2
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Characterization of the chloroplast genome of Gleditsia species and comparative analysis

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The genus Gleditsia has significant medicinal and economic value, but information about the chloroplast genomic characteristics of Gleditsia species has been limited. Using the Illumina sequencing, we assembled and annotated the whole chloroplast genomes of seven Gleditsia species ( Gleditsia sinensis, Gleditsia japonica var. delavayi ( G. delavayi), G. fera, G. japonica, G. microphylla, Fructus Gleditsiae Abnormalis (Zhū Yá Zào), G. microphylla mutant). The assembled genomes revealed that Gleditsia species have a typical circular tetrad structure, with genome sizes ranging from 162,746 to 170,907 bp. Comparative genomic analysis showed that most (65.8–75.8%) of the abundant simple sequence repeats in Gleditsia and Gymnocladus species were located in the large single copy region. The Gleditsia chloroplast genome prefer T/A-ending codons and avoid C/G-ending codons, positive selection was acting on the rpoA, rpl20, atpB, ndhA and ycf4 genes, most of the chloroplast genes of Gleditsia species underwent purifying selection. Expansion and contraction of the inverted repeat (IR)/single copy (SC) region showed similar patterns within the Gleditsia genus. Polymorphism analysis revealed that coding regions were more conserved than non-coding regions, and the IR region was more conserved than the SC region. Mutational hotspots were mostly found in intergenic regions such as “ rps16- trnQ”, “ trnT- trnL”, “ ndhG- ndhI”, and " rpl32- trnL” in Gleditsia. Phylogenetic analysis showed that G. fera is most closely related to G. sinensis,G. japonica and G. delavayi are relatively closely related. Zhū Yá Zào can be considered a bud mutation of the G. sinensis. The albino phenotype of G. microphylla mutant is not caused by variations in the chloroplast genome, and that the occurrence of the albino phenotype may be due to mutations in chloroplast-related genes involved in splicing or localization functions. This study will help us enhance our exploration of the genetic evolution and geographical origins of the Gleditsia genus.

          Related collections

          Most cited references51

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          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.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

            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%.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              fastp: an ultra-fast all-in-one FASTQ preprocessor

              Abstract Motivation Quality control and preprocessing of FASTQ files are essential to providing clean data for downstream analysis. Traditionally, a different tool is used for each operation, such as quality control, adapter trimming and quality filtering. These tools are often insufficiently fast as most are developed using high-level programming languages (e.g. Python and Java) and provide limited multi-threading support. Reading and loading data multiple times also renders preprocessing slow and I/O inefficient. Results We developed fastp as an ultra-fast FASTQ preprocessor with useful quality control and data-filtering features. It can perform quality control, adapter trimming, quality filtering, per-read quality pruning and many other operations with a single scan of the FASTQ data. This tool is developed in C++ and has multi-threading support. Based on our evaluation, fastp is 2–5 times faster than other FASTQ preprocessing tools such as Trimmomatic or Cutadapt despite performing far more operations than similar tools. Availability and implementation The open-source code and corresponding instructions are available at https://github.com/OpenGene/fastp.
                Bookmark

                Author and article information

                Contributors
                zhy737@126.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                21 February 2024
                21 February 2024
                2024
                : 14
                : 4262
                Affiliations
                [1 ]Institute for Forest Resources and Environment of Guizhou, Key Laboratory of Forest Cultivation in Plateau Mountain of Guizhou Province, College of Forestry, Guizhou University, ( https://ror.org/02wmsc916) Guiyang, 550025 Guizhou China
                [2 ]College of Continuing Education, Yanbian University, ( https://ror.org/039xnh269) Yanji, 133002 Jilin China
                Article
                54608
                10.1038/s41598-024-54608-6
                10881578
                38383559
                8d4b49ed-8625-49aa-99c1-44d9c011d3a3
                © The Author(s) 2024

                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/.

                History
                : 15 July 2023
                : 14 February 2024
                Funding
                Funded by: Science and Technology Plan Project of Guizhou Province
                Award ID: [2022] general 102
                Award Recipient :
                Categories
                Article
                Custom metadata
                © Springer Nature Limited 2024

                Uncategorized
                evolution,genetics,plant sciences
                Uncategorized
                evolution, genetics, plant sciences

                Comments

                Comment on this article