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      Whole-Genome Sequence of Ligilactobacillus faecis WILCCON 0062, Isolated from Feces of a Wild Boar (Sus scrofa)

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      Author(s): a , a , a ,
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      Publication date (Electronic, pub):
      Publication date (Electronic, collection):
      Journal: Microbiology Resource Announcements
      Publisher: American Society for Microbiology

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          ABSTRACT

          We report the whole genome of a strain of Ligilactobacillus faecis. The complete circular chromosome and plasmid of strain WILCCON 0062 were obtained through a combination of short- and long-read sequencing and may be used to derive unprecedented insights into the genome-level phylogeny and functional capacities of Ligilactobacillus faecis.

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          Trimmomatic: a flexible trimmer for Illumina sequence data

          Anthony M. Bolger, Marc Lohse, Bjoern Usadel (2014)
          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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            IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

            Lam-Tung Nguyen, Heiko Schmidt, Arndt von Haeseler … (2014)
            Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%.
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              BLAST+: architecture and applications

              Christiam Camacho, George Coulouris, Vahram Avagyan … (2009)
              Background Sequence similarity searching is a very important bioinformatics task. While Basic Local Alignment Search Tool (BLAST) outperforms exact methods through its use of heuristics, the speed of the current BLAST software is suboptimal for very long queries or database sequences. There are also some shortcomings in the user-interface of the current command-line applications. Results We describe features and improvements of rewritten BLAST software and introduce new command-line applications. Long query sequences are broken into chunks for processing, in some cases leading to dramatically shorter run times. For long database sequences, it is possible to retrieve only the relevant parts of the sequence, reducing CPU time and memory usage for searches of short queries against databases of contigs or chromosomes. The program can now retrieve masking information for database sequences from the BLAST databases. A new modular software library can now access subject sequence data from arbitrary data sources. We introduce several new features, including strategy files that allow a user to save and reuse their favorite set of options. The strategy files can be uploaded to and downloaded from the NCBI BLAST web site. Conclusion The new BLAST command-line applications, compared to the current BLAST tools, demonstrate substantial speed improvements for long queries as well as chromosome length database sequences. We have also improved the user interface of the command-line applications.
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                Author and article information

                Contributors
                Sandra Kittelmann:
                ORCID: https://orcid.org/0000-0002-6019-9854
                Vanja Klepac-Ceraj: Role: Editor
                Journal
                Journal ID (nlm-ta): Microbiol Resour Announc
                Journal ID (iso-abbrev): Microbiol Resour Announc
                Journal ID (publisher-id): mra
                Title: Microbiology Resource Announcements
                Publisher: American Society for Microbiology (1752 N St., N.W., Washington, DC )
                ISSN (Electronic): 2576-098X
                Publication date (Electronic, pub): 14 June 2023
                Publication date (Electronic, collection): July 2023
                Publication date PMC-release: 14 June 2023
                Volume: 12
                Issue: 7
                Electronic Location Identifier: e00376-23
                Affiliations
                [a ] Wilmar International Ltd., WIL@NUS Corporate Laboratory, Centre for Translational Medicine, National University of Singapore, Singapore, Republic of Singapore
                Wellesley College
                Author notes

                The authors declare a conflict of interest. All authors were employed with Wilmar International Limited, Singapore. This does not alter the authors' adherence to ASM policy on sharing data and materials.

                Author information
                https://orcid.org/0000-0001-9754-5258
                https://orcid.org/0000-0002-4129-7424
                https://orcid.org/0000-0002-6019-9854
                Article
                Publisher ID: 00376-23 Publisher ID: mra.00376-23
                DOI: 10.1128/mra.00376-23
                PMC ID: 10353350
                PubMed ID: 37314351
                SO-VID: c70ba04d-fe49-4835-8c27-7fff8126f5dc
                Copyright © Copyright © 2023 Heng et al.
                License:

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

                History
                Date received : 5 May 2023
                Date accepted : 30 May 2023
                Page count
                Figures: 1, Tables: 1, Equations: 0, References: 17, Pages: 4, Words: 1758
                Categories
                Subject: Genome Sequences
                Compound subject: genomics-and-proteomics, Genomics and Proteomics
                Custom metadata
                cover-date July 2023

                Data availability:

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