                S2589-0042(23)02329-5 108252
                10.1016/j.isci.2023.108252
                10641506
                37965150
                e1850298-11b9-4a56-b5e2-eea67ecaaa38
                © 2023 The Authors

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 10 April 2023
                : 1 September 2023
                : 16 October 2023
                Categories
                Article

                genomics,phylogeny
                genomics, phylogeny

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