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      Genomic insights into Penicillium chrysogenum adaptation to subseafloor sedimentary environments

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          Abstract

          Background

          Penicillium chrysogenum is a filamentous fungal species with diverse habitats, yet little is known about its genetics in adapting to extreme subseafloor sedimental environments.

          Results

          Here, we report the discovery of P. chrysogenum strain 28R-6-F01, isolated from deep coal-bearing sediments 2306 m beneath the seafloor. This strain possesses exceptional characteristics, including the ability to thrive in extreme conditions such as high temperature (45 °C), high pressure (35 Mpa), and anaerobic environments, and exhibits broad-spectrum antimicrobial activity, producing the antibiotic penicillin at a concentration of 358 μg/mL. Genome sequencing and assembly revealed a genome size of 33.19 Mb with a GC content of 48.84%, containing 6959 coding genes. Comparative analysis with eight terrestrial strains identified 88 unique genes primarily associated with penicillin and aflatoxins biosynthesis, carbohydrate degradation, viral resistance, and three secondary metabolism gene clusters. Furthermore, significant expansions in gene families related to DNA repair were observed, likely linked to the strain’s adaptation to its environmental niche.

          Conclusions

          Our findings provide insights into the genomic and biological characteristics of P. chrysogenum adaptation to extreme anaerobic subseafloor sedimentary environments, such as high temperature and pressure.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12864-023-09921-1.

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          Most cited references82

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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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            RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies

            Motivation: Phylogenies are increasingly used in all fields of medical and biological research. Moreover, because of the next-generation sequencing revolution, datasets used for conducting phylogenetic analyses grow at an unprecedented pace. RAxML (Randomized Axelerated Maximum Likelihood) is a popular program for phylogenetic analyses of large datasets under maximum likelihood. Since the last RAxML paper in 2006, it has been continuously maintained and extended to accommodate the increasingly growing input datasets and to serve the needs of the user community. Results: I present some of the most notable new features and extensions of RAxML, such as a substantial extension of substitution models and supported data types, the introduction of SSE3, AVX and AVX2 vector intrinsics, techniques for reducing the memory requirements of the code and a plethora of operations for conducting post-analyses on sets of trees. In addition, an up-to-date 50-page user manual covering all new RAxML options is available. Availability and implementation: The code is available under GNU GPL at https://github.com/stamatak/standard-RAxML. Contact: alexandros.stamatakis@h-its.org Supplementary information: Supplementary data are available at Bioinformatics online.
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              TBtools - an integrative toolkit developed for interactive analyses of big biological data

              The rapid development of high-throughput sequencing techniques has led biology into the big-data era. Data analyses using various bioinformatics tools rely on programming and command-line environments, which are challenging and time-consuming for most wet-lab biologists. Here, we present TBtools (a Toolkit for Biologists integrating various biological data-handling tools), a stand-alone software with a user-friendly interface. The toolkit incorporates over 130 functions, which are designed to meet the increasing demand for big-data analyses, ranging from bulk sequence processing to interactive data visualization. A wide variety of graphs can be prepared in TBtools using a new plotting engine ("JIGplot") developed to maximize their interactive ability; this engine allows quick point-and-click modification of almost every graphic feature. TBtools is platform-independent software that can be run under all operating systems with Java Runtime Environment 1.6 or newer. It is freely available to non-commercial users at https://github.com/CJ-Chen/TBtools/releases.
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                Author and article information

                Contributors
                chliu@nju.edu.cn
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                2 January 2024
                2 January 2024
                2024
                : 25
                : 4
                Affiliations
                State Key Laboratory of Pharmaceutical Biotechnology, Nanjing University, ( https://ror.org/01rxvg760) Nanjing, 210023 China
                Article
                9921
                10.1186/s12864-023-09921-1
                10759354
                6ae9459d-85c7-4dd1-9edb-9c859501e1e5
                © The Author(s) 2023

                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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 11 July 2023
                : 17 December 2023
                Categories
                Research
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2024

                Genetics
                penicillium chrysogenum,subseafloor sediment,secondary metabolites,environmental adaptation,fungi

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