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Article

A Mycorrhiza-Associated Receptor-like Kinase Regulates Disease Resistance in Rice

by
Zichao Zheng
1,2,
Ke Zou
2,
Guodong Lu
1,
Zonghua Wang
1,3,
Haitao Cui
4,* and
Airong Wang
1,*
1
State Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, Fujian Agriculture and Forestry University, Fuzhou 350002, China
2
Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops, Plant Immunity Center, Fujian Agriculture and Forestry University, Fuzhou 350002, China
3
Ministerial and Provincial Joint Innovation Centre for Safety Production of Cross-Strait Crops, Minjiang University, Fuzhou 350108, China
4
College of Plant Protection, Shandong Agricultural University, Tai’an 271018, China
*
Authors to whom correspondence should be addressed.
Agronomy 2025, 15(10), 2298; https://doi.org/10.3390/agronomy15102298
Submission received: 15 August 2025 / Revised: 20 September 2025 / Accepted: 26 September 2025 / Published: 28 September 2025
(This article belongs to the Special Issue Interaction Mechanisms Between Crops and Pathogens)
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Abstract

Most terrestrial plants establish symbiotic relationships with microorganisms to acquire nutrients and simultaneously restrict pathogen infection. In rice, the receptor-like kinase OsARK1 is essential for the colonization and development of arbuscular mycorrhizal (AM) fungi. However, whether OsARK1 participates in plant–pathogen interactions remain unknown. Here, we demonstrate that OsARK1 is involved in the transcriptional reprogramming of immune defense-related genes prior to and following AM colonization. Mutation of OsARK1 resulted in increased susceptibility to Magnaporthe oryzae (blast fungus) and Xanthomonas oryzae (bacterial blight). Transcriptomic profiling during blast infection demonstrated OsARK1 coordinates early immune responses; particularly, the upregulation of genes encoding lectin receptor-like kinases (LecRLKs), nucleotide-binding leucine-rich repeat (NLR) immune receptors and secondary metabolism-related genes was significantly impaired in Osark1 mutant. Collectively, OsARK1 acts as a positive regulator of rice immunity against pathogens while fine-tuning defense suppression during beneficial AM symbiosis.

1. Introduction

Plants and microorganisms interact in ways that influence plant growth, development, and resilience to stresses [1]. AM fungi establish symbiotic associations with more than 80% of plant species, thereby enhancing the nutrient acquisition capacity of host plants and increasing their resistance to various abiotic stresses, including salinity, drought, heavy metal toxicity, and extreme temperatures [2,3]. Pathogens can adversely affect plant growth and development, and in severe cases, may even cause a significant reduction in crop yields. To perceive the presence of microorganisms, plants have evolved a series of sophisticated recognition mechanisms [4,5,6]. Plants recognize microbe/pathogen-associated molecular patterns (MAMPs/PAMPs) or symbiotic signaling molecules, such as chitin, flagellin, lipopolysaccharide, peptidoglycan, lipochitooligosaccharides, Myc factor and Nod factor, via cell surface Pattern Recognition Receptors (PRRs) [5,7,8,9]. Different lysin motif (LysM) receptors on the cell surface specifically recognize and bind to symbiotic signals or MAMPs, initiating symbiosis or MAMP-triggered immunity (MTI), respectively [5].
MAMPs are conserved molecular patterns found in many microorganisms, including pathogens and beneficial species like AM fungi, such as chitin and beta-glucans, the prominent components of fungal cell walls [10]. Symbiotic signaling molecules, like Nod and Myc factors, resemble carbohydrate-based pattern recognition molecules such as chitin in structure [11,12]. One layer of plant defense against pathogenic microorganisms involves the recognition of conserved microbial features, referred to as MAMPs, which subsequently activate MTI. Well-defined MAMPs include flg22, a flagellin-derived peptide that is a major component of bacterial flagella, which is recognized by the leucine-rich repeat receptor-like kinase AtFLS2 in Arabidopsis thaliana [13,14]. Additionally, chitin derived from fungal cell walls are perceived by the LysM receptor-like protein (LysM-RLP) LYM2 as well as the LysM-RLKs AtLYK4, AtLYK5, and AtCERK1 (Chitin Elicitor Receptor Kinase 1) in A. thaliana [15,16,17,18,19].
The PRRs form a symbiotic association with AM fungi by recognizing short-chain chitosan oligosaccharides (COs) and non-sulfated lipid-chitin oligosaccharides (LCOs) secreted by AM fungi [20,21,22,23,24,25,26]. OsCERK1, as a typical LysM-RLK, is simultaneously involved in the symbiotic signal recognition of AM fungi and the immune response to Magnaporthe oryzae [27,28,29]. The symbiotic receptor OsMYR1 (Myc Factor Receptor 1) and its CO4 ligand significantly reduce the sensitivity of rice to MAMPs by inhibiting the formation of the complex between OsCERK1 and OsCEBiP, further blocking the phosphorylation of OsCERK1 on its downstream substrates [22,28,29,30,31]. LCOs are acylated COs of 4–5 GlcNAc residues [21], which are recognized by two LysM-RLKs phylogenetic groups called LYRIA and LYRIIIA to regulate immunity and symbiosis [24,32,33,34,35]. Two LysM RLKs, MtNFP (Nod Factor Perception) and MtLYK3 (Lysin Motif Receptor-Like Kinase 3), are essential for recognizing nodulation (Nod) factors in Medicago trncatula [11,36,37,38,39,40,41]. The cytoplasmic kinase MtLICK1/2 (LYK3-Interacting Cytoplasmic Kinase 1/2) and MtLYK3 engage in reciprocal activation to promote symbiotic signaling, and MtLICK1/2 specifically suppresses plant immunity in the rhizobia infection zone [42]. In addition to these NFRs, SymRK (Symbiosis Receptor like Kinase) is essential for Nod factor signaling and may form a receptor complex with LjNFR5 in Lotus japonicus [43,44]. LjSymRK associates with BAK1 (Brassinosteroid Insensitive 1-Associated receptor Kinase 1), a well-characterized positive regulator of plant immunity, and directly inhibits LjBAK1 kinase activity to suppress the host’s ability to mount a defense response during symbiosis [45].
The rice Arbuscular Receptor-like Kinase 1 (OsARK1) belongs to the Unknown Receptor Kinase-2 (URK-2) subfamily, a group of land plant-specific RLKs that remains largely uncharacterized [46]. Fungal fitness relies on OsARK1, a gene critical for maintaining fungal vigor and sustaining symbiotic balance after arbuscule formation and found only in the genomes of plants capable of forming AM fungi, indicating its evolutionarily conserved role in plant symbiosis [47,48,49,50,51,52]. Although OsARK1 plays a crucial role in maintaining the AM fungal-plant symbiosis, it remains uncertain whether OsARK1 is involved in plant defense against invasive pathogens.
To evaluate this hypothesis, we combined phenotypic assays of pathogen resistance with transcriptome analysis in wild-type and Osark1 mutant rice during AM colonization and pathogen infection, thereby enabling genome-wide identification of OsARK1-regulated defense responses. Our analysis revealed that Osark1 mutants display substantial dysregulation of defense-related genes, both constitutively and during AM symbiosis. Phenotypic assessments further indicated that OsARK1 positively modulates resistance against the fungal pathogen M. oryzae and the bacterial pathogen Xanthomonas oryzae pv. oryzae (Xoo). Collectively, these findings support the hypothesis that OsARK1 acts as a dual-function regulator orchestrating plant responses to both pathogenic and mutualistic microorganisms, highlighting its central role in immune homeostasis and symbiotic compatibility.

2. Materials and Methods

2.1. Plant Materials and Growth Conditions

The Osark1 knockout mutants listed in Table 1 in the japonica rice cultivar Zhonghua11 (ZH11) background were generated via clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated nuclease 9 (Cas9)-mediated genome editing through the service of Borun Biosciences Co., Ltd., Wuhan, China. The guide RNA sequence is: 5′-GGCCTGCGCTACCGGAGCCA-3′. Among the transgenic T1 plants, the target DNA fragments were amplified and validated by Sanger sequencing, allowing the identification of two homozygous knockout lines with distinct edits: Osark1 #1 carrying a T insertion at position 341, and Osark1 #2 carrying a C deletion at position 342. For planting rice, the seeds were surface sterilized with 3% (v/v) sodium hypochlorite for 40 min, then sown on 1/2 MS agar plates. Seedlings were grown in a growth chamber under a 16 h:8 h, day:night photoperiod at 28 °C:24 °C and 65% humidity, as previously described [52].

2.2. Rice Blast and Bacterial Blight Infection Assay

For blast infection assay, the M. oryzae B.C.Couch (Taxonomy ID 242507) isolate Guy11, precultured on complete medium (CM), was subsequently grown on rice bran medium for 7 days at 25 °C in darkness. After removing aerial mycelium, plates were transferred to a light-controlled incubator (200–400 μmol/m2/s, 12 h light/12 h dark cycle, 25 °C) to induce sporulation. A spore suspension was prepared by harvesting and resuspending spores in sterile water containing 0.02% (v/v) Tween-20 (Solarbio Co., Ltd., Beijing, China) to a concentration of approximately 5 × 105 spores per milliliter. This suspension was used for both spray and punch inoculation methods. For punch inoculation, 5 μL of the spore suspension was applied directly to each wound site. Leaves were spray- or punch-inoculated as described previously [53,54]. At 5 days post-inoculation (dpi), fungal growth was quantified by measuring the abundance of M. oryzae MoPot2 transposon DNA, normalized to the rice OsActin gene (LOC_Os03g50885), using quantitative PCR (qPCR) [55]. For each genotype, 12 leaves collected from 12 individual plants were sampled. Pathogenicity assessments were based on three replicates, each consisting of four leaves each, and fungal biomass was calculated from three biological replicates. The entire assay was repeated three times. The following primer sets were used: for MoPot2, 5′-ACGACCCGTCTTTACTTATTTGG-3′ and 5′-AAGTAGCGTTGGTTTTGTTGGAT-3′; and for OsActin, 5′-CAACACCCCTGCTATGTACG-3′ and 5′-CATCACCAGAGTCCAACACAA-3′.
For bacterial blight assays, field-grown rice plants at booting stage were inoculated with Xoo strain PXO86 using the leaf-clipping method [56]. Lesion length was measured at 14 days post-inoculation on 25 leaves per genotype, each collected from a separate plant. Average lesion length was determined, and the experiment was repeated three times.

2.3. AM Fungus Inoculation

AM fungus used in this study was Rhizophagus ir regularis (Błaszk., Wubet, Renker & Buscot) C. Walker & A. Schüssler (Taxonomy ID 588596). Spores of R. irregularis were obtained by co-cultivating the fungus with Zea mays L. for three months in a substrate consisting of sterile sand and R. irregularis inoculum (1:1, v/v), with weekly supplementation of Hoagland’s nutrient solution. After harvest, spores were carefully rinsed, air-dried, and stored under dry conditions at 4 °C until use.
For AM colonization, after 7 days of germination on 0.8% (w/v) agar plates, rice seedlings were transplanted into pots (four per pot) including a mixture of sterilized sand and inoculum (1:1, v/v) with approximately 300 spores per plant of R. irregularis. A total of 25 mL of Hogland solution containing 100 μM NH4H2PO4 was applied to the plants twice weekly until harvested. Eight pots were used for each treatment group, including AM-colonized and non-colonized ZH11 and Osark1. Under both AM-inoculated and non-inoculated (mock) conditions, infection phenotypes were assessed, and samples for RNA-seq analysis were harvested 6 weeks post-inoculation.
We quantified AM colonization in rice roots using trypan blue staining followed by microscopic examination according to established protocols [57]. Stained root tissues were examined via microscopic examination and categorized into five distinct groups based on colonization patterns: no colonization, hyphae only (H), hyphae with arbuscules (A + H), hyphae with vesicles (V + H), and hyphae with both arbuscules and vesicles (A + V + H). The proportion of each category was subsequently quantified.

2.4. 3,3′-Diaminobenzidine (DAB) Staining

DAB (Sigma-AldrichTrading Co., Ltd., Shanghai, China, D8001) staining was used to detect hydrogen peroxide, following a previously established protocol [58]. Rice leaves inoculated with M. oryzae at 48 h post-inoculation (hpi) were stained with a 1% (w/v) DAB solution in Tris–HCl buffer (pH 6.5). After vacuum infiltration for 30 min, the leaves were incubated in the dark for 12h. Subsequently, they were immersed in absolute ethanol and boiled in a 95 °C water bath for 2 h, with the ethanol replaced frequently to ensure effective destaining. The leaves were observed under a light microscope (Zeiss Axio Imager 2). For each genotype (ZH11 and Osark1), a total of 24 inoculated leaves were prepared, from which 5 leaves were randomly selected for quantitative analysis. From these leaves, 21 microscopic fields were examined, and the DAB-stained areas were quantified using ImageJ software (version 1.54 g). The results are presented as the mean ± SD of the measured areas from one representative experimental replicate (of three independent experiments).

2.5. Callose Deposition Assay

For the observation and quantification of chitin-induced callose deposition, leaves from 14-day-old seedlings were excised and incubated for 30 min in 0.8 μM chitin solution (Cayman Chemical Co., Inc., Ann Arbor, MI, USA, 17864). The assay was performed as previously described [59]. A UV-fluorescence microscope (excitation 405 nm, emission 498 nm; Zeiss LSM880) was used to capture images of callose deposits. The number of deposits per field was then quantified using ImageJ software (version 1.54 g) and the average deposit quantity across 15 fields of view was measured for visualization. The experiments were independently repeated three times with consistent results.

2.6. RNA Extraction and RT-qPCR Analysis

Total RNA from leaves was extracted with TRIGene reagent (GenStar Co., Ltd., Beijing, China, P118-05) according to the manufacturer’s instructions. First-strand cDNA was synthesized from 1 μg RNA with the All-in-One First-Strand cDNA Synthesis SuperMix for qPCR (TransGen Biotech, AE341-02). Quantitative Polymerase Chain Reaction (qPCR) was performed with Perfect Start Green qPCR SuperMix (TransGen Biotech Co., Ltd., Beijing, China, AQ601) on a Bio-Rad CFX96 real-time PCR detection system(Bio-Rad Laboratories Co., Inc., Heracles, CA, USA). The rice ubiquitin gene served as the internal reference. qPCR analyses were conducted using the following gene-specific primer sets: OsPR3, 5′-GTCACCGAGGCGTTCTTCA-3′ and 5′-GCTTGGAGTCGTCGTTGGT-3′; for OsPR10, 5′-CGCCGCAAGTCATGTCCTA and GCTTCGTCTCCGTCGAGTGT-3′; for OsWRKY62 5′-ATCACACTCGACCTGACGAA-3′ and 5′-CAGGAATGTGTGGGATTTGA-3′. Three biological replicates were used for quantification, and the relative expression levels were calculated using the comparative ΔCT method with OsActin gene as the internal control. Mean values ± SD from the biological replicates were presented.

2.7. RNA-Seq Analysis

Rice leaves were inoculated with a suspension of M. spores (~5 × 105 spores/mL) containing 0.02% (v/v) Tween-20, while control leaves were treated with an aqueous solution of 0.02% (v/v) Tween-20 alone (mock). Leaf samples were collected at 24 and 48 h post-inoculation for RNA-seq analysis. Total RNA quality was assessed using Qsep4000 system (BiOptic Inc., Taiwan), and only samples with an RNA Quality Number (RQN) ≥ 7.0 were used for library preparation. Library construction and RNA sequencing were carried out by BGI Genomics Co., Ltd. (Shenzhen, China) using DNBSEQ-T7 platform, generating 150 bp paired-end reads and yielding approximately 6 GB of data per sample. Raw reads have been deposited in the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database under accession number GSE157400. Clean reads were aligned to the Oryza sativa L. cv. Nipponbare reference genome (IRGSP-1.0, EnsemblPlants Assembly GCA_001433935.1, downloaded on April 2020) using HISAT2 (version 2.1.0) [60], and gene-level read counts were obtained using HTSeq (version 2.0.5) [61]. For principal component analysis (PCA), raw read counts were transformed using the regularized log (rlog) function implemented in DESeq2 to stabilize variance across the dynamic range of expression values, and the resulting rlog-transformed counts were used for sample clustering. The PCA plot was constructed based on three replicates per sample, demonstrating the variance among the analyzed samples. Differential expression analysis was carried out with the DESeq2 package in R (version 4.3.0) [62]. Genes with a false discovery rate FDR < 0.05 and |log2FC| > 1 were considered differentially expressed (DEGs). Gene Ontology (GO) enrichment was performed using gprofiler2 (https://biit.cs.ut.ee/gprofiler/page/r, accessed on 5 December 2022) in R package. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment was assessed with a hypergeometric test; Go terms or KEGG pathway terms with Q-value (Bonferroni-adjusted p-value) ≤ 0.05 were deemed significant.

2.8. Statistical Analysis

Data on plant fungal biomass, lession length, H2O2 accumulation, callose deposition, and gene expression were analyzed using IBM SPSS Statistics for Windows (version 27.0). RNA-seq data were analyzed using R version 4.3.0. One-way analysis of variance (ANOVA) was performed, followed by post hoc comparisons using Tukey’s HSD test. Differences were considered statistically significant at p < 0.05.

3. Results

3.1. OsARK1 Regulates Expression of Defense-Related Genes During AM Symbiosis in Roots

Beneficial symbiotic microorganisms must overcome host’s defenses to successfully colonize roots. OsARK1 contributes to AM colonization and promote vesicle formation [47,49]. To investigate the OsARK1-regulated signaling pathways during the colonization process of AM fungi in rice roots, we performed transcriptomic comparation analysis using RNA-seq on AM-colonized and noncolonized ZH11 and Osark1 knock-out mutant. Consistent with earlier reports, AM colonization was significantly lower in the Osark1 mutant than in ZH11 (Figure S1A). To assess the variability and clustering patterns across all samples, PCA was performed using rlog-transformed read counts obtained from DESeq2. The PCA plot shows that the three biological replicates for each sample were tightly clustered and distinctly segregated according to treatments (noncolonized conditions: CK, colonized conditions: AM) and genotypes (ZH11 and Osark1) (Figure 1A). Especially the AM treatment clustered away from CK treatment for both Osark1 and ZH11, indicating that AM induced substantial transcriptome changes in Osark1 and ZH11. Indeed, the comparison between AM and CK treatment in ZH11 and Osark1 identified 6659 and 5111 DEGs (|log2 FC| > 1, FDR < 0.05) respectively (Figure S1B). Among the 6659 DEGs in ZH11, 2411 were upregulated and 4248 were downregulated, and among the 5111 DEGs in Osark1, 1980 were upregulated and 3131 were downregulated. Notably, Osark1 clustered close to ZH11 in both CK and AM treatments (Figure S1B), and around 80% DEGs (4044 from 5111) in Osark1 were also differentially expressed in ZH11 (Figure S1C). Notably, a heatmap of these DEGs show that in Osark1, AM colonization induced foldchange is generally less than which in ZH11 (Figure S1D). Coupled with the reduced number of DEGs in Osark1 relative to ZH11, these results suggest that the loss of OsARK1 moderately attenuated AM-induced global transcriptional reprogramming.
The comparison between Osark1 and ZH11 under noncolonized conditions identified 1268 DEGs (|log2 FC| > 1, FDR < 0.05), including 861 upregulated and 407 downregulated genes (Figure 1B). A total of 435 DEGs were identified under colonized conditions, comprising 229 upregulated and 206 downregulated genes (Figure 1B). Cluster analysis revealed four gene groups (Figure 1C), with only 121 DEGs overlapping between conditions (Figure 1D). We subsequently conducted a functional analysis of the combined DEGs (1147 + 121 + 314 = 1585) by examining their associations with KEGG) pathways and GO enrichment, thereby elucidating the underlying biological significance of these genes. Interestingly, terms of “defense response” and “regulation of defense response” were markedly enriched in Go enrichment analysis (Figure 1E). Consistently, “plant–pathogen interaction” and “MAPK signaling pathway” were significantly enriched in the KEGG pathway analysis (Figure 1F). Over 60 genes were enriched in the “defense response” GO term, visualized as a heatmap of published genes, such as OsPR10, OsPR1, OsWRKY45, OsFLS2, OsPAD4, etc. (Figure 1G). Based on expression patterns, these genes were divided into two clusters and further subdivided into four subsets (Figure 1G). Cluster 1 genes were upregulated in Osark1, while Cluster 2 genes were downregulated. In Cluster 1_A, genes (OsWRKY45-OsFLS2) were significantly upregulated in ZH11 after AM treatment but partially suppressed in Osark1 (Figure 1G). AM strongly suppressed Cluster 1_B genes (OsRH3-OsJAZ5) (Figure 1G). Compared to the control (CK), Cluster 1_C genes including OsKS3, OsXIP, and OsPR1 were suppressed in ZH11 while they were induced in Osark1 mutant after AM treatment (Figure 1G). Notably, under non-mycorrhizal conditions, most stress- and oxidation-responsive genes were differentially expressed in Osark1 mutants relative to ZH11(Figure S1E,F, Table S3). After AM inoculation, however, these transcriptional differences were largely attenuated or became non-significant over time (Figure S1E,F, Table S3). These findings imply that basal transcriptional differences may underlie the reduced AM colonization efficiency in Osark1, while AM-induced modulation may partially compensate by restoring transcriptional homeostasis. Together, the data indicate that OsARK1 may play a critical role in immune regulation during AM colonization in rice.

3.2. OsARK1 Positively Regulates Rice Resistance to Blast Fungus

To further test the involvement of OsARK1 in immune regulation, we tested the resistance of Osark1 mutant to blast fungus compared with wild-type ZH11. The infection experiment was carried out by whole foliar spraying with the conidia of M. oryzae strain Guy11 that is pathogenic to ZH11 varieties. We observed significantly larger and denser lesions, and the relative fungal biomass was remarkably increased in Osark1 leaves compared with wild-type (Figure 2A). Similarly, Osark1 plants displayed larger lesions and permitted more fungal biomass compared with ZH11 in the punch inoculation assays (Figure 2B). Taken together, our data demonstrated that OsARK1 functions as a positive regulator of rice resistance to the blast fungus.

3.3. OsARK1 Positively Regulates Rice Resistance to Bacterial Blight

To determine whether OsARK1 functions in rice resistance to other pathogen, we carried out disease assays to investigate the resistance of Osark1 and ZH11 to Xoo, which causes bacterial blight. As shown in Figure 2C, the disease severity was higher in Osark1, leading to larger lesion areas compared with those in ZH11. This result indicates that OsARK1 plays a positive regulatory role in rice immunity against bacterial blight.

3.4. OsARK1 Positively Regulates Immune Responses

To investigate the involvement of OsARK1 in immune responses, we compared chitin-induced callose deposition and pathogen-induced ROS accumulation between Osark1 and ZH11. There was a nearly fourfold reduction in chitin-induced callose deposition in Osark1 compared with ZH11 (Figure 3A), as detected by the autofluorescence emitted from callose under ultraviolet (UV) light. Diaminobenzidine (DAB) staining revealed a markedly lighter reddish-brown color at the infection sites of Osark1 leaves challenged by Guy11, indicating a substantial reduction in H2O2 accumulation in Osark1 leaves relative to ZH11 (Figure 3B). Furthermore, the transcript levels of pathogenesis-related genes OsPR3, OsPR10 and OsWRKY62 in infected leaves at 48 h post-inoculation (hpi) were significantly lower in Osark1 than in ZH11 (Figure 3C–E). These results indicate that OsARK1 positively affects the chitin-induced callose deposition and pathogen-induced H2O2 accumulation and expression of defense-related genes, thereby promotes rice immunity against M. oryzae.

3.5. OsARK1 Coordinates Early Transcriptional Reprogramming of Immune Receptors and Metabolic Pathways in Rice Blast Defense

To gain molecular insights into the mechanisms by which OsARK1 regulates resistance to blast disease, in-depth comprehensive transcriptome profiles of the Osark1 mutant were compared with ZH11 through RNA-seq experiments. Three-week-old rice plants were subjected to spray inoculation with Guy11 spores or mock-inoculated with distilled H2O, and then leaf samples were collected at 24 and 48 hpi, with three biological replicates for each condition, for subsequent RNA-seq analysis. The PCA plot of the RNA-seq data reveled that the triplicate biological replicates were tightly clustered and distinctly separated according to treatment and genotype (Figure 4A). We identified DEGs between the fungal and mock treatment in Osark1 and ZH11 at each time point. The rice gene expression levels were subsequently compared between Guy11 and the mock treatment at both 24 hpi and 48 hpi. By applying the criterion of |log2 FC| > 1 and FDR < 0.05. we identified 368 downregulated and 434 upregulated genes in Osark1, while 116 downregulated and 689 upregulated genes in ZH11 at 24 hpi. At 48 hpi, Osark1 exhibited 2167 downregulated and 1861 upregulated genes, whereas ZH11 had 515 downregulated and 1055 upregulated genes (Figure 4B), indicating that these genes were steadily differentially expressed in Osark1 and ZH11.
To identify OsARK1-regulated defensive genes, we analyzed DEGs across different genotypes and treatments using Venn diagrams at 24 and 48 hpi of Guy11. The diagrams show that Guy11 regulated DEGs included 677 specific to Osark1 and 680 specific to ZH11, and 125 overlapping DEGs between the two groups at 24 hpi (Figure 4C). At 48 hpi, the number of DEGs was significantly greater than at 24 hpi, with 3111 being specific to Osark1 and 653 specific to ZH11, and 917 overlapping DEGs (Figure 4C). We selected the 24 hpi DEGs (677 + 680) for GO enrichment analysis. The GO enrichment analysis revealed that the terms related to “defense response”, “biological process involved interspecies interaction” and “response to external biotic stimuli” were significantly enriched in ZH11 but not in Osark1 (Figure 4E). We selected the term “defense response” genes to construct a heatmap. Notably, we observed that the expression of genes encoding NBS-LRR domain containing protein and LecRLKs were remarkably downregulated in Osark1 compared to ZH11 at 24 hpi (Figure 4D). It has been reported that LecRLKs, located on the cell membrane, play crucial roles in plant development and responses to abiotic and biotic stresses [63]. NLR function as monitors that directly or indirectly detect the pathogen effectors to activate immune response [64]. These findings suggest that Osark1 mutant directly affects the transcription of these genes involved in immunity. Interestingly, only “regulation of RNA biosynthetic process”, “regulation of nucleic acid-templated transcription”, “regulation of DNA-templated transcription” and “plant hormone signal transduction” were significantly enriched in the GO analysis of Osark1 (Figure 4E).
At 48 hpi, GO enrichment analysis of the 515 down-regulated DEGs in ZH11 identified significant enrichment only for light signal-related terms (Figure S2). No significant GO terms were enriched among the 1055 up-regulated DEGs. This limited response is likely attributable to weak infection by Guy11 in this experiment. PCA further supports this conclusion, revealing that the Guy11 treatment explained only 5% of the variance (PC2), while time accounted for 84% (PC1) (Figure 4A). In contrast, analysis of the 2167 down-regulated DEGs in Osark1 at 48 hpi identified significant enrichment for defense-related processes, including “diterpenoid biosynthetic Process”, “diterpenoid metabolic process”, “regulation of primary metabolic process” and “aromatic compound biosynthetic process” (Figure S2). Diterpene phytoalexins, aromatic compounds and primary metabolism are established positive contributors to plant pathogens resistance [65,66,67,68]. Collectively, these results illustrated that OsARK1 regulates transcriptional reprogramming upon Guy11 infection, activating expression of NLR genes, LecRLKs and metabolic synthesis genes essential for defense.
To further elucidate the role of OsARK1 in redox regulation, we analyzed the expression of ROS-related genes from our transcriptomic data. While Osark1 mutants showed clearly reduced ROS accumulation (Figure 3D), most genes encoding ROS-producing enzymes (e.g., Rboh NADPH oxidases) and ROS-scavenging components (e.g., SOD, CAT, APX, GPX) did not exhibit significant transcriptional changes (Table S4). This suggests that OsARK1 likely regulates ROS homeostasis through post-translational mechanisms rather than transcriptional control of these genes.

4. Discussion

In nature, plants constantly interact with different types of microbes, requiring them to distinguish between beneficial and pathogenic microbes and to modulate immunity accordingly—either fostering symbiosis or mounting defense. The previous studies showed that OsARK1 is required for the maintenance of AM symbiosis in rice, Medicago truncatula, Marchantia paleacea and Lotus japonicus [48,49,51,52], and is evolutionarily conserved across the genomes of plant species capable of forming AM symbiosis [52,69]. In this study, we discovered that OsARK1 plays a pivotal and previously unrecognized dual role in rice-microbe interactions: it not only facilitates beneficial AM fungal colonization by modulating host defense gene expression but also acts as a positive regulator of rice immunity against pathogenic fungi and bacteria.
Our transcriptomic analyses revealed that OsARK1 critically influences defense-related transcriptional reprogramming during both symbiosis in roots and pathogen attack on leaves. In roots, the loss of OsARK1 attenuated the global transcriptional response and impaired the regulation of a group of defense-related genes enriched in GO terms like “defense response” and KEGG pathways such as “plant–pathogen interaction” and “MAPK signaling” (Figure 1E,F). Notably, OsARK1 was required for the appropriate induction or suppression of key defense genes (e.g., OsWRKY45, OsFLS2, OsPR1, OsJAZ5) (Figure 1G), suggesting its function is integral for regulating host immunity sufficiently to allow symbiosis, potentially by integrating symbiotic signals with defense pathways.
The high degree of overlap (~80%) in differentially expressed genes between Osark1 and wild-type ZH11 under AM colonization conditions suggests the existence of functional redundancy or compensatory mechanisms within the rice immune regulatory network (Figure S1B). This phenomenon may be mediated by other receptor-like kinases or signaling components that partially compensate for the loss of OsARK1, thereby maintaining basal expression levels of a substantial proportion of responsive genes. While OsARK1 loss clearly impairs specific transcriptional reprogramming necessary for both symbiosis and immunity, this network-level robustness may explain why the mutant does not exhibit more severe phenotypic consequences.
Crucially, our data demonstrates the role of OsARK1 extends beyond symbiosis to direct pathogen defense. Osark1 mutants exhibited significantly enhanced susceptibility to both the blast fungus pathogen M. oryzae and the bacterial blight pathogen Xoo (Figure 2A–C). This heightened susceptibility was underpinned by compromised basal immune responses, including reduced chitin-induced callose deposition, diminished pathogen-induced ROS accumulation, and impaired induction of pathogenesis-related genes (OsPR3, OsPR10, OsWRKY62) upon M. oryzae infection (Figure 3A–E). Transcriptome profiling during M. oryzae infection provided deeper molecular insights. OsARK1 was essential for the early (24 hpi) transcriptional reprogramming of immunity, particularly the upregulation of genes encoding crucial PRRs, such as NBS-LRR proteins and LecRLKs (Figure 4D). The significant enrichment of defense-related GO terms (“defense response”, “response to external biotic stimuli”) specifically in wild-type ZH11, but not in Osark1, at this early time point (Figure 4E), highlights a critical role of OsARK1 in initiating immune signaling. Furthermore, the significantly higher number of differentially expressed genes (DEGs) in Osark1 at 48 hpi compared to ZH11 suggests a loss of transcriptional homeostasis in the mutant (Figure S2). In ZH11, OsARK1 appears to facilitate the transition from early immune activation to subsequent metabolic reprogramming, contributing to the decline in DEGs over time. In contrast, Osark1 mutants exhibit persistent transcriptional dysregulation, particularly affecting metabolic pathways such as diterpenoid phytoalexin biosynthesis and aromatic compound metabolism, both of which are known to directly contribute to antimicrobial defense [65,66,67,68]. This persistent imbalance reflects a disrupted transition to later immune responses and highlights the role of OsARK1 in coordinating the temporal dynamics of defense-related transcriptional reprogramming, including the regulation of metabolic processes essential for effective immunity.
Furthermore, our in-depth analysis of reactive oxygen species (ROS)-homeostasis-related genes and the core genes within enriched GO categories such as “response to stress” and “response to oxygen-containing compound” provides novel mechanistic insights into the role of OsARK1 in integrating redox balance and immune responses. Despite the clear defect in pathogen-induced ROS accumulation in the Osark1 mutant (Figure 3D), most genes encoding ROS-producing enzymes (e.g., Rboh NADPH oxidases) and ROS-scavenging enzymes (e.g., SOD, CAT, APX, GPX) showed no significant differential expression at the transcript level. This apparent discrepancy strongly suggests that OsARK1 regulates the ROS burst primarily at the post-translational level (e.g., by modulating the phosphorylation status or activity of existing Rboh proteins), rather than through transcriptional reprogramming. This interpretation is consistent with the well-established paradigm that ROS signaling is primarily regulated at the protein level through phosphorylation, calcium signaling, and protein–protein interactions to enable rapid responses to biotic stress [70]. Additionally, analysis of the “response to stress” and “response to oxygen-containing compound” GO categories revealed that many genes in these pathways showed pre-existing expression differences in Osark1 under mock conditions, but these disparities were attenuated following AM inoculation (Table S3). This pattern further supports the role of OsARK1 as an integrator of redox balance and immune responses across different microbial interactions.
Notably, OsARK1 exhibits a unique dual-positive regulatory role that distinguishes it from other immune-symbiotic integrators such as SYMRK in Lotus japonicus, which promotes symbiosis by suppressing immunity [45], or CERK1, which activates distinct responses through perception of different chitin oligosaccharides [29,71]. Unlike these proteins, OsARK1 positively regulates both symbiotic colonization and pathogen resistance, raising the key question of how it context-dependently facilitates AM fungal colonization in roots while enhancing immune responses against pathogens in leaves. We propose that OsARK1 may act as a central signaling integrator whose functional specificity could arise from mechanisms such as tissue-specific co-receptor interactions (e.g., with OsMYR1 in roots vs. immunity-related partners in leaves), differential ligand perception, or post-translational modifications. During symbiosis, AM fungal signals likely recruit OsARK1 to fine-tune defense responses and enable colonization, whereas pathogenic infection in leaves activates alternative OsARK1 complexes, triggering robust immune outputs including ROS production, callose deposition, and defense gene induction. The severe attenuation of early immune responses in Osark1 mutants underscores its essential role within core signaling networks. Although structurally distinct from ligand-binding receptors like CERK1, OsARK1 may serve as a regulatory scaffold that amplifies context-dependent signals. The convergent evolution of dual-function receptors highlights the importance of signaling integration at the plant–microbe interface, yet the precise mechanism underlying OsARK1′s context-dependent regulation remains a fundamental question for future research.

5. Conclusions

Our study demonstrates that OsARK1 acts as a dual-function regulator essential for both maintaining symbiotic accommodation with AM fungi and enhancing immune resistance against pathogens by orchestrating context-specific transcriptional reprogramming. Furthermore, OsARK1 mediates the transition from early immune activation to subsequent metabolic regulation, with its loss leading to sustained dysregulation of defense and specialized metabolic pathways critical for antimicrobial defense. Understanding the precise mechanisms by which OsARK1 differentially regulates these contrasting outcomes—potentially involving specific interacting proteins, post-translational modifications, or subcellular localization in response to different microbial signatures—represents a fascinating avenue for future research into plant–microbe communication and immunity modulation. Furthermore, tissue-specific manipulation of OsARK1 expression, for example, by enhancing its activity in leaves while maintaining native levels in roots, could improve pathogen resistance without compromising symbiotic capabilities with arbuscular mycorrhizal fungi. This strategy may ultimately contribute to developing rice cultivars with balanced resilience and nutrient efficiency.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy15102298/s1, Figure S1. Analysis of differentially expressed genes (DEGs) between Osark1 and ZH11 under AM fungi treatment. Figure S2. GO term enrichment analysis of all DEGs in ZH11 and Osark1 treated with the M. oryzae at 48 hpi. Table S1. The expression values for all differentially expressed genes between AM fungi and mock treatment in the rice roots. Table S2. The expression values for all differentially expressed genes between M. oryzae and mock treatment in the rice leaves. Table S3. Fig1E_GO_1582. Table S4. Expression values of reactive oxygen species (ROS)-associated genes in rice leaves after M. oryzae challenge versus mock treatment.

Author Contributions

Conceptualization, H.C.; methodology, Z.Z. and K.Z.; figures, Z.Z.; data analysis, G.L. and A.W.; methodology, Z.Z., K.Z., G.L. and H.C.; software, H.C.; validation, Z.Z., Z.W. and A.W.; formal analysis, Z.Z. and K.Z.; investigation, Z.Z. and K.Z.; resources, G.L., Z.W., A.W. and H.C.; data curation, H.C.; writing—original draft, Z.Z. and H.C.; writing—review and editing, G.L., H.C., Z.W. and A.W.; visualization, Z.Z., H.C. and A.W.; supervision, H.C. and A.W.; project administration, H.C.; funding acquisition, Z.W., H.C. and A.W. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by grants from the Fujian Provincial Science and Technology Key Project (2022NZ030014), the Fujian Provincial Specialized Financial Project (KKY22047XB), the Natural Science Foundation of Fujian Province (Key program, 2023J02011) and Funding for the ‘First Class Discipline’ Construction Project of Shandong Agricultural University (SKL81105).

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors on request.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Trivedi, P.; Leach, J.E.; Tringe, S.G.; Sa, T.; Singh, B.K. Plant–microbiome interactions: From community assembly to plant health. Nat. Rev. Microbiol. 2020, 18, 607–621. [Google Scholar] [CrossRef] [PubMed]
  2. Chowdhary, N.A.; Songachan, L.S. Boosting sustainable agriculture by arbuscular mycorrhizal fungi under abiotic stress condition. Plant Stress. 2025, 17, 100945. [Google Scholar] [CrossRef]
  3. Szentpéteri, V.; Virág, E.; Mayer, Z.; Duc, N.H.; Hegedűs, G.; Posta, K. First Peek into the Transcriptomic Response in Heat-Stressed Tomato Inoculated with Septoglomus constrictum. Plants 2024, 13, 2266. [Google Scholar] [CrossRef]
  4. Cao, Y.; Halane, M.K.; Gassmann, W.; Stacey, G. The Role of Plant Innate Immunity in the Legume-Rhizobium Symbiosis. Annu. Rev. Plant Biol. 2017, 68, 535–561. [Google Scholar] [CrossRef] [PubMed]
  5. Zipfel, C.; Oldroyd, G.E. Plant signalling in symbiosis and immunity. Nature 2017, 543, 328–336. [Google Scholar] [CrossRef]
  6. Rodriguez, P.A.; Rothballer, M.; Chowdhury, S.P.; Nussbaumer, T.; Gutjahr, C.; Falter-Braun, P. Systems Biology of Plant-Microbiome Interactions. Mol. Plant 2019, 12, 804–821. [Google Scholar] [CrossRef] [PubMed]
  7. Antolín-Llovera, M.; Petutsching, E.K.; Ried, M.K.; Lipka, V.; Nürnberger, T.; Robatzek, S.; Parniske, M. Knowing your friends and foes—Plant receptor-like kinases as initiators of symbiosis or defence. New Phytol. 2014, 204, 791–802. [Google Scholar] [CrossRef]
  8. Macho, A.P.; Zipfel, C. Plant PRRs and the activation of innate immune signaling. Mol. Cell 2014, 54, 263–272. [Google Scholar] [CrossRef]
  9. Zipfel, C. Plant pattern-recognition receptors. Trends Immunol. 2014, 35, 345–351. [Google Scholar] [CrossRef]
  10. Zeng, T.; Rodriguez-Moreno, L.; Mansurkhodzaev, A.; Wang, P.; van den Berg, W.; Gasciolli, V.; Cottaz, S.; Fort, S.; Thomma, B.P.H.J.; Bono, J.J.; et al. A lysin motif effector subverts chitin-triggered immunity to facilitate arbuscular mycorrhizal symbiosis. New Phytol. 2019, 225, 448–460. [Google Scholar] [CrossRef]
  11. Oldroyd, G.E.D. Speak, friend, and enter: Signalling systems that promote beneficial symbiotic associations in plants. Nat. Rev. Microbiol. 2013, 11, 252–263. [Google Scholar] [CrossRef]
  12. Shinya, T.; Nakagawa, T.; Kaku, H.; Shibuya, N. Chitin-mediated plant-fungal interactions: Catching, hiding and handshaking. Curr. Opin. Plant Biol. 2015, 26, 64–71. [Google Scholar] [CrossRef]
  13. Zipfel, C.; Robatzek, S.; Navarro, L.; Oakeley, E.J.; Jones, J.D.; Felix, G.; Boller, T. Bacterial disease resistance in Arabidopsis through flagellin perception. Nature 2004, 428, 764–767. [Google Scholar] [CrossRef]
  14. Sun, Y.; Li, L.; Macho, A.P.; Han, Z.; Hu, Z.; Zipfel, C.; Zhou, J.M.; Chai, J. Structural basis for flg22-induced activation of the Arabidopsis FLS2-BAK1 immune complex. Science 2013, 342, 624–628. [Google Scholar] [CrossRef]
  15. Wan, J.; Zhang, X.C.; Neece, D.; Ramonell, K.M.; Clough, S.; Kim, S.Y.; Stacey, M.G.; Stacey, G. A LysM receptor-like kinase plays a critical role in chitin signaling and fungal resistance in Arabidopsis. Plant Cell 2008, 20, 471–481. [Google Scholar] [CrossRef]
  16. Liu, T.; Liu, Z.; Song, C.; Hu, Y.; Han, Z.; She, J.; Fan, F.; Wang, J.; Jin, C.; Chang, J.; et al. Chitin-induced dimerization activates a plant immune receptor. Science 2012, 336, 1160–1164. [Google Scholar] [CrossRef] [PubMed]
  17. Cao, Y.; Liang, Y.; Tanaka, K.; Nguyen, C.T.; Jedrzejczak, R.P.; Joachimiak, A.; Stacey, G. The kinase LYK5 is a major chitin receptor in Arabidopsis and forms a chitin-induced complex with related kinase CERK1. eLife 2014, 3, e03766. [Google Scholar] [CrossRef] [PubMed]
  18. Cheval, C.; Samwald, S.; Johnston, M.G.; de Keijzer, J.; Breakspear, A.; Liu, X.; Bellandi, A.; Kadota, Y.; Zipfel, C.; Faulkner, C. Chitin perception in plasmodesmata characterizes submembrane immune-signaling specificity in plants. Proc. Natl. Acad. Sci. USA 2020, 117, 9621–9629. [Google Scholar] [CrossRef] [PubMed]
  19. Miya, A.; Albert, P.; Shinya, T.; Desaki, Y.; Ichimura, K.; Shirasu, K.; Narusaka, Y.; Kawakami, N.; Kaku, H.; Shibuya, N. CERK1, a LysM receptor kinase, is essential for chitin elicitor signaling in Arabidopsis. Proc. Natl. Acad. Sci. USA 2007, 104, 19613–19618. [Google Scholar] [CrossRef]
  20. Genre, A.; Chabaud, M.; Balzergue, C.; Puech-Pagès, V.; Novero, M.; Rey, T.; Fournier, J.; Rochange, S.; Bécard, G.; Bonfante, P.; et al. Short-chain chitin oligomers from arbuscular mycorrhizal fungi trigger nuclear Ca2+ spiking in Medicago truncatula roots and their production is enhanced by strigolactone. New Phytol. 2013, 198, 190–202. [Google Scholar] [CrossRef]
  21. Maillet, F.; Poinsot, V.; Andre, O.; Puech-Pages, V.; Haouy, A.; Gueunier, M.; Cromer, L.; Giraudet, D.; Formey, D.; Niebel, A.; et al. Fungal lipochitooligosaccharide symbiotic signals in arbuscular mycorrhiza. Nature 2011, 469, 58–63. [Google Scholar] [CrossRef]
  22. He, J.; Zhang, C.; Dai, H.; Liu, H.; Zhang, X.; Yang, J.; Chen, X.; Zhu, Y.; Wang, D.; Qi, X.; et al. A LysM Receptor Heteromer Mediates Perception of Arbuscular Mycorrhizal Symbiotic Signal in Rice. Mol. Plant 2019, 12, 1561–1576. [Google Scholar] [CrossRef] [PubMed]
  23. Feng, F.; Sun, J.; Radhakrishnan, G.V.; Lee, T.; Bozsoki, Z.; Fort, S.; Gavrin, A.; Gysel, K.; Thygesen, M.B.; Andersen, K.R.; et al. A combination of chitooligosaccharide and lipochitooligosaccharide recognition promotes arbuscular mycorrhizal associations in Medicago truncatula. Nat. Commun. 2019, 10, 5047. [Google Scholar] [CrossRef] [PubMed]
  24. Girardin, A.; Wang, T.; Ding, Y.; Keller, J.; Buendia, L.; Gaston, M.; Ribeyre, C.; Gasciolli, V.; Auriac, M.-C.; Vernié, T.; et al. LCO Receptors Involved in Arbuscular Mycorrhiza Are Functional for Rhizobia Perception in Legumes. Curr. Biol. 2019, 29, 4249–4259.e4245. [Google Scholar] [CrossRef] [PubMed]
  25. Carotenuto, G.; Chabaud, M.; Miyata, K.; Capozzi, M.; Takeda, N.; Kaku, H.; Shibuya, N.; Nakagawa, T.; Barker, D.G.; Genre, A. The rice LysM receptor-like kinase OsCERK1 is required for the perception of short-chain chitin oligomers in arbuscular mycorrhizal signaling. New Phytol. 2017, 214, 1440–1446. [Google Scholar] [CrossRef]
  26. Bozsoki, Z.; Cheng, J.; Feng, F.; Gysel, K.; Vinther, M.; Andersen, K.R.; Oldroyd, G.; Blaise, M.; Radutoiu, S.; Stougaard, J. Receptor-mediated chitin perception in legume roots is functionally separable from Nod factor perception. Proc. Natl. Acad. Sci. USA 2017, 114, E8118–E8127. [Google Scholar] [CrossRef]
  27. Huang, R.; Li, Z.; Mao, C.; Zhang, H.; Sun, Z.; Li, H.; Huang, C.; Feng, Y.; Shen, X.; Bucher, M.; et al. Natural variation at OsCERK1 regulates arbuscular mycorrhizal symbiosis in rice. New Phytol. 2020, 225, 1762–1776. [Google Scholar] [CrossRef]
  28. Zhang, X.; Dong, W.; Sun, J.; Feng, F.; Deng, Y.; He, Z.; Oldroyd, G.E.; Wang, E. The receptor kinase CERK1 has dual functions in symbiosis and immunity signalling. Plant J. 2015, 81, 258–267. [Google Scholar] [CrossRef]
  29. Zhang, C.; He, J.; Dai, H.; Wang, G.; Zhang, X.; Wang, C.; Shi, J.; Chen, X.; Wang, D.; Wang, E. Discriminating symbiosis and immunity signals by receptor competition in rice. Proc. Natl. Acad. Sci. USA 2021, 118, e2023738118. [Google Scholar] [CrossRef]
  30. Miyata, K.; Kozaki, T.; Kouzai, Y.; Ozawa, K.; Ishii, K.; Asamizu, E.; Okabe, Y.; Umehara, Y.; Miyamoto, A.; Kobae, Y.; et al. The bifunctional plant receptor, OsCERK1, regulates both chitin-triggered immunity and arbuscular mycorrhizal symbiosis in rice. Plant Cell Physiol. 2014, 55, 1864–1872. [Google Scholar] [CrossRef]
  31. Shimizu, T.; Nakano, T.; Takamizawa, D.; Desaki, Y.; Ishii-Minami, N.; Nishizawa, Y.; Minami, E.; Okada, K.; Yamane, H.; Kaku, H.; et al. Two LysM receptor molecules, CEBiP and OsCERK1, cooperatively regulate chitin elicitor signaling in rice. Plant J. 2010, 64, 204–214. [Google Scholar] [CrossRef] [PubMed]
  32. Buendia, L.; Wang, T.; Girardin, A.; Lefebvre, B. The LysM receptor-like kinase SlLYK10 regulates the arbuscular mycorrhizal symbiosis in tomato. New Phytol. 2015, 210, 184–195. [Google Scholar] [CrossRef]
  33. Broghammer, A.; Krusell, L.; Blaise, M.; Sauer, J.; Sullivan, J.T.; Maolanon, N.; Vinther, M.; Lorentzen, A.; Madsen, E.B.; Jensen, K.J.; et al. Legume receptors perceive the rhizobial lipochitin oligosaccharide signal molecules by direct binding. Proc. Natl. Acad. Sci. USA 2012, 109, 13859–13864. [Google Scholar] [CrossRef]
  34. Fliegmann, J.; Jauneau, A.; Pichereaux, C.; Rosenberg, C.; Gasciolli, V.; Timmers, A.C.J.; Burlet-Schiltz, O.; Cullimore, J.; Bono, J.J. LYR3, a high-affinity LCO-binding protein of Medicago truncatula, interacts with LYK3, a key symbiotic receptor. FEBS Lett. 2016, 590, 1477–1487. [Google Scholar] [CrossRef]
  35. Wang, T.; Gasciolli, V.; Gaston, M.; Medioni, L.; Cumener, M.; Buendia, L.; Yang, B.; Bono, J.J.; He, G.; Lefebvre, B. LysM receptor-like kinases involved in immunity perceive lipo-chitooligosaccharides in mycotrophic plants. Plant Physiol. 2023, 192, 1435–1448. [Google Scholar] [CrossRef]
  36. Arrighi, J.-F.; Barre, A.; Ben Amor, B.; Bersoult, A.; Soriano, L.C.; Mirabella, R.; de Carvalho-Niebel, F.; Journet, E.-P.; Ghérardi, M.l.; Huguet, T.; et al. The Medicago truncatula Lysine Motif-Receptor-Like Kinase Gene Family Includes NFP and New Nodule-Expressed Genes. Plant Physiol. 2006, 142, 265–279. [Google Scholar] [CrossRef]
  37. Haney, C.H.; Riely, B.K.; Tricoli, D.M.; Cook, D.R.; Ehrhardt, D.W.; Long, S.R. Symbiotic Rhizobia Bacteria Trigger a Change in Localization and Dynamics of the Medicago truncatula Receptor Kinase LYK3. Plant Cell 2011, 23, 2774–2787. [Google Scholar] [CrossRef]
  38. Limpens, E.; Franken, C.; Smit, P.; Willemse, J.; Bisseling, T.; Geurts, R. LysM Domain Receptor Kinases Regulating Rhizobial Nod Factor-Induced Infection. Science 2003, 302, 630–633. [Google Scholar] [CrossRef]
  39. Moling, S.; Pietraszewska-Bogiel, A.; Postma, M.; Fedorova, E.; Hink, M.A.; Limpens, E.; Gadella, T.W.; Bisseling, T. Nod factor receptors form heteromeric complexes and are essential for intracellular infection in medicago nodules. Plant Cell 2014, 26, 4188–4199. [Google Scholar] [CrossRef] [PubMed]
  40. Smit, P.; Limpens, E.; Geurts, R.; Fedorova, E.; Dolgikh, E.; Gough, C.; Bisseling, T. Medicago LYK3, an Entry Receptor in Rhizobial Nodulation Factor Signaling. Plant Physiol. 2007, 145, 183–191. [Google Scholar] [CrossRef] [PubMed]
  41. Radutoiu, S.; Madsen, L.H.; Madsen, E.B.; Felle, H.H.; Umehara, Y.; Grønlund, M.; Sato, S.; Nakamura, Y.; Tabata, S.; Sandal, N.; et al. Plant recognition of symbiotic bacteria requires two LysM receptor-like kinases. Nature 2003, 415, 585–592. [Google Scholar] [CrossRef]
  42. Wang, D.; Jin, R.; Shi, X.; Guo, H.; Tan, X.; Zhao, A.; Lian, X.; Dai, H.; Li, S.; Xin, K.; et al. A kinase mediator of rhizobial symbiosis and immunity in Medicago. Nature 2025, 643, 768–775. [Google Scholar] [CrossRef]
  43. Silke, S.; Catherine, K.; Satoko, Y.; Lonneke, M.; Shusei, S.; Takakazu, K.; Satoshi, T.; Niels, S.; Jens, S.; Krzysztof, S.; et al. A plant receptor-like kinase required for both bacterial and fungal symbiosis. Nature 2002, 417, 959–962. [Google Scholar] [CrossRef]
  44. Antolin-Llovera, M.; Ried, M.K.; Parniske, M. Cleavage of the SYMBIOSIS RECEPTOR-LIKE KINASE ectodomain promotes complex formation with Nod factor receptor 5. Curr. Biol. 2014, 24, 422–427. [Google Scholar] [CrossRef] [PubMed]
  45. Feng, Y.; Wu, P.; Liu, C.; Peng, L.; Wang, T.; Wang, C.; Tan, Q.; Li, B.; Ou, Y.; Zhu, H.; et al. Suppression of LjBAK1-mediated immunity by SymRK promotes rhizobial infection in Lotus japonicus. Mol. Plant 2021, 14, 1935–1950. [Google Scholar] [CrossRef] [PubMed]
  46. Lehti-Shiu, M.D.; Shiu, S.-H. Diversity, classification and function of the plant protein kinase superfamily. Philos. Trans. R. Soc. B Biol. Sci. 2012, 367, 2619–2639. [Google Scholar] [CrossRef] [PubMed]
  47. Montero, H.; Lee, T.; Pucker, B.; Ferreras-Garrucho, G.; Oldroyd, G.; Brockington, S.F.; Miyao, A.; Paszkowski, U. A mycorrhiza-associated receptor-like kinase with an ancient origin in the green lineage. Proc. Natl. Acad. Sci. USA 2021, 118, e2105281118. [Google Scholar] [CrossRef]
  48. Sgroia, M.; Hoeyb, D.; Medina Jimenezc, K.; Bowdend, S.L.; Hoped, M.; Paszkowskia, U. The receptor-like kinase ARK controls symbiotic balance across land plants. Proc. Natl. Acad. Sci. USA 2024, 121, e2318982121. [Google Scholar] [CrossRef]
  49. Roth, R.; Chiapello, M.; Montero, H.; Gehrig, P.; Grossmann, J.; O’Holleran, K.; Hartken, D.; Walters, F.; Yang, S.Y.; Hillmer, S.; et al. A rice Serine/Threonine receptor-like kinase regulates arbuscular mycorrhizal symbiosis at the peri-arbuscular membrane. Nat. Commun. 2018, 9, 4677. [Google Scholar] [CrossRef]
  50. Irving, T.B.; Chakraborty, S.; Ivanov, S.; Schultze, M.; Mysore, K.S.; Harrison, M.J.; Ané, J.M. KIN3 impacts arbuscular mycorrhizal symbiosis and promotes fungal colonisation in Medicago truncatula. Plant J. 2022, 110, 513–528. [Google Scholar] [CrossRef]
  51. Bravo, A.; York, T.; Pumplin, N.; Mueller, L.A.; Harrison, M.J. Genes conserved for arbuscular mycorrhizal symbiosis identified through phylogenomics. Nat. Plants 2016, 2, 15208. [Google Scholar] [CrossRef]
  52. Leng, J.; Wei, X.; Jin, X.; Wang, L.; Fan, K.; Zou, K.; Zheng, Z.; Saridis, G.; Zhao, N.; Zhou, D.; et al. ARBUSCULAR MYCORRHIZA-INDUCED KINASES AMK8 and AMK24 associate with the receptor-like kinase KINASE3 to regulate arbuscular mycorrhizal symbiosis in Lotus japonicus. Plant Cell 2023, 35, 2006–2026. [Google Scholar] [CrossRef]
  53. Deng, Y.; Zhai, K.; Xie, Z.; Yang, D.; Zhu, X.; Liu, J.; Wang, X.; Qin, P.; Yang, Y.; Zhang, G.; et al. Epigenetic regulation of antagonistic receptors confers rice blast resistance with yield balance. Science 2017, 355, 962–965. [Google Scholar] [CrossRef] [PubMed]
  54. Niu, Y.; Huang, X.; He, Z.; Zhang, Q.; Meng, H.; Shi, H.; Feng, B.; Zhou, Y.; Zhang, J.; Lu, G.; et al. Phosphorylation of OsTGA5 by casein kinase II compromises its suppression of defense-related gene transcription in rice. Plant Cell 2022, 34, 3425–3442. [Google Scholar] [CrossRef]
  55. Park, C.-H.; Chen, S.; Shirsekar, G.; Zhou, B.; Khang, C.H.; Songkumarn, P.; Afzal, A.J.; Ning, Y.; Wang, R.; Bellizzi, M.; et al. The Magnaporthe oryzae Effector AvrPiz-t Targets the RING E3 Ubiquitin Ligase APIP6 to Suppress Pathogen-Associated Molecular Pattern–Triggered Immunity in Rice. Plant Cell 2012, 24, 4748–4762. [Google Scholar] [CrossRef]
  56. Kauffman, H.E.; Reddy, A.; Hsieh, S.P.Y.; Merca, S.D. An improved technique for evaluating resistance of rice varieties to Xanthomonas oryzae. Plant Dis. Report. 1973, 57, 537–541. [Google Scholar]
  57. Xue, L.; Klinnawee, L.; Zhou, Y.; Saridis, G.; Vijayakumar, V.; Brands, M.; Dormann, P.; Gigolashvili, T.; Turck, F.; Bucher, M. AP2 transcription factor CBX1 with a specific function in symbiotic exchange of nutrients in mycorrhizal Lotus japonicus. Proc. Natl. Acad. Sci. USA 2018, 115, E9239–E9246. [Google Scholar] [CrossRef] [PubMed]
  58. Yang, C.; Li, W.; Cao, J.; Meng, F.; Yu, Y.; Huang, J.; Jiang, L.; Liu, M.; Zhang, Z.; Chen, X.; et al. Activation of ethylene signaling pathways enhances disease resistance by regulating ROS and phytoalexin production in rice. Plant J. 2017, 89, 338–353. [Google Scholar] [CrossRef]
  59. Yang, C.; Yu, Y.; Huang, J.; Meng, F.; Pang, J.; Zhao, Q.; Islam, M.A.; Xu, N.; Tian, Y.; Liu, J. Binding of the Magnaporthe oryzae Chitinase MoChia1 by a Rice Tetratricopeptide Repeat Protein Allows Free Chitin to Trigger Immune Responses. Plant Cell 2019, 31, 172–188. [Google Scholar] [CrossRef]
  60. Kim, D.; Langmead, B.; Salzberg, S.L. HISAT: A fast spliced aligner with low memory requirements. Nat. Methods 2015, 12, 357–360. [Google Scholar] [CrossRef]
  61. Anders, S.; Pyl, P.T.; Huber, W. HTSeq—A Python framework to work with high-throughput sequencing data. Bioinformatics 2015, 31, 166–169. [Google Scholar] [CrossRef] [PubMed]
  62. Wang, L.; Feng, Z.; Wang, X.; Wang, X.; Zhang, X. DEGseq: An R package for identifying differentially expressed genes from RNA-seq data. Bioinformatics 2010, 26, 136–138. [Google Scholar] [CrossRef] [PubMed]
  63. Liu, L.; Liu, J.; Xu, N. Ligand recognition and signal transduction by lectin receptor-like kinases in plant immunity. Front. Plant Sci. 2023, 14, 1201805. [Google Scholar] [CrossRef]
  64. Cui, H.; Tsuda, K.; Parker, J.E. Effector-triggered immunity: From pathogen perception to robust defense. Annu. Rev. Plant Biol. 2015, 66, 487–511. [Google Scholar] [CrossRef]
  65. Zhan, C.; Lei, L.; Liu, Z.; Zhou, S.; Yang, C.; Zhu, X.; Guo, H.; Zhang, F.; Peng, M.; Zhang, M.; et al. Selection of a subspecies-specific diterpene gene cluster implicated in rice disease resistance. Nat. Plants 2020, 6, 1447–1454. [Google Scholar] [CrossRef]
  66. Kumar, P.; Kumar, D.; Pal, S.; Singh, S. Plant secondary metabolites in defense against phytopathogens: Mechanisms, biosynthesis, and applications. Physiol. Mol. Plant Pathol. 2025, 138, 102639. [Google Scholar] [CrossRef]
  67. Bolton, M.D. Primary Metabolism and Plant Defense—Fuel for the Fire. Mol. Plant-Microbe Interact. 2009, 22, 487–497. [Google Scholar] [CrossRef]
  68. Zaynab, M.; Fatima, M.; Sharif, Y.; Zafar, M.H.; Ali, H.; Khan, K.A. Role of primary metabolites in plant defense against pathogens. Microb. Pathog. 2019, 137, 103728. [Google Scholar] [CrossRef]
  69. Radhakrishnan, G.V.; Keller, J.; Rich, M.K.; Vernié, T.; Mbadinga Mbadinga, D.L.; Vigneron, N.; Cottret, L.; Clemente, H.S.; Libourel, C.; Cheema, J.; et al. An ancestral signalling pathway is conserved in intracellular symbioses-forming plant lineages. Nat. Plants 2020, 6, 280–289. [Google Scholar] [CrossRef]
  70. Waszczak, C.; Carmody, M.; Kangasjarvi, J. Reactive Oxygen Species in Plant Signaling. Annu. Rev. Plant Biol. 2018, 69, 209–236. [Google Scholar] [CrossRef] [PubMed]
  71. Tan, X.; Wang, D.; Zhang, X.; Zheng, S.; Jia, X.; Liu, H.; Liu, Z.; Yang, H.; Dai, H.; Chen, X.; et al. A pair of LysM receptors mediates symbiosis and immunity discrimination in Marchantia. Cell 2025, 188, 1330–1348.e27. [Google Scholar] [CrossRef] [PubMed]
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Figure 1. OsARK1 regulates expression of defense-related genes during AM symbiosis in roots. (A) Principal component analysis (PCA) of the transcriptome data from ZH11 and Osark1 under treatment with or without the AM fungi. (B) The numbers of up- and down-regulated genes in Osark1 versus ZH11 under AM colonized (AM) and non-colonized (Mock) conditions (|log2 fold change| > 1 and adjust p-value < 0.05). (C) Hierarchical clustering of all DEGs (in (B)) identified in the Osark1 vs. ZH11 comparison under AM and Mock conditions. (D) Venn diagram of total DEGs (in (B)) identified in the Osark1 vs. ZH11 comparison under AM and Mock conditions. (E,F) GO and KEGG pathway enrichment analysis of total DEGs in (B). 1147 + 121 + 314 = 1585 DEGs in (D). (G) The heatmap depicts the fold change of genes associated with the GO term “defense response” in (E).
Figure 1. OsARK1 regulates expression of defense-related genes during AM symbiosis in roots. (A) Principal component analysis (PCA) of the transcriptome data from ZH11 and Osark1 under treatment with or without the AM fungi. (B) The numbers of up- and down-regulated genes in Osark1 versus ZH11 under AM colonized (AM) and non-colonized (Mock) conditions (|log2 fold change| > 1 and adjust p-value < 0.05). (C) Hierarchical clustering of all DEGs (in (B)) identified in the Osark1 vs. ZH11 comparison under AM and Mock conditions. (D) Venn diagram of total DEGs (in (B)) identified in the Osark1 vs. ZH11 comparison under AM and Mock conditions. (E,F) GO and KEGG pathway enrichment analysis of total DEGs in (B). 1147 + 121 + 314 = 1585 DEGs in (D). (G) The heatmap depicts the fold change of genes associated with the GO term “defense response” in (E).
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Figure 2. Osark1 mutants display compromised resistance to M. oryzae and Xoo. (A) Four-week-old wild type (ZH11) and Osark1 mutant plants were spray-inoculated with the rice blast fungus M. oryzae isolate Guy11. Disease symptoms were observed at 4 dpi (left panel). Scale bar = 1 cm. Relative fungal biomass in lesions was quantified by qPCR using the M. oryzae Pot2 gene normalized to the rice OsActin gene (right panel). Data are represented as the mean ± SD (n = 3). Different letters indicate significant differences (one-way ANOVA, p < 0.01). # present different lines. (B) Lesions on four-week-old ZH11 and Osark1 mutant at 7 days after punch-inoculation with M. oryzae isolate Guy11 (left panel). Scale bar = 1 cm. Relative fungal biomass in lesions was quantified by qPCR as in (A) (right panel). Data are represented as the mean ± SD (n = 3). Different letters indicate significant differences (one-way ANOVA, p < 0.01). (C) Booting stage ZH11 and Osark1 plants were inoculated with bacterial suspension Xoo strain PXO86 (OD600 = 0.8) using leaf-clipping method. Photographs (left panel) were taken and lesion length was measured at 14 dpi. Data presented as means ± SD (n = 25, p < 0.01, one-way ANOVA) (right panel).
Figure 2. Osark1 mutants display compromised resistance to M. oryzae and Xoo. (A) Four-week-old wild type (ZH11) and Osark1 mutant plants were spray-inoculated with the rice blast fungus M. oryzae isolate Guy11. Disease symptoms were observed at 4 dpi (left panel). Scale bar = 1 cm. Relative fungal biomass in lesions was quantified by qPCR using the M. oryzae Pot2 gene normalized to the rice OsActin gene (right panel). Data are represented as the mean ± SD (n = 3). Different letters indicate significant differences (one-way ANOVA, p < 0.01). # present different lines. (B) Lesions on four-week-old ZH11 and Osark1 mutant at 7 days after punch-inoculation with M. oryzae isolate Guy11 (left panel). Scale bar = 1 cm. Relative fungal biomass in lesions was quantified by qPCR as in (A) (right panel). Data are represented as the mean ± SD (n = 3). Different letters indicate significant differences (one-way ANOVA, p < 0.01). (C) Booting stage ZH11 and Osark1 plants were inoculated with bacterial suspension Xoo strain PXO86 (OD600 = 0.8) using leaf-clipping method. Photographs (left panel) were taken and lesion length was measured at 14 dpi. Data presented as means ± SD (n = 25, p < 0.01, one-way ANOVA) (right panel).
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Figure 3. Loss of OsARK1 impairs immune responses. (A) Chitin-induced callose deposition in ZH11 and Osark1 leaves. Rice leaves were treated with 800 nM chitin, and callose deposition was visualized by aniline blue staining under UV microscope (left panel), scale bars = 50 μm. The amount of callose deposition was quantified using ImageJ (right panel). Data are means ± SD (n = 15). Significant differences were determined by one-way ANOVA (p < 0.01). (B) DAB staining of infection sites in ZH11 and Osark1 mutant leaves at 3 dpi. The size of the dark-brown area correlates with the H2O2 level (left panels). Scale bars: 5 mm (top), 500 μm (bottom). Quantification of DAB staining areas as a percentage of the total area in the bottom panels of (B) (right panel). The relative H2O2 level was calculated based on pixel quantification using ImageJ, with the formula: H2O2 area per rectangle = (pixel of H2O2 area per leaf)/(pixel of rectangle). Data are represented as mean ± SD (n = 21). Different letters indicate significant differences (one-way ANOVA, p < 0.01). (C–E) Relative transcript levels of defense-related genes in ZH11 and Osark1 before and after spray inoculation with the conidia of M. oryzae Guy11, as determined by RT-qPCR. Rice ubiquitin gene was used as the internal reference gene. Data represent means± SD (n = 3). Different letters indicate significant differences (one-way ANOVA, p < 0.01). These experiments were repeated three times with similar results.
Figure 3. Loss of OsARK1 impairs immune responses. (A) Chitin-induced callose deposition in ZH11 and Osark1 leaves. Rice leaves were treated with 800 nM chitin, and callose deposition was visualized by aniline blue staining under UV microscope (left panel), scale bars = 50 μm. The amount of callose deposition was quantified using ImageJ (right panel). Data are means ± SD (n = 15). Significant differences were determined by one-way ANOVA (p < 0.01). (B) DAB staining of infection sites in ZH11 and Osark1 mutant leaves at 3 dpi. The size of the dark-brown area correlates with the H2O2 level (left panels). Scale bars: 5 mm (top), 500 μm (bottom). Quantification of DAB staining areas as a percentage of the total area in the bottom panels of (B) (right panel). The relative H2O2 level was calculated based on pixel quantification using ImageJ, with the formula: H2O2 area per rectangle = (pixel of H2O2 area per leaf)/(pixel of rectangle). Data are represented as mean ± SD (n = 21). Different letters indicate significant differences (one-way ANOVA, p < 0.01). (C–E) Relative transcript levels of defense-related genes in ZH11 and Osark1 before and after spray inoculation with the conidia of M. oryzae Guy11, as determined by RT-qPCR. Rice ubiquitin gene was used as the internal reference gene. Data represent means± SD (n = 3). Different letters indicate significant differences (one-way ANOVA, p < 0.01). These experiments were repeated three times with similar results.
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Figure 4. Transcriptome comparison of ZH11 and Osark1 in response to M. oryzae treatment. (A) Principal component analysis (PCA) of the time-series transcriptome data from ZH11 and Osark1 samples treated with the M. oryzae Guy11 or mock (H2O) at 24 and 48 hpi. (B) Numbers of genes upregulated and downregulated by M. oryzae in ZH11 or Osark1 compared to the mock treatment. (C) Venn diagram of DEGs induced by M. oryzae in ZH11 and Osark1 compared to mock treatment at 24 hpi and 48 hpi. (D) Heatmap showing the fold change of genes associated with the GO term “defense response” identified in the enrichment analysis shown in (E). (E) GO term enrichment analyses of all DEGs in ZH11 and Osark1 treated with M. oryzae or H2O at 24 hpi.
Figure 4. Transcriptome comparison of ZH11 and Osark1 in response to M. oryzae treatment. (A) Principal component analysis (PCA) of the time-series transcriptome data from ZH11 and Osark1 samples treated with the M. oryzae Guy11 or mock (H2O) at 24 and 48 hpi. (B) Numbers of genes upregulated and downregulated by M. oryzae in ZH11 or Osark1 compared to the mock treatment. (C) Venn diagram of DEGs induced by M. oryzae in ZH11 and Osark1 compared to mock treatment at 24 hpi and 48 hpi. (D) Heatmap showing the fold change of genes associated with the GO term “defense response” identified in the enrichment analysis shown in (E). (E) GO term enrichment analyses of all DEGs in ZH11 and Osark1 treated with M. oryzae or H2O at 24 hpi.
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Table 1. Description of rice genotypes used in this study.
Table 1. Description of rice genotypes used in this study.
Genotype NameTypeGenetic BackgroundDescriptionKey Role in Experiments
ZH11Wild-type (WT)ZH11Oryza sativa ssp. japonica cv. Zhonghua 11 (WT)Served as the control in all experiments (AM colonization, pathogen infection, transcriptome analysis, etc.).
Osark1 #1MutantZH11CRISPR-Cas9 knockout mutant in ZH11 background; T insertion at position 341.Used to assess the loss-of-function phenotypes in AM symbiosis, immune response, and transcriptomic reprogramming.
Osark1 #2MutantZH11CRISPR-Cas9 knockout mutant in ZH11 background; C deletion at poition 342.Served as a biological replicate to confirm the phenotypes observed in Osark1 #1.
Note: # present different lines.
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MDPI and ACS Style

Zheng, Z.; Zou, K.; Lu, G.; Wang, Z.; Cui, H.; Wang, A. A Mycorrhiza-Associated Receptor-like Kinase Regulates Disease Resistance in Rice. Agronomy 2025, 15, 2298. https://doi.org/10.3390/agronomy15102298

AMA Style

Zheng Z, Zou K, Lu G, Wang Z, Cui H, Wang A. A Mycorrhiza-Associated Receptor-like Kinase Regulates Disease Resistance in Rice. Agronomy. 2025; 15(10):2298. https://doi.org/10.3390/agronomy15102298

Chicago/Turabian Style

Zheng, Zichao, Ke Zou, Guodong Lu, Zonghua Wang, Haitao Cui, and Airong Wang. 2025. "A Mycorrhiza-Associated Receptor-like Kinase Regulates Disease Resistance in Rice" Agronomy 15, no. 10: 2298. https://doi.org/10.3390/agronomy15102298

APA Style

Zheng, Z., Zou, K., Lu, G., Wang, Z., Cui, H., & Wang, A. (2025). A Mycorrhiza-Associated Receptor-like Kinase Regulates Disease Resistance in Rice. Agronomy, 15(10), 2298. https://doi.org/10.3390/agronomy15102298

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