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      High‐quality genomes reveal significant genetic divergence and cryptic speciation in the model organism Folsomia candida (collembola)

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          Abstract

          The collembolan Folsomia candida Willem, 1902, is widely distributed throughout the world and has been frequently used as a test organism in soil ecology and ecotoxicology studies. However, it is questioned as an ideal “standard” because of differences in reproductive modes and cryptic genetic diversity between strains from various geographical origins. In this study, we obtained two high‐quality chromosome‐level genomes of F. candida, for a parthenogenetic strain (named FCDK, 219.08 Mb, 25,139 protein‐coding genes) and a sexual strain (named FCSH, 153.09 Mb, 21,609 protein‐coding genes), reannotated the genome of the parthenogenetic strain reported by Faddeeva‐Vakhrusheva et al. in 2017 (named FCBL, 221.7 Mb, 25,980 protein‐coding genes) and conducted comparative genomic analyses of the three strains. High genome similarities between FCDK and FCBL based on synteny, genome architecture, mitochondrial and nuclear gene sequences suggest that they are conspecific. The seven chromosomes of FCDK are each 25%–54% larger than the corresponding chromosomes of FCSH, showing obvious repetitive element expansions and large‐scale inversions and translocations but no whole‐genome duplication. The strain‐specific genes, expanded gene families and genes in nonsyntenic chromosomal regions identified in FCDK are highly related to the broader environmental adaptation of parthenogenetic strains. In addition, FCDK has fewer strain‐specific microRNAs than FCSH, and their mitochondrial and nuclear genes have diverged greatly. In conclusion, FCDK/FCBL and FCSH have accumulated independent genetic changes and evolved into distinct species after 10 million years ago. Our work provides important genomic resources for studying the mechanisms of rapidly cryptic speciation and soil arthropod adaptation to soil ecosystems.

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          clusterProfiler: an R package for comparing biological themes among gene clusters.

          Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.
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            Fast and accurate short read alignment with Burrows–Wheeler transform

            Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk
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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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                Author and article information

                Contributors
                yxluan@scnu.edu.cn
                fzhang@njau.edu.cn
                lisheng@scnu.edu.cn
                Journal
                Mol Ecol Resour
                Mol Ecol Resour
                10.1111/(ISSN)1755-0998
                MEN
                Molecular Ecology Resources
                John Wiley and Sons Inc. (Hoboken )
                1755-098X
                1755-0998
                05 September 2022
                January 2023
                : 23
                : 1 ( doiID: 10.1111/men.v23.1 )
                : 273-293
                Affiliations
                [ 1 ] Guangdong Provincial Key Laboratory of Insect Development Biology and Applied Technology, Institute of Insect Science and Technology, School of Life Sciences South China Normal University Guangzhou China
                [ 2 ] Guangdong Laboratory for Lingnan Modern Agriculture Guangzhou China
                [ 3 ] BGI‐Shenzhen Shenzhen China
                [ 4 ] Department of Entomology, College of Plant Protection Nanjing Agricultural University Nanjing China
                [ 5 ] Department of Pomology, College of Horticulture South China Agricultural University Guangzhou China
                [ 6 ] CAS Key Laboratory of Insect Developmental and Evolutionary Biology, CAS Center for Excellence in Molecular Plant Sciences Chinese Academy of Sciences Shanghai China
                [ 7 ] Moscow Pedagogical State University Moscow Russia
                [ 8 ] Natural History Research Center, Shanghai Natural History Museum Shanghai Science & Technology Museum Shanghai China
                [ 9 ] Guangmeiyuan R&D Center, Guangdong Provincial Key Laboratory of Insect Developmental Biology and Applied Technology South China Normal University Meizhou China
                Author notes
                [*] [* ] Correspondence

                Yun‐Xia Luan and Sheng Li, Guangdong Provincial Key Laboratory of Insect Development Biology and Applied Technology, Institute of Insect Science and Technology, School of Life Sciences, South China Normal University, Guangzhou, China.

                Emails: yxluan@ 123456scnu.edu.cn ; lisheng@ 123456scnu.edu.cn

                Feng Zhang, Department of Entomology, College of Plant Protection, Nanjing Agricultural University, Nanjing, China.

                Email: fzhang@ 123456njau.edu.cn

                Author information
                https://orcid.org/0000-0003-3573-7144
                https://orcid.org/0000-0002-4217-2367
                Article
                MEN13699 MER-21-0590.R2
                10.1111/1755-0998.13699
                10087712
                35962787
                128f0882-833f-410f-8146-e5792be02b56
                © 2022 The Authors. Molecular Ecology Resources published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                : 08 August 2022
                : 30 November 2021
                : 09 August 2022
                Page count
                Figures: 6, Tables: 2, Pages: 21, Words: 13767
                Funding
                Funded by: National Natural Science Foundation of China , doi 10.13039/501100001809;
                Award ID: 32170425
                Award ID: 31970434
                Award ID: 31772510
                Award ID: 31620103917
                Funded by: the Laboratory of Lingnan Modern Agriculture Project
                Award ID: NT2021003
                Funded by: National Key R&D Program of China
                Award ID: 2019YFD1002102
                Funded by: National Science & Technology Fundamental Resources Investigation Program of China
                Award ID: 2018FY100300
                Categories
                Resource Article
                RESOURCE ARTICLES
                Permanent Genetic Resources
                Custom metadata
                2.0
                January 2023
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.2.7 mode:remove_FC converted:11.04.2023

                Ecology
                chromosome‐level genome,comparative mitogenomics,cryptic species,genome synteny,mirna distribution,repetitive element expansion

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