Metabolomic Profiling of BPH14/BPH15 Pyramiding Rice and Its Implications for Brown Planthopper Resistance

Abstract

Rice, a vital crop, faces significant threats from the brown planthopper (BPH), which impacts plant growth and yield. Pyramiding the BPH resistance genes BPH14 and BPH15 provides rice crops with reliable and lasting protection against BPH. Nonetheless, current research lacks clarity on the molecular processes responsible for BPH14/BPH15-mediated resistance to BPH. In this study, utilizing high-throughput metabolomics and integrating transcriptomic data, we investigated the metabolic adaptations of the BPH14/BPH15 pyramiding line (B1415) and its recurrent parent (RP) during early and late infestation stages. The analysis identified 1007 metabolites, mainly consisting of lipids and lipid-like molecules, together with phenylpropanoid and polyketide classes. Differentially accumulated metabolites (DAMs) displayed different patterns in B1415 and RP, particularly in flavonoid and phenylpropanoid biosynthesis pathways, which were more pronounced in the resistant B1415. Furthermore, ferulic acid (FA) was found to negatively regulate BPH resistance. These findings elucidate critical metabolic pathways involved in rice defense mechanisms and underscore the potential of B1415’s enhanced metabolic responses in conferring durable resistance against BPH.

1. Introduction

Consumed by approximately 50% of people worldwide, rice (Oryza sativa L.) is regarded as essential for maintaining global food security [1]. Nevertheless, rice production encounters significant challenges from pests, particularly the brown planthopper (Nilaparvata lugens Stal, BPH), which damages rice crops by both drawing phloem sap and spreading pathogenic agents, resulting in stunting, wilting, and substantial yield losses [2]. Since this insect poses a persistent threat to rice crops, resistance mechanisms are integral to sustainable rice production. Such mechanisms include the transcriptional activation of defense genes and the biosynthesis of protective secondary metabolites [3].

The beginning of research into rice’s defense against BPH can be traced to 1969, when the International Rice Research Institute (IRRI) first identified the BPH resistance gene BPH1. Subsequently, seventeen BPH resistance genes, including the pioneering BPH14 and BPH15, have been identified through cloning methods [4]. BPH14 is the first gene discovered to provide BPH resistance; it creates a coiled-coil nucleotide-binding site leucine-rich repeat protein. Upon recognizing a BPH effector, this protein triggers immune responses by inducing defense gene transcription, enhancing salicylic acid (SA) signaling, increasing reactive oxygen species (ROS) accumulation, and promoting callose deposition [5,6,7]. Conversely, BPH15 is a membrane-bound lectin receptor-like kinase that mediates immune signaling by identifying herbivore- or damage-related molecules. It confers resistance against BPH and multiple other pathogens [8].

Pyramiding BPH resistance genes represents an effective strategy for durable, broad-spectrum BPH control [9]. Marker-assisted combination of BPH14 and BPH15 has shown superior resistance in rice [10,11,12]. Wang et al. incorporated both genes into the elite cultivar “Wushansimiao”, producing the BPH14/BPH15 pyramiding line (B1415), which improved BPH resistance without compromising agronomic traits [13]. Although B1415 confers effective resistance, its molecular mechanisms remain largely unclear, warranting further investigation.

Metabolomics enables detailed analysis of rice’s metabolic responses to BPH infestation and elucidates the interactions between rice and BPH [14,15,16,17]. BPH alters metabolite levels, with resistant varieties showing early changes in the shikimate pathway, amino acid metabolism, and gluconeogenesis, suggesting the activation of defense mechanisms such as nucleotide biosynthesis, [14]. Untargeted metabolomics identified herbivory-induced compounds like feruloylputrescine and p-coumaroylputrescine, which increase BPH mortality [15]. GC-MS analysis revealed that the BPH15-containing variety YHY15 activates the shikimate pathway and influences amino acid absorption and urea metabolism [16]. BPH6-mediated resistance in transgenic rice enhances wax and sterol biosynthesis and phytol metabolism in the leaf sheath. These metabolic changes were less pronounced in the susceptible Nipponbare variety during BPH infestation [17]. These findings underscore the significance of metabolic reprogramming in enhancing BPH resistance in rice.

Rice–BPH interactions are effectively analyzed through integrated transcriptomics and metabolomics analyses [18,19,20,21]. These analyses have revealed strong correlations between differentially expressed genes and metabolites (DEGs and DAMs, respectively) in pathways, including flavonoid biosynthesis, phenylpropane biosynthesis, and hormone signaling. Resistant rice enhances BPH resistance by modulating IAA and SA levels, inducing epigallocatechin production, and maintaining higher constitutive lignin content [18]. Furthermore, BPH30-mediated resistance reduces IAA and increases flavonoids, strengthening resistance mechanisms [19]. BPH infestation also triggers GABA shunt activation and shikimate-mediated secondary metabolism across varieties [20]. In resistant Rathu Heenati (RH) and susceptible Taichung Native 1 (TN1) cultivars, rice resistance to BPH resistance is linked to altered starch, sucrose, and galactose metabolism [21]. However, comprehensive integrative analyses of these responses remain limited.

This investigation employed high-throughput metabolomics to elucidate the metabolic responses of B1415 and its recurrent parent (RP) before and after BPH infestation. Integration with previously acquired transcriptomic data showed that B1415 demonstrated more targeted metabolic changes, particularly in flavonoid and phenylpropanoid biosynthesis, supporting its enhanced BPH resistance. Ferulic acid (FA) was observed to act antagonistically in the modulation of rice defense against BPH. Our findings explain the metabolic resistance in BPH14 and BPH15, and inform breeding strategies for improved pest resistance through metabolic and molecular engineering.

2. Materials and Methods

2.1. Experimental Materials

B1415, a pyramided line carrying both BPH14 and BPH15 resistance genes, was developed using “Wushansimiao” as the recurrent parent due to its agronomic advantages, despite its susceptibility to BPH [13]. Rice seedlings were established in plastic pots (15 × 9 cm), with 15–20 seeds sown per pot, and maintained under growth chamber conditions s featuring a 14 h light (32 ± 2 °C)/10 h dark (26 ± 2 °C) cycle. The TN1 cultivar (IRRI Acc. No. 00105), which contains no documented BPH resistance genes, was used as the host for maintaining BPH insects under the same conditions as rice seedlings [22]. Experimental conditions mirrored those described in our previous RNA-seq study [23].

2.2. BPH Infestation and Sample Collection

Four-leaf stage seedlings of B1415 and RP received eight 3rd instar BPH nymphs per seedling at 0, 3, 6, 12, 24, 48, and 72 h. For each treatment, there were three biological replicates that contained about fifteen seedlings each. Following an end-point sampling strategy [24], the treatments were initiated at different time points but concluded simultaneously. We classified leaf sheath samples based on their infestation stages into three groups, onset (0 h), early infestation (3, 6, 12 h), and late infestation (24, 48, 72 h), following established methodology [23]. These samples were designated as B1415_0, B1415_early, B1415_late, RP_0, RP_early, and RP_late, respectively. We immediately placed all obtained samples into liquid nitrogen before storing them at −80 °C pending analyses.

2.3. Metabolites Extraction and Liquid Chromatography–Tandem Mass Spectrometry (LC–MS/MS) Analysis

The collected leaf sheaths (80 mg per sample) were cryogenically frozen and pulverized to a powdery form with a mortar and pestle. The powdered tissue was mixed with 1 mL of a solvent blend comprising methanol, acetonitrile, and water in a 2:2:1 volume ratio. The homogenized mixture received centrifugation (14,000× g, 4 °C, 20 min). Subsequently, the liquid phase was concentrated to dryness under vacuum. After reconstitution in 100 μL acetonitrile: water (1:1), the samples were centrifuged (14,000× g, 4 °C, 15 min) and the upper phase was used for LC–MS/MS injection.

Metabolite detection was implemented by use of a non-targeted metabolomics approach employing LC–MS/MS at Personal Biotechnology Co., Ltd. (Shanghai, China). The analytical platform included an Agilent 1290 Infinity UHPLC system (Agilent Technologies, Waldbronn, Germany) connected to an AB Sciex TripleTOF 6600 quadrupole time-of-flight mass spectrometer (AB Sciex, Framingham, MA, USA). Metabolites were separated on a BEH Amide column (ACQUITY UPLC, Waters, Wexford, Ireland; 2.1 mm × 100 mm, 1.7 µm) operated under HILIC mode. A mixture of acetonitrile (solvent B) and a water solution of ammonium acetate/ammonium hydroxide (25 mM each, solvent A) was applied as the mobile phase system. The gradient began with 95% B for 0.5 min, transitioned to 65% at 6.5 min, to 40% at 7.5 min, held for 1 min, ramped back to 95% at 7.6 min, and equilibrated for an additional 3 min.

The system operated using electrospray ionization (ESI) in dual polarity (positive and negative). Source gases (Gas1 and Gas2) were maintained at 60 psi, with Curtain Gas at 30 psi, and the spray was generated at 600 °C with a floating voltage of ±5500 V. A scan range from m/z 60 to 1000 was used in MS mode, with each spectrum recorded over 0.20 s. Spectra in auto MS/MS mode were recorded using information-dependent acquisition (IDA) within the m/z range of 25–1000 Da, with 0.05 s per scan, 35 V collision energy with a ±15 eV spread, and ±60 V for declustering. The IDA protocol allowed selection of no more than ten candidate ions per cycle, with isotopes excluded within 4 Da.

2.4. Metabolite Data Processing and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Analyses

The raw MS data were converted to the LC–MS/MS files using ProteoWizard software (V3.0.8789) to mzXML format for subsequent processing with R package (version 3.3.2). The files were imported into R/Wilcox.test/t.test (V4.0.3) for principal component analysis (PCA). Metabolite annotation and identification were based on the Human Metabolome Database (HMDB) (http://www.hmdb.ca, accessed on 2 November 2020), Metlin (https://metlin.scripps.edu, accessed on 2 November 2020), Massbank (http://www.massbank.jp/, accessed on 2 November 2020), mzCloud (https://www.mzcloud.org, accessed on 4 December 2023), and a proprietary standards database at Personal Biotechnology Co., Ltd. (Shanghai, China). Metabolites were designated as DAMs when they showed statistically significant differences (p < 0.05), |log2 (Fold Change)| > 1 and variable importance in projection (VIP) > 1. KEGG (http://www.genome.jp/kegg, accessed on 8 December 2021), MetaboAnalyst (http://www.metaboanalyst.ca, accessed on 8 December 2021), and HMDB were referenced for comprehensive assessment of metabolite functions as well as metabolic and transcriptomic pathways. The significance of KEGG pathway involvement was determined via the Fisher’s exact test [25].

2.5. Integrating Transcriptome and Metabolome Analysis

Initially, DEGs and DAMs were extracted from previously published RNA sequencing data [23] and the metabolome results in this study, respectively. Subsequently, the corresponding transcripts of related enzymes were identified based on metabolic information from the KEGG database. Finally, the DEGs and associated DAMs were assigned to relevant metabolic pathways.

2.6. RNA Isolation and Gene Expression Assessment

Leaf sheaths experienced total RNA extraction by use of TRIzol reagent (Invitrogen, Waltham, MA, USA) to generate first-strand cDNA with a PrimeScript RT Reagent Kit containing gDNA Eraser (RR047A, TaKaRa, Shiga, Japan), as per the manufacturer’s protocol. Expression profiling through quantitative RT-PCR (qRT-PCR) utilized primers (Supplementary Table S1). SYBR Green Real-Time PCR Master Mix (QPK-201, Toyobo, Osaka, Japan) was used for PCR on a CFX96 real-time system (Bio-Rad, Hercules, CA, USA). Then, we used TBP as their reference gene for relative gene expression quantification [26].

2.7. FA Content Measurement

The protocol for leaf sheath sample collection matches the description from Section 2.2. Sample tissues were flash-frozen and subsequently pulverized using liquid nitrogen cooling. A 1.5 mL EP tube, pre-equilibrated at low temperature, was loaded with 50 mg of sample powder and treated with 500 µL of cold methanol/water solution (70%, v/v). The mixture received thorough vortexing before incubation at 4 °C overnight. Following incubation, high-speed centrifugation (14,000× g, 4 °C, 20 min) was performed. The supernatant (400 µL) was passed through a 0.22 µm nylon filter for particulate removal. FA detection was conducted by injecting the filtered extract into a mass spectrometer. LC–MS/MS analysis involved using an ExionLC system (AB Sciex, Framingham, MA, USA) coupled with a Qtrap 5500+ mass spectrometer (AB Sciex). Experimental separation occurred through a chromatographic system equipped with an Acquity Premier HSS T3 column, which had dimensions of 2.1 mm × 100 mm with 1.8 µm particle size (Waters, Milford, MA, USA). Metabolite standards for FA (Yuanye, catalog no. B20007, Shanghai, China) were diluted to prepare the standard curve. FA identification and quantification were based on matching the chromatographic retention times and peak areas with those of the pure standard.

2.8. BPH Resistance Evaluation of Rice

We employed the evaluation approach to BPH resistance in rice as previously described [6]. Fifteen to twenty seeds of RP or B1415 with uniform germination were sown in plastic pots (height × width = 15 cm × 9 cm). The experimental plot consisted of approximately 15 carefully selected seedlings with uniform growth at the four-leaf stage, which received infestation from eight third-instar BPH nymphs per seedling. We examined the plants after the entire treatment control seedlings died or when the experimental materials exhibited signs of damage. A scoring system (0, 1, 3, 5, 7, or 9) was used to measure insect resistance in the seedlings, where lower scores indicated superior resistance [6].

2.9. BPH Honeydew Excretion and Weight Gain Measurements

Established techniques were adopted for assessing honeydew production and weight increase in BPH [6]. Pre-weighed parafilm sachets were utilized to contain pre-weighed third-instar BPH nymphs, which had been subjected to a 2 h starvation period. These sachets were then securely attached to the leaf sheathes of B1415 and RP plants at the five-leaf stage. Following a 2-day feeding period, insects were extracted from the sachets, which were removed from the tested plants. We conducted another weighing process for both insects and sachets. The difference between the two weight measurements of parafilm sachets and insects determined the quantity of BPH honeydew excretion and insect weight increase.

2.10. FA Treatments

For the FA treatment, pots (15 cm tall and 9 cm wide, containing 800 g fresh soil as described above) were treated with FA (Aladdin, catalog no. F103701, Shanghai, China) at concentrations of 0 (control, treated with an equivalent volume of ultrapure water), 0.01, 0.02, and 0.04 μmol/g soil. FA solution or ultrapure water (10 mL per application) was administered to the soil via a syringe every two days for a total of eight applications, until the rice reached its fourth-leaf stage (for BPH resistance evaluation) or five-leaf stage (for BPH honeydew excretion and weight gain measurements). Following a 24 h period, BPH was introduced to the seedlings as described previously, with minor modifications [27].

2.11. Statistical Analyses and Reproducibility

All experiments were conducted in triplicate, yielding consistent results. Statistical analysis was performed using Student’s t-test with significance defined as p < 0.05.

3. Results

3.1. Summary of Rice Metabolome Profiling in Response to BPH Feeding

We assessed metabolite extraction on leaf sheaths from resistant B1415 and susceptible RP plants at three stages, pre-infestation, early infestation, and late infestation, as previously characterized for BPH resistance [23]. The extracts were analyzed using LC–MS/MS. PCA revealed clear differentiation among all groups, with the three biological repeats in each group clustering together, validating the data’s reliability for subsequent analyses (Figure 1A). The analysis identified 1007 metabolites, of which 863 were classified into 12 categories, while 144 remained unclassified (Supplementary Table S2 and Figure 1B). The high abundance of lipids and phenylpropanoids suggests their involvement in rice’s metabolic response to BPH infestation (Figure 1B).

3.2. Metabolomic Analysis of DAMs in B1415 and RP During BPH Infestation

We identified 527 DAMs across all comparisons, comprising 349 DAMs between varieties (B1415_0/RP_0, B1415_early/RP_early, and B1415_late/RP_late) and 422 DAMs across infestation stages (RP_early/RP_0, RP_late/RP_0, B1415_early/B1415_0, and B1415_late/B1415_0), using |log₂ (Fold Change)| > 1, VIP > 1 and p < 0.05 as the filtering criteria (Figure 2 and Supplementary Table S3). Specifically, the analysis revealed 229 DAMs in B1415_0/RP_0, 159 DAMs in B1415_early/RP_early, 132 DAMs in B1415_late/RP_late, 126 DAMs in RP_early/RP_0, 262 DAMs in RP_late/RP_0, 71 DAMs in B1415_early/B1415_0, and 224 DAMs in B1415_late/B1415_0 (Figure 2A). The findings demonstrate that BPH infestation triggers DAMs in both varieties, with distinct regulatory patterns observed at different stages (Figure 2A). The classification of DAMs closely mirrored the overall metabolite composition, suggesting that BPH-induced changes primarily occurred within dominant categories, consistent with the pattern observed in Figure 1B (Figure 2B).

3.3. Identification of DAMs Associated with BPH Resistance Before and After BPH Infestation

To investigate how DAMs affect BPH resistance, a KEGG functional analysis comparing metabolic profiles of B1415 and RP was implemented at three stages: before infestation (B1415_0/RP_0), early stage (B1415_early/RP_early), and late stage (B1415_late/RP_late). Prior to BPH infestation, significantly enriched pathways among DAMs in the B1415_0/RP_0 group included aminoacyl-tRNA biosynthesis, ABC transporters, and D-amino acid metabolism pathways (Figure 3A; Supplementary Table S4). Following infestation, DAMs in the B1415_early/RP_early and B1415_late/RP_late groups were predominantly associated with flavone and flavonol biosynthesis, flavonoid biosynthesis, and aminoacyl-tRNA biosynthesis (Figure 3B,C, Supplementary Tables S5 and S6). These findings indicate significant alterations in primary and secondary metabolic pathways before and after BPH infestation, reflecting dynamic metabolic responses to BPH stress.

To further elucidate these metabolic changes, we constructed Venn diagrams to identify unique and shared DAMs between B1415 and RP. Analysis of the B1415_0/RP_0 group revealed 229 DAMs, with 143 of these being unique, far exceeding the 159 DAMs (43 unique) in the B1415_early/RP_early group and the 132 DAMs (37 unique) in the B1415_late/RP_late group (Figure 3D). The data imply that the regulation and accumulation of these metabolites prior to infestation play a crucial role in enhancing rice resistance, potentially conferring B1415 a defensive advantage before BPH attacks. After BPH infestation, an additional 120 DAMs were identified, with 40 overlapping between B1415_early/RP_early (83 DAMs) and B1415_late/RP_late (77 DAMs). The comparable number of DAMs observed in early and late infestation phases suggested their involvement in both rapid (early) and sustained (late) defense responses against BPH invasion (Figure 3D). Across all comparisons, 349 DAMs were identified and categorized into 11 classes, listed from most to least abundant: lipids (87), phenylpropanoids and polyketides (80), organoheterocyclic compounds (30), organic acids and derivatives (29), organic oxygen compounds (25), benzenoids (21), alkaloids (14), nucleosides (9), organic nitrogen compounds (8), lignans/neolignans (3), and hydrocarbons (1) (Supplementary Table S7). Additionally, 42 DAMs remained unclassified. The dominance of lipids and phenylpropanoids suggests they are central to rice defense against BPH (Supplementary Table S7). Further analysis identified 14 candidate DAMs from these two dominant metabolite classes that exhibited opposite expression patterns before and after BPH infestation, suggesting that they are potential contributors to BPH resistance, pending further experimental verification (Figure 3E). These metabolites have been previously linked to resistance against pathogens and herbivores [28,29,30,31,32,33,34,35,36,37,38,39,40,41]. Notably, in the pre-infestation stage (B1415_0/RP_0), most DAMs were upregulated in B1415, while post-infestation (B1415_early/RP_early and B1415_late/RP_late), more DAMs were downregulated in B1415. These findings imply a possible association of lipid-derived signaling molecules and phenylpropanoid-derived secondary metabolites with basal and inducible responses to BPH, warranting functional validation.

3.4. Identification of DAMs Associated with BPH Resistance in Early and Late Infestation Stages

The KEGG enrichment analysis helped us understand the roles of DAMs identified in RP and B1415 plants following BPH infestation. The arginine biosynthesis along with histidine metabolism and aminoacyl-tRNA biosynthesis pathways showed significant enrichment among DAMs from the early feeding stage (RP_early/RP_0 comparison) (Figure 4A and Supplementary Table S8). In RP, late-stage DAMs were enriched in flavone/flavonol, flavonoid, and aminoacyl-tRNA biosynthesis (Figure 4B and Supplementary Table S9). In B1415, early-stage DAMs were enriched in histidine metabolism, flavone/flavonol, and phenylpropanoid biosynthesis (Figure 4C and Supplementary Table S10), while late-stage DAMs showed enrichment in flavonoid, flavone/flavonol biosynthesis, and pyrimidine metabolism (Figure 4D and Supplementary Table S11). This pattern reflects a more robust secondary metabolic adjustment in B1415 than in RP, particularly involving flavonoid and phenylpropanoid biosynthesis.

To examine DAMs associated with BPH resistance, we utilized Venn diagrams to compare DAMs before and after BPH infestation (RP_early/RP_0, RP_late/RP_0, B1415_early/B1415_0, and B1415_late/B1415_0) (Figure 4E and Supplementary Table S12). During the early infestation stage, B1415_early/B1415_0 displayed notably fewer DAMs (71) compared to RP_early/RP_0 (126), with only 16 DAMs shared between the two groups (Figure 4E). This suggests that B1415 may employ a more focused or efficient metabolic adjustment in the initial stages of infestation. In the late infestation stage, although the number of DAMs in B1415_late/B1415_0 (224) and RP_late/RP_0 (262) was similar, their composition differed, with only 124 shared DAMs. This indicates distinct metabolic strategies for responding to prolonged infestation in B1415 and RP (Figure 4E). A comparison of early and late infestation stages within the same plant revealed that B1415_early/B1415_0 had significantly fewer DAMs (71), approximately one-third of those identified in B1415_late/B1415_0 (224), with only 35 DAMs overlapping. This indicates a dynamic and stage-specific metabolic response in B1415. Conversely, RP_early/RP_0 exhibited fewer DAMs (126) than RP_late/RP_0 (262), with 76 DAMs shared between the two stages. This suggests that while RP demonstrates an increase in DAMs over time, the overlap indicates a more gradual or less distinct shift in its metabolic response from early to late infestation stages compared to B1415 (Figure 4E). A total of 422 DAMs were identified across the stages (RP_early/RP_0, RP_late/RP_0, B1415_early/B1415_0, and B1415_late/B1415_0). To further investigate the metabolic changes associated with BPH resistance at different infestation stages, these DAMs were classified into 10 groups, listed in descending order of abundance: lipids and lipid-like molecules (113 DAMs), phenylpropanoids and polyketides (78 DAMs), organoheterocyclic compounds (49 DAMs), organic oxygen compounds (35 DAMs), benzenoids (27 DAMs), organic acids and derivatives (25 DAMs), nucleosides, nucleotides, and analogs (16 DAMs), alkaloids and derivatives (10 DAMs), lignans, neolignans, and related compounds (8 DAMs), and organic nitrogen compounds (8 DAMs). Additionally, 53 DAMs were not classified into any of these groups (Supplementary Table S12). Notably, 16 candidate DAMs from these two classes exhibited contrasting expression profiles in B1415 and RP plants under BPH stress and were identified as candidate metabolites associated with BPH resistance (Figure 4F). These metabolites have previously been linked to resistance against pathogens and herbivores [28,29,31,32,33,35,42,43,44,45,46,47,48,49,50,51].

3.5. Joint Transcriptomic and Metabolomic Insights into BPH Resistance Mechanisms

An integrated study of rice regulatory networks in response to BPH infestation was performed through transcriptomic and metabolomic investigations of RP and B1415 plants. KEGG pathway enrichment analysis was applied to DEGs and DAMs across four comparison groups: RP_early/RP_0, RP_late/RP_0, B1415_early/B1415_0, and B1415_late/B1415_0.

The RP_early/RP_0 group showed marked enrichment in cutin, suberine, and wax biosynthetic processes, as well as amino acid metabolism involving alanine, aspartate, glutamate, and histidine. Moreover, early enrichment of unsaturated fatty acid biosynthesis was observed, alongside enrichment of ABC transporters. In the RP_late/RP_0 group, metabolic reprogramming became more extensive. The rice recovery phase was further supported by enrichment in metabolic processes involving amino sugars and nucleotide sugars. Pathways associated with defense, such as phenylpropanoid biosynthesis and flavonoid biosynthesis, were also enriched at this stage. In contrast to RP, B1415 demonstrated a more focused defense response during early infestation, with pathway enrichment primarily in phenylpropanoid biosynthesis, indicating efficient resource allocation toward defense rather than generalized stress adaptation. During prolonged infestation, B1415 maintained sustained enrichment of phenylpropanoid and flavonoid biosynthesis, reinforcing structural defenses and defense compound production. Pathways supporting recovery, including pyrimidine and amino sugar/nucleotide sugar metabolism, were simultaneously activated. These coordinated responses indicated B1415’s superior capacity to prioritize defense-related metabolic adjustments over general stress adaptation (Figure 5A).

As previously described, the phenylpropanoid biosynthesis and flavonoid biosynthesis pathways demonstrate earlier enrichment and longer persistence in the resistant B1415 line, indicating their crucial roles in conferring resistance to BPH infestation. Given prior analyses suggesting xanthohumol’s involvement in flavonoid biosynthesis and its potential contribution to enhancing basal resistance (Figure 3E, Supplementary Table S7), this study specifically examines the role of FA, which is involved in phenylpropanoid biosynthesis, in BPH14/BPH15-mediated resistance. Phenylalanine transforms into cinnamic acid through phenylalanine ammonia-lyase (PAL) in the phenylpropanoid metabolism pathway). Both RP and B1415 exhibited upregulation of PAL genes (OsPAL1, Os02g0626100, and OsPAL3, Os02g0626600), with B1415 displaying stronger and more balanced expression (Figure 5B). This supports enhanced flux into phenylpropanoid-derived pathways, which is critical for BPH resistance. Subsequently, cinnamic acid was transformed into p-cinnamic acid through cinnamic acid 4-hydroxylase (C4H). The enzyme p-coumarate 3-hydroxylase used p-cinnamic acid to generate caffeic acid. Finally, caffeic acid is converted into FA by caffeic acid O-methyltransferase. Suppression of C4H gene (OsC4H2, Os05g0320700) and COMT gene (OsCOMT, Os08g0157500) aligns with reduced FA accumulation, particularly in late stages, in both RP and B1415 groups, suggesting a key role in limiting precursor supply (Figure 5B). Moreover, the enzyme FA 5-hydroxylase (F5H) shows increased activity in both lines due to its elevated expression level, especially in the late stage of the B1415 group. This enzyme converts FA to 5-hydroxyferulic acid, which serves as an essential intermediate in lignin biosynthesis. This upregulation likely contributes to the observed decrease in FA levels by promoting its rapid conversion into downstream compounds. These findings suggest that elevated F5H gene (OsF5HL, Os06g0349700) expression may drive a metabolic shift, redirecting FA toward lignin biosynthesis or other defense-related pathways, particularly in resistant B1415 (Figure 5B). The variation in gene expression was confirmed by qRT-PCR, and the results corroborate our transcriptomic sequencing data (Figure 5C).

3.6. FA Negatively Modulated BPH Resistance in Rice

The aforementioned integrated analyses suggested that FA, involved in phenylpropanoid biosynthesis, exerted negative effects on BPH resistance in rice. A quantitative assessment of FA content in B1415 and RP plants was implemented at various feeding stages to determine its influence on rice defense against BPH (Figure 6A). FA content exhibited a decreasing trend throughout BPH infestation in both lines. In B1415, FA levels declined progressively from pre-infestation to the early feeding stage and continued to decrease at the late feeding stage. A similar pattern was observed in RP (Figure 6A). These findings suggest that FA content is reduced in response to BPH feeding, potentially playing a negative role in its resistance mechanism. We verified our hypothesis by adding exogenous FA to B1415 seedlings to elucidate how this compound affects the BPH resistance triggered by BPH14 and BPH15. After 14 days of BPH feeding, B1415 plants treated with increasing concentrations of FA showed greater susceptibility, with average damage scores of 4.6, 5.1, and 6.8, respectively, compared to 3.8 in untreated plants (Figure 6B,C). BPH feeding on FA-treated plants exhibited significantly higher weight gain and honeydew production (Figure 6D,E). qRT-PCR analysis revealed that FA treatment significantly downregulated BPH14 and BPH15 expressions in B1415, indicating that FA may interfere with key resistance signaling pathways mediated by these genes (Figure 6F,G). Similar results were observed in RP plants. After five days of BPH feeding, FA-treated RP plants had higher damage scores (6.0, 7.4, and 8.2, respectively) than controls (4.5) (Supplementary Figure S1A,B), and BPHs on these plants gained more weight and produced more honeydew (Supplementary Figure S1C,D). These observations unveil that FA helps BPH attack rice by negatively regulating the plant’s defense.

4. Discussion

Metabolites are critical in rice defense against BPH stress [18,19], yet the defense mechanisms in BPH14/BPH15 pyramiding lines, such as B1415, remains insufficiently characterized. This study utilized high-throughput metabolomics, integrated with transcriptomic data, to investigate the metabolic responses of B1415 and its RP pre- and post-BPH infestation. This analysis offers a comprehensive understanding of B1415’s resistance to BPH attacks and implicates FA as a potential negative modulator of BPH defense, pending functional validation.

The reliability of the metabolomics data is validated through PCA, which distinctly differentiates between the experimental groups (Figure 1A). This clear separation in the PCA plot underscores the robustness and quality of the data, ensuring the accuracy of subsequent analyses. To ensure consistency in cross-omics comparisons, both metabolomic and transcriptomic datasets were generated using the same rice lines (B1415 and RP), subjected to identical BPH treatments, and grown under uniform greenhouse conditions. Sampling time points and tissue types were precisely matched. Although the transcriptomic data were obtained in a previous experiment, their integration with current metabolomic profiles offers valuable, albeit exploratory, insights into BPH-induced defense responses. Further studies involving simultaneous multi-omics sampling and expanded biological replicates would be valuable to validate these findings. While triplicate experiments confirmed data reliability, validation across diverse cultivars and environments is necessary to assess the generalizability of these resistance-associated metabolic traits for breeding applications. This study identified a total of 1007 metabolites, with lipids and phenylpropanoids as the most abundant classes (Figure 1B and Supplementary Table S2). These metabolites likely play a role in preventing BPH infestation [17,18].

The metabolomic analysis identified 527 DAMs across various comparisons, revealing distinct metabolic responses between B1415 and RP, as well as dynamic changes across different infestation stages (Figure 2A and Supplementary Table S3). Among the 349 DAMs detected between the two varieties, 229 DAMs were present before BPH infestation (B1415_0/RP_0), which is significantly higher than the number detected after infestation (159 DAMs in B1415_early/RP_early and 132 DAMs in B1415_late/RP_late) (Figure 2A and Supplementary Table S4). This metabolic divergence suggests that B1415 engages in constitutive metabolic reprogramming, reflecting a basal defense strategy that may enhance its resistance to BPH. For the 422 DAMs identified across different infestation stages, the number of DAMs in RP consistently exceeded that in B1415, with 126 DAMs in RP_early/RP_0 versus 71 DAMs in B1415_early/B1415_0, and 262 DAMs in RP_late/RP_0 versus 224 DAMs in B1415_late/B1415_0, respectively (Figure 2A). These data suggest that BPH infestation causes greater metabolic disruption and physiological damage in RP. Conversely, the relatively lower number of DAMs in B1415 implies that its metabolic homeostasis was less disrupted, likely due to its stronger BPH resistance level.

KEGG enrichment analysis of DAMs in B1415 and RP, prior to and following BPH infestation, revealed the functional pathways associated with metabolic shifts. Prior to infestation, DAMs were primarily enriched in aminoacyl-tRNA biosynthesis, ABC transporters, and D-amino acid metabolism pathways. Aminoacyl-tRNA biosynthesis likely enhances translational efficiency under stress conditions, and ABC transporters are crucial for detoxifying xenobiotics and transporting defense-related secondary metabolites. Additionally, D-amino acid metabolism has been linked to antimicrobial activities, suggesting a potential role in enhancing plant defense responses against biotic stress [52,53,54]. These findings suggest that a defensive condition in B1415 is likely maintained through the pre-infestation activation of primary metabolic pathways (Figure 3A and Supplementary Table S4). In contrast, after BPH infestation, enriched pathways in the B1415_early/RP_early and B1415_late/RP_late comparison included flavone/flavonol biosynthesis, flavonoid biosynthesis, and aminoacyl-tRNA biosynthesis (Figure 3B,C, Supplementary Tables S5 and S6). Flavonoids are pivotal for BPH resistance owing to its regulation on the OsmiR396-OsGRF8-OsF3H pathway, which enhances its accumulation and strengthens plant defense against herbivory [55]. This metabolic shift implies the recruitment of secondary pathways for plant defense under herbivory, although further functional analyses are needed to substantiate this conclusion. Venn diagram analysis further highlighted the dynamic nature of these metabolic responses. A greater number of unique DAMs were observed before infestation (143 unique DAMs in B1415_0/RP_0) compared to after infestation (43 unique DAMs in B1415_early/RP_early and 37 unique DAMs in B1415_late/RP_late) (Figure 3D and Supplementary Table S7). This suggests that B1415 possesses a pre-existing metabolite profile that confers a defensive advantage, while post-infestation responses involve a more conserved set of metabolic changes. The similar DAM numbers in early and late stages indicate that both rapid and long-term metabolic responses support BPH resistance in B1415. A total of 87 and 80 DAMs were classified under lipids and lipid-like molecules and phenylpropanoids and polyketides, respectively, making them the most enriched classes (Supplementary Table S7). Additionally, 14 candidate DAMs from these categories exhibited opposing expression patterns before and after BPH feeding. These metabolites, previously associated with biotic stress responses in plants, may be involved in herbivore-induced defense mechanisms. (Figure 3E). For the lipids and lipid-like molecules category, pseudojervine is a jerveratrum-type steroidal alkaloid known for its broad-spectrum antifungal activity [28]. Costunolide, a sesquiterpene lactone, also shows promising antifungal properties [29]. Ecdysterone serves as a key hormone for growth regulation while protecting plant species through its insect-molting hormone characteristics [30]. The above three metabolites are all relatively highly expressed in B1415 than in RP before BPH feeding, likely helping the plant maintain a state of preemptive defense against pest attack. Tretinoin, a vitamin A derivative, has been shown to induce an inflammatory, interferon-associated tumor microenvironment, enhancing immune responses [31]. Similarly, echinocystic acid boosts plant resistance to potato spindle tuber viroid (PSTVd) in tomatoes. It was upregulated in response to PSTVd infection, helping to reduce disease symptoms [32]. Both metabolites were highly expressed in B1415 before infestation, but significantly downregulated during early feeding, suggesting a role in modulating immune responses and maintaining an optimal defense state. Betulinic acid was initially more abundant in RP, but its levels declined in RP while increasing in B1415 during early infestation. By late infestation, B1415 maintained higher betulinic acid accumulation, suggesting a role in modulating immune responses and secondary metabolism to counter BPH stress [33]. For the phenylpropanoids and polyketides category, xanthohumol, known for broad antiviral activity, was upregulated in B1415 before and during early BPH infestation, suggesting a defensive role [34]. Delphinidin-3-O-glucoside exhibits strong antioxidant activity, and its significant reduction after BPH infestation in B1415 suggests its potential role in mitigating oxidative stress during defense responses against herbivory [35]. Bergaptol, a naturally occurring furanocoumarin with anti-inflammatory and antimicrobial properties, exhibits higher expression in B1415 than in RP pre- and post-BPH infestation, suggesting its potential role in modulating plant defense responses against BPH in B1415 [36]. Isoimperatorin, a furanocoumarin with anti-inflammatory and antibacterial properties, is highly expressed in B1415 versus RP before BPH infestation, suggesting its potential involvement in enhancing plant defense mechanisms against BPH [37]. The formononetin derivative demonstrates significant antibacterial activity against Xanthomonas oryzae pv. oryzae (Xoo) and can activate the defense enzymes of host plants, thereby enhancing their disease resistance [38]. In B1415, the expression of formononetin is relatively higher than in RP, from the pre-infestation stage to the early infestation stage, suggesting a possible implication in the defense mechanism against BPH feeding. In contrast, the expression of psoralidin in B1415 remains relatively higher than in RP, from pre-infestation stage to the early stages, with a notable decrease in late stages. This pattern suggests that psoralidin functions in BPH response, aligning with its known antibacterial and anti-inflammatory capabilities, as well as its ability to control various cell signaling pathways and molecular mechanisms [39]. Scopoletin, a natural coumarin with antifungal properties, enhances resistance to pathogens such as Verticillium dahliae through its accumulation in cotton [40]. In B1415, scopoletin expression remains relatively higher than in RP at the early infestation stages, suggesting its role in enhancing resistance to BPH infestation. Procyanidin B2, known for its strong antioxidant capacity [41], shows dynamic regulation in B1415 in response to BPH infestation. Prior to BPH feeding, its expression is relatively downregulated, helping maintain oxidative stress levels for defense. At the early stages of infestation, its expression increases to mitigate oxidative stress and preserve physiological health. Later, its expression returns to a downregulated state, supporting the continued balance of oxidative stress for effective defense against BPH.

In B1415 and RP rice plants, KEGG pathway analysis of DAMs revealed distinct metabolic adjustments at early and late infestation stages. In RP, early infestation induced enrichment in arginine biosynthesis, histidine metabolism, and aminoacyl-tRNA biosynthesis (Figure 4A and Supplementary Table S8). These pathways suggest a general stress response where amino acid metabolism may play a role in maintaining protein synthesis and metabolic homeostasis during the initial phase of BPH attack, consistent with previous studies [18,19]. The increase in flavonoid-related pathways during the late infestation stage in RP indicates a delayed shift from primary to specialized secondary metabolism as part of the defense response (Figure 4B and Supplementary Table S9) [55]. In contrast, B1415 exhibited early enrichment in flavonoid biosynthesis, phenylpropanoid biosynthesis, and histidine metabolism (Figure 4C and Supplementary Table S10). The above data underscore B1415’s ability to employ specialized defense pathways early on, potentially providing a preemptive defense response against BPH feeding. The upregulation of flavonoids and phenylpropanoids, known for their role in rice against BPH [18,55], further suggests that B1415 can initiate a more effective, early-stage defense response. The metabolic shift observed in B1415 during the late infestation stage reinforces this view, with sustained enrichment in flavonoid biosynthesis and phenylpropanoids, alongside additional involvement of pyrimidine metabolism, which may contribute to broader immune responses (Figure 4D and Supplementary Table S11) [56]. Venn diagram analysis unveiled that the number of DAMs in B1415 was notably lower during early infestation (71 DAMs from B1415_early/B1415_0) compared to RP (126 DAMs from RP_early/RP_0), suggesting that B1415’s response is more efficient and targeted. This difference could imply a selective metabolic adjustment that minimizes unnecessary metabolic shifts, focusing resources on specific defense-related metabolites. In the late infestation stage, DAM numbers were similar (224 in B1415 vs. 262 in RP), but only 124 were shared, highlighting distinct metabolic strategies for responding to prolonged infestation. This finding suggests that B1415 may rely on a more focused and sophisticated metabolic strategy, while RP shows a broader, less refined adjustment over time (Figure 4E and Supplementary Table S12). Within each variety, B1415 showed a stage-specific response, with only 35 DAMs shared between early and late stages, while RP had 76 DAMs shared between stages. These findings suggest that B1415’s stage-specific metabolic adjustments may enhance its BPH resistance, while RP relies on a broader, less refined defense strategy (Figure 4E and Supplementary Table S12). DAMs across all infestation stages were most enriched in lipids and phenylpropanoids, consistent with inter-varietal comparisons (Supplementary Tables S7 and S12). Several candidate DAMs, including delphinidin-3-O-glucoside chloride, pseudojervine, costunolide, tretinoin, echinocystic acid, and betulinic acid, were identified in both comparison approaches (Figure 3E and Figure 4F). These compounds are known for their defense-related functions, such as antimicrobial properties, immune modulation, and stress regulation [28,29,31,32,33,35]. Their consistent identification further supports their potential significance in BPH resistance mechanisms. For the rest of the candidates in the lipids and lipid-like molecules category, stevia and echinenone have both demonstrated significant antibacterial and antioxidant properties [42,43]. In RP, steviol (a diterpene compound derived from stevia) and echinenone were upregulated throughout the BPH infestation, suggesting their role in enhancing resistance through antibacterial and antioxidant activities. In contrast, B1415 showed downregulation of these metabolites, indicating a more controlled defense response, where excessive accumulation may be unnecessary. Notoginsenoside R1 (NGR1) has been shown to exert protective effects in various ischemic conditions by attenuating oxidative stress and inflammation while stimulating angiogenesis [44]. Cholic acid, a primary bile acid, has been recognized for its potential bioactivity, and its conjugation with thiadiazole has shown promising antibacterial and antioxidant effects in recent studies [45]. Unlike steviol and echinenone, NGR1 and cholic acid displayed a notable elevation at the late stages of BPH infestation in t RP, whereas in B1415, its expression was mildly downregulated, suggesting that while NGR1 and cholic acid may help susceptible varieties resist BPH, its role is less critical in resistant varieties with other defense mechanisms. Trans-fatty acids, including trans-vaccenic acid, have been found to promote inflammatory responses and cell death, which can serve as a defense mechanism against stress or pathogen attack [46]. Similarly, glyceryl monooleate contributes to enhancing the antimicrobial efficacy of antimicrobial peptides [47]. In RP, both trans-vaccenic acid and glyceryl monooleate were significantly downregulated at both early and late stages of BPH infestation, suggesting a potential reduction in the plant’s defense response, possibly induced by effectors or other compounds released by BPH. In contrast, the mild upregulation observed in B1415 indicates a more balanced defense response, which may contribute to resistance by supporting controlled antimicrobial activity against BPH-induced stress. For the rest of the candidates in the phenylpropanoids and polyketides category, sinapine and kuwanon H have demonstrated notable antimicrobial and antioxidant properties in previous studies [48,49]. In our research, both sinapine and kuwanon H were upregulated in RP at the late infestation stage, implying a delayed and potentially compensatory defense response. In contrast, these compounds were downregulated in B1415, indicating a more controlled defense response, possibly avoiding excessive accumulation of antimicrobial compounds due to the presence of more efficient mechanisms to combat BPH. Primulin, a noncompetitive inhibitor for Neurospora crassa chitin synthetase activity [50], was significantly elevated at the late infestation stage in RP while exhibiting a slight downregulation in B1415. Given chitin’s structural role in insect exoskeletons, this contrasting trend suggests divergent primulin-associated defense pathways between the two lines. Sappanone A dimethyl ether, a derivative with known antioxidant and anti-inflammatory capabilities [51], was downregulated in RP during early infestation and only slightly reduced later, whereas it showed minimal change in B1415. Its early-stage downregulation in RP may indicate a compromised ability to regulate oxidative stress response, potentially weakening the plant’s defense against BPH. In contrast, the absence of significant changes in B1415 suggests a more stable or rapidly compensatory regulatory mechanism in the resistant line, which may help sustain effective defense responses throughout the infestation period.

To clarify the roles of DAMs in BPH resistance, we grouped them into three interconnected modules: antimicrobial defense, oxidative stress regulation, and hormonal or immune modulation. In B1415, DAMs, such as pseudojervine [28], costunolide [29], bergaptol [36], Isoimperatorin [37], formononetin [38], psoralidin [39], glyceryl monooleate [47], and kuwanon H [48] possess documented antimicrobial or antifungal activities, likely limiting pathogen invasion after BPH feeding. Antioxidant DAMs, including delphinidin-3-O-glucoside [35], procyanidin B2 [41], echinenone [43], NGR1 [44], and sappanone A [51] are likely involved in regulating ROS to maintain cellular redox balance and avoid oxidative damage during defense activation. Notably, some DAMs, such as stevia [42], cholic acid [45], and sinapine [49], contribute to both antimicrobial defense and oxidative stress control, and thus represent metabolite types with potentially enhanced functional versatility. Additionally, several DAMs, such as ecdysterone [30], tretinoin [31], echinocystic acid [32], betulinic acid [33], xanthohumol [34], scopoletin [40], trans-vaccenic acid [46], and primulin [50], may participate in hormonal or immune signaling processes, either by mimicking insect hormones or by modulating plant defense pathways. These metabolites exhibited stage-specific accumulation patterns: some were enriched before infestation as preemptive defenses, and others dynamically regulated during early or late infestation to sustain resistance. Compared with RP, B1415 demonstrated more controlled and timely regulation of these metabolites, indicating a more coordinated and efficient metabolic response. In contrast, RP often showed delayed or excessive metabolite accumulation, suggesting a reactive rather than proactive defense strategy. These integrated patterns underscore a metabolically primed state in B1415 that supports rapid and sustained resistance against BPH. Although further functional validation is needed, this study provides a systemic view of how diverse classes of DAMs may collectively contribute to rice defense mechanisms.

To elucidate the differential responses of RP and B1415 to BPH infestation, we implemented transcriptomic and metabolomic analyses on these two rice lines (Figure 5A). In RP, the early enrichment of primary metabolic processes, especially involving amino acid and unsaturated fatty acid biosynthesis, suggests an attempt to reallocate resources for stress mitigation [57]. However, the delayed activation of phenylpropanoid biosynthesis pathways indicates a less efficient defense mechanism. Conversely, B1415 exhibited early activation and sustained enrichment of phenylpropanoid and flavonoid biosynthesis pathways, supporting cell wall reinforcement and secondary metabolite-based defense [58]. These findings indicate that the B1415 line demonstrates a more targeted and efficient defense strategy against BPH infestation, characterized by rapid enrichment of secondary metabolite pathways and minimal reliance on primary metabolism. In contrast, the RP line displays a delayed, generalized stress response with extensive metabolic reprogramming but less focused defense, underscoring the superior resistance of B1415.

The metabolic shift in the phenylpropanoid biosynthesis pathway provides further insight into the mechanisms underlying BPH resistance (Figure 5B). The more pronounced and sustained upregulation of PAL genes in B1415 indicates a more efficient channeling of precursors into phenylpropanoid-derived defense compounds. The downregulation of C4H and COMT genes in both RP and B1415, coupled with the upregulation of OsF5HL in B1415, likely contributes to reduced FA accumulation (Figure 5C). This reduction aligns with LC–MS/MS detection results, further corroborating the reliability of the findings (Figure 6A). FA has been shown to influence plant susceptibility to biotic stress. Tian et al. observed that high FA concentrations in strawberry rhizosphere soil promoted Fusarium oxysporum growth, resulting in increased disease severity and reduced resistance in strawberry plants [59]. Similarly, Jin et al. demonstrated that FA accumulation in the cucumber rhizosphere altered microbial composition, exacerbating Fusarium oxysporum infection and weakening cucumber resistance [27]. Analogous to its role in Fusarium wilt disease, FA may contribute to increased BPH susceptibility by modifying defense responses in rice. In this study, FA content declined in both B1415 and RP during BPH infestation, and FA-treated plants exhibited increased susceptibility to BPH, evidenced by severe wilting, higher BPH weight gain and honeydew excretion, and reduced expression of BPH14 and BPH15 in B1415 (Figure 6). These results implicate FA as a negative regulator of BPH resistance. While our exogenous application supports this role, genetic validation is needed. FA-deficient mutants, generated through gene editing or natural variation, would help validate the mechanistic role of FA and further clarify its integration within the rice-BPH defense network.

The metabolomic responses in B1415 are also consistent with known gene-mediated resistance pathways. For instance, BPH6 enhances cell wall integrity and activates coordinated cytokinin, SA, and jasmonic acid (JA) signaling pathways while preserving normal yield levels [60]. BPH9, an NLR protein, induces strong SA and JA signaling, conferring antixenosis and antibiosis, with allelic diversity offering adaptability to different BPH populations [61]. BPH30 strengthens sclerenchyma tissues in the leaf sheath, forming a mechanical barrier that prevents BPH stylet penetration and phloem access. These structural and biochemical mechanisms reflect multiple layers of resistance [62]. In B1415, BPH14 and BPH15 provide resistance through distinct but complementary mechanisms. The CC-NB-LRR protein encoded by BPH14 activates SA signaling, promotes callose deposition, and interacts with WRKY transcription factors to regulate downstream defense genes [5,6]. A lectin receptor-like kinase encoded by BPH15 participates in innate immune response, regulating defense gene expression and contributing to both herbivore and pathogen resistance [8]. The metabolic changes observed in B1415, such as the accumulation of antimicrobial and antioxidant metabolites, the modulation of hormone-related compounds, and the coordinated expression response under FA treatment, are consistent with the BPH14/BPH15-mediated signaling. These parallels suggest that the enhanced resistance in B1415 is supported by both known genetic mechanisms and associated metabolic reprogramming, reflecting a multifaceted defense strategy against BPH infestation.

5. Conclusions

This investigation presents new findings about the metabolic mechanisms underlying BPH resistance in BPH14/BPH15 pyramiding rice. Integrated metabolic and transcriptomic analyses of B1415 and RP plants identified key pathways, including flavonoid and phenylpropanoid biosynthesis. B1415 showed early, targeted activation of these secondary metabolic pathways, while RP exhibited broader, less specific responses. Furthermore, exogenous FA was found to negatively regulate resistance, highlighting its potential as a target for metabolic modulation. These findings support breeding strategies that select for early defense pathway activation and reduced FA accumulation. These metabolic features provide a foundation for integrating marker-assisted and metabolic engineering strategies in the development of resistant cultivars. In conclusion, this research adds new knowledge about rice’s complex defense network and provides valuable insights for improving BPH resistance through genetic and metabolic modifications.