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

      Transcriptome analysis of Artemisia argyi following methyl jasmonate (MeJA) treatment and the mining of genes related to the stress resistance pathway

      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

          Artemisia argyi Lev. et Vant. ( A. argyi) is a perennial grass in the Artemisia family, the plant has a strong aroma. Methyl jasmonate (MeJA) is critical to plant growth and development, stress response, and secondary metabolic processes. The experimental material Artemisia argyi was utilized in this study to investigate the treatment of A. argyi with exogenous MeJA at concentrations of 100 and 200 μmol/L for durations of 9 and 24 h respectively. Transcriptome sequencing was conducted using the Illumina HiSeq platform to identify stress resistance-related candidate genes. Finally, a total of 102.43 Gb of data were obtained and 162,272 unigenes were identified. Differential analysis before and after MeJA treatment resulted in the screening of 20,776 differentially expressed genes. The GO classification revealed that the annotated unigenes were categorized into three distinct groups: cellular component, molecular function, and biological process. Notably, binding, metabolic process, and cellular process emerged as the most prevalent categories among them. The results of KEGG pathway statistical analysis revealed that plant hormone signal transduction, MAPK signaling pathway-plant, and plant-pathogen interaction were significant transduction pathways in A. argyi’s response to exogenous MeJA-induced abiotic stress. With the alteration of exogenous MeJA concentration and duration, a significant upregulation was observed in the expression levels of calmodulin CaM4 (ID: EVM0136224) involved in MAPK signaling pathway-plant and auxin response factor ARF (ID: EVM0055178) associated with plant-pathogen interaction. The findings of this study establish a solid theoretical foundation for the future development of highly resistant varieties of A. argyi.

          Related collections

          Most cited references35

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

          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

            The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Elicitor signal transduction leading to production of plant secondary metabolites.

              Plant secondary metabolites are unique sources for pharmaceuticals, food additives, flavors, and other industrial materials. Accumulation of such metabolites often occurs in plants subjected to stresses including various elicitors or signal molecules. Understanding signal transduction paths underlying elicitor-induced production of secondary metabolites is important for optimizing their commercial production. This paper summarizes progress made on several aspects of elicitor signal transduction leading to production of plant secondary metabolites, including: elicitor signal perception by various receptors of plants; avirulence determinants and corresponding plant R proteins; heterotrimeric and small GTP binding proteins; ion fluxes, especially Ca2+ influx, and Ca2+ signaling; medium alkalinization and cytoplasmic acidification; oxidative burst and reactive oxygen species; inositol trisphosphates and cyclic nucleotides (cAMP and cGMP); salicylic acid and nitric oxide; jasmonate, ethylene, and abscisic acid signaling; oxylipin signals such as allene oxide synthase-dependent jasmonate and hydroperoxide lyase-dependent C12 and C6 volatiles; as well as other lipid messengers such as lysophosphatidylcholine, phosphatidic acid, and diacylglycerol. All these signal components are employed directly or indirectly by elicitors for induction of plant secondary metabolite accumulation. Cross-talk between different signaling pathways is very common in plant defense response, thus the cross-talk amongst these signaling pathways, such as elicitor and jasmonate, jasmonate and ethylene, and each of these with reactive oxygen species, is discussed separately. This review also highlights the integration of multiple signaling pathways into or by transcription factors, as well as the linkage of the above signal components in elicitor signaling network through protein phosphorylation and dephosphorylation. Some perspectives on elicitor signal transduction and plant secondary metabolism at the transcriptome and metabolome levels are also presented.
                Bookmark

                Author and article information

                Contributors
                URI : https://loop.frontiersin.org/people/2381330/overviewRole:
                URI : https://loop.frontiersin.org/people/613578/overviewRole:
                Role:
                Role:
                Role:
                URI : https://loop.frontiersin.org/people/520018/overview
                Journal
                Front Genet
                Front Genet
                Front. Genet.
                Frontiers in Genetics
                Frontiers Media S.A.
                1664-8021
                02 November 2023
                2023
                : 14
                : 1279850
                Affiliations
                [1] 1 Biotechnology Research Center , China Three Gorges University , Yichang, China
                [2] 2 College of Biology and Food Engineering , Anyang Institute of Technology , Anyang, China
                Author notes

                Edited by: Romit Seth, North Carolina State University, United States

                Reviewed by: Abhishek Bhandawat, National Agri-Food Biotechnology Institute, India

                Namo Dubey, Institute of Himalayan Bioresource Technology (CSIR), India

                *Correspondence: Kunpeng Zhang, zhangkunpengag@ 123456163.com ; Xiangling Shen, shenxl1982@ 123456hotmail.com
                [ † ]

                These authors have contributed equally to this work

                Article
                1279850
                10.3389/fgene.2023.1279850
                10652873
                38028600
                3bef43da-f14d-44f5-b3d3-2f69a87bc766
                Copyright © 2023 Wang, Cui, Li, Gao, Zhang and Shen.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 18 August 2023
                : 17 October 2023
                Funding
                The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This research was funded by the Doctoral Scientific Research Foundation of Anyang Institute of Technology (BSJ2021011), the National Natural Science Foundation of China (Grant No. 31901509), and Henan Artemisia vulgaris L. natural product utilization and development engineering research center.
                Categories
                Genetics
                Original Research
                Custom metadata
                Genomics of Plants and the Phytoecosystem

                Genetics
                artemisia argyi,meja,transcriptome,abiotic stress,response
                Genetics
                artemisia argyi, meja, transcriptome, abiotic stress, response

                Comments

                Comment on this article