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      Full-length transcriptome characterization and comparative analysis of Gleditsia sinensis

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          Abstract

          As an economically important tree, Gleditsia sinensis Lam. is widely planted. A lack of background genetic information on G. sinensis hinders molecular breeding. Based on PacBio single-molecule real-time (SMRT) sequencing and analysis of G. sinensis, a total of 95,183 non-redundant transcript sequences were obtained, of which 93,668 contained complete open reading frames (ORFs), 2,858 were long non-coding RNAs (LncRNAs) and 18,855 alternative splicing (AS) events were identified. Genes orthologous to different Gleditsia species pairs were identified, stress-related genes had been positively selected during the evolution. AGA, AGG, and CCA were identified as the universal optimal codon in the genus of Gleditsia. EIF5A was selected as a suitable fluorescent quantitative reference gene. 315 Cytochrome P450 monooxygenases ( CYP450s) and 147 uridine diphosphate (UDP)-glycosyltransferases ( UGTs) were recognized through the PacBio SMRT transcriptome. Randomized selection of GsIAA14 for cloning verified the reliability of the PacBio SMRT transcriptome assembly sequence. In conclusion, the research data lay the foundation for further analysis of the evolutionary mechanism and molecular breeding of Gleditsia.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12864-023-09843-y.

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          Most cited references62

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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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            KEGG: kyoto encyclopedia of genes and genomes.

            M Kanehisa (2000)
            KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the GENES database, which is a collection of gene catalogs for all the completely sequenced genomes and some partial genomes with up-to-date annotation of gene functions. The higher order functional information is stored in the PATHWAY database, which contains graphical representations of cellular processes, such as metabolism, membrane transport, signal transduction and cell cycle. The PATHWAY database is supplemented by a set of ortholog group tables for the information about conserved subpathways (pathway motifs), which are often encoded by positionally coupled genes on the chromosome and which are especially useful in predicting gene functions. A third database in KEGG is LIGAND for the information about chemical compounds, enzyme molecules and enzymatic reactions. KEGG provides Java graphics tools for browsing genome maps, comparing two genome maps and manipulating expression maps, as well as computational tools for sequence comparison, graph comparison and path computation. The KEGG databases are daily updated and made freely available (http://www. genome.ad.jp/kegg/).
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              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.
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                Author and article information

                Contributors
                zhy737@126.com
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                8 December 2023
                8 December 2023
                2023
                : 24
                : 757
                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 ]School of Continuing Education, Yanbian University, ( https://ror.org/039xnh269) Yanji, 133002 Jilin China
                Article
                9843
                10.1186/s12864-023-09843-y
                10709882
                38066414
                60a54a39-4faf-4d8a-8f4f-7092ca578c12
                © 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
                : 26 March 2023
                : 25 November 2023
                Funding
                Funded by: Science and Technology Plan Project of Guizhou Province
                Award ID: [2022] general 102
                Award ID: [2022] general 102
                Award Recipient :
                Categories
                Research
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2023

                Genetics
                gleditsia sinensis,comparative transcriptome,pacbio smrt,ka/ks
                Genetics
                gleditsia sinensis, comparative transcriptome, pacbio smrt, ka/ks

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