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      Genome-wide identification of the GRF family in sweet orange ( Citrus sinensis) and functional analysis of the CsGRF04 in response to multiple abiotic stresses

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          Abstract

          Background

          Citrus is one of the most valuable fruits worldwide and an economic pillar industry in southern China. Nevertheless, it frequently suffers from undesirable environmental stresses during the growth cycle, which severely restricts the growth, development and yield of citrus. In plants, the growth-regulating factor (GRF) family of transcription factors (TF) is extensively distributed and plays an vital part in plant growth and development, hormone response, as well as stress adaptation. However, the systematic identification and functional analysis of GRF TFs in citrus have not been reported.

          Results

          Here, a genome-wide identification of GRF TFs was performed in Citrus sinensis, 9 members of CsGRFs were systematically identified and discovered to be scattered throughout 5 chromosomes. Subsequently, physical and chemical properties, phylogenetic relationships, structural characteristics, gene duplication events, collinearity and cis-elements of promoter were elaborately analyzed. In particular, the expression patterns of the CsGRF genes in response to multiple phytohormone and abiotic stress treatments were investigated. Predicated on this result, CsGRF04, which exhibited the most differential expression pattern under multiple phytohormone and abiotic stress treatments was screened out. Virus-induced gene silencing (VIGS) technology was utilized to obtain gene silenced plants for CsGRF04 successfully. After the three stress treatments of high salinity, low temperature and drought, the CsGRF04-VIGS lines showed significantly reduced resistance to high salinity and low temperature stresses, but extremely increased resistance to drought stress.

          Conclusions

          Taken together, our findings systematically analyzed the genomic characterization of GRF family in Citrus sinensis, and excavated a CsGRF04 with potential functions under multiple abiotic stresses. Our study lay a foundation for further study on the function of CsGRFs in abiotic stress and hormone signaling response.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12864-023-09952-8.

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          Most cited references61

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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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            MEGA11: Molecular Evolutionary Genetics Analysis Version 11

            The Molecular Evolutionary Genetics Analysis (MEGA) software has matured to contain a large collection of methods and tools of computational molecular evolution. Here, we describe new additions that make MEGA a more comprehensive tool for building timetrees of species, pathogens, and gene families using rapid relaxed-clock methods. Methods for estimating divergence times and confidence intervals are implemented to use probability densities for calibration constraints for node-dating and sequence sampling dates for tip-dating analyses. They are supported by new options for tagging sequences with spatiotemporal sampling information, an expanded interactive Node Calibrations Editor , and an extended Tree Explorer to display timetrees. Also added is a Bayesian method for estimating neutral evolutionary probabilities of alleles in a species using multispecies sequence alignments and a machine learning method to test for the autocorrelation of evolutionary rates in phylogenies. The computer memory requirements for the maximum likelihood analysis are reduced significantly through reprogramming, and the graphical user interface has been made more responsive and interactive for very big data sets. These enhancements will improve the user experience, quality of results, and the pace of biological discovery. Natively compiled graphical user interface and command-line versions of MEGA11 are available for Microsoft Windows, Linux, and macOS from www.megasoftware.net .
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              Clustal W and Clustal X version 2.0.

              The Clustal W and Clustal X multiple sequence alignment programs have been completely rewritten in C++. This will facilitate the further development of the alignment algorithms in the future and has allowed proper porting of the programs to the latest versions of Linux, Macintosh and Windows operating systems. The programs can be run on-line from the EBI web server: http://www.ebi.ac.uk/tools/clustalw2. The source code and executables for Windows, Linux and Macintosh computers are available from the EBI ftp site ftp://ftp.ebi.ac.uk/pub/software/clustalw2/
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                Author and article information

                Contributors
                daiwenshan77@foxmail.com
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                6 January 2024
                6 January 2024
                2024
                : 25
                : 37
                Affiliations
                College of Life Sciences, Gannan Normal University, National Navel Orange Engineering Research Center, ( https://ror.org/02jf7e446) Ganzhou, 341000 Jiangxi China
                Article
                9952
                10.1186/s12864-023-09952-8
                10770916
                38184538
                9c5bda68-6273-4166-a7f2-5bc2444332fe
                © 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/. 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
                : 23 November 2023
                : 28 December 2023
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 32002012
                Award ID: 32060670
                Funded by: FundRef http://dx.doi.org/10.13039/100022957, Double Thousand Plan of Jiangxi Province;
                Award ID: 461869
                Categories
                Research
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2024

                Genetics
                citrus sinensis,grf transcription factor,genome-wide identification,expression pattern,functional identification

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