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      A highly-contiguous genome assembly of the Eurasian spruce bark beetle, Ips typographus, provides insight into a major forest pest

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          Abstract

          Conifer-feeding bark beetles are important herbivores and decomposers in forest ecosystems. These species complete their life cycle in nutritionally poor substrates and some can kill enormous numbers of trees during population outbreaks. The Eurasian spruce bark beetle ( Ips typographus) can destroy >100 million m 3 of spruce in a single year. We report a 236.8 Mb I. typographus genome assembly using PacBio long-read sequencing. The final phased assembly has a contig N 50 of 6.65 Mb in 272 contigs and is predicted to contain 23,923 protein-coding genes. We reveal expanded gene families associated with plant cell wall degradation, including pectinases, aspartyl proteases, and glycosyl hydrolases. This genome sequence from the genus Ips provides timely resources to address questions about the evolutionary biology of the true weevils (Curculionidae), one of the most species-rich animal families. In forests of today, increasingly stressed by global warming, this draft genome may assist in developing pest control strategies to mitigate outbreaks.

          Abstract

          Daniel Powell et al. present a high-quality genome assembly of the Eurasian spruce bark beetle, Ips typographus, which is known to cause substantial damage to European forests. Their results provide an important resource for investigation of the underlying physiology of this pest species and limit future threats to European forests.

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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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            The Sequence Alignment/Map format and SAMtools

            Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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              HISAT: a fast spliced aligner with low memory requirements.

              HISAT (hierarchical indexing for spliced alignment of transcripts) is a highly efficient system for aligning reads from RNA sequencing experiments. HISAT uses an indexing scheme based on the Burrows-Wheeler transform and the Ferragina-Manzini (FM) index, employing two types of indexes for alignment: a whole-genome FM index to anchor each alignment and numerous local FM indexes for very rapid extensions of these alignments. HISAT's hierarchical index for the human genome contains 48,000 local FM indexes, each representing a genomic region of ∼64,000 bp. Tests on real and simulated data sets showed that HISAT is the fastest system currently available, with equal or better accuracy than any other method. Despite its large number of indexes, HISAT requires only 4.3 gigabytes of memory. HISAT supports genomes of any size, including those larger than 4 billion bases.
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                Author and article information

                Contributors
                martin_n.andersson@biol.lu.se
                Journal
                Commun Biol
                Commun Biol
                Communications Biology
                Nature Publishing Group UK (London )
                2399-3642
                9 September 2021
                9 September 2021
                2021
                : 4
                : 1059
                Affiliations
                [1 ]GRID grid.15866.3c, ISNI 0000 0001 2238 631X, Czech University of Life Sciences Prague, Faculty of Forestry and Wood Sciences, Excellent Team for Mitigation (ETM), Kamýcká 129, ; Praha 6, Suchdol Czech Republic
                [2 ]GRID grid.4514.4, ISNI 0000 0001 0930 2361, Department of Biology, , Lund University, ; Lund, Sweden
                [3 ]GRID grid.454322.6, ISNI 0000 0004 4910 9859, Division of Biotechnology and Plant Health, , Norwegian Institute of Bioeconomy Research, ; Ås, Norway
                [4 ]GRID grid.15866.3c, ISNI 0000 0001 2238 631X, Czech University of Life Sciences Prague, Faculty of Forestry and Wood Sciences, EVA 4.0 Unit, Kamýcká 129, ; Praha 6, Suchdol Czech Republic
                [5 ]GRID grid.418160.a, ISNI 0000 0004 0491 7131, Entomology Department, , Max Planck Institute for Chemical Ecology, ; Jena, Germany
                [6 ]GRID grid.6341.0, ISNI 0000 0000 8578 2742, Department of Plant Protection Biology, , Swedish University of Agricultural Sciences, ; Alnarp, Sweden
                [7 ]GRID grid.1034.6, ISNI 0000 0001 1555 3415, Present Address: Global Change Ecology Research Group, School of Science, Technology and Engineering, , University of the Sunshine Coast, ; Sippy Downs, QLD Australia
                Author information
                http://orcid.org/0000-0001-6323-7791
                http://orcid.org/0000-0002-3116-6922
                http://orcid.org/0000-0001-9807-8524
                http://orcid.org/0000-0002-1244-0308
                Article
                2602
                10.1038/s42003-021-02602-3
                8429705
                34504275
                cb6ea1ea-2f7e-40d3-85a4-332748fe86cf
                © The Author(s) 2021

                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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 29 January 2021
                : 25 August 2021
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100004359, Vetenskapsrådet (Swedish Research Council);
                Award ID: 2017-03804
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100001862, Svenska Forskningsrådet Formas (Swedish Research Council Formas);
                Award ID: 217-2014-689
                Award ID: 2018-01444
                Award Recipient :
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                Custom metadata
                © The Author(s) 2021

                comparative genomics,dna sequencing,molecular evolution

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