Abstract
RNA silencing plays an important role in plant antiviral responses, which trigger the production of virus-derived small interfering RNAs (vsiRNAs). The competing endogenous RNA (ceRNA) hypothesis revealed a unique mechanism in which circular RNAs (circRNAs) and long non-coding RNAs (lncRNAs) can interact with small RNAs to regulate the expression of corresponding target mRNAs. Sugarcane mosaic virus (SCMV) infection causes severe economic losses in maize (Zea mays L.) production worldwide. This study compared and analyzed characteristics of vsiRNAs derived from SCMV and their target genes in resistant (Chang7-2) and susceptible (Mo17) maize inbred lines through whole-transcriptome RNA sequencing and degradome sequencing. The results showed that 706 transcripts were targeted by 204 vsiRNAs, including 784 vsiRNA-target gene pairs. Furthermore, ceRNA networks of circRNA/lncRNA-vsiRNA-mRNA in response of maize to SCMV infection were obtained, including 3 differentially expressed (DE) circRNAs, 36 DElncRNAs, 105 vsiRNAs, and 342 DEmRNAs in Mo17 plants, and 3 DEcircRNAs, 35 DElncRNAs, 23 vsiRNAs, and 87 DEmRNAs in Chang7-2 plants. Our results also showed that the transcripts of ZmDCLs, ZmAGOs, and ZmRDRs were differentially accumulated in resistant and susceptible maize inbred lines after SCMV infection. These findings provide valuable insights into the relationship between SCMV-derived vsiRNAs and potential ceRNAs fine-tuning the SCMV-maize interaction and offer novel clues to reveal the mechanism underlying the pathogenesis of SCMV.
Similar content being viewed by others
Background
Maize (Zea mays L.) is an essential crop for human food, animal feed, and industrial material, which is also a classic model plant for genetics research (Gore et al. 2009). Sugarcane mosaic virus (SCMV) is a positive-sense single-stranded RNA (+ ssRNA) virus in the genus Potyvirus of the family Potyviridae. SCMV can infect maize, sorghum (Sorghum vulgare), sugarcane (Saccharum sinensis), and many other Gramineae crops, causing significant losses in various field crops worldwide (Shi et al. 2005). SCMV is the primary causal agent of maize dwarf mosaic disease in China, which initially causes chlorotic symptoms at the base of the leaf and then extends to the whole leaf until a stripe mosaic pattern appears on maize (Jiang and Zhou 2002). Breeding and planting resistant maize varieties are the most economical and effective methods to control SCMV infection. Therefore, exploring the interaction between SCMV and maize plants is important for develo** effective virus-control strategies and cultivating disease-resistant varieties.
RNA silencing is a natural antiviral mechanism in plants, which is triggered by double-stranded RNAs (dsRNAs) with different sources and lengths (Pumplin and Voinnet 2013). Plant Dicer-like (DCL) and Argonaute (AGO) proteins play crucial antiviral roles in the RNA silencing pathway (Bouché et al. 2006; Schuck et al. 2013). The dsRNAs are cleaved by DCL proteins into virus-derived small interfering RNAs (vsiRNAs) of 21 to 24 nucleotides (nt) (Ding and Voinnet 2007). Previous studies have shown that plants infected with positive-strand RNA viruses mainly generate 21-nt vsiRNAs processed by DCL4, while 22-nt vsiRNAs produced by DCL2 are accumulated when the activity of DCL4 is reduced or inhibited (Bouché et al. 2006; Ding 2010). DCL1 and DCL3 can produce 21- and 24-nt vsiRNAs in dcl2/dcl3/dcl4 and dcl2/dcl4 mutant plants, respectively (Bouché et al. 2006; Qu et al. 2008). The vsiRNAs are loaded into RNA-induced silencing complexes (RISCs), which contain Argonaute (AGO) proteins, guiding the degradation of viral RNAs and host target mRNAs in a sequence-specific manner (Baumberger and Baulcombe 2005). In Arabidopsis, AGOs 1, 2, 4, 5, 7, and 10 can bind vsiRNAs upon different virus infections (Carbonell and Carrington 2015). AGO1 is most important in plant antiviral defense (Harvey et al. 2011). Moreover, AGO2 can protect against suppressor-defective tomato bushy stunt virus (TBSV) in Nicotiana benthamiana (Scholthof et al. 2011). AGO4 also shows antiviral function in CMV-infected N. benthamiana (Ye et al. 2009). AGO1 and AGO18 are the main antiviral AGOs against rice stripe virus (RSV) and rice dwarf virus (RDV) in rice (Carbonell and Carrington 2015). In plants, the effect of RNA silencing can be amplified by cellular RNA-dependent RNA polymerases (RDRs), which synthesize dsRNAs and produce secondary vsiRNAs (Wang et al. 2010).
Previous studies have shown that vsiRNAs are mainly responsible for RNA silencing mediated antiviral immunity (Zhu et al. 2011). Recently, more and more studies suggest that vsiRNAs play potential regulatory roles in the expression of host genes, which determines the manifestation of viral symptoms in host plants (Wang et al. 2022). The first report of this phenomenon was the vsiRNAs derived from CMV Y-satellite that specifically regulate the expression of chlorophyll-related gene (ChlI) and modulate the typical yellowing symptoms in N. benthamiana (Smith et al. 2011; Shimura et al. 2011). It has also been reported that Chinese wheat mosaic virus (CWMV) RNA1-derived vsiRNA-20 can cleave the mRNA of TaVP to maintain a weak alkaline environment in the cytoplasm to enhance CWMV infection in wheat (Yang et al. 2020; Huang et al. 2022).
Recently, competing endogenous RNAs (ceRNAs) have been widely accepted as a new mode of gene regulation, of which circular RNAs (circRNAs) and long non-coding RNAs (lncRNAs) can act as ceRNAs to regulate miRNA or vsiRNA activity (Song et al. 2021). Based on this mechanism, many studies have analyzed the regulatory network of ceRNA-miRNA/siRNA-target gene in plants (Salmena et al. 2011). For example, maize lncRNA PILNCR1 inhibits miR399-guided cleavage of PHOSPHATE2 (PHO2) to regulate plant tolerance to low phosphate (Du et al. 2018). Tomato lncRNA08489-miR482e module was reported to enhance host resistance to Phytophthora infestans through the reactive oxygen species (ROS)-scavenging system (Liu et al. 2022). In addition, LINC-AP2 contributes to the formation of shorter stamen in the flowers of A. thaliana plants infected with turnip crinkle virus (TCV) by anti-cis downregulating the expression of AP2 gene (Gao et al. 2016). Tomato lncRNA SlLNR1 interacts with vsiRNAs derived from a non-coding intergenic region (IR) of tomato yellow leaf curl virus (TYLCV) and suppresses disease development during viral infection (Yang et al. 2019). However, there is still a lack of comprehensive research on the interactions among circRNA, lncRNA, vsiRNA, and mRNA in virus-infected maize plants.
Our previous studies have reported the vsiRNA expression profiles in SCMV-infected maize inbred lines Zong 31 and B73 plants (** and transcriptome assembly
The raw data of whole-transcriptome RNA sequencing were processed using SOAPnuke v1.5.2 (Chen et al. 2018), and sequence quality was verified with FastQC (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). For small RNA sequencing data, clean reads from each sample were screened in a range of length (18–36 nt). Next, these small RNA sequences were mapped to SCMV genome (Accession number: AY042184), and only those sequences that were identical or complementary to the viral genome sequences within two mismatches were identified as vsiRNAs. For RNA sequencing data, clean reads were mapped to B73 reference genome (ftp://ftp.ensemblgenomes.org/pub/release-45/plants/fasta/zea_mays/dna/, B73_RefGen_v4) using HISAT2 software (http://ccb.jhu.edu/software/hisat2/index.shtml). StringTie v1.3.0 was used to assemble the mapped reads of each sample (Pertea et al. 2015).
Degradome library construction and sequencing analysis
Total RNA from both treatment and control groups was pooled together to prepare the degradome library. The process of library construction was as follows: (a) mRNA fragments with poly (A) sequences were specifically captured with poly (T) magnetic beads; (b) 5′ RNA adapters were ligated to RNAs containing 5′ monophosphates; (c) The ligated products were purified and reverse-transcribed into cDNAs using biotinylated random primers; (d) The cDNAs were amplified by PCR to construct the degradome libraries; (e) Single-end (36 bp) sequencing was then performed on an Illumina Hiseq 2500 (LC Bio, Hangzhou, China). The original data of degradome sequencing (BioProject: GSE234274) have been uploaded to NCBI database.
The raw reads were processed using ACGT101-DEG (LC Sciences, Houston, Texas, USA) and potential siRNA editing sites were identified using the small RNA sequencing data by CleaveLand4 software (Addo-Quaye et al. 2009). Thereafter, based on the characteristics and abundance of maize RNA sequencing data, T-plots were established for high efficiency analysis of potential siRNA targets.
GO and KEGG pathway analysis
The predicted target genes of vsiRNAs were aligned based on BLAST (http://blast.ncbi.nlm.nih.gov/). GO analysis was performed to construct annotations of vsiRNA targets using AgriGO v2.0 (Tian et al. 2017). KEGG pathway analysis was implemented to understand the function among targets of vsiRNA by KOBAS 2.0 (**e et al. 2011). The threshold of significant GO terms and KEGG pathways was set to p < 0.05.
Target gene prediction and visualization of ceRNA regulatory network
To understand the potential molecular functions of the candidate vsiRNAs, according to the ceRNA theory, the interaction of ncRNA-vsiRNA and vsiRNA-mRNA pairs were predicted simultaneously by psRNATarget (Dai and Zhao 2011). The ceRNAs networks regulatory network was visualized using Cytoscape v3.7.2 software (Shannon et al. 2003) to display the potential relationships between circRNAs, lncRNAs, vsiRNAs, and mRNAs.
qRT-PCR analysis
Total RNA was extracted from samples by TRIzol Reagent (Vazyme, Nan**g, China) according to the manufacturer’s instructions. About 2 μg of total RNA was reverse-transcribed into cDNA with PrimeScript RT Reagent (TaKaRa, Dalian, China). The qRT-PCR reactions were performed on StepOne plus real time PCR platform (Applied Biosystems, Foster City, USA) using SYBR Green PCR Master Mix (Vazyme, Nan**g, China) as instructed. ZmUBI (XM_008647047) gene was used as an internal control, and relative gene expression levels in different samples were calculated by the 2−ΔΔCT method (Schefe et al. 2006). All primers were listed in Additional file 1: Table S19.
Availability of data and materials
The datasets presented in this study have been deposited in the NCBI. The accession number is PRJNA978581, GSE233952, and GSE234274.
Abbreviations
- AGO:
-
Argonaute
- CBB:
-
Coomassie brilliant blue
- ceRNA:
-
Competing endogenous RNA
- circRNA:
-
Circular RNA
- CP:
-
Coat protein
- DCL:
-
Dicer-like
- DE:
-
Differentially expressed
- lncRNA:
-
Long non-coding RNA
- MC:
-
Chang7-2 inoculated with phosphate buffer
- MM:
-
Mo17 inoculated with phosphate buffer
- qRT-PCR:
-
Quantitative real time reverse transcription-polymerase chain reaction
- RISC:
-
RNA-induced silencing complex
- RT-PCR:
-
Reverse transcription-polymerase chain reaction
- SA:
-
Salicylic acid
- SC:
-
Chang7-2 inoculated with SCMV
- SCMV:
-
Sugarcane mosaic virus
- SM:
-
Mo17 inoculated with SCMV
- vsiRNA:
-
Virus-derived small interfering RNA
References
Addo-Quaye C, Miller W, Axtell MJ. CleaveLand: a pipeline for using degradome data to find cleaved small RNA targets. Bioinformatics. 2009;25:130–1. https://doi.org/10.1093/bioinformatics/btn604.
Baumberger N, Baulcombe DC. Arabidopsis ARGONAUTE1 is an RNA Slicer that selectively recruits microRNAs and short interfering RNAs. Proc Natl Acad Sci U S A. 2005;102:11928–33. https://doi.org/10.1073/pnas.0505461102.
Bouché N, Lauressergues D, Gasciolli V, Vaucheret H. An antagonistic function for Arabidopsis DCL2 in development and a new function for DCL4 in generating viral siRNAs. EMBO J. 2006;25:3347–56. https://doi.org/10.1038/sj.emboj.7601217.
Carbonell A, Carrington JC. Antiviral roles of plant ARGONAUTES. Curr Opin Plant Biol. 2015;27:111–7. https://doi.org/10.1016/j.pbi.2015.06.013.
Chen Y, Chen Y, Shi C, Huang Z, Zhang Y, Li S, et al. SOAPnuke: a MapReduce acceleration-supported software for integrated quality control and preprocessing of high-throughput sequencing data. Gigascience. 2018;7:1–6. https://doi.org/10.1093/gigascience/gix120.
Chiba Y, Shimizu T, Miyakawa S, Kanno Y, Koshiba T, Kamiya Y, et al. Identification of Arabidopsis thaliana NRT1/PTR FAMILY (NPF) proteins capable of transporting plant hormones. J Plant Res. 2015;128:679–86. https://doi.org/10.1007/s10265-015-0710-2.
Choudhary MK, Basu D, Datta A, Chakraborty N, Chakraborty S. Dehydration-responsive nuclear proteome of rice (Oryza sativa L.) illustrates protein network, novel regulators of cellular adaptation, and evolutionary perspective. Mol Cell Proteom. 2009;8:1579–98. https://doi.org/10.1074/mcp.M800601-MCP200.
Cui X, Fan B, Scholz J, Chen Z. Roles of Arabidopsis cyclin-dependent kinase C complexes in cauliflower mosaic virus infection, plant growth, and development. Plant Cell. 2007;19:1388–402. https://doi.org/10.1105/tpc.107.051375.
Dai X, Zhao PX. psRNATarget: a plant small RNA target analysis server. Nucleic Acids Res. 2011;39:155–9. https://doi.org/10.1093/nar/gkr319.
Ding SW. RNA-based antiviral immunity. Nat Rev Immunol. 2010;10:632–44. https://doi.org/10.1038/nri2824.
Ding S, Voinnet O. Antiviral immunity directed by small RNAs. Cell. 2007;130:413–26. https://doi.org/10.1016/j.cell.2007.07.039.
Donaire L, Barajas D, Martínez-García B, Martínez-Priego L, Pagán I, Llave C. Structural and genetic requirements for the biogenesis of Tobacco rattle virus-derived small interfering RNAs. J Virol. 2008;82:5167–77. https://doi.org/10.1128/jvi.00272-08.
Donaire L, Wang Y, Gonzalez-Ibeas D, Mayer KF, Aranda MA, Llave C. Deep-sequencing of plant viral small RNAs reveals effective and widespread targeting of viral genomes. Virology. 2009;392:203–14. https://doi.org/10.1016/j.virol.2009.07.005.
Du Q, Wang K, Zou C, Xu C, Li WX. The PILNCR1-miR399 regulatory module is important for low phosphate tolerance in maize. Plant Physiol. 2018;177:1743–53. https://doi.org/10.1104/pp.18.00034.
Fusaro AF, Matthew L, Smith NA, Curtin SJ, Dedic-Hagan J, Ellacott GA, et al. RNA interference-inducing hairpin RNAs in plants act through the viral defence pathway. EMBO Rep. 2006;7:1168–75. https://doi.org/10.1038/sj.embor.7400837.
Gao R, Liu P, Irwanto N, Loh R, Wong SM. Upregulation of LINC-AP2 is negatively correlated with AP2 gene expression with Turnip crinkle virus infection in Arabidopsis thaliana. Plant Cell Rep. 2016;35:2257–67. https://doi.org/10.1007/s00299-016-2032-9.
Gore MA, Chia JM, Elshire RJ, Sun Q, Ersoz ES, Hurwitz BL, et al. A first-generation haplotype map of maize. Science. 2009;326:1115–7. https://doi.org/10.1126/science.1177837.
Hamera S, Song X, Su L, Chen X, Fang R. Cucumber mosaic virus suppressor 2b binds to AGO4-related small RNAs and impairs AGO4 activities. Plant J. 2012;69:104–15. https://doi.org/10.1111/j.1365-313X.2011.04774.x.
Harvey JJ, Lewsey MG, Patel K, Westwood J, Heimstädt S, Carr JP, et al. An antiviral defense role of AGO2 in plants. PLoS ONE. 2011;6: e14639. https://doi.org/10.1371/journal.pone.0014639.
Huang X, Li F, Zhang X, Chen J, Wang J, Wei J, et al. A virus-derived small RNA targets the rice transcription factor ROC1 to induce disease-like symptom. Phytopathol Res. 2022;4:7. https://doi.org/10.1186/s42483-022-00112-6.
Jiang J, Zhou X. Maize dwarf mosaic disease in different regions of China is caused by Sugarcane mosaic virus. Arch Virol. 2002;147:2437–43. https://doi.org/10.1007/s00705-002-0890-7.
Karim S, Holmström KO, Mandal A, Dahl P, Hohmann S, Brader G, et al. AtPTR3, a wound-induced peptide transporter needed for defence against virulent bacterial pathogens in Arabidopsis. Planta. 2007;225:1431–45. https://doi.org/10.1007/s00425-006-0451-5.
Liu J, Yang J, Bi H, Zhang P. Why mosaic? Gene expression profiling of African cassava mosaic virus-infected cassava reveals the effect of chlorophyll degradation on symptom development. J Integr Plant Biol. 2014;56:122–32. https://doi.org/10.1111/jipb.12133.
Liu W, Cui J, Luan Y. Overexpression of lncRNA08489 enhances tomato immunity against Phytophthora infestans by decoying miR482e-3p. Biochem Biophys Res Commun. 2022;587:36–41. https://doi.org/10.1016/j.bbrc.2021.11.079.
Mi S, Cai T, Hu Y, Chen Y, Hodges E, Ni F, et al. Sorting of small RNAs into Arabidopsis Argonaute complexes is directed by the 5’ terminal nucleotide. Cell. 2008;133:116–27. https://doi.org/10.1016/j.cell.2008.02.034.
Peng Y, Bartley LE, Canlas P, Ronald PC. OsWRKY IIa transcription factors modulate rice innate immunity. Rice. 2010;3:36–42. https://doi.org/10.1007/s12284-010-9039-6.
Pertea M, Pertea GM, Antonescu CM, Chang TC, Mendell JT, Salzberg SL. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat Biotechnol. 2015;33:290–5. https://doi.org/10.1038/nbt.3122.
Prasad ME, Stone SL. Further analysis of XBAT32, an Arabidopsis RING E3 ligase, involved in ethylene biosynthesis. Plant Signal Behav. 2010;5:1425–9. https://doi.org/10.4161/psb.5.11.13294.
Pumplin N, Voinnet O. RNA silencing suppression by plant pathogens: defence, counter-defence and counter-counter-defence. Nat Rev Microbiol. 2013;11:745–60. https://doi.org/10.1038/nrmicro3120.
Qin Q, Li G, ** L, Huang Y, Wang Y, Wei C, et al. Auxin response factors (ARFs) differentially regulate rice antiviral immune response against rice dwarf virus. PLoS Pathog. 2020;16: e1009118. https://doi.org/10.1371/journal.ppat.1009118.
Qu F, Ye X, Morris TJ. Arabidopsis DRB4, AGO1, AGO7, and RDR6 participate in a DCL4-initiated antiviral RNA silencing pathway negatively regulated by DCL1. Proc Natl Acad Sci U S A. 2008;105:14732–7. https://doi.org/10.1073/pnas.0805760105.
Salmena L, Poliseno L, Tay Y, Kats L, Pandolfi PP. A ceRNA hypothesis: the Rosetta Stone of a hidden RNA language? Cell. 2011;146:353–8. https://doi.org/10.1016/j.cell.2011.07.014.
Schefe JH, Lehmann KE, Buschmann IR, Unger T, Funke-Kaiser H. Quantitative real-time RT-PCR data analysis: current concepts and the novel “gene expression’s CT difference” formula. J Mol Med. 2006;84:901–10. https://doi.org/10.1007/s00109-006-0097-6.
Schneider CA, Rasband WS, Eliceiri KW. NIH Image to ImageJ: 25 years of image analysis. Nat Methods. 2012;9:671–5. https://doi.org/10.1038/nmeth.2089.
Scholthof HB, Alvarado VY, Vega-Arreguin JC, Ciomperlik J, Odokonyero D, Brosseau C, et al. Identification of an ARGONAUTE for antiviral RNA silencing in Nicotiana benthamiana. Plant Physiol. 2011;156:1548–55. https://doi.org/10.1104/pp.111.178764.
Schuck J, Gursinsky T, Pantaleo V, Burgyán J, Behrens SE. AGO/RISC-mediated antiviral RNA silencing in a plant in vitro system. Nucleic Acids Res. 2013;41:5090–103. https://doi.org/10.1093/nar/gkt193.
Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13:2498–504. https://doi.org/10.1101/gr.1239303.
Shi C, Ingvardsen C, Thümmler F, Melchinger AE, Wenzel G, Lübberstedt T. Identification by suppression subtractive hybridization of genes that are differentially expressed between near-isogenic maize lines in association with sugarcane mosaic virus resistance. Mol Genet Genom. 2005;273:450–61. https://doi.org/10.1007/s00438-004-1103-8.
Shimura H, Pantaleo V, Ishihara T, Myojo N, Inaba J, Sueda K, et al. A viral satellite RNA induces yellow symptoms on tobacco by targeting a gene involved in chlorophyll biosynthesis using the RNA silencing machinery. PLoS Pathog. 2011;7: e1002021. https://doi.org/10.1371/journal.ppat.1002021.
Smith NA, Eamens AL, Wang MB. Viral small interfering RNAs target host genes to mediate disease symptoms in plants. PLoS Pathog. 2011;7: e1002022. https://doi.org/10.1371/journal.ppat.1002022.
Song L, Fang Y, Chen L, Wang J, Chen X. Role of non-coding RNAs in plant immunity. Plant Commun. 2021;2: 100180. https://doi.org/10.1016/j.xplc.2021.100180.
Tian T, Liu Y, Yan H, You Q, Yi X, Du Z, et al. AgriGO v2.0: a GO analysis toolkit for the agricultural community. Nucleic Acids Res. 2017;45:122–9. https://doi.org/10.1093/nar/gkx382.
Wang XB, Wu Q, Ito T, Cillo F, Li WX, Chen X, et al. RNAi-mediated viral immunity requires amplification of virus-derived siRNAs in Arabidopsis thaliana. Proc Natl Acad Sci U S A. 2010;107:484–9. https://doi.org/10.1073/pnas.0904086107.
Wang Y, Cui X, Yang B, Xu S, Wei X, Zhao P, et al. WRKY55 transcription factor positively regulates leaf senescence and the defense response by modulating the transcription of genes implicated in the biosynthesis of reactive oxygen species and salicylic acid in Arabidopsis. Development. 2020. https://doi.org/10.1242/dev.189647.
Wang C, Jiang F, Zhu S. Complex small RNA-mediated regulatory networks between viruses/viroids/satellites and host plants. Virus Res. 2022;311: 198704. https://doi.org/10.1016/j.virusres.2022.198704.
**a Z, Peng J, Li Y, Chen L, Li S, Zhou T, et al. Characterization of small interfering RNAs derived from Sugarcane mosaic virus in infected maize plants by deep sequencing. PLoS ONE. 2014;9: e97013. https://doi.org/10.1371/journal.pone.0097013.
**a Z, Zhao Z, Chen L, Li M, Zhou T, Deng C, et al. Synergistic infection of two viruses MCMV and SCMV increases the accumulations of both MCMV and MCMV-derived siRNAs in maize. Sci Rep. 2016;6:20520. https://doi.org/10.1038/srep20520.
**e C, Mao X, Huang J, Ding Y, Wu J, Dong S, et al. KOBAS 2.0: a web server for annotation and identification of enriched pathways and diseases. Nucleic Acids Res. 2011;39:316–22. https://doi.org/10.1093/nar/gkr483.
Yang Y, Liu T, Shen D, Wang J, Ling X, Hu Z, et al. Tomato yellow leaf curl virus intergenic siRNAs target a host long non-coding RNA to modulate disease symptoms. PLoS Pathog. 2019;15: e1007534. https://doi.org/10.1371/journal.ppat.1007534.
Yang J, Zhang T, Li J, Wu N, Wu G, Yang J, et al. Chinese wheat mosaic virus-derived vsiRNA-20 can regulate virus infection in wheat through inhibition of vacuolar- (H+)-PPase induced cell death. New Phytol. 2020;226:205–20. https://doi.org/10.1111/nph.16358.
Ye J, Qu J, Zhang JF, Geng YF, Fang RX. A critical domain of the Cucumber mosaic virus 2b protein for RNA silencing suppressor activity. FEBS Lett. 2009;583:101–6. https://doi.org/10.1016/j.febslet.2008.11.031.
Zhao W, Li Y, Fan S, Wen T, Wang M, Zhang L, et al. The transcription factor WRKY32 affects tomato fruit colour by regulating YELLOW FRUITED-TOMATO 1, a core component of ethylene signal transduction. J Exp Bot. 2021;72:4269–82. https://doi.org/10.1093/jxb/erab113.
Zhu H, Duan CG, Hou WN, Du QS, Lv DQ, Fang RX, et al. Satellite RNA-derived small interfering RNA satsiR-12 targeting the 3’ untranslated region of Cucumber mosaic virus triggers viral RNAs for degradation. J Virol. 2011;85:13384–97. https://doi.org/10.1128/jvi.05806-11.
Zhu Y, Schluttenhoffer CM, Wang P, Fu F, Thimmapuram J, Zhu JK, et al. CYCLIN-DEPENDENT KINASE8 differentially regulates plant immunity to fungal pathogens through kinase-dependent and -independent functions in Arabidopsis. Plant Cell. 2014;26:4149–70. https://doi.org/10.1105/tpc.114.128611.
Acknowledgements
The authors thank Prof. Zaifeng Fan (China Agricultural University, Bei**g) for providing the source of SCMV.
Funding
This research was supported by grants from the National Natural Science Foundation of China (31801702).
Author information
Contributions
XG, KH, ZD, and SZ performed the experiments. XG analyzed the data. ZX and YW designed the study. XG wrote the draft manuscript. ZX, YW, MA, and ZW revised the manuscript. All authors read and approved the final manuscript.
Corresponding authors
Ethics declarations
Ethical approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Supplementary Information
Additional file 1:
Table S1. Statistical analysis of small RNAs from Mock- and SCMV-inoculated resistant and susceptible maize inbred lines. Table S2. Statistical analysis of RNA-seq data from 12 cDNA libraries of maize samples. Table S3. The differentially expressed circRNAs in Mo17 plants. Table S4. The differentially expressed circRNAs in Chang7-2 plants. Table S5. The differentially expressed lncRNAs in Mo17 plants. Table S6. The differentially expressed lncRNAs in Chang7-2 plants. Table S7. The differentially expressed mRNAs in Mo17 plants. Table S8. The differentially expressed mRNAs in Chang7-2 plants. Table S9. vsiRNAs with high abundance in SM libraries. Table S10. vsiRNAs with high abundance in SC libraries. Table S11. GO analysis of target genes of selected vsiRNAs from MM libraries. Table S12. GO analysis of target genes of selected vsiRNAs from MC libraries. Table S13. KEGG analysis of target genes of selected vsiRNAs from MM libraries. Table S14. KEGG analysis of target genes of selected vsiRNAs from MC libraries. Table S15. GO terms and KEGG pathways for the target genes of selected 10 vsiRNAs. Table S16. The ceRNA networks in Mo17 plants. Table S17. The ceRNA networks in Chang7-2 plants. Table S18. The important vsiRNAs and their associated circRNAs, lncRNAs and mRNAs. Table S19. The primers used in this study.
Additional file 2
: Figure S1. Relative frequency of the 5′-terminal nucleotides of vsiRNAs and the distribution of sense and antisense stand vsiRNAs. Figure S2. Validation of circRNAs. RT-PCR and PCR assays were conducted with a mixed sample consisting of Mock- and SCMV-inoculated Mo17 and Chang7-2 maize plants.
Rights and permissions
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/.
About this article
Cite this article
Gao, X., Hao, K., Du, Z. et al. Identification of ceRNA-vsiRNA-mRNA network for exploring the mechanism underlying pathogenesis of sugarcane mosaic virus in resistant and susceptible maize inbred lines. Phytopathol Res 5, 60 (2023). https://doi.org/10.1186/s42483-023-00216-7
Received:
Accepted:
Published:
DOI: https://doi.org/10.1186/s42483-023-00216-7