Transcriptome analysis reveals different response of resistant and susceptible rice varieties to rice stripe virus infection

LIU Yu ,LIU Wen-wen ,LI Li ,Frederic FRANCIS# ,WANG Xi-feng#

1 State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, P.R.China

2 Functional &Evolutionary Entomology, Gembloux Agro-BioTech, University of Liège, Gembloux 5030, Belgium

Abstract Rice stripe disease,caused by rice stripe virus (RSV) which is transmitted by small brown planthopper (SBPH,Laodelphax striatellus Fallen),resulted in serious losses to rice production during the last 2 decades.Research on the molecular differences between resistant and susceptible rice varieties and the interaction between rice and RSV remains inadequate.In this study,RNA-Seq was used to analyze the transcriptomic differences between the resistant and susceptible rice varieties at different times post RSV infection.Through Gene Ontology (GO) annotation,the differentially expressed genes (DEGs) related to transcription factors,peroxidases,and kinases of 2 varieties at 3 time points were identified.Comparing these 2 varieties,the DEGs associated with these 3 GOs were numerically less in the resistant variety than in the susceptible variety,but the expression showed a significant up-or down-regulation trend under the conditions of |log2(Fold change)|>0 &Padj<0.05 by significance analysis.Then through Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation,DEGs involved in some pathways that have a contribution to disease resistance including plant hormone signal transduction and plant–pathogen interaction were found.The results showed that resistance responses regulated by abscisic acid (ABA) and brassinosteroids (BR) were the same for 2 varieties,but that mediated by salicylic acid (SA) and jasmonic acid (JA)/ethylene (ET) were different.The DEGs in resistant and susceptible varieties at the 3 time points were identified in both PAMP-triggered immunity (PTI) and Effector proteintriggered immunity (ETI),with that most of the unigenes of the susceptible variety were involved in PTI,whereas most of the unigenes of the resistant variety were involved in ETI.These results revealed the different responses of resistant and susceptible varieties in the transcription level to RSV infection.

Keywords: transcriptomics,resistance,susceptibility,rice stripe virus (RSV),infection

1.Introduction

Rice stripe disease is responsible for significant yield losses in rice production in temperate and subtropical east Asian countries (Wanget al.2008).It occurs in more than 20 provinces and cities in China (Zhanget al.2007;Liet al.2016).From 2000 to 2005,1 700 000 hectares of rice fields were affected by this virus in Jiangsu Province,including 1 000 000 hectares where yield losses exceeded 50%,and some places without any rice harvest (Zhanget al.2007;Wanget al.2008;Weiet al.2009).The disease is caused by RSV,which is transmitted by SBPH in a persistent propagative manner (Qinet al.2018;Chenet al.2019).RSV belongs to the genusTenuivirus,and its genome consists of 4 single-stranded RNA segments which can encode 7 proteins (Sunet al.2016;Wuet al.2018).These proteins are involved in many biological processes including virus movement,viral encapsidation,RNA silencing inhibition,viral transcription and virus transmission (Xionget al.2008,2009;Zhouet al.2012).Symptoms of rice stripe disease typically include irregular chlorosis mottlings or yellow-white stripes at the base of the heart leaves parallel to the veins.Forjaponicarice,the heart leaves gradually turn yellow and curl up into papertwisting drooping,while forindicarice,only irregular chlorosis mottlings appear on the leaves (Wanget al.2015).

Plant disease resistance means the ability of plants to avoid,prevent or block the invasion and expansion of pathogens (Savaryet al.2019).During long-term coevolution,disease resistance is the result of mutual adaptation and selection between plant and pathogen(Chisholmet al.2006).The purpose of investigating plant disease resistance is to understand the regularity of disease resistance and how to utilize the resistance to protect plants (Joneset al.2006;Penget al.2020).

Plant disease resistance mainly depends on the signal pathway network of innate immunity and the resistance gene (Rgene) (Heet al.2007).Plant defense systems include basic defense systems and specific defense systems.Basic defense systems detect pathogens invading plants and provide immunity when infection occurs;specific defense mechanisms limit pathogen growth and disease progression through hypersensitive response (HR) resulting from programmed cell death around the site of infection (Joneset al.2006;Yinet al.2022).In addition,many biological processes and cellular compounds are involved in the immunity process of plants in the interaction between plant and pathogen(Bailey-Serres and Mittler 2006;Bari and Jones 2009;Taoet al.2009;Zhanget al.2010;Derrienet al.2012).It is reported that cytokinin and SA signal transduction enhances rice resistance to biotrophic pathogens in a synergistic way (Jianget al.2013).Besides,autophagy leads to programmed cell death (PCD) at the sites of TMV infection,uninfected adjacent tissue and the systemic leaves inNgene-containing plants to limit the spread of pathogens (Liuet al.2005).Moreover,OsWRKY45-2(a kind of transcription factor) shows resistance toXanthomonasoryzaepv.oryzae(Xoo)resulting in the increasing accumulation of jasmonic acid(JA) (Taoet al.2009).Previous research found that plants produced reactive oxygen species (ROS) to limit the invasion of pathogens by strengthening cell walls and cellulose deposition to enhance the innate immune response (Tripathy and Oelmüller 2012).Kinases form the largest gene family of receptors in plants and play an important role in recognizing pathogen-associated molecular patterns and regulating plant immunity to pathogens (Zhanget al.2010).However,research on the molecular differences between resistant and susceptible rice varieties and the interaction between rice and RSV remains inadequate.

As a transcriptome research method,RNA-Seq helps to provide more information about the transcription level of organisms (Mortazaviet al.2008).Recently,RNASeq has been used to research the structure of proteincoding genes,obtain new protein-coding genes and quantify and compare gene expression (Wanget al.2009;Garberet al.2011;Raoet al.2019).RNA-Seq also works in the study of the overall changes in hostgene expression during plant–virus interaction (Choet al.2015;Sunet al.2016;Liuet al.2020).In this study,we analyzed the transcriptome differences between resistant and susceptible rice varieties after RSV infection by RNASeq.We found that the DEGs associated with disease resistance,including transcription factors,peroxidases,kinases,plant hormone signal transduction and plant–pathogen interaction of the resistant variety were more significantly up-or down-regulated than that of the susceptible variety.These findings will provide valuable information for further research on the interaction between rice and RSV,and the molecular mechanisms of rice resistance to RSV infection.

2.Materials and methods

2.1.Rice seedlings inoculated with RSV

Rice seedlings of resistant variety (Zhendao 88) and susceptible variety (Wuyujing 3) were planted in plastic pots containing nutrient soil in the greenhouse.When seedlings grow at the stage of 3 leaves,both varieties were inoculated with 5 third instar viruliferous SBPHs in a plastic pot and healthy insects as the control.At 2 days post-inoculation (dpi),these insects were removed from the plants and rice seedlings continue to grow in the greenhouse.The insect vector (SBPH) was reared in a 1-L glass beaker in a climate chamber at 26°C with a photoperiod of 14 h light and 10 h dark.

2.2.RNA extraction and illumina sequencing

Heart leaves of each rice plant were both collected from susceptible and resistant lines in RSV inoculated and mock plants at 2,10 and 20 dpi.Then samples were immediately immersed in liquid nitrogen and stored at–80°C until RNA extraction.We recorded phenotypes of rice seedlings at 3 time points,and typical symptoms showed at 20 dpi (Fig.1).Total RNA was extracted by Trizol reagent (Invitrogen Trading,Shanghai,China)according to the protocols.Total RNA concentration in different samples was measured using Agilent 2100 Bioanalyzer (Plant RNA Nano Chip,Agilent,USA).The library construction and sequencing were done by Novogene (Novogene Bioinformatics Technology Co.,Ltd.,Beijing,China).

Fig.1 Phenotypes of rice seedlings of WYJ3 and ZD88 inoculated with rice stripe virus (RSV) at 3 time points.A,C,and E,phenotypes of WYJ3 at 2,10,and 20 days post-inoculation(dpi),respectively.B,D,and F,phenotypes of ZD88 at 2,10,and 20 dpi,respectively.Mock,mock-treated rice plant;RSVinfected,RSV-inoculated rice plant.

2.3.Analysis of the RNA-Seq data

Raw reads were producedviathe fastQC application(Anders and Huber 2010).Clean data (clean reads) were obtained by removing reads containing adapter,reads containing ploy-N and low-quality reads from raw data.Index of the reference genome was built and paired-end clean reads (200–300 bp) were aligned to the reference genome using HISAT2 (2.0.5) (http://ccb.jhu.edu/software/hisat2/faq.shtml).FeatureCounts (1.5.0-p3) was used to count the reads numbers mapped to each gene.And then number of Fragments Per Kilobase of transcript sequence per Million base pairs sequenced (FPKM) of each gene was calculated based on the length of the gene and reads count mapped to this gene.The differential expression analysis between RSV-inoculated and mock samples was performed using the DESeq2 R package (1.16.1).Genes with |log2(Fold change)|>0 andPadj<0.05 were considered as DEGs in comparative analysis.

2.4.Bioinformatics analysis

For a clearer understanding of the DEGs,the GO annotation for functional analysis and KEGG for the complex biological processes were done using the clusterProfiler Software.For GO annotation,these DEGs were classified based on the molecular function,biological process,and cellular components,and GO term with correctedP-value<0.05 was considered significantly enriched by DEGs.And for pathway analysis,we obtained all the pathway items that all the DEGs were involved in,and then screened the significantly enriched pathway items,taking correctedP-value<0.05 as a threshold.

2.5.Validation by RT-qPCR

The transcriptional level of identified genes was detected by RT-qPCR.The reverse transcription was done by the TRUEscript 1st Strand cDNA Synthesis Kit (Aidlab,Beijing) according to the manufacturer’s instructions.Then RT-qPCR was performed using the SYBR TransStart?Green qPCR SuperMix (Transgen,Beijing) with the ABI 7500 Real-Time PCR Thermal Cycler(Applied Biosystems,USA).The following cycle program:94°C for 30 s,followed by 40 cycles of 95°C for 5 s and 60°C for 34 s.Data for the melt curve were collected at 95°C for 15 s,60°C for 1 min,95°C for 30 s,and 60°C for 15 s.UBCwas set as the reference gene.Relative gene expression was calculated by the 2–ΔΔCTmethod.All reactions were performed in 3 technical and biological replicates.All the primers were designed by Vector NTI(Thermo Fisher Scientific,USA).Detailed information on primers showed in Appendix A.

3.Results

3.1.Sequencing and de novo assembly of transcriptome

To obtain a global view of the transcriptome changes of the rice plants in response to RSV infection,the expression profiles of RSV-infected rice samples(2W1,2W2,2W3,10W1,10W2,10W3,20W1,20W2,20W3,2Z1,2Z2,Z23,10Z1,10Z2,10Z3,20Z1,20Z2 and 20Z3) were compared to mock-inoculated control plants (2WC1,2WC2,2WC3,10WC1,10WC2,10WC3,20WC1,20WC2,20WC3,2ZC1,2ZC2,10ZC1,10ZC2,10ZC3,20ZC1,20ZC2 and 20ZC3) by high-throughput sequencing.RNA-Seq yielded 41 894 242 to 58 786 946 and 43 519 758 to 68 782 166 raw reads for the RSVinfected plant group and the control group,respectively.After the low-quality reads and adapter sequences were removed,the clean reads ranged from 39 578 458 to 57 615 764 for the RSV-infected group,and 40 498 626 to 67 380 462 for the control group,respectively (Appendix B).To show technical reproducibility between all the samples,we used hierarchical clustering analysis for gene expression and homogenized the rows of expression data.Samples with similar expression patterns are clustered together (Appendix C).The number of DEGs obtained is shown in Fig.2.

Fig.2 The number of differently expressed genes of WYJ3 (A) and ZD88 (B) at 2,10 and 20 days post-inoculation (dpi).

Fig.3 Top 20 KEGG pathways enriched of differently expressed genes (DEGs) for WYJ3.The size of each circle represents the number of DEGs and the rich factor was calculated using the number of enriched genes divided by the total number of background genes in the corresponding pathway.A,C,and E,down-regulated DEGs of WYJ3 at 2,10,and 20 days post-inoculation (dpi).B,D,and F,up-regulated DEGs of WYJ3 at 2,10,and 20 dpi.P-value was calculated using the Benjamini-Hochberg correction;P<0.05 is considered significantly enriched.

Fig.4 Top 20 KEGG pathways enriched of differently expressed genes (DEGs) for ZD88.The size of each circle represents the number of DEGs and the rich factor was calculated using the number of enriched genes divided by the total number of background genes in the corresponding pathway.A,C,and E,down-regulated DEGs of ZD88 at at 2,10,and 20 days post-inoculation (dpi).B,D,and F,up-regulated DEGs of ZD88 at 2,10,and 20 dpi.P-value was calculated using the Benjamini-Hochberg correction;P<0.05 is considered significantly enriched.

3.2.Metabolic pathway’s difference between resistant and susceptible varieties

Through KEGG analysis,the pathways that the DEGs of the resistant and susceptible varieties at 3 time points involved in are shown in Figs.3 and 4.As for the pathways that contribute to plant growth and development,including “photosynthesis”,“chlorophyll biosynthesis”,“carbon metabolism”,“amino acid biosynthesis” and“ribosome”,the DEGs of the 2 varieties were both downregulated.

For the “plant–pathogen interaction” pathway,which is related to plant disease resistance,the DEGs of these 2 varieties were both up-regulated at 3 time points.In our experiment,the DEGs related to PAMP-triggered immunity (PTI) and Effector-triggered immunity (ETI)of the 2 varieties at 3 time points were identified to be up-regulated.However,comparing these 2 varieties,at 2 dpi,the unique genes of the susceptible variety were all involved in PTI;but for the resistant variety,the unigenes were mainly related to ETI,and just one gene encoding WRKY22 was involved in PTI.At 10 dpi,for the susceptible variety,2 genes related to WRKY33 which was involved in PTI and 3 related to HSP90 which was involved in ETI were observed;but for the resistant variety,the unigenes were only involved in ETI.At 20 dpi,the unique genes of the susceptible variety were all involved in PTI;while for the resistant variety,the unigenes were mainly related to ETI,and just one gene encoding MEKK1 was involved in PTI.As time went by,the up-regulated genes involved in this pathway were always significantly enriched for the resistant variety,but for the susceptible variety,the number of DEGs involved in this pathway gradually decreased at 3 time points,suggesting that RSV invasion may have an effect on this pathway (Fig.5-A).

Fig.5 Heatmap of differential expression of genes involved in plant hormone signal transduction (A),plant–pathogen interaction(B) of two varieties (W,WYJ3;Z,ZD88) at 2,10,and 20 days post-inoculation.Each gene involved in biotic stress pathway is depicted by color signal where red signifies the genes expressed highly and green indicates the genes down-regulated after rice stripe virus (RSV) infection.The intensity of the color is representing the level of expression.PTI,PAMP-triggered immunity;ETI,Effector protein-triggered immunity;JA,jasmonic acid;ET,ethylene;SA,salicylic acid;BR,brassinosteroids;ABA,abscisic acid.

Another pathway that is related to disease resistance is “plant hormone signal transduction”.Plant hormones play an important role in plant growth and development,including auxin (Aux),cytokinins (CK),gibberellins (GA),brassinosteroids (BR),ET,abscisic acid (ABA),SA and JA,among them,JA,ET,BR,SA and ABA signaling pathway are related to disease resistance (Yanget al.2013).Comparing these 2 varieties,no DEGs involved in the ABA signaling pathway were identified in the susceptible variety at 20 dpi,but down-regulated genes involved in this pathway were found at 2 and 10 dpi;the DEGs involved in this pathway were identified at 3 time points for the resistant variety and showed downregulation.The up-regulated genes involved in the BR signaling pathway were only identified in the resistant variety at 10 dpi,while the DEGs involved in this pathway were identified in the susceptible variety at 3 time points and were up-regulated.The SA-mediated resistance is antagonistic to JA/ET,the resistance response may be mediated by SA in the resistant variety,while the resistance response may be mainly mediated by JA/ET in the susceptible variety (Fig.5-B).

3.3.Function annotation’s difference between resistant and susceptible varieties

Through GO annotation,we described the molecular function,the cellular component and the biological process of the DEGs of the resistant and susceptible varieties at 3 time points (Appendices D and E).Comparing the 2 varieties,the DEGs annotated “ubiquitinprotein transferase activity” and “transcription factor activity” are both significantly up-regulated.We identified DEGs related to “transcription factor”,“kinase” and“peroxidase”,the changes of expression in different stages for resistant and susceptible varieties are shown in Fig.6.Transcription factors of rice are classified into 56 families (http://planttfdb.gao-lab.org/).In this study,the DEGs belonging to 17 TF families (AP2,HSF,WRKY,bZIP,HTH,EIN3,GATA,SRF,Med11,Med7,E2F,Med14,Med12,SCAI,ZF-TAC,HD-ZIP,and Med22) were identified (Appendix F).The number of DEGs related to AP2 TF and WRKY TF was the largest,and these 2 TFs are also the most studied TFs related to disease resistance (Zhaoet al.2012;Hwanget al.2016).At 2 dpi,the DEGs related to WRKY TF were up-regulated in the resistant variety,while the up-regulated genes of the susceptible variety were mainly related to AP2 TF.At 10 and 20 dpi,the DEGs belonging to AP2 TF were upregulated in resistant and susceptible varieties;the DEGs related to WRKY TF were significantly down-regulated in the susceptible variety,and up-regulated in the resistant variety.

Fig.6 Heatmap of differential expression of genes related to transcription factor (A),kinase (B) and peroxidase (C) of two varieties(W,WYJ3;Z,ZD88) at 2,10 and 20 days post-inoculation.Each gene involved in biotic stress pathway is depicted by color signal where red signifies the genes expressed highly and green indicates the genes down-regulated after rice stripe virus (RSV) infection.The intensity of the color is representing the level of expression.

For the kinase of susceptible variety,4 DEGs encoding histidine kinase,phosphotransferase,phosphate kinase and SRK5 protein were identified to be 4 upregulated.At 10 dpi,one gene related to pyruvate kinase was down-regulated,whereas,4 up-regulated DEGs encoding histidine kinase,phosphotransferase,phosphate kinase and protein kinase were found.Moreover,at 20 dpi,3 DEGs including 2 protein kinases and one phosphofructokinase were retrieved to be downregulated,while among 3 up-regulated DEGs,2 genes related to phosphotransferase and one phosphate kinase.And for the resistant variety,at 2 dpi,4 genes were identified to be up-regulated,including one SRK5 protein,one protein kinase,one pyruvate kinase and one phosphofructokinase.At 10 dpi,2 down-regulated DEGs encoding phosphofructokinase and pyruvate kinase were found;however,4 kinase-related genes(2 phosphotransferase,one phosphate kinase and one protein kinase) were down-regulated.While,at 20 dpi,2 genes (one down-regulated and one up-regulated)encoding phosphofructokinase and phosphotransferase were identified to be differently expressed,respectively(Appendix G).More kinase-related DEGs were found in the susceptible variety,and the down-regulation trend was more significant.

In our study,for the susceptible variety,23 significantly differently expressed responsive peroxidase genes were identified at 2 dpi,including 15 down-regulated and 8 up-regulated.At 10 dpi,14 down-regulated and 6 upregulated DEGs were identified after RSV infection.Nevertheless,at 20 dpi,6 DEGs were identified to be down-regulated and 12 DEGs were up-regulated.As for the resistant variety,at 2 dpi,only 2 down-regulated and 13 up-regulated genes were observed in RSV-infectedvs.mock.At 10 dpi,16 DEGs were down-regulated and 7 were up-regulated.Moreover,at 20 dpi,only one gene was down-regulated and 3 genes were up-regulated in RSV-inoculated leaves (Appendix H).Most of the PODrelated DEGs in these 2 varieties were down-regulated,but the DEGs of the susceptible variety were significantly up-regulated at the later stage,while the DEGs in the resistant variety were more significantly up-regulated at the early stage.

3.4.Validation of transcriptomics data by RT-qPCR

Five genes that were differentially expressed in 2 varieties at 3 time points were assessed for their expression quantity to validate the transcriptome data,besides,UBCwas selected to be the reference gene (Fig.7).Os01g0905200encodes “Exocyst subunit Exo70 family protein”,Os08g0452500encodes “Auxin-induced proteinrelated-like protein”,Os01g0622600encodes “Calciumdependent protein kinase 1”,Os08g0386200encodes“Putative transcription factor WRKY5” andOs09g0486500encodes “Zinc finger A20 and AN1 domain-containing stress-associated protein 1”.The variation trend of these selected genes was consistent with the transcriptomics data.It suggests that RNA-Seq is an accurate and reliable method to study the rice transcriptome changes after RSV infection.

Fig.7 Validation of transcriptome results by RT-qPCR.Five genes that differentially expressed in 2 varieties (W,WYJ3;Z,ZD88)at 3 time points (2,10,and 20 days post-inoculation) were selected from the RNA-Seq data for RT-qPCR.The error bars represent standard deviations of the means (n=3).Asterisks mean significant difference: ＊,P<0.05;＊＊,P<0.01;＊＊＊,P<0.001.

4.Discussion

In nature,plants are attacked by different pathogens,as a result,various metabolic processes are interfered with to varying degrees.Accordingly,plants have evolved kinds of physiological,cellular and molecular mechanisms to cope with these pathogens (Joneset al.2006).

4.1.Transcription factors (TFs)

Plant immune receptors activate several genes in response to biotic stresses and coordinate their stress response with growth to maximize their fitness.Transcription factors interact withcis-regulatory elements in the promoter regions of stress-related genes and upregulate the expression of many genes to activate biotic stress tolerance (Agrawalet al.2000).The AP2/ERF TFs are plant-specific and play a crucial role throughout the plant life cycle,such as involving in nutrition signaling pathways and response to various biotic and abiotic stresses (Zhanget al.2020).Under different biotic stress conditions,AP2/ERF TFs can activate the defense-related genes,namelyPR(pathogenesis-related proteins),osmolyte,β-1,3-glucanase and chitinase response genes inArabidopsis(Zareiet al.2011;Moffatet al.2012).WRKY TFs play a very important role in regulating the expression of plant defense-related genes.Arabidopsis thalianageneRRS1,which is resistant toRalstonia solanacearum,has a typical R protein structural domain of TIR-NBS-LRR at the N-terminal and a typical WRKY52 protein at the C-terminal;the R protein recognizes the avirulence (Avr) protein signal and subsequently activates the expression of defense-related genes through the functional domain of WRKY TFs (Deslandeet al.2003).In addition,the expression product of the resistance geneTIZZ,induced by TMV,also has a WRKY structural domain and a C2H2 zinc finger structural domain (Yodaet al.2002).A previous study found that a group I WRKY transcription factor,NbWRKY1,can regulate mulberry mosaic dwarf-associated virus (MMDaV)-triggered cell death inNicotianabenthamianato improve plant defense (Sunet al.2022).In the present study,AP2/ERF TF-related genes were differentially expressed in both varieties,and most of them were up-regulated.In terms of expression quantity,for ZD88,AP2/E2F TFrelated DEGs were mostly down-regulated at the early stage,and up-regulated at the middle and late stages;while for WYJ3,the DEGs were mostly significantly upregulated expressed at the 3 stages,indicating that AP2/ERF TFs may have regulated PR response genes after RSV infection in both varieties.Unlike AP2/ERF TFs,WRKY TFs were significantly up-regulated in ZD88 than in WYJ3,suggesting that WRKY TFs have more influence on the expression of disease-resistance-related genes in resistant variety.

4.2.Peroxidase

Peroxidase is one of the key enzymes in the plant defense system under adverse conditions,scavenging excess free radicals and maintaining them at a normal level inside the plants,thus interacting synergistically with superoxide dismutase (SOD) and catalase to improve the stress tolerance of plants.It has been shown that several species of plants infected with citrus exocortis viroid(CEV) induce the accumulation or expression of several peroxidases at the transcriptional level (Gadeaet al.1996).Peroxidase mediates ROS production in the plant(Khokonet al.2010),and previous research reported that down-regulation of the light-harvesting chlorophylla/bcomplex protein 3 (LHCB3) of photosystem II is involved in defense against turnip mosaic virus (TuMV) by inducing ROS production inN.benthamiana(Qiuet al.2021).Peroxidase is required for lignin biosynthesis(Liuet al.2018),and increasing peroxidase activity can promote lignification of the infected tissues and play a role in limiting the movement of the virus in the plant.In our study,peroxidase-related DEGs were mostly downregulated,and in WYJ3,the DEGs showed significantly up-regulated expression in the late stage,indicating that peroxidase-related genes may regulate the lignin biosynthesis process and promote lignification in susceptible variety,thus playing a defensive role.

4.3.Plant–pathogen interaction

The plant’s innate immune system consists of 2 main immune responses,namely,PTI and ETI.In our experiment,analysis of transcriptome data revealed that both varieties triggered PTI after RSV invasion,in which kinase and related signal-mediated genes acted as pattern recognition receptors to activate the plant defense system (Abramovitchet al.2006).In terms of expression quantity,the kinase-related DEGs identified in ZD88 showed significant up-or down-regulation,indicating that resistant variety activates the defense system more actively.Moreover,several DEGs involved in ETI were identified in ZD88 at all 3 time points,and relatively few in WYJ3,suggesting that the susceptible variety lacks ETI and shows susceptibility.

4.4.Plant hormone signal transduction

Plant hormones play a critical role in almost every aspect of plant biological processes,including growth,development and pathogen defense.Disruption of normal development physiology is usually associated with changes in phytohormone accumulation and signaling during viral infection.As mentioned previously,our study analyzed DEGs related to SA,JA,ET,BR and ABA signalings.SA and JA/ET signaling pathways respond to adversity in an antagonistic manner (Koornneefet al.2008).SA pathway mainly targets biotrophic pathogens,while responses induced by necrotrophic pathogens are synergistically regulated by the JA and ET pathways.SA is required for systemic acquired resistance (SAR)(Gaffneyet al.1993).Dingetal.(2018) reported that SA may play an important role in the amplification of PTI and ETI responses through the induction of the expression of related genes.BR is involved in the regulation of innate immunity based on BAK1-dependent and BAK1-independent defense responses.On the other hand,ABA is usually associated with tolerance of abiotic stress and is a negative regulator of biotic stress responses.In our study,DEGs of the resistant variety were mainly involved in SA-mediated resistance response,while DEGs of the susceptible variety were mainly involved in JA/ET synergistic resistance;DEGs associated with BRmediated signaling pathways showed up-regulation in both varieties,and DEGs associated with ABA signaling pathways showed down-regulation in both varieties,indicating that there are similarities and differences in effects of hormones on the resistance response of both varieties.

5.Conclusion

In this study,RNA-Seq was used to analyze the transcriptomic differences between the resistant and susceptible rice varieties at different times after RSV infection.Through GO annotation,the DEGs related to transcription factors,peroxidases,and kinases of 2 varieties at 3 time points were identified.Comparing these 2 varieties,the DEGs associated with these 3 proteins were numerically less in the resistant variety than in the susceptible variety,but the expression showed a significant up-or down-regulation trend by significance analysis.Then through KEGG annotation,DEGs involved in some pathways that have a contribution to disease resistance including plant hormone signal transduction and plant–pathogen interaction were found.The results showed that resistance responses regulated by ABA and BR were the same for the 2 varieties,but that mediated by SA and JA/ET were different.The DEGs in resistant and susceptible varieties at the 3 time points were identified in both PTI and ETI,but most of the unigenes of the susceptible variety were involved in PTI,whereas most of the unigenes of the resistant variety were involved in ETI.These results revealed the different responses of resistant and susceptible varieties in the transcription level to RSV infection.Our study provides valuable and novel information to obtain putative resistance-related genes by bioinformatics analysis.

Acknowledgements

This research was supported by the National Key Research and Development Plan of China(2019YFE0108500).We thank Dr.Hazen B E (Willows End Scientific Editing and Writing,USA) for critically reading and revising the manuscript.

Declaration of competing interest

The authors declare that they have no conflict of interest.

Appendicesassociated with this paper are available on https://doi.org/10.1016/j.jia.2022.10.010