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      Genome-wide identification and comparative analysis of DNA methyltransferase and demethylase gene families in two ploidy Cyclocarya paliurus and their potential function in heterodichogamy

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          Abstract

          Background

          DNA methylation is one of the most abundant epigenetic modifications, which plays important roles in flower development, sex differentiation, and regulation of flowering time. Its pattern is affected by cytosine-5 DNA methyltransferase (C5-MTase) and DNA demethylase (dMTase). At present, there are no reports on C5-MTase and dMTase genes in heterodichogamous Cyclocarya paliurus.

          Results

          In this study, 6 CpC5-MTase and 3 CpdMTase genes were identified in diploid (2n = 2 ×  = 32) C. paliurus, while 20 CpC5-MTase and 13 CpdMTase genes were identified in autotetraploid (2n = 4 ×  = 64). 80% of identified genes maintained relatively fixed positions on chromosomes during polyploidization. In addition, we found that some DRM subfamily members didn’t contain the UBA domain. The transcript abundance of CpC5-MTase and CpdMTase in male and female flowers of two morphs (protandry and protogyny) from diploidy was analyzed. Results showed that all genes were significantly up-regulated at the stage of floral bud break (S2), but significantly down-regulated at the stage of flower maturation (S4). At S2, some CpC5-MTase genes showed higher expression levels in PG-M than in PG-F, whereas some CpdMTase genes showed higher expression levels in PA-M than in PA-F. In addition, these genes were significantly associated with gibberellin synthesis-related genes (e.g. DELLA and GID1), suggesting that DNA methylation may play a role in the asynchronous floral development process through gibberellin signal.

          Conclusions

          These results broaden our understanding of the CpC5-MTase and CpdMTase genes in diploid and autotetraploid C. paliurus, and provide a novel insight into regulatory mechanisms of DNA methylation in heterodichogamy.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12864-023-09383-5.

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          Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.

          S Altschul (1997)
          The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permits the execution time of the BLAST programs to be decreased substantially while enhancing their sensitivity to weak similarities. A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original. In addition, a method is introduced for automatically combining statistically significant alignments produced by BLAST into a position-specific score matrix, and searching the database using this matrix. The resulting Position-Specific Iterated BLAST (PSI-BLAST) program runs at approximately the same speed per iteration as gapped BLAST, but in many cases is much more sensitive to weak but biologically relevant sequence similarities. PSI-BLAST is used to uncover several new and interesting members of the BRCT superfamily.
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            StringTie enables improved reconstruction of a transcriptome from RNA-seq reads.

            Mihaela Pertea, Geo M Pertea, Corina M Antonescu … (2016)
            Methods used to sequence the transcriptome often produce more than 200 million short sequences. We introduce StringTie, a computational method that applies a network flow algorithm originally developed in optimization theory, together with optional de novo assembly, to assemble these complex data sets into transcripts. When used to analyze both simulated and real data sets, StringTie produces more complete and accurate reconstructions of genes and better estimates of expression levels, compared with other leading transcript assembly programs including Cufflinks, IsoLasso, Scripture and Traph. For example, on 90 million reads from human blood, StringTie correctly assembled 10,990 transcripts, whereas the next best assembly was of 7,187 transcripts by Cufflinks, which is a 53% increase in transcripts assembled. On a simulated data set, StringTie correctly assembled 7,559 transcripts, which is 20% more than the 6,310 assembled by Cufflinks. As well as producing a more complete transcriptome assembly, StringTie runs faster on all data sets tested to date compared with other assembly software, including Cufflinks.
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              TBtools - an integrative toolkit developed for interactive analyses of big biological data

              Chengjie Chen, Hao Chen, Yi Zhang … (2020)
              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
                Xiangxiang Fu: xxfu@njfu.edu.cn
                Journal
                Journal ID (nlm-ta): BMC Genomics
                Journal ID (iso-abbrev): BMC Genomics
                Title: BMC Genomics
                Publisher: BioMed Central (London )
                ISSN (Electronic): 1471-2164
                Publication date (Electronic): 29 May 2023
                Publication date PMC-release: 29 May 2023
                Publication date Collection: 2023
                Volume: 24
                Electronic Location Identifier: 287
                Affiliations
                [1 ]GRID grid.410625.4, ISNI 0000 0001 2293 4910, Co-Innovation Center for Sustainable Forestry in Southern China, College of Forestry, , Nanjing Forestry University, ; Nanjing, 210037 China
                [2 ]GRID grid.443668.b, ISNI 0000 0004 1804 4247, Fishery College, , Zhejiang Ocean University, ; Zhoushan, 316022 Zhejiang China
                [3 ]Jiangsu Vocational College of Agriculture and Forestry, Zhenjiang, 212400 Jiangsu China
                Article
                Publisher ID: 9383
                DOI: 10.1186/s12864-023-09383-5
                PMC ID: 10226219
                SO-VID: 8066e6a3-e31e-4fe8-a06a-e84576e51f7c
                Copyright © © The Author(s) 2023
                License:

                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
                Date received : 13 February 2023
                Date accepted : 16 May 2023
                Categories
                Subject: Research
                Custom metadata
                issue-copyright-statement © BioMed Central Ltd., part of Springer Nature 2023

                ScienceOpen disciplines: Genetics
                Keywords: dna methylase,dna demethylase,polyploidization,heterodichogamy
                Data availability:
                ScienceOpen disciplines: Genetics
                Keywords: dna methylase, dna demethylase, polyploidization, heterodichogamy

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