Comparative Insights Into Detoxification, Regulation, and Evolution of Neonicotinoid Resistance in Three Planthoppers

ABSTRACT

Planthoppers, the brown planthopper (BPH, Nilaparvata lugens), white‐backed planthopper (WBPH, Sogatella furcifera), and small BPH (SBPH, Laodelphax striatellus) are among the most destructive rice pests in Asia. Neonicotinoid insecticides, particularly imidacloprid, have been widely deployed for their control, but intensive use has driven rapid evolution of high‐level resistance across multiple species and regions. Long‐term monitoring reveals pronounced spatial and temporal variation in resistance levels, shaped by local selection pressure and seasonal migration dynamics. Resistance is predominantly mediated by metabolic detoxification, with cytochrome P450 monooxygenases (CYPs), especially CYP6ER1 in BPH and its orthologs in WBPH and SBPH playing a central role, as confirmed by RNAi, heterologous expression, and genome‐editing studies. Carboxylesterases, glutathione S‐transferases, UDP‐glycosyltransferases, and ATP‐binding cassette transporters contribute additional detoxification capacity, whereas target‐site mutations in nicotinic acetylcholine receptors remain comparatively minor in field populations. Transcriptomic analyses reveal that regulatory networks, including CncC/MafK, HNF4, and MAPK signaling‐govern CYP overexpression, with comparative evidence highlighting convergent evolution of detoxification pathways across species. This review synthesizes current knowledge on resistance monitoring, molecular mechanisms, and evolutionary dynamics of neonicotinoid resistance in rice planthoppers, with emphasis on the BPH–imidacloprid system and comparative insights from WBPH and SBPH. Implications for integrated resistance management and sustainable pest control, including RNAi‐based approaches, are also discussed.

Integrated neonicotinoid resistance mechanism in planthoppers.

Summary

• CYP6ER1 and related P450 orthologs are major drivers of neonicotinoid resistance in rice planthoppers.

• BPH shows the most rapid resistance escalation, whereas WBPH and SBPH display lower or more heterogeneous trends.

• Comparative evidence supports integrated resistance management and highlights key regulatory gaps across species.

1. Introduction

Rice planthoppers, particularly the brown planthopper (Nilaparvata lugens, BPH), the white‐backed planthopper (Sogatella furcifera, WBPH), and the small brown planthopper (Laodelphax striatellus, SBPH), are among the most destructive sap‐feeding pests of rice across Asia. These species cause substantial economic losses through direct phloem feeding that leads to plant wilting and the characteristic “hopper burn” symptoms, as well as indirectly through the transmission of plant viruses such as rice stripe virus and rice grassy stunt virus (Wang et al. 2022). Their high fecundity, short generation times, seasonal long‐distance migration, and considerable genetic plasticity facilitate rapid population growth and adaptation to agricultural management practices. Consequently, insecticide resistance has become a persistent challenge in rice production systems (Huang et al. 2023).

Neonicotinoid insecticides, introduced in the 1990s, rapidly became central components of chemical control programs for planthoppers because of their high insecticidal potency, systemic activity within plants, and relatively favorable mammalian safety profiles. Imidacloprid, the first commercially available neonicotinoid, acts as an agonist of insect nicotinic acetylcholine receptors (nAChRs), causing prolonged neuronal excitation that ultimately results in paralysis and death. Following its widespread adoption in rice‐growing regions, imidacloprid provided effective and reliable control of BPH, WBPH, and SBPH for nearly a decade (Liu et al. 2005; Zhang et al. 2018). In many rice production systems, neonicotinoids are applied not only as foliar sprays but also prophylactically as seed or seedling treatments, allowing the systemic compound to protect young plants for several weeks during early crop establishment. This early‐season protection is particularly valuable because rice seedlings are highly susceptible to planthopper infestation, and early pest outbreaks can substantially reduce plant vigor and yield potential (Simon‐Delso et al. 2015; Tooker et al. 2017).

However, intensive and prolonged use of imidacloprid has exerted strong selection pressure on field populations, leading to the rapid emergence of resistance. High levels of imidacloprid resistance were first documented in BPH populations from East Asia in the early 2000s, with resistance ratios (RRs) increasing dramatically over time and spreading through migratory populations (Matsumura et al. 2014). In SBPH, regional heterogeneity in resistance was already evident by the mid‐2000s. For example, populations from Jiangsu Province exhibited high resistance to imidacloprid and several other insecticides, whereas populations from other regions remained largely susceptible (Gao et al. 2008). Subsequent monitoring studies confirmed that resistance dynamics vary among planthopper species and geographic regions, reflecting differences in insecticide use patterns, local selection pressures, and migration‐mediated gene flow (Li et al. 2021; Zhang et al. 2014).

To address the declining efficacy of imidacloprid, additional neonicotinoids, including thiamethoxam, clothianidin, dinotefuran, and nitenpyram, were subsequently incorporated into rice pest management programs. Although these compounds initially restored control in some regions, cross‐resistance soon became evident, particularly in BPH and SBPH populations exhibiting enhanced detoxification capacity (Mu et al. 2016; Xiao et al. 2020; Zhang et al. 2018). Accumulating evidence indicates that neonicotinoid resistance in planthoppers is predominantly mediated by metabolic detoxification mechanisms involving the overexpression of cytochrome P450 monooxygenases (CYPs), with additional contributions from esterases and ATP‐binding cassette (ABC) transporters (Elzaki et al. 2017; Sun et al. 2017; Wang et al. 2017). Functional validation studies have demonstrated that several planthopper CYP enzymes can directly metabolize imidacloprid and related neonicotinoids, providing strong mechanistic links between gene overexpression and resistance phenotypes (Elzaki et al. 2017; Miah et al. 2017; Teng et al. 2025; Xiao et al. 2020).

At the same time, the continued use of neonicotinoids is increasingly influenced by regulatory and environmental considerations. Concerns regarding their potential impacts on pollinators and other beneficial arthropods have led to restrictions or bans on certain neonicotinoid uses in several regions, particularly within the European Union (Bass et al. 2015; Bass and Field 2018; Jeschke et al. 2011). These regulatory developments highlight the need to better understand resistance evolution, improve resistance management strategies, and explore alternative pest management approaches that maintain effective control while reducing ecological risks.

Recent transcriptomic, functional, and structural studies further suggest that the evolution of neonicotinoid resistance in planthoppers involves complex regulatory changes rather than simple single‐gene mutations. In SBPH, for example, resistance may involve a combination of target‐site alterations, extensive transcriptional reprogramming, and activation of metabolic pathways capable of detoxifying multiple insecticide classes (Choi et al. 2025; Zhang et al. 2018). Comparative analyses across BPH, WBPH, and SBPH also indicate notable evolutionary convergence in detoxification function, even when the specific resistance‐associated genes differ among species (Teng et al. 2025; Yang et al. 2018).

This review synthesizes current knowledge on resistance monitoring, molecular and biochemical mechanisms, regulatory signaling networks, and evolutionary dynamics underlying neonicotinoid resistance in rice planthoppers. Particular emphasis is placed on the BPH‐imidacloprid system as a well‐characterized model, while comparative insights from WBPH and SBPH are incorporated to highlight shared and species‐specific resistance trajectories. Finally, emerging resistance management strategies and future research directions for sustainable control of planthopper populations are discussed.

Despite extensive characterization of CYP‐mediated resistance, critical gaps remain. The precise molecular mechanisms driving CYP6ER1 overexpression—whether through gene duplication, promoter variation, transposable element insertion, or epigenetic regulation—are still not fully resolved. Moreover, the apparent species‐specific differences in CYP regulation between BPH, WBPH, and SBPH suggest that distinct regulatory architectures may underlie convergent resistance phenotypes. Understanding these upstream regulatory triggers represents a major research priority.

1.1. Literature Search Strategy and Data Selection

This review was conducted using a structured literature survey to ensure comprehensive coverage of neonicotinoid resistance in rice planthoppers. Peer‐reviewed articles were retrieved from major scientific databases, including Web of Science, Scopus, PubMed, and Google Scholar. Searches were performed using combinations of keywords such as “N. lugens,” “S. furcifera,” “L. striatellus,” “neonicotinoid resistance,” “imidacloprid,” “cytochrome P450,” “detoxification,” “cross‐resistance,” and “RNA interference (RNAi).”

Studies published between approximately 2000 and 2025 were prioritized to capture long‐term resistance trends and recent molecular advances. Inclusion criteria comprised: (i) field or laboratory resistance monitoring studies reporting lethal concentration 50% (LC₅₀), lethal dose 50% (LD₅₀), or RRs; (ii) functional or transcriptomic analyses of resistance mechanisms; and (iii) comparative or review studies relevant to planthopper resistance biology. Studies lacking quantitative data or clear methodological descriptions were excluded.

Long‐term monitoring data presented in Figure 1 and Supporting Information S1: Table 2 were synthesized from multiple independent studies across East and Southeast Asia to provide a representative overview of temporal and geographic resistance dynamics.

Figure 1.

Temporal, geographic, and cross‐resistance dynamics of neonicotinoid resistance in rice planthoppers. (A) Temporal evolution of neonicotinoid resistance in the three major rice planthopper species—brown planthopper (BPH), white‐backed planthopper (WBPH), and small brown planthopper (SBPH)—demonstrating pronounced species‐specific resistance trajectories. BPH shows rapid and extreme resistance escalation over time, whereas WBPH and SBPH exhibit slower and more heterogeneous resistance development. (B) Regional dynamics of imidacloprid resistance in BPH populations from China, Japan, Korea, and Vietnam, illustrating strong temporal increases and regional synchronization consistent with sustained insecticide selection pressure and long‐distance migration along the East Asian migratory corridor. (C) Cross‐resistance patterns among neonicotinoids in BPH populations from China, showing concurrent resistance increases to imidacloprid, thiamethoxam, dinotefuran, and clothianidin. Resistance levels are expressed as resistance ratios (RRs) relative to baseline susceptibility derived from laboratory‐susceptible or early field populations (see Supporting Information S1: Tables 1 and 2).

2. Resistance Monitoring: Distribution, Dynamics, and Evolution

2.1. Geographic and Temporal Patterns

Most resistance monitoring studies on rice planthoppers have been conducted in Asian rice production systems, particularly in East and South Asia, where these pests cause the greatest economic losses. The synthesis presented here therefore, focuses on resistance data from these regions. To illustrate major resistance trends, Figure 1 compiles representative monitoring data derived from published studies across China, Japan, Korea, Vietnam, and several additional Asian countries. In total, the dataset summarized in Figure 1 and Supporting Information S1: Table 2 includes monitoring results from multiple long‐term field surveys and laboratory studies spanning approximately two decades, covering the three major rice planthopper species (BPH, SBPH, and WBPH). Baseline susceptibility values were obtained from laboratory‐susceptible strains or early field populations exhibiting very low LC₅₀ and LD₅₀ values (Supporting Information S1: Table 1). These baselines provide essential reference points for calculating RRs and for interpreting long‐term resistance trajectories.

Among the three major species, BPH exhibits the most pronounced resistance escalation over time (Figure 1A). Early studies reported extremely low LC₅₀ values for imidacloprid in susceptible populations (0.08 mg/L; Supporting Information S1: Table 1), reflecting the high intrinsic toxicity of neonicotinoids at the time of their introduction (Wang et al. 2008). However, resistance increased sharply after the mid‐2000s, with RRs rising from relatively low levels in the early 2000s (Zewen et al. 2003) to >3000‐fold by approximately 2012 and exceeding 9,000‐fold in some Chinese populations between 2020 and 2023 (Supporting Information S1: Table 2; Figure 1B) (Ye et al. 2024). These patterns are clearly reflected in Figure 1A,B, where BPH shows steep temporal and regional increases. Comparable trends in Japan and Korea further indicate that resistance escalation is regionally synchronized, likely driven by intensive insecticide use and long‐distance migration (Matsumura et al. 2014; Fujii, Sanada‐Morimura, Oe, et al. 2020; Fujii, Sanada‐Morimura, Matsukura, et al. 2020; Choi et al. 2025).

In contrast, WBPH exhibits a more moderate and comparatively stable resistance trajectory, as shown in Figure 1A. Although baseline susceptibility is similar to that of BPH (Supporting Information S1: Table 1), field populations generally display low‐to‐moderate resistance levels. Data summarized in Supporting Information S1: Table 2 indicate that RRs for WBPH typically range from near‐susceptible levels to approximately 60‐fold, even in recent surveys from China and Japan (Jin et al. 2017; Li et al. 2021). Long‐term monitoring across China, Japan, and Korea indicates that resistance in WBPH has increased more gradually and remains substantially lower than in BPH (Figure 1A). Unlike BPH, WBPH does not show a steep temporal escalation in Figure 1A, but rather a gradual and limited increase. This pattern suggests weaker or less consistent selection pressure and may reflect ecological differences such as broader host plant utilization and reduced exposure intensity within rice‐dominated systems.

Similarly, SBPH exhibits moderate but spatially heterogeneous resistance development, with patterns also visible in Figure 1A. Supporting Information S1: Table 2 shows that SBPH RRs generally remain below approximately 100‐fold, although higher values (up to ~799‐fold) have occasionally been reported in earlier studies (Gao et al. 2008; Jeong et al. 2016; Zhang et al. 2014). Unlike BPH, SBPH does not exhibit consistent temporal escalation but instead shows fluctuating resistance levels across regions, suggesting that local selection pressures and population structure play a stronger role than large‐scale regional spread.

Regional comparisons further support these species‐specific differences. As shown in Figure 1B, East Asia represents the primary hotspot of resistance evolution, particularly for BPH, where China, Japan, and Korea show strong and synchronized increases over time. In contrast, data from Southeast and South Asia (Supporting Information S1: Table 2) indicate lower and more variable resistance levels across all three species (Bao et al. 2016; Chowdary et al. 2025; Fujii, Sanada‐Morimura, Oe, et al. 2020; Garrood et al. 2016), with especially limited escalation in WBPH and SBPH.

Experimental selection studies further support these field observations. High realized heritability of resistance in BPH (Diptaningsari et al. 2019) is consistent with the rapid increases shown in Figure 1A,B. In contrast, the comparatively limited resistance ranges observed for WBPH and SBPH in Supporting Information S1: Table 2 suggest a slower evolutionary response under similar selection pressure.

Resistance amplification is not limited to imidacloprid. Monitoring data summarized in Figure 1C and Supporting Information S1: Table 2 demonstrate increasing resistance to other neonicotinoids in BPH, including thiamethoxam, dinotefuran, and clothianidin. However, comparable multi‐insecticide resistance patterns are less pronounced in WBPH and SBPH, where resistance levels remain relatively moderate across compounds (Wang et al. 2008; Zhang et al. 2016).

Overall, long‐term monitoring data indicate distinct species‐specific resistance trajectories in Asian rice agroecosystems: BPH has undergone rapid and extensive resistance evolution, whereas WBPH and SBPH exhibit slower, or more gradual, and spatially heterogeneous resistance development. These patterns are clearly summarized in Figure 1.

It is important to note that the interpretation of regional resistance trends may be influenced by differences in sampling intensity, monitoring frequency, and experimental methodologies among studies. In addition, Figure 1 and Supporting Information S1: Table 2 summarize representative values and therefore do not capture the full range of variability among populations. These limitations should be considered when comparing resistance levels across regions or species.

2.2. Cross‐Resistance and Inheritance

Resistance monitoring and laboratory selection studies demonstrate that cross‐resistance among neonicotinoid is well established in BPH populations. As illustrated in Figure 1C, resistance to imidacloprid is often accompanied by increasing resistance to thiamethoxam, dinotefuran, and clothianidin. Supporting Information S1: Table 2 further supports these trends, showing concurrent increases in RRs across multiple compounds in the same populations (Fujii, Sanada‐Morimura, Oe, et al. 2020; Wu et al. 2018; Ye et al. 2024; Zhang et al. 2016).

In WBPH, evidence for cross‐resistance is present but comparatively limited. Data from Supporting Information S1: Table 2 indicate that populations exposed to imidacloprid may show reduced susceptibility to other neonicotinoids; however, resistance levels across compounds generally remain within low‐to‐moderate ranges (Jin et al. 2017; Li et al. 2021). Unlike BPH, WBPH does not exhibit strong multi‐insecticide resistance escalation, suggesting weaker or less consistent cross‐resistance development.

Similarly, SBPH exhibits partial cross‐resistance patterns, although these are less consistent and more region‐dependent. Supporting Information S1: Table 2 shows that SBPH populations resistant to imidacloprid may display moderate resistance to other neonicotinoids, but without the pronounced and coordinated increases observed in BPH. These findings indicate that cross‐resistance occurs across all three species but differs substantially in magnitude and consistency.

These interspecific differences likely reflect variation in underlying resistance mechanisms. In BPH, cross‐resistance is often strongly associated with enhanced metabolic detoxification, whereas in WBPH and SBPH, resistance appears to involve more complex and less well‐characterized mechanisms (Mu et al. 2016; Wang et al. 2008; Ye et al. 2024). Consequently, cross‐resistance patterns should be interpreted cautiously and may not always reflect identical molecular mechanisms across species.

Studies on inheritance further highlight these differences. In BPH, resistance is typically autosomal and partially dominant (Ding et al. 2013; Diptaningsari et al. 2019), facilitating rapid spread under selection pressure. In contrast, inheritance patterns in WBPH and SBPH remain comparatively understudied, although their more moderate resistance levels and variability (Supporting Information S1: Table 2) suggest potentially more complex or polygenic genetic architectures.

Taken together, these findings indicate that while BPH serves as a primary model for understanding neonicotinoid resistance, WBPH and SBPH exhibit similar but less intense and less predictable cross‐resistance and inheritance patterns, highlighting important gaps in current knowledge.

2.3. Fitness Costs and Evolutionary Stability

Fitness costs associated with neonicotinoid resistance vary across species, resistance mechanisms, and environmental conditions. In BPH, some highly resistant populations show reduced fecundity, delayed development, or decreased survival in the absence of insecticide exposure (Chowdary et al. 2025; Ding et al. 2013; Wu et al. 2018; Ye et al. 2024). However, compensatory evolution or additional genetic changes may reduce these costs over time, potentially allowing resistant populations to persist even when selection pressure is reduced (Chowdary et al. 2025; Ding et al. 2013; Wu et al. 2018; Ye et al. 2024).

In contrast, WBPH populations exhibiting moderate resistance often show relatively minimal fitness penalties, which may facilitate the maintenance of resistance alleles once they arise (Li et al. 2021; Zhang et al. 2017). SBPH populations similarly display relatively stable resistance phenotypes across regions and years in several monitoring (Jeong et al. 2016; Zhang et al. 2014).

Taken together, these observations suggest that neonicotinoid resistance in rice planthoppers, particularly in BPH, can remain evolutionarily stable under continued insecticide exposure. The temporal and geographic patterns summarized in Figure 1, therefore, highlight the challenges associated with long‐term reliance on neonicotinoid insecticides for planthopper management in Asian rice production systems.

3. Resistance Mechanisms

Neonicotinoid resistance in rice planthoppers results from multiple physiological and molecular processes that reduce insecticide toxicity. These processes broadly include alterations in the molecular target, enhanced metabolic detoxification, and regulatory mechanisms controlling detoxification gene expression. Current evidence indicates that metabolic resistance represents the dominant mechanism in most field populations, whereas target‐site modifications appear to play a relatively minor role.

3.1. Target‐Site Mutation Based Resistance

Neonicotinoids exert their insecticidal activity by binding to nAChRs, which are heteropentameric ligand‐gated ion channels composed of multiple α and β subunits in the insect nervous system. Mutations affecting these receptors represent an important resistance mechanism in several insect taxa. However, evidence for target‐site resistance in rice planthoppers remains limited.

To date, only a single substitution in the nAChR α‐subunit (Y151S) has been reported in BPH. This mutation was identified in a laboratory‐selected strain originating from China (Liu et al. 2005). Although experimental analyses demonstrated that Y151S can reduce receptor sensitivity to imidacloprid under laboratory conditions, subsequent studies have relied on the same genetic background, and the mutation has not been detected in independent field populations despite extensive resistance monitoring across Asia (Matsumura et al. 2008; Ye et al. 2024). Available data also indicate that this substitution may impose measurable fitness costs, including reduced fecundity, impaired reproductive performance, and developmental delays, which could limit its persistence under natural conditions (Zhang et al. 2022).

The limited occurrence of nAChR mutations in planthoppers contrasts with resistance patterns observed in other sap‐feeding pests such as aphids, where β‐subunit mutations in nAChRs have been repeatedly associated with high resistance levels. Experimental work in model systems has demonstrated that certain β‐subunit substitutions can substantially reduce neonicotinoid binding affinity while maintaining normal receptor function (Cheng et al. 2025). Similar mechanisms have been reported in aphids and other hemipteran pests (Zhang et al. 2022). However, comparable mutations have not yet been detected in planthopper field populations, suggesting that the evolutionary pathways leading to target‐site resistance may differ among insect lineages.

Recent functional evidence from the western flower thrips, Frankliniella occidentalis, further illustrates the evolutionary feasibility of β‐subunit–mediated resistance in some insects. (Huang et al. 2026) demonstrated that the β1‐subunit R80T mutation significantly reduces the affinity and efficacy of several neonicotinoids, including imidacloprid, acetamiprid, clothianidin, and dinotefuran, without affecting acetylcholine sensitivity. Such mutations, however, have not been detected in planthopper populations despite extensive molecular surveillance.

In addition to structural mutations, several transcriptomic studies have reported altered expression of specific nAChR subunits in resistant planthopper populations. Nevertheless, available evidence suggests that these changes alone are unlikely to explain the high RRs observed in field populations, which often exceed several hundred‐fold (Garrood et al. 2016; Matsumura et al. 2008; Thany 2025; Ye et al. 2024). Consequently, target‐site mechanisms appear to contribute only marginally to neonicotinoid resistance in most planthopper populations.

The rarity of target‐site mutations in planthoppers raises important evolutionary questions. One possible explanation is structural constraint, where mutations in nAChR subunits may disrupt essential neuronal function, leading to strong fitness penalties. Alternatively, the high efficiency and flexibility of metabolic detoxification pathways may reduce selective pressure for target‐site evolution. These hypotheses remain largely untested and represent an important direction for future research.

3.2. Metabolic Resistance: Detoxification and Regulation

Accumulating evidence indicates that metabolic detoxification is the primary mechanism underlying neonicotinoid resistance in rice planthoppers. This process involves enzymatic biotransformation of insecticides into less toxic or more easily excretable metabolites, typically through a coordinated sequence of phase I (functionalization), phase II (conjugation), and phase III (transport) reactions. Among these, cytochrome P450 monooxygenases (CYPs) play a central role in phase I oxidation, while glutathione S‐transferases (GSTs), UDP‐glycosyltransferases (UGTs), and carboxyl/cholinesterases (CCEs) contribute to downstream detoxification processes (Wang et al. 2008; Cheng et al. 2025; Yang et al. 2020).

In rice planthoppers, numerous studies have demonstrated that resistant populations exhibit significantly elevated detoxification enzyme activity and gene expression compared with susceptible strains. For example, increased CYP‐mediated metabolism has been consistently associated with resistance to imidacloprid and other neonicotinoids in BPH (Bass et al. 2011; Pang et al. 2016; Zhang et al. 2023). Similar trends have been reported in WBPH and SBPH, where transcriptomic and biochemical analyses indicate enhanced detoxification capacity in resistant populations (Jin et al. 2017; Li et al. 2021; Elzaki et al. 2017).

In addition to enzymatic activity, regulatory mechanisms controlling detoxification gene expression play a critical role in resistance evolution. Exposure to neonicotinoids can induce transcriptional responses mediated by signaling pathways such as MAPK cascades and transcription factors (TFs), including CncC/MafK and AhR/ARNT, which regulate detoxification genes (Mao et al. 2022; Tang et al. 2020). These regulatory processes contribute to inducible and adaptive resistance phenotypes, enabling rapid physiological responses to insecticide exposure.

Together, these findings indicate that metabolic resistance in planthoppers is not driven by single genes alone but rather by integrated detoxification networks and regulatory systems, as illustrated in Figure 2.

Figure 2.

Integrated metabolic and regulatory framework of neonicotinoid resistance in planthoppers. Neonicotinoids primarily induce resistance through enhanced cytochrome P450–mediated detoxification, supported by cytochrome P450 reductase (CPR), phase II enzymes (CCEs, GSTs, UGTs). Reactive oxygen species (ROS), MAPK (JNK–ERK) signaling, and multiple TFs coordinate the regulation of detoxification genes, while nitric oxide (NO) and chemosensory proteins may contribute additional modulatory effects. Arrows indicate activation or induction.

3.3. Cytochrome P450 Monooxygenases and Cytochrome P450 Reductase

CYPs represent the most extensively characterized detoxification enzymes associated with neonicotinoid resistance in rice planthoppers. In BPH, the gene CYP6ER1 has repeatedly been identified as a key resistance determinant. Multiple studies have demonstrated strong overexpression of CYP6ER1 in resistant populations, with transcript levels several‐fold higher than in susceptible strains. Functional validation through RNAi, heterologous expression, and CRISPR‐based knockout experiments has confirmed its ability to metabolize imidacloprid and related compounds (Pang et al. 2014; Zhang et al. 2023; Zimmer et al. 2018). These findings are summarized in Table 1.

Table 1.

Key cytochrome P450 genes implicated in neonicotinoid resistance in rice planthoppers.

Species	Key CYP genes	Evidence for involvement	Reported expression differences (fold change)	Functional significance	References
Nilaparvata lugens	CYP6ER1 (vA, vB, vC)	Overexpression in multiple resistant populations; RNAi knockdown; transgenic expression; CRISPR knockout; qRT‐PCR; miRNA regulation; knockout susceptibility; cross‐resistance assays	Up to ~40‐fold (field populations); ~13–30‐fold in resistant populations (population‐dependent)	Primary neonicotinoid‐metabolizing enzyme with strong transcriptional upregulation and variant‐specific catalytic activity across multiple neonicotinoids	Bass et al. (2011); Choi et al. (2025); Jin et al. (2019); Jin et al. (2025); Pang et al. (2016); Tang et al. (2020); Zhang et al. (2023); Zimmer et al. (2018)
	CYP6AY1	Inducible expression; metabolism assays; qRT‐PCR	~4–5‐fold overexpression in resistant populations	Additive or conditional contribution to resistance	Bao et al. (2016)
	CYP4CE1	Transcriptomic overexpression correlated with CYP activity	> 5‐fold overexpression in resistant strain(s)	Contributes to metabolic detoxification network	Zhang et al. (2016)
Laodelphax striatellus	CYP6ER2	RNA‐seq, qRT‐PCR, molecular docking	> 30–35‐fold upregulation in resistant strain	Structural and functional homolog of CYP6ER1; transcriptionally driven detoxification and cross‐class resistance	Choi et al. (2025)
	CYP353D1v2	Heterologous expression; metabolism assays, molecular docking‐enzyme assay, synergist test, qRT‐PCR, RNAi	Significantly overexpressed (up to 16 folds after selection)	Efficient imidacloprid metabolism; convergent evolution	Elzaki et al. (2017); Elzaki et al. (2016)
	CYP6AY3v2	Functional expression and enzymatic assays	Associated with resistance (up to about eightfolds)	Strong catalytic activity toward neonicotinoids	Elzaki et al. (2016); Wang et al. (2017)

In addition to CYP6ER1, several other CYP genes—including CYP6AY1, CYP4ACE1, CYP6CS1, CYP6CW1, CYP6CW9, CYP425B1, and CYP6FJ3—have been implicated in resistance through transcriptomic and functional analyses (Bao et al. 2016; Choi et al. 2026; Xia et al. 2022; Zhang et al. 2024; Zhang et al. 2016). Structural variation, including amino acid substitutions in substrate recognition sites, as well as gene duplication and copy‐number variation, further enhances metabolic capacity in resistant populations (Choi et al. 2025; Gong et al. 2023).

Importantly, similar detoxification mechanisms have also been identified in WBPH and SBPH, although they are less extensively characterized. In SBPH, CYP353D1v2 and CYP6AY3v2 have been functionally validated to metabolize imidacloprid efficiently, demonstrating convergent evolution of detoxification pathways across species (Elzaki et al. 2016; Elzaki et al. 2017; Wang et al. 2017). Transcriptomic studies in WBPH have also revealed overexpression of multiple CYP genes associated with neonicotinoid exposure, suggesting a similar metabolic resistance framework (Jin et al. 2017; Li et al. 2021).

Cytochrome P450 reductase (CPR) is an essential partner enzyme that transfers electrons required for CYP catalytic activity. Functional studies have demonstrated that knockdown of CPR significantly increases susceptibility to neonicotinoids, confirming its critical role in supporting P450‐mediated detoxification (He et al. 2023). The coordinated action of CYPs and CPR therefore constitutes a central metabolic system underlying resistance.

Overall, these findings indicate that CYP‐mediated detoxification represents a conserved but species‐specific mechanism, with BPH showing the strongest and most well‐characterized response, while WBPH and SBPH exhibit similar but comparatively moderate and less well‐defined patterns.

3.4. Additional Detoxification Pathways

In addition to CYP enzymes, several other detoxification systems may contribute to neonicotinoid tolerance. CCEs are frequently expanded in insect genomes, and elevated esterase activity has been reported in resistant populations of both the BPH and WBPH (Li et al. 2021; Mao et al. 2021). These enzymes may participate in insecticide hydrolysis or in the detoxification of intermediate metabolites generated during CYP‐mediated oxidation.

GSTs and UGTs are typically involved in phase II detoxification processes, conjugating reactive metabolites and increasing their solubility for subsequent excretion (Cheng et al. 2021; Yang et al. 2020). ABC transporters further facilitate the removal of insecticides and their metabolites from cells, thereby reducing intracellular concentrations (Sun et al. 2017; Wang et al. 2022).

While numerous studies have reported associations between the expression of these enzymes and neonicotinoid resistance, most evidence remains correlative and derived primarily from transcriptomic analyses rather than direct metabolic assays comparable to those available for CYP enzymes. Consequently, their roles are best interpreted as supporting components of broader detoxification networks rather than primary resistance determinants.

3.5. Regulatory Networks Controlling Detoxification

Recent studies suggest that metabolic resistance in planthoppers is also shaped by regulatory pathways controlling detoxification gene expression. Exposure to xenobiotics can activate signaling cascades that modulate TFs regulating detoxification enzymes. Several TFs, including CncC/MafK, HNF4, AP‐1, AhR/ARNT, FoxO, and CREB, have been implicated in the regulation of detoxification genes in insects. In planthoppers, transcriptomic and functional evidence suggest that these regulatory factors may influence the expression of P450 enzymes and other detoxification genes. Activation of mitogen‐activated protein kinase (MAPK) signaling pathways, particularly JNK‐ERK cascades, has also been associated with insecticide‐induced transcriptional responses (Cheng et al. 2021; Mao et al. 2022; Tang et al. 2020).

However, the regulatory architecture underlying detoxification gene expression in planthoppers remains incompletely understood, and many regulatory interactions have been inferred from expression patterns rather than direct functional experiments.

3.6. Oxidative Stress and Signaling Responses

Metabolism of xenobiotics frequently generates reactive oxygen species (ROS), which can function both as cytotoxic by‐products and as signaling molecules. Elevated ROS levels have been shown to activate MAPK signaling cascades, thereby linking metabolic stress with transcriptional regulation of detoxification genes.

Reactive nitrogen species, particularly nitric oxide (NO), have also been proposed as modulators of insect stress responses. Experimental studies in BPH indicate that treatment with NO donors can partially restore susceptibility to neonicotinoids, suggesting that NO may interfere with detoxification pathways or redox homeostasis (Elzaki et al. 2020).

NO signaling is well characterized in plants and vertebrates (Al Azzawi et al. 2023; Khan et al. 2021), where it participates in neural communication, immune responses, and physiological regulation (Müller 1997). However, despite this physiological framework, direct mechanistic links between NO signaling and insecticide resistance remain largely unexplored.

In several insect systems, NO also interacts with immune pathways and oxidative signaling networks. For example, studies in S. exigua have demonstrated NO‐mediated regulation of phospholipase A₂ activity and immune responses (Sadekuzzaman et al. 2018). Deployment of NOS inhibitors such as NG‐nitro‐L‐arginine methyl ester alongside NO donors in behavioral and immune assays has revealed complex modulation of insect physiology by NO (Han et al. 2022). Despite these insights, the role of NO in regulating detoxification systems or resistance evolution remains an emerging research area.

3.7. Integrated Framework of Neonicotinoid Resistance

The mechanisms described above collectively demonstrate that neonicotinoid resistance in rice planthoppers arises from a complex interaction of metabolic, regulatory, and physiological processes (Figure 2). Current evidence consistently indicates that enhanced metabolic detoxification—primarily mediated by CYP enzymes—represents the central mechanism underlying resistance in most field populations (Bass et al. 2011; Pang et al. 2016; Zhang et al. 2023).

Phase I metabolism by CYP enzymes is supported by phase II detoxification systems, including GSTs, UGTs, and CCEs, as well as phase III transport processes mediated by ABC transporters, which collectively facilitate the detoxification and elimination of insecticides (Cheng et al. 2021; Yang et al. 2020; Sun et al. 2017). Regulatory signaling pathways, including MAPK cascades and TFs such as CncC/MafK and AhR/ARNT, further modulate detoxification gene expression in response to xenobiotic exposure (Cheng et al. 2021; Mao et al. 2022; Tang et al. 2020).

In addition, physiological processes such as oxidative stress responses contribute to resistance dynamics. The generation of ROS during insecticide metabolism can activate signaling pathways that influence detoxification gene expression, thereby linking metabolic stress with adaptive responses (Elzaki et al. 2020). Emerging evidence also suggests that NO may modulate redox balance and influence susceptibility to insecticides, although its mechanistic role remains incompletely understood.

In contrast, target‐site resistance plays a relatively minor role in planthoppers compared with metabolic mechanisms, as supported by the limited occurrence of nAChR mutations in field populations (Matsumura et al. 2008; Ye et al. 2024).

Taken together, these interacting mechanisms highlight that neonicotinoid resistance is a multifactorial and dynamic trait, shaped by both genetic and environmental factors. The integrated framework presented in Figure 2 therefore provides a conceptual model linking detoxification pathways, regulatory networks, and physiological responses underlying resistance evolution in rice planthoppers.

4. Management Strategies and Future Perspectives

Although neonicotinoid insecticides have historically provided effective control of rice planthoppers, their long‐term sustainability has been compromised by the widespread emergence of resistance. In addition to resistance concerns, increasing regulatory scrutiny and documented non‐target impacts on pollinators and beneficial arthropods have further complicated their continued use in crop protection programs (Bass and Field 2018; Jeschke et al. 2011). Consequently, future management strategies must move beyond reliance on a single class of insecticides and instead adopt integrated resistance management approaches.

Several recently introduced insecticides, including sulfoxaflor, triflumezopyrim, and flupyrimin, currently remain effective against many planthopper populations and are increasingly incorporated into rice pest management programs. However, the extensive metabolic capacity of planthoppers and the demonstrated involvement of broadly acting detoxification enzymes raise concerns that resistance could eventually develop to these newer chemistries as well (Liao et al. 2021; Roy et al. 2025; Zhang et al. 2020). Therefore, carefully designed insecticide rotation programs based on different modes of action remain essential for slowing resistance evolution.

Resistance monitoring also represents a critical component of sustainable management. Routine bioassays combined with molecular diagnostics can help detect early shifts in susceptibility before control failures occur. In particular, monitoring changes in the expression or prevalence of resistance‐associated detoxification genes, including CYP family enzymes, may provide useful early warning indicators of evolving metabolic resistance (Feyereisen 2012; Nauen et al. 2022). Long‐term, standardized monitoring frameworks across regions will be especially important for tracking resistance dynamics and informing adaptive management strategies.

Beyond chemical control, integrated pest management (IPM) strategies are increasingly recognized as essential for long‐term planthopper suppression. Cultural practices such as synchronous planting, balanced nitrogen fertilization, and optimized irrigation regimes can reduce planthopper population growth and limit outbreaks (Horgan 2024). Host‐plant resistance has also played an important role in rice pest management, with several resistant rice varieties demonstrating partial suppression of planthopper populations (Horgan et al. 2015; Jena and Kim 2010). However, the durability of host resistance can be compromised by the rapid adaptive capacity of planthoppers, highlighting the need for continuous breeding and diversification of resistance genes (Horgan et al. 2018).

Biological control agents further contribute to planthopper regulation in rice ecosystems. Natural enemies, including parasitoids, predatory mirid bugs, spiders, and other arthropod predators, can substantially reduce planthopper populations under favorable ecological conditions (Lu et al. 2014; Wang et al. 2024). Conservation of these beneficial organisms through reduced insecticide use and habitat management can therefore enhance biological control services and contribute to more resilient pest management systems (Bari et al. 2025; Zheng et al. 2021).

In addition to these established approaches, emerging molecular technologies may provide complementary tools for future pest management. RNAi has attracted increasing attention as a potential strategy for targeting essential insect genes, including those involved in detoxification or physiological regulation. Advances in dsRNA stabilization and delivery systems—such as nanoparticle carriers, layered double hydroxide nanocarriers, chitosan‐based formulations, and sprayable dsRNA technologies—have improved the feasibility of RNAi‐based pest control under experimental and greenhouse conditions (Christiaens et al. 2020; Yan et al. 2020). Recent studies further demonstrate that RNAi can be deployed through both transgenic and non‐transgenic delivery systems, including foliar sprays, irrigation, trunk injection, and nanoparticle‐mediated delivery, expanding its potential applicability in crop protection (Dong et al. 2022; Khan et al. 2025).

However, despite these advances, RNAi remains a developing technology with several important limitations. The efficiency of dsRNA uptake in phloem‐feeding insects such as planthoppers is often low, and degradation by nucleases can significantly reduce stability under field conditions. In addition, variability in RNAi responsiveness among species and populations may limit its consistency and reliability. These constraints highlight the need for improved delivery systems and a deeper understanding of RNAi machinery in planthoppers. Consequently, RNAi should be considered a complementary tool within integrated pest management frameworks rather than a standalone solution.

Overall, sustainable management of planthopper populations will require a coordinated, multi‐faceted approach. Combining resistance monitoring, rational insecticide rotation, host‐plant resistance, biological control, and emerging molecular technologies will be essential to reduce selection pressure and delay further resistance evolution. Future strategies should therefore emphasize integration rather than reliance on any single control method, ensuring both effective pest suppression and long‐term agricultural sustainability.

5. Conclusions

Rice planthoppers remain major challenges to rice production across Asia, and the evolution of neonicotinoid resistance highlights their strong adaptive capacity. Current evidence indicates that resistance is primarily driven by enhanced metabolic detoxification, particularly through CYPs and associated pathways. Although target‐site mutations have been reported under laboratory conditions, they appear to play a limited role in most field populations. Comparative studies among the BPH, WBPH, and SBPH suggest that resistance evolution involves similar detoxification mechanisms but distinct genetic trajectories shaped by species‐specific biology and local selection pressures. Advances in genomics, transcriptomics, and functional genetics have improved our understanding of the molecular networks underlying resistance. From a management perspective, sustainable control will require integrated pest management strategies combining chemical, biological, and cultural approaches. Resistance monitoring, insecticide rotation, conservation of natural enemies, and deployment of resistant rice varieties remain key components of such strategies. Emerging molecular technologies, including RNAi‐based approaches, may provide additional tools but will likely function most effectively when integrated with existing practices. A deeper understanding of resistance mechanisms and their ecological consequences will be essential for designing effective long‐term strategies. Continued interdisciplinary research linking molecular biology, ecology, and pest management will be critical for maintaining the effectiveness of current and future control tools.

Author Contributions

Minyoung Choi: conceptualization, investigation, writing – original draft, writing – review and editing, visualization, data curation, software. Murtaza Khan: conceptualization, writing – original draft, writing – review and editing, validation, visualization, formal analysis. Juil Kim: conceptualization, investigation, funding acquisition, writing – review and editing, project administration, supervision, data curation.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Table S1: LC₅₀ and LD₅₀ values of the susceptibility baseline of planthoppers.

Table S2: Overview of Neonicotinoid resistance monitoring in East Asian planthopper populations.

Choi, M. , Khan M., and Kim J.. 2026. “Comparative Insights Into Detoxification, Regulation, and Evolution of Neonicotinoid Resistance in Three Planthoppers.” Archives of Insect Biochemistry and Physiology 122: e70165. 10.1002/arch.70165.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.