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      Whole transcriptome analysis and construction of a ceRNA regulatory network related to leaf and petiole development in Chinese cabbage ( Brassica campestris L. ssp. pekinensis)

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          Abstract

          Background

          The growth and development of leaves and petioles have a significant effect on photosynthesis. Understanding the molecular mechanisms underlying leaf and petiole development is necessary for improving photosynthetic efficiency, cultivating varieties with high photosynthetic efficiency, and improving the yield of crops of which the leaves are foodstuffs. This study aimed to identify the mRNAs, long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and circular RNAs (circRNAs) related to leaf and petiole development in Chinese cabbage ( Brassica campestris L. ssp. pekinensis). The data were used to construct a competitive endogenous RNA (ceRNA) network to obtain insights into the mechanisms underlying leaf and petiole development.

          Results

          The leaves and petioles of the ‘PHL’ inbred line of Chinese cabbage were used as research materials for whole transcriptome sequencing. A total of 10,646 differentially expressed (DE) mRNAs, 303 DElncRNAs, 7 DEcircRNAs, and 195 DEmiRNAs were identified between leaves and petioles. Transcription factors and proteins that play important roles in leaf and petiole development were identified, including xyloglucan endotransglucosylase/hydrolase, expansion proteins and their precursors, transcription factors TCP15 and bHLH, lateral organ boundary domain protein, cellulose synthase, MOR1-like protein, and proteins related to plant hormone biosynthesis. A ceRNA regulatory network related to leaf and petiole development was constructed, and 85 pairs of ceRNA relationships were identified, including 71 DEmiRNA–DEmRNA, 12 DEmiRNA–DElncRNA, and 2 DEmiRNA–DEcircRNA pairs. Three LSH genes ( BrLSH1, BrLSH2 and BrLSH3) with significant differential expression between leaves and petioles were screened from transcriptome data, and their functions were explored through subcellular localization analysis and transgenic overexpression verification. BrLSH1, BrLSH2 and BrLSH3 were nuclear proteins, and BrLSH2 inhibited the growth and development of Arabidopsis thaliana.

          Conclusions

          This study identifies mRNAs and non-coding RNAs that may be involved in the development of leaves and petioles in Chinese cabbage, and establishes a ceRNA regulatory network related to development of the leaves and petioles, providing valuable genomic resources for further research on the molecular mechanisms underlying leaf and petiole development in this crop species.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12864-023-09239-y.

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          Most cited references73

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          edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

          Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org). Contact: mrobinson@wehi.edu.au
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            NIH Image to ImageJ: 25 years of image analysis

            For the past twenty five years the NIH family of imaging software, NIH Image and ImageJ have been pioneers as open tools for scientific image analysis. We discuss the origins, challenges and solutions of these two programs, and how their history can serve to advise and inform other software projects.
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              Cutadapt removes adapter sequences from high-throughput sequencing reads

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                Author and article information

                Contributors
                yexueling@syau.edu.cn
                liuzhiyong99@syau.edu.cn
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                24 March 2023
                24 March 2023
                2023
                : 24
                : 144
                Affiliations
                [1 ]GRID grid.412557.0, ISNI 0000 0000 9886 8131, Department of Horticulture, , Shenyang Agricultural University, ; 120 Dongling Road, Shenhe District, Shenyang, 110866 China
                [2 ]GRID grid.464367.4, ISNI 0000 0004 1764 3029, Vegetable Research Institute of Liaoning Academy of Agricultural Sciences, ; Shenyang, 110161 China
                Article
                9239
                10.1186/s12864-023-09239-y
                10039531
                36964498
                22726bdb-e84d-4251-8ccc-02df86a8c8bc
                © The Author(s) 2023

                Open AccessThis 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
                : 27 December 2022
                : 9 March 2023
                Funding
                Funded by: National Natural Science Foundation of China
                Award ID: 31772298
                Funded by: Key Research and Development Program of Liaoning
                Award ID: 2021JH2/10200003
                Categories
                Research
                Custom metadata
                © The Author(s) 2023

                Genetics
                chinese cabbage,leaf,petiole,whole transcriptome,cerna
                Genetics
                chinese cabbage, leaf, petiole, whole transcriptome, cerna

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