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      Complete genome sequence data of Pseudomonas nitroreducens L4, an endophyte isolated from cotton plants

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          Abstract

          Pseudomonas nitroreducens L4 was isolated from the interior of cotton plants, which showed strong biocontrol activity against Verticillium dahlia and other fungal pathogens. To elucidate the biocontrol mechanism, the genome sequence of L4 was sequenced using the Illumina and Nanopore sequencing platform. The assembled genome of L4 consisted of a single circular chromosome was 6,229,472 bp, with an average GC content of 64.95 %, 5,629 protein-coding genes, 72 tRNA, 16 rRNA and 1 tm RNA. Six secondary metabolite biosynthetic gene clusters are identified in the genome. The genome sequence provided a theoretical basis for analyzing the biocontrol mechanism of this strain.

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          Prokka: rapid prokaryotic genome annotation.

          T Seemann (2014)
          The multiplex capability and high yield of current day DNA-sequencing instruments has made bacterial whole genome sequencing a routine affair. The subsequent de novo assembly of reads into contigs has been well addressed. The final step of annotating all relevant genomic features on those contigs can be achieved slowly using existing web- and email-based systems, but these are not applicable for sensitive data or integrating into computational pipelines. Here we introduce Prokka, a command line software tool to fully annotate a draft bacterial genome in about 10 min on a typical desktop computer. It produces standards-compliant output files for further analysis or viewing in genome browsers. Prokka is implemented in Perl and is freely available under an open source GPLv2 license from http://vicbioinformatics.com/. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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            Unicycler: Resolving bacterial genome assemblies from short and long sequencing reads

            Ryan Wick, Louise Judd, Claire Gorrie … (2017)
            The Illumina DNA sequencing platform generates accurate but short reads, which can be used to produce accurate but fragmented genome assemblies. Pacific Biosciences and Oxford Nanopore Technologies DNA sequencing platforms generate long reads that can produce complete genome assemblies, but the sequencing is more expensive and error-prone. There is significant interest in combining data from these complementary sequencing technologies to generate more accurate “hybrid” assemblies. However, few tools exist that truly leverage the benefits of both types of data, namely the accuracy of short reads and the structural resolving power of long reads. Here we present Unicycler, a new tool for assembling bacterial genomes from a combination of short and long reads, which produces assemblies that are accurate, complete and cost-effective. Unicycler builds an initial assembly graph from short reads using the de novo assembler SPAdes and then simplifies the graph using information from short and long reads. Unicycler uses a novel semi-global aligner to align long reads to the assembly graph. Tests on both synthetic and real reads show Unicycler can assemble larger contigs with fewer misassemblies than other hybrid assemblers, even when long-read depth and accuracy are low. Unicycler is open source (GPLv3) and available at github.com/rrwick/Unicycler.
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              antiSMASH 6.0: improving cluster detection and comparison capabilities

              Kai Blin, Simon Shaw, Alexander Kloosterman … (2021)
              Many microorganisms produce natural products that form the basis of antimicrobials, antivirals, and other drugs. Genome mining is routinely used to complement screening-based workflows to discover novel natural products. Since 2011, the "antibiotics and secondary metabolite analysis shell—antiSMASH" ( https://antismash.secondarymetabolites.org/ ) has supported researchers in their microbial genome mining tasks, both as a free-to-use web server and as a standalone tool under an OSI-approved open-source license. It is currently the most widely used tool for detecting and characterising biosynthetic gene clusters (BGCs) in bacteria and fungi. Here, we present the updated version 6 of antiSMASH. antiSMASH 6 increases the number of supported cluster types from 58 to 71, displays the modular structure of multi-modular BGCs, adds a new BGC comparison algorithm, allows for the integration of results from other prediction tools, and more effectively detects tailoring enzymes in RiPP clusters. Graphical Abstract Here, we present version 6 of the secondary/specialized metabolite genome mining platform antiSMASH with improved detection capabilities, a new cluster compare feature and many further improvements.
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                Author and article information

                Contributors
                Lubo Zhuang
                Qingchao Zeng
                Journal
                Journal ID (nlm-ta): Data Brief
                Journal ID (iso-abbrev): Data Brief
                Title: Data in Brief
                Publisher: Elsevier
                ISSN (Electronic): 2352-3409
                Publication date PMC-release: 13 June 2024
                Publication date Collection: August 2024
                Publication date (Electronic): 13 June 2024
                Volume: 55
                Electronic Location Identifier: 110639
                Affiliations
                [a ]Institute of Plant Protection, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, China
                [b ]MOA Key Lab of Pest Monitoring and Green Management, Department of Plant Pathology, China Agricultural University, Beijing 100193, China
                [c ]Institute of Plant Protection, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
                Author notes
                Article
                Publisher Item ID: S2352-3409(24)00606-1 Publisher ID: 110639
                DOI: 10.1016/j.dib.2024.110639
                PMC ID: 11252606
                PubMed ID: 39022698
                SO-VID: 51d04c3f-5073-42bf-bbba-9aeaa83d1af0
                Copyright © © 2024 The Authors
                License:

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

                History
                Date received : 8 January 2024
                Date revision received : 24 February 2024
                Date accepted : 10 June 2024
                Categories
                Subject: Data Article

                Keywords: pseudomonas nitroreducens,biocontrol,genome sequence,cotton verticillium wilt,endophyte
                Data availability:
                Keywords: pseudomonas nitroreducens, biocontrol, genome sequence, cotton verticillium wilt, endophyte

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