Transcriptome profiling of JG30 genotype for DEGs
RNA isolated from the JG30 leaves inoculated with PXO99A and PH by needless syringe, were subjected to RNA-Seq (Fig. 1a); additionally, healthy leaves of JG30 plants were infected by PXO99A and PH strains via scissors dipped inoculation method for confirmation of the reaction pattern; JG30 is highly susceptible to PXO99A but not to PH (Fig. 1b). Summary of the RNA-Seq analysis and depicted results are given in the Additional file 1: Table S1. Raw reads were ranged from 43,590,580 to 57,064,782. After the low-quality reads and adapter sequences were trimmed, the clean readswere ranged from 42,414,410 to 54,514,722. The clean reads were mapped to the available reference genome of rice using HISAT2 (2.1.0). Approximately, 79 to 84.42% reads were successfully mapped to the rice reference genome of Nipponbare. Given the high genome coverage of the Illumina sequencing reads, we depicted that the RNA-Seq data are useful for further deep bioinformatics analysis.
To determine the expression pattern of the JG30 genotype after PXO99A and PH inoculations, a pairwise comparison between PXO99A vs PH strains was made at a specific time point. A threshold level of p-value was set to 0.05 and revealed 1143 significant DEGs between PXO99A vs PH at different time points (Additional file 1: Table S2). An overview of the comparative analysis between PXO99A vs PH revealed that there were more up-regulated genes than downregulated genes (Fig. 1c, d). Briefly, there were 263 (192 upregulated and 71 downregulated), 541 (335 upregulated and 206 downregulated), 265 (97 upregulated and 168 downregulated), and 174 (89 upregulated and 85 downregulated) DEGs were identified at 12, 24, 36 and 48 hpi in PXO99A vs PH.
Identification of the differentially expressed TFs
TFs are the key players, reported as differentially expressed in plants as a response to bacterial, fungal and viral infection (Amorim et al. 2017). In our experiment, 43 differentially expressed TFs, belonging to different TF families were retrieved (Fig. 2 and Additional file 1: Table S3). Among 10 differentially expressed TFs at 12 hpi, three TFs which belongs to the AP2-ERF (LOC_Os03g08490.1), Dof (LOC_Os06g17410.1) and mitochondrial-related TF (LOC_Os03g24590.1) were found to be upregulated in PXO99A inoculated leaves of JG30 genotype than that of PH. At 24 hpi, six AP2-ERF, two bZIP, one bHLH, two NAC, two MYB, four WRKY, and two zinc finger domain related TFs were upregulated in PXO99A vs PH. At 36 hpi, only two TFs belonging to the C2H2 (LOC_Os07g40300.1) and heat shock (LOC_Os10g07210.1) related TFs were upregulated; however, five TFs of different families were downregulated in PXO99A inoculated leaves. Furthermore, four out of five differentially expressed TFs including one AP2-ERF (LOC_Os04g52090.1), two NAC (LOC_Os11g05614.1 and LOC_Os07g37920.1) and one C2H2 (LOC_Os03g55540.1) belonged to the downregulated genes in PXO99A vs PH; whereas, only one TF of AP2-ERF (LOC_Os01g04800.1) was identified to be upregulated at 48 hpi. Shortly, among 43 TFs, 27 genes were upregulated and 16 genes were downregulated in PXO99A inoculated leaves relative to the PH. Hence, upregulated genes may be involved in the susceptibility after PXO99A infection.
Identification of the kinase and peroxidase responsive genes in RNA-Seq data
Kinases form the largest gene family of the receptors in plants and have an important role in recognizing pathogen-associated molecular patterns and modulating the plant immunity in response to the invasive pathogen. We identified 28 significant differentially expressed kinase responsive genes at different time points (Fig. 3a and Additional file 1: Table S4). At 12 hpi, 10 DEGs (nine upregulated and one downregulated) were identified; among the nine upregulated DEGs, one adenylate kinase (LOC_Os11g20790.1), two MAPK (LOC_Os05g02500.1 and LOC_Os06g48590.1), one orthophosphate dikinase precursor (LOC_Os05g33570.1), two genes related to the protein kinase (LOC_Os01g48990.1 and LOC_Os04g52780.1), one casein kinase-like protein (LOC_Os01g54100.2), one CBL interacting protein kinase (LOC_Os09g25100.1), and one wall-associated kinase (LOC_Os10g10130.5) were retrieved to be upregulated in PXO99A inoculated leaf samples relative to PH. In 24 hpi, 10 DEGs (nine upregulated and one downregulated) were identified. Among nine upregulated genes, including one pyrophosphate related kinase (LOC_Os01g09570.1), four protein kinase related genes (LOC_Os02g42190.1, LOC_Os03g50220.1, LOC_Os03g50220.1, LOC_Os09g16950.1, and LOC_Os09g27010.1), one MAPK (LOC_Os03g17700.1), one KI domain interacting kinase (LOC_Os05g41370.1), and two serine/threonine kinase related genes (LOC_Os05g46760.1 and LOC_Os02g02120.1) were upregulated in PXO99A vs PH. Moreover, four genes were upregulated and two genes were downregulated (LOC_Os11g12530.1 and LOC_Os11g46900.1) at 36 hpi. At 48 hpi, four genes were identified to be upregulated, including three protein kinase related genes (LOC_Os03g27990.1, LOC_Os09g18360.1, and LOC_Os09g16950.1) and one serine/threonine kinase (LOC_Os01g10890.1); however, one gene from phosphoenolpyruvate kinase was downregulated in PXO99A relative to the PH. The upregulated genes might have played role in basal defense against PXO99A, but the defense was not strong enough to cope with the pathogen attack.
The peroxidase responsive genes are important in plants controlling different processes such as development, growth, response to biotic and abiotic stress, and programmed cell death (Bailey-Serres and Mittler 2006). In our RNA-Seq experiment, 50 significant differentially expressed peroxidase responsive genes were identified at different time points (Fig. 3b and Additional file 1: Table S5). Among the 50 genes, 29 genes were upregulated and 21 genes were downregulated. At 12 hpi, two DEGs (LOC_Os07g02440.1 and LOC_Os09g35940.1) were observed to be upregulated, and five DEGs (LOC_Os01g73200.1, LOC_Os02g41954.1, LOC_Os04g49210.1, LOC_Os04g55740.1, and LOC_Os05g38420.1) were downregulated in PXO99A inoculated JG30 leaves relative to PH. At 24 hpi, 19 DEGs were upregulated and 14 DEGs were downregulated in PXO99A vs PH. At 36 hpi, nine DEGs were upregulated and only two genes (LOC_Os06g15990.1 and LOC_Os08g36860.1) were downregulated. Nevertheless, at 48 hpi, six genes (LOC_Os05g40384.1, LOC_Os06g37224.1, LOC_Os07g01410.1, LOC_Os08g39660.1, LOC_Os09g10340.1, and LOC_Os10g36848.1) were upregulated and three genes (LOC_Os01g62490.1, LOC_Os03g16610.1, and LOC_Os08g39840.1) were downregulated in PXO99A inoculated leaves than that of PH. It is depicted that downregulated peroxidase responsive genes might have role in the resistance against PXO99A in rice.
Pathway enrichment analysis
We mapped the DEGs of JG30 genotype to the KEGG database to identify the significant pathways at different time points. The KEGG pathways were retrieved on the basis of p-value ≤0.05 (Additional file 1: Table S6). The “biosynthesis of phenylpropanoids” and “photosynthesis” were the prominent pathways at 12, 24 and 48 hpi. In photosynthesis pathway, the DEGs (LOC_Os07g37240.1, LOC_Os08g33820.1, and LOC_Os09g26810.1) were involved in the light harvesting chlorophyll (LHC) protein complex; Lhca4 and Lhcb4 were seemed to be downregulated in PXO99A infected leaf samples of JG30 than that of PH (Fig. 4).
To elucidate the role of identified DEGs in biotic stress response, the MapMan package was employed to investigate the genes involved in plant-pathogen interactions. The input command of the DEGs was given in MapMan package to design a particular biological process using the rice annotation project database (RAP-DB). The DEGs with known functions, e.g., TFs, secondary metabolites, ethylene, proteolysis, and signaling are shown in Fig. 5. The detailed data are given in Additional file 1: Table S7. Briefly, most of the DEGs related to the peroxidase, redox state, signaling, and MAPK responsive genes were upregulated after PXO99A infection relative to the PH strain. Eight out of ten ethylene responsive genes were identified as upregulated; moreover, all the five WRKY and one Dof responsive genes were upregulated in PXO99A infected leaf samples, which indicates that these upregulated WRKY genes might have a key role in PXO99A infection. The expression levels of 13 DEGs representing the secondary metabolites, three pathogenesis-related (PR) genes were influenced by PXO99A; these upregulated genes might have a role in the the susceptibility after PXO99A infection in JG30 plants.
The two DEGs encoding auxins and nine ethylene-related genes were upregulated; on the contrary, five DEGs of ethylene, three JA and one brassinosteroids responsive genes were downregulated after PXO99A infection. Afterward, 18 DEGs related to the cell wall were identified; among these 18 DEGs, 11 genes were upregulated and seven were downregulated in PXO99A infected leaves as compared to the PH. Likewise, among the 31 proteolysis DEGs, 22 were upregulated and 9 nine genes were downregulated.
As an additional analysis to get a clear understanding of the participation of metabolic pathway in PXO99A infection relative to the PH, MapMan package was used to classify the DEGs into metabolic pathways and processes (Fig. 6 and Additional file 1: Table S8). The genes having higher expression level are involved in the “light reaction” and “photorespiration” bins representing the photosynthesis category. Additionally, some genes encoding the “lipids”, “sucrose” and “starch” were upregulated in metabolic pathway. In secondary metabolism, most of the DEGs representing the “terpenes”, “phenylpropanoids and phenolics”, and “nucleotide metabolism” (ribonucleoside-diphosphate reductase) were upregulated in susceptibility conditions after PXO99A infection. The visual annotations of the DEGs provided a valuable resource for the exploration of the pathways involved in susceptibility after PXO99A infection.
Gene ontology enrichment analysis
The GO analysis functionally characterizes the DEGs into three different categories, i.e., biological process, cellular component, and molecular function. The GO analysis was done using the AgriGO online tool. The GO analysis of all the DEGs is shown in the Additional file 1: Table S9. The significant GO terms after infection of PXO99A and PH at each time point were retrieved using the false discovery rate (FDR) ≤ 0.05 (Additional file 1: Table S10). In PXO99A vs PH at 12 hpi, the GO terms were significantly enriched in biological process (10), cellular component (6) and molecular function (7). At 24 hpi, 56 significant enriched GO were identified, including 28 biological processes, five cellular function, and 23 molecular function related terms. In PXO99A vs PH at 36 hpi, the significant GO terms were classified into the biological process (5), cellular component (1) and molecular function (13). Unlike 36 hpi, only five enriched GO terms were identified, including biological process (4) and molecular function (1).
The significant biological process related GO term in all time points (12, 24, 36, 48 hpi) are mentioned as follows: “biological regulation (GO:0065007)”, “response to chemical stimulus (GO:0042221)”, “response to biotic stimulus (GO:0009607)”, “lipid localization (GO:0010876)”, “generation of precursor metabolites and energy (GO:0006091)”, “photosynthesis (GO:0015979)”, “carbohydrate metabolic process (GO:0005975)”, “response to oxidative stress (GO:0006979)”, “lipid transport (GO:0006869)”, “photosynthesis, light reaction (GO:0019684)”, “polysaccharide metabolic process (GO:0005976)”, “photosynthesis, light harvesting (GO:0009765)”, and “Polysaccharide catabolic process (GO:0000272)” (Fig. 7).
RNA-Seq data validation
Eight randomly selected DEGs were evaluated for their expression patterns at different time points to validate the RNA-Seq data (Fig. 8). The gene sequences were retrieved from phytozome v12.1. LOC_Os01g03730.1, encoding nuclease I gene was highly expressed at 12 hpi in PH inoculated leaves of JG30 than that of PXO99A. LOC_Os09g26810.1, representing the type II chlorophyll binding protein was upregulated at 12 hpi in PXO99A vs PH. Moreover, R2R3-MYB (LOC_Os02g41510.1) TF was exhibited to be overexpressed at 24 and 36 hpi in PXO999A vs PH. LOC_Os04g58920.1 encoding the zinc finger domain-containing protein was induced at 24, 36 and 48 hpi in PXO99A inoculated leaves relative to the PH. 2OG-Fe (II) oxygenase responsive gene (LOC_Os04g49210.1) was highly expressed at 24 and 36 hpi in PXO99A vs PH, respectively. LOC_Os02g02120.1 and LOC_Os05g04490.1 representing the Serine/threonine kinase and peroxidase responsive genes, respectively, were upregulated at 24 and 36 hpi in PXO99A vs PH. Pyruvate/Phosphoenolpyruvate kinase gene (LOC_Os12g08760.1) was overexpressed in PH infected samples as compared to the PXO99A. In short, the qRT-PCR results validated the expression pattern of selected DEGs mentioned in RNA-Seq data.