Integrated transcriptome and microRNA profiles analysis reveals molecular mechanisms underlying the consecutive monoculture problem of Polygonatum odoratum

Yong Chen; Zhi Liu; Naimei Tu; Yihong Hu; Chenzhong Jin; Yucai Luo; Aiyu Liu; Xianwen Zhang

doi:10.14715/2020.66.2.7

Issue

Vol. 66 No. 2: Issue 2

Issue Published : May 16, 2020

The undersigned hereby assign all rights, included but not limited to copyright, for this manuscript to CMB Association upon its submission for consideration to publication on Cellular and Molecular Biology. The rights assigned include, but are not limited to, the sole and exclusive rights to license, sell, subsequently assign, derive, distribute, display and reproduce this manuscript, in whole or in part, in any format, electronic or otherwise, including those in existence at the time this agreement was signed. The authors hereby warrant that they have not granted or assigned, and shall not grant or assign, the aforementioned rights to any other person, firm, organization, or other entity. All rights are automatically restored to authors if this manuscript is not accepted for publication.

Integrated transcriptome and microRNA profiles analysis reveals molecular mechanisms underlying the consecutive monoculture problem of Polygonatum odoratum

https://doi.org/10.14715/2020.66.2.7

Yong Chen

College of Agronomy, Hunan Agricultural University, Changsha 410128, China

Zhi Liu

College of Bioscience and Biotechnology, Hunan Agricultural University, Changsha 410128, China

Naimei Tu

College of Agronomy, Hunan Agricultural University, Changsha 410128, China

Yihong Hu

Collaborative Innovation Center for Field Weeds Control of Hunan Province, Hunan University of Humanities, Science and Technology, Loudi 417000, China

Chenzhong Jin

Collaborative Innovation Center for Field Weeds Control of Hunan Province, Hunan University of Humanities, Science and Technology, Loudi 417000, China

Yucai Luo

Collaborative Innovation Center for Field Weeds Control of Hunan Province, Hunan University of Humanities, Science and Technology, Loudi 417000, China

Aiyu Liu

College of Agronomy, Hunan Agricultural University, Changsha 410128, China

Xianwen Zhang

College of Bioscience and Biotechnology, Hunan Agricultural University, Changsha 410128, China

Corresponding Author(s) : Aiyu Liu

aiyuliu399@gmail.com

Cellular and Molecular Biology, Vol. 66 No. 2: Issue 2
Article Published : May 15, 2020

Abstract

Polygonatum odoratum is a historically traditional Chinese medicine plant. However, the consecutive monoculture problem (CMP) widespread in other Chinese medicine limiting their cultivation on a large scale. In this study, the physiological data showed the adverse effect of CMP on the growth of P. odoratum under the consecutive cropping (CC) compared with the first cropping (FC). Then the high-throughput sequencing of miRNA and mRNA libraries of leaves and roots from FC and CC P. odoratum plants identified 671 differentially expressed genes (DEGs) and 184 differentially expressed miRNAs and revealed that the DEGs and target genes of the miRNAs were mainly involved in starch and sucrose metabolism, phenylpropanoid and brassinosteroid biosynthesis. The KEGG analysis revealed that the DEGs between CC and FC roots were enriched in the plant-pathogen interaction pathway. This study provided the expression regulation of genes related to CMP of P. odoratum but also suggested that CMP may result in the serious damage of pathogens to roots and cause the slow growth in the consecutive cropping plants.

Keywords

Polygonatum odoratum Consecutive monoculture problem (CMP) miRNA KEGG Plant-pathogen interaction

Chen, Y., Liu, Z., Tu, N., Hu, Y., Jin, C., Luo, Y., Liu, A., & Zhang, X. (2020). Integrated transcriptome and microRNA profiles analysis reveals molecular mechanisms underlying the consecutive monoculture problem of Polygonatum odoratum. Cellular and Molecular Biology, 66(2), 47–52. https://doi.org/10.14715/2020.66.2.7

Download Citation

References

Zhou X, Yuping Z, Zhao H, Liang J, Zhang Y, Shi S. Antioxidant homoisoflavonoids from Polygonatum odoratum, Food Chem 2015; 186: 63-68.
Liang Y, Lin Q, Huang P, Wang Y, Li J, Zhang L and Cao J: Rice Bioactive Peptide Binding with TLR4 To Overcome H2O2-Induced Injury in Human Umbilical Vein Endothelial Cells through NF-ÎºB Signaling. J Agri Food Chem 66(2): 440-448, 2018.
Wang L, Lin Q, Yang T, Liang Y, Nie Y, Luo Y and Luo F: Oryza¬nol modifies high fat diet-induced obesity, liver gene expression pro¬file, and inflammation response in mice. J Agri Food Chem 65(38): 8374-8385, 2017.
Lou Y, Shi J, Guo D, Qureshi AK and Song L: Function of PD-L1 in antitumor immunity of glioma cells. Saudi J Boil Sci 24(4): 803-807, 2017.
Guo T, Lin Q, Li X, Nie Y, Wang L, Shi L and Luo F: Octacosa¬nol attenuates inflammation in both RAW264. 7 macrophages and a mouse model of colitis. J Agri Food Chem 65(18): 3647-3658, 2017.
Li W, Jia MX, Wang JH, Lu JL, Deng J, Tang JX and Liu C: As¬sociation of MMP9-1562C/T and MMP13-77A/G polymorphisms with non-small cell lung cancer in southern Chinese population. Biomol 9(3): 107-119, 2019.
Nie Y, Luo F, Wang L, Yang T, Shi L, Li X, Shen J, Xu W, Guo T and Lin Q: Anti-hyperlipidemic effect of rice bran polysaccharide and its potential mechanism in high-fat diet mice. Food Func 8(11): 4028-4041, 2017.
Wu H, Wu L, Wang J, Zhu Q, Lin S, Xu J, Zheng C, Chen J, Qin X, Fang C, Zhang Z, Azeem S, Lin W. Mixed Phenolic Acids Media¬ted Proliferation of Pathogens Talaromyces helicus and Kosakonia sacchari in Continuously Monocultured Radix pseudostellariae Rhi¬zosphere Soil. Front Microbiol 2016; 7: 335-348.
Zhang H, Jin W, Zhu X, Liu L, He Z, Yang S, Liang Z, Yan X, He Y, Liu Y, Identification and Characterization of Salvia miltiorrhizain miRNAs in Response to Replanting Disease. PLoS One 2016; 11: e0159905.
Tian Y, Feng F, Zhang B, Li M, Wang F, Gu L, Chen A, Li Z, Shan W, Wang X, Chen X, Zhang Z. Transcriptome analysis reveals metabolic alteration due to consecutive monoculture and abiotic stress stimuli in Rehamannia glutinosa Libosch. Plant Cell Rep 2017; 36: 859-875.
Weiss S, Bartsch M, Winkelmann T. Transcriptomic analysis of molecular responses in Malus Domestica 'M26' roots affected by apple replant disease. Plant Mol Biol 2017; 94: 303-318.
Li MJ, Yang YH, Chen XJ, Wang FQ, Lin WX, Yi YJ, Zeng L, Yang SY, Zhang ZY. Transcriptome/degradome-wide identification of R. glutinosa miRNAs and their targets: the role of miRNA activity in the replanting disease. PLoS One 2013; 8: e68531.
Zhao Y, Wu L, Chu L, Yang Y, Li Z, Azeem S, Zhang Z, Fang C, Lin W. Interaction of Pseudostellaria heterophylla with Fusarium oxysporum f.sp. heterophylla mediated by its root exudates in a consecutive monoculture system. Sci Rep 2015; 5: 8197-8203.
Kato-Noguchi H, Ino T, Sata N, Yamamura S. Isolation and iden¬tification of a potent allelopathic substance in rice root exudates. Physiol Plant 2002; 115: 401-405.
Yang YH, Li MJ, Li XY, Chen XJ, Lin WX, Zhang ZY. Trans¬criptome-wide identification of the genes responding to replanting disease in Rehmannia glutinosa L. roots. Mol Biol Rep 2015; 42: 881-892.
Lou Y, Yang J, Wang L, Chen X, Xin X and Liu Y: The clini¬cal efficacy study of treatment to Chiari malformation type I with syringomyelia under the minimally invasive surgery of resection of Submeningeal cerebellar Tonsillar Herniation and reconstruction of Cisterna magna. Saudi J Biol Sci 26(8): 1927-1931, 2019.
Lou Y, Guo D, Zhang H and Song L: Effectiveness of mesenchy¬mal stems cells cultured by hanging drop vs. conventional culturing on the repair of hypoxic-ischemic-damaged mouse brains, measured by stemness gene expression. Open Life Sci 11(1): 519-523, 2016.
Chen X, Xu Y, Meng L, Chen X, Yuan L, Cai Q, Shi W and Huang G: Non-parametric partial least squares–discriminant analy¬sis model based on sum of ranking difference algorithm for tea grade identification using electronic tongue data identify tea grade using e-tongue data. Sens Actuators B Chem 127924, 2020.
Nie Y, Luo F and Lin Q: Dietary nutrition and gut microflora: A promising target for treating diseases. Trends Food Sci Technol 75: 72-80, 2018.
Ren Y, Jiao X and Zhang L: Expression level of fibroblast growth factor 5 (FGF5) in the peripheral blood of primary hypertension and its clinical significance. Saudi J Biol Sci 25(3): 469-473, 2018.
Sunkar R, Li YF, Jagadeeswaran G. Functions of microRNAs in plant stress responses. Trends Plant Sci 2012; 17: 196-203.
Haas BJ, Papanicolaou A, Yassour M, Grabherr M, Blood PD, Bowden J, Couger MB, Eccles D, Li B, Lieber M, MacManes MD, Ott M, Orvis J, Pochet N, Strozzi F, Weeks N, Westerman R, Wil¬liam T, Dewey CN, Henschel R, LeDuc RD, Friedman N, Regev A. De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis. Nat Protoc 2013; 8: 1494-1512.
Davidson NM, Oshlack A. Corset: enabling differential gene expression analysis for de novo assembled transcriptomes. Genome Biol 2014; 15: 410-423.
Conesa A, Götz S, García-Gómez JM, Terol J, Talón M, Robles M. Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics 2005; 21: 3674-3676.
Langmead B, Trapnell C, Pop M, Salzberg SL. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 2009; 10: R25.
Kozomara A, Griffiths-Jones S. miRBase: annotating high confi¬dence microRNAs using deep sequencing data. Nucleic Acids Res 2014; 42: D68-D73.
Wen M, Shen Y, Shi S, Tang T. miREvo: an integrative microR¬NA evolutionary analysis platform for next-generation sequencing experiments. BMC Bioinformatics 2012; 13: 140-149.
Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinfor¬matics 2011; 12: 323-338.
Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 2014; 15: 550.
Dai X, Zhuang Z, Zhao PX. psRNATarget: a plant small RNA target analysis server (2017 release). Nucleic Acids Res 2018; 46: W49-W54.
Young MD, Wakefield MJ, Smyth GK, Oshlack A. Gene onto¬logy analysis for RNA-seq: accounting for selection bias. Genome Biol 2010; 11: R14.
Mao X, Cai T, Olyarchuk JG, Wei L. Automated genome annota¬tion and pathway identification using the KEGG Orthology (KO) as a controlled vocabulary. Bioinformatics 2005; 21: 3787-3793.
Varkonyi-Gasic E, Wu R, Wood M, Walton EF, Hellens RP. Pro¬tocol: a highly sensitive RT-PCR method for detection and quantifi¬cation of microRNAs. Plant Methods 2007; 3: 12-23.
Suzuki H, Takahashi S, Watanabe R, Fukushima Y, Fujita N, Noguchi A, Yokoyama R, Nishitani K, Nishino T, Nakayama T. An isoflavone conjugate-hydrolyzing beta-glucosidase from the roots of soybean (Glycine max) seedlings: purification, gene cloning, phy¬logenetics, and cellular localization, J Biol Chem 2006; 281: 30251- 30259.
Wu G, Park MY, Conway SR, Wang JW, Weigel D, Poethig RS. The sequential action of miR156 and miR172 regulates develop¬mental timing in Arabidopsis. Cell 2009; 138: 750-759.
Lu X, Dun H, Lian C, Zhang X, Yin W, Xia X. The role of peu-miR164 and its target PeNAC genes in response to abiotic stress in Populus euphratica. Plant Physiol Biochem 2017; 115: 418-438.
Cui LG, Shan JX, Shi M, Gao JP, Lin HX. The miR156-SPL9- DFR pathway coordinates the relationship between development and abiotic stress tolerance in plants. Plant J 2014; 80: 1108-1117.
Yin H, Hong G, Li L, Zhang X, Kong Y, Sun Z, Li J, Chen J, He Y. miR156/SPL9 Regulates Reactive Oxygen Species Accumula¬tion and Immune Response in Arabidopsis thaliana. Phytopathology 2019; 109: 632-642.
Sunkar R, Kapoor A, Zhu JK. Posttranscriptional induction of two Cu/Zn superoxide dismutase genes in Arabidopsis is mediated by downregulation of miR398 and important for oxidative stress tolerance. Plant Cell 2006; 18: 2051-2065.
Schommer JM, Debernardi EG, Bresso RE, Rodriguez JF. Palat¬nik, Repression of cell proliferation by miR319-regulated TCP4. Mol Plant 2014; 7: 1533-1544.
DeFalco TA, Moeder W, Yoshioka K. Opening the Gates: Insights into Cyclic Nucleotide-Gated Channel-Mediated Signaling. Trends Plant Sci 2016; 21: 903-906.
Saand MA, Xu YP, Munyampundu JP, Li W, Zhang XR, Cai XZ. Phylogeny and evolution of plant cyclic nucleotide-gated ion chan¬nel (CNGC) gene family and functional analyses of tomato CNGCs. DNA Res 2015; 22: 471-483.
Sang JR, Zhang A, Lin F, Tan MP, Jiang MY. Cross-talk between calcium-calmodulin and nitric oxide in abscisic acid signaling in leaves of maize plants. Cell Research 2008; 18: 577-588.
Neill S, Barros R, Bright J, Desikan R, Hancock J, Harrison J, Morris P, Ribeiro D, Wilson I. Nitric oxide, stomatal closure, and abiotic stress. J Exp Bot 2008; 59: 165-176.
Zhang X, Li J, Liu A, Zou J, Zhou X, Xiang J, Rerksiri W, Peng Y, Xiong X, Chen X. Expression profile in rice panicle: insights into heat response mechanism at reproductive stage. PLoS One 2012; 7: e49652.
Mersmann S, Bourdais G, Rietz S, Robatzek S. Ethylene signa¬ling regulates accumulation of the FLS2 receptor and is required for the oxidative burst contributing to plant immunity. Plant Physiol 2012; 154: 391-400.
Zheng Z, Qamar SA, Chen Z, Mengiste T. Arabidopsis WRKY33 transcription factor is required for resistance to necrotrophic fungal pathogens. Plant J 2006; 48: 592-605.
Zhou J, Wang J, Zheng Z, Fan B, Yu JQ, Chen Z. Characteriza¬tion of the promoter and extended C-terminal domain of Arabidopsis WRKY33 and functional analysis of tomato WRKY33 homologues in plant stress responses. J Exp Bot 2015; 66: 4567-4583.
Ghaheri M, Kahrizi D., Bahrami GR, Mohammadi Motlagh HR. Study of gene expression and steviol glycosides accumulation in Stevia rebaudiana Bertoni under various mannitol concentrations. Mol Biol Rep 2019; 46:7-16.
Eastmond PJ. Glycerol-insensitive Arabidopsis mutants: gli1 seedlings lack glycerol kinase, accumulate glycerol and are more resistant to abiotic stress, Plant J 37 (2004) 617-625.

References

Zhou X, Yuping Z, Zhao H, Liang J, Zhang Y, Shi S. Antioxidant homoisoflavonoids from Polygonatum odoratum, Food Chem 2015; 186: 63-68.

Liang Y, Lin Q, Huang P, Wang Y, Li J, Zhang L and Cao J: Rice Bioactive Peptide Binding with TLR4 To Overcome H2O2-Induced Injury in Human Umbilical Vein Endothelial Cells through NF-ÎºB Signaling. J Agri Food Chem 66(2): 440-448, 2018.

Wang L, Lin Q, Yang T, Liang Y, Nie Y, Luo Y and Luo F: Oryza¬nol modifies high fat diet-induced obesity, liver gene expression pro¬file, and inflammation response in mice. J Agri Food Chem 65(38): 8374-8385, 2017.

Lou Y, Shi J, Guo D, Qureshi AK and Song L: Function of PD-L1 in antitumor immunity of glioma cells. Saudi J Boil Sci 24(4): 803-807, 2017.

Guo T, Lin Q, Li X, Nie Y, Wang L, Shi L and Luo F: Octacosa¬nol attenuates inflammation in both RAW264. 7 macrophages and a mouse model of colitis. J Agri Food Chem 65(18): 3647-3658, 2017.

Li W, Jia MX, Wang JH, Lu JL, Deng J, Tang JX and Liu C: As¬sociation of MMP9-1562C/T and MMP13-77A/G polymorphisms with non-small cell lung cancer in southern Chinese population. Biomol 9(3): 107-119, 2019.

Nie Y, Luo F, Wang L, Yang T, Shi L, Li X, Shen J, Xu W, Guo T and Lin Q: Anti-hyperlipidemic effect of rice bran polysaccharide and its potential mechanism in high-fat diet mice. Food Func 8(11): 4028-4041, 2017.

Wu H, Wu L, Wang J, Zhu Q, Lin S, Xu J, Zheng C, Chen J, Qin X, Fang C, Zhang Z, Azeem S, Lin W. Mixed Phenolic Acids Media¬ted Proliferation of Pathogens Talaromyces helicus and Kosakonia sacchari in Continuously Monocultured Radix pseudostellariae Rhi¬zosphere Soil. Front Microbiol 2016; 7: 335-348.

Zhang H, Jin W, Zhu X, Liu L, He Z, Yang S, Liang Z, Yan X, He Y, Liu Y, Identification and Characterization of Salvia miltiorrhizain miRNAs in Response to Replanting Disease. PLoS One 2016; 11: e0159905.

Tian Y, Feng F, Zhang B, Li M, Wang F, Gu L, Chen A, Li Z, Shan W, Wang X, Chen X, Zhang Z. Transcriptome analysis reveals metabolic alteration due to consecutive monoculture and abiotic stress stimuli in Rehamannia glutinosa Libosch. Plant Cell Rep 2017; 36: 859-875.

Weiss S, Bartsch M, Winkelmann T. Transcriptomic analysis of molecular responses in Malus Domestica 'M26' roots affected by apple replant disease. Plant Mol Biol 2017; 94: 303-318.

Li MJ, Yang YH, Chen XJ, Wang FQ, Lin WX, Yi YJ, Zeng L, Yang SY, Zhang ZY. Transcriptome/degradome-wide identification of R. glutinosa miRNAs and their targets: the role of miRNA activity in the replanting disease. PLoS One 2013; 8: e68531.

Zhao Y, Wu L, Chu L, Yang Y, Li Z, Azeem S, Zhang Z, Fang C, Lin W. Interaction of Pseudostellaria heterophylla with Fusarium oxysporum f.sp. heterophylla mediated by its root exudates in a consecutive monoculture system. Sci Rep 2015; 5: 8197-8203.

Kato-Noguchi H, Ino T, Sata N, Yamamura S. Isolation and iden¬tification of a potent allelopathic substance in rice root exudates. Physiol Plant 2002; 115: 401-405.

Yang YH, Li MJ, Li XY, Chen XJ, Lin WX, Zhang ZY. Trans¬criptome-wide identification of the genes responding to replanting disease in Rehmannia glutinosa L. roots. Mol Biol Rep 2015; 42: 881-892.

Lou Y, Yang J, Wang L, Chen X, Xin X and Liu Y: The clini¬cal efficacy study of treatment to Chiari malformation type I with syringomyelia under the minimally invasive surgery of resection of Submeningeal cerebellar Tonsillar Herniation and reconstruction of Cisterna magna. Saudi J Biol Sci 26(8): 1927-1931, 2019.

Lou Y, Guo D, Zhang H and Song L: Effectiveness of mesenchy¬mal stems cells cultured by hanging drop vs. conventional culturing on the repair of hypoxic-ischemic-damaged mouse brains, measured by stemness gene expression. Open Life Sci 11(1): 519-523, 2016.

Chen X, Xu Y, Meng L, Chen X, Yuan L, Cai Q, Shi W and Huang G: Non-parametric partial least squares–discriminant analy¬sis model based on sum of ranking difference algorithm for tea grade identification using electronic tongue data identify tea grade using e-tongue data. Sens Actuators B Chem 127924, 2020.

Nie Y, Luo F and Lin Q: Dietary nutrition and gut microflora: A promising target for treating diseases. Trends Food Sci Technol 75: 72-80, 2018.

Ren Y, Jiao X and Zhang L: Expression level of fibroblast growth factor 5 (FGF5) in the peripheral blood of primary hypertension and its clinical significance. Saudi J Biol Sci 25(3): 469-473, 2018.

Sunkar R, Li YF, Jagadeeswaran G. Functions of microRNAs in plant stress responses. Trends Plant Sci 2012; 17: 196-203.

Haas BJ, Papanicolaou A, Yassour M, Grabherr M, Blood PD, Bowden J, Couger MB, Eccles D, Li B, Lieber M, MacManes MD, Ott M, Orvis J, Pochet N, Strozzi F, Weeks N, Westerman R, Wil¬liam T, Dewey CN, Henschel R, LeDuc RD, Friedman N, Regev A. De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis. Nat Protoc 2013; 8: 1494-1512.

Davidson NM, Oshlack A. Corset: enabling differential gene expression analysis for de novo assembled transcriptomes. Genome Biol 2014; 15: 410-423.

Conesa A, Götz S, García-Gómez JM, Terol J, Talón M, Robles M. Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics 2005; 21: 3674-3676.

Langmead B, Trapnell C, Pop M, Salzberg SL. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 2009; 10: R25.

Kozomara A, Griffiths-Jones S. miRBase: annotating high confi¬dence microRNAs using deep sequencing data. Nucleic Acids Res 2014; 42: D68-D73.

Wen M, Shen Y, Shi S, Tang T. miREvo: an integrative microR¬NA evolutionary analysis platform for next-generation sequencing experiments. BMC Bioinformatics 2012; 13: 140-149.

Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinfor¬matics 2011; 12: 323-338.

Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 2014; 15: 550.

Dai X, Zhuang Z, Zhao PX. psRNATarget: a plant small RNA target analysis server (2017 release). Nucleic Acids Res 2018; 46: W49-W54.

Young MD, Wakefield MJ, Smyth GK, Oshlack A. Gene onto¬logy analysis for RNA-seq: accounting for selection bias. Genome Biol 2010; 11: R14.

Mao X, Cai T, Olyarchuk JG, Wei L. Automated genome annota¬tion and pathway identification using the KEGG Orthology (KO) as a controlled vocabulary. Bioinformatics 2005; 21: 3787-3793.

Varkonyi-Gasic E, Wu R, Wood M, Walton EF, Hellens RP. Pro¬tocol: a highly sensitive RT-PCR method for detection and quantifi¬cation of microRNAs. Plant Methods 2007; 3: 12-23.

Suzuki H, Takahashi S, Watanabe R, Fukushima Y, Fujita N, Noguchi A, Yokoyama R, Nishitani K, Nishino T, Nakayama T. An isoflavone conjugate-hydrolyzing beta-glucosidase from the roots of soybean (Glycine max) seedlings: purification, gene cloning, phy¬logenetics, and cellular localization, J Biol Chem 2006; 281: 30251- 30259.

Wu G, Park MY, Conway SR, Wang JW, Weigel D, Poethig RS. The sequential action of miR156 and miR172 regulates develop¬mental timing in Arabidopsis. Cell 2009; 138: 750-759.

Lu X, Dun H, Lian C, Zhang X, Yin W, Xia X. The role of peu-miR164 and its target PeNAC genes in response to abiotic stress in Populus euphratica. Plant Physiol Biochem 2017; 115: 418-438.

Cui LG, Shan JX, Shi M, Gao JP, Lin HX. The miR156-SPL9- DFR pathway coordinates the relationship between development and abiotic stress tolerance in plants. Plant J 2014; 80: 1108-1117.

Yin H, Hong G, Li L, Zhang X, Kong Y, Sun Z, Li J, Chen J, He Y. miR156/SPL9 Regulates Reactive Oxygen Species Accumula¬tion and Immune Response in Arabidopsis thaliana. Phytopathology 2019; 109: 632-642.

Sunkar R, Kapoor A, Zhu JK. Posttranscriptional induction of two Cu/Zn superoxide dismutase genes in Arabidopsis is mediated by downregulation of miR398 and important for oxidative stress tolerance. Plant Cell 2006; 18: 2051-2065.

Schommer JM, Debernardi EG, Bresso RE, Rodriguez JF. Palat¬nik, Repression of cell proliferation by miR319-regulated TCP4. Mol Plant 2014; 7: 1533-1544.

DeFalco TA, Moeder W, Yoshioka K. Opening the Gates: Insights into Cyclic Nucleotide-Gated Channel-Mediated Signaling. Trends Plant Sci 2016; 21: 903-906.

Saand MA, Xu YP, Munyampundu JP, Li W, Zhang XR, Cai XZ. Phylogeny and evolution of plant cyclic nucleotide-gated ion chan¬nel (CNGC) gene family and functional analyses of tomato CNGCs. DNA Res 2015; 22: 471-483.

Sang JR, Zhang A, Lin F, Tan MP, Jiang MY. Cross-talk between calcium-calmodulin and nitric oxide in abscisic acid signaling in leaves of maize plants. Cell Research 2008; 18: 577-588.

Neill S, Barros R, Bright J, Desikan R, Hancock J, Harrison J, Morris P, Ribeiro D, Wilson I. Nitric oxide, stomatal closure, and abiotic stress. J Exp Bot 2008; 59: 165-176.

Zhang X, Li J, Liu A, Zou J, Zhou X, Xiang J, Rerksiri W, Peng Y, Xiong X, Chen X. Expression profile in rice panicle: insights into heat response mechanism at reproductive stage. PLoS One 2012; 7: e49652.

Mersmann S, Bourdais G, Rietz S, Robatzek S. Ethylene signa¬ling regulates accumulation of the FLS2 receptor and is required for the oxidative burst contributing to plant immunity. Plant Physiol 2012; 154: 391-400.

Zheng Z, Qamar SA, Chen Z, Mengiste T. Arabidopsis WRKY33 transcription factor is required for resistance to necrotrophic fungal pathogens. Plant J 2006; 48: 592-605.

Zhou J, Wang J, Zheng Z, Fan B, Yu JQ, Chen Z. Characteriza¬tion of the promoter and extended C-terminal domain of Arabidopsis WRKY33 and functional analysis of tomato WRKY33 homologues in plant stress responses. J Exp Bot 2015; 66: 4567-4583.

Ghaheri M, Kahrizi D., Bahrami GR, Mohammadi Motlagh HR. Study of gene expression and steviol glycosides accumulation in Stevia rebaudiana Bertoni under various mannitol concentrations. Mol Biol Rep 2019; 46:7-16.

Eastmond PJ. Glycerol-insensitive Arabidopsis mutants: gli1 seedlings lack glycerol kinase, accumulate glycerol and are more resistant to abiotic stress, Plant J 37 (2004) 617-625.

Author biographies is not available.