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Article

Screening of Positive Controls for Environmental Safety Assessment of RNAi Products

by
Kaixuan Ding
1,2,†,
Xiaowei Yang
2,†,
Qinli Zhou
2,
Geng Chen
2,
Fengping Chen
3,4,
Yao Tan
3,4,
Jing Li
1,* and
Lanzhi Han
2,*
1
College of Plant Protection, Hebei Agricultural University, Baoding 071000, China
2
State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, China
3
College of Horticulture and Plant Protection, Inner Mongolia Agricultural University, Hohhot 010018, China
4
Research Center for Grassland Entomology, Inner Mongolia Agricultural University, Hohhot 010000, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Agronomy 2025, 15(10), 2399; https://doi.org/10.3390/agronomy15102399
Submission received: 9 September 2025 / Revised: 7 October 2025 / Accepted: 14 October 2025 / Published: 16 October 2025
(This article belongs to the Special Issue Genetically Modified (GM) Crops and Pests Management)
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Abstract

RNA interference (RNAi) represents a promising pest control strategy, applicable to both insect-resistant genetically modified (IRGM) crops and sprayable RNAi insecticides. These products can achieve sequence-specific gene silencing and require rigorous environmental risk assessment (ERA) prior to approval. However, current environmental safety assessments of RNAi products and other RNAi experiments frequently use double-stranded EGFP (dsEGFP) as a negative control, while suitable RNAi-based positive controls are lacking. Sometimes conventional chemical toxins (e.g., chlorpyrifos) or protein inhibitors (e.g., trypsin inhibitors) are used as substitutes, but their distinct mechanisms, persistence, and metabolism make them inappropriate for RNAi-specific evaluations. In this study, we evaluated the suitability of RNAi-based positive controls for assessing non-target effects on Harmonia axyridis, a widely distributed predatory beetle used as a bioindicator in biosafety assessments. Under laboratory conditions, we tested one microRNA (miR-92a) and two double-stranded RNAs (dsHaSnf7 and dsHaDiap1) for their effects on H. axyridis. Injection of miR-92a showed no significant difference in mortality compared to controls, whereas dsHaSnf7 and dsHaDiap1 significantly reduced survival rates and target gene expression, as confirmed by qPCR. These findings suggest that HaSnf7 and HaDiap1 are suitable candidate genes for establishing RNAi-specific positive controls in environmental risk assessments of RNAi-based products.

1. Introduction

RNA interference (RNAi) is a gene silencing process activated by double-stranded RNA (dsRNA). The RNAi pathway is initiated by the enzymatic cleavage of dsRNA into small interfering RNAs (siRNAs) by Dicer. These siRNAs are subsequently loaded into the RNA-induced silencing complex (RISC), which guides the sequence-specific recognition and degradation of target mRNAs via complementary base pairing, resulting in post-transcriptional gene silencing [1]. Due to its precision, effectiveness, and safety, RNAi technology has become not only a key method for functional genomics in insects but also a groundbreaking approach for pest control [2].
Building on these applications, RNAi-based products—such as insect-resistant genetically modified (IRGM) crops and sprayable RNA biopesticides—are now advancing toward commercialization [3,4]. However, prior to market release, such RNAi products must undergo rigorous environmental risk assessment (ERA), which is a crucial procedure to ensure environmental safety [5,6]. ERA process aims to evaluate the potential impacts that biopesticides and genetically modified organisms (GMOs) pose to ecosystems and establishes a scientific basis for risk management [7,8,9,10]. In particular, it focused on recognizing and evaluating the possible adverse impacts of biopesticides and GMOs on non-target organisms (NTOs), biodiversity, and ecosystem functionality [11,12,13]. In 2017, the United States Environmental Protection Agency (EPA) approved the commercial cultivation of the transgenic maize MON87411. As the world’s first insect-resistant crop in the form of a Plant-Incorporated Protectant (PIP), this maize variety targets the DvSnf7 gene of the Western Corn Rootworm (Diabrotica virgifera virgifera) and enhances its own resistance to this pest by expressing double-stranded RNA (dsRNA) of the DvSnf7 gene [14,15]. Bachmann et al. conducted an ecological risk assessment (ERA) on MON87411, a transgenic maize line expressing DvSnf7 RNA. Using 14 taxa of non-target organisms (NTOs), including pollinators and natural enemy insects, as research subjects, the team performed laboratory toxicity tests, calculations of the maximum expected environmental concentration (MEEC), and bioinformatics analyses. The results showed that all tested species exhibited no lethal or sublethal effects when exposed to concentrations ≥ MEEC, and the margin of exposure (MOE) for all NTOs was more than 10 times the MEEC. Integrating the key characteristics of DvSnf7 RNA—its activity being restricted to the subfamily Galerucinae (Chrysomelidae, Coleoptera), rapid degradation in the environment, and the presence of digestive barriers in vertebrates—the study ultimately concluded that MON87411 exerts no adverse effects on non-target organisms under field exposure conditions. This study provides a referable methodological framework for the ecological risk assessment of RNA interference (RNAi)-based Plant-Incorporated Protectants (PIPs) [16]. In addition to RNA biopesticides based on Plant-Incorporated Protectants (PIPs), the research progress and commercial applications of sprayable RNA biopesticides—with exogenously synthesized double-stranded RNA (dsRNA) as their core component—have also attracted increasing attention from the industry in recent years. Calantha™, an RNA biopesticide developed for controlling the Colorado Potato Beetle (Leptinotarsa decemlineata), has successfully obtained registration approval from the U.S. Environmental Protection Agency (EPA), making it the world’s first RNA insecticide approved for commercial use that can be directly sprayed onto plant surfaces [17]. Wenninger et al. conducted field experiments in three U.S. states (Idaho, Wisconsin, and Maine) to compare Calantha™—a novel double-stranded RNA (dsRNA) bioinsecticide with ledprona as its active ingredient—with conventional insecticides, in terms of their control efficacy against the Colorado Potato Beetle (Leptinotarsa decemlineata) and impacts on non-target arthropods. The results showed that Calantha™ had no significant negative effects on beneficial insects, neutral insects, or other beetle species, whereas conventional insecticides exhibited stronger non-target effects; additionally, arthropods sampled via vacuuming showed a significantly more pronounced response to insecticides than those sampled via pitfall traps. The study confirmed that rotating Calantha™ with other biorational products can balance pest control and beneficial insect protection, thereby contributing to the biological control of pests in potato fields [18]. Romeis & Widmer’s study focuses on the environmental risk assessment of foliar-sprayed dsRNA products to non-target arthropods. It elaborates on the applications and challenges of RNA interference (RNAi) technology in pest control, introduces the content of the “problem formulation” phase in the context of environmental risk assessment (ERA), analyzes the routes through which non-target arthropods are exposed to dsRNA and the types of hazards posed by dsRNA, and proposes criteria for selecting test species as well as key design points for laboratory toxicity studies. Additionally, the study identifies current uncertainties, such as the transfer of dsRNA in the food chain and the impact of sequence mismatches, and emphasizes the need to flexibly adjust the risk assessment framework to address the unique challenges posed by dsRNA spray products [19].
Yet, despite the established importance of ERA, significant methodological gaps persist, particularly in the design and implementation of appropriate experimental controls for RNAi-based crop assessments. Positive controls are a critical element in toxicity assays conducted to support environmental risk assessment (ERA). They serve several purposes: confirming that test organisms were exposed to the treatment, demonstrating that the test system can detect biological effects, and allowing comparisons with results from other studies [20]. Numerous studies have included species-specific dsRNAs as positive controls in RNAi toxicity assays. For instance, Pan et al. used dsRNA targeting the v-ATPase A gene of the monarch butterfly (Danaus plexippus) itself (designated as dsDP) as the positive control in their research; similarly, Vélez et al., Haller et al., and Pan et al. all adopted species-specific dsRNAs targeting the v-ATPase A gene of their respective test organisms as positive controls in their studies [21,22,23,24]. However, in many studies related to RNA interference, positive controls are either omitted or replaced with chemical insecticides (such as chlorpyrifos), protease inhibitors (such as trypsin inhibitors), or toxic reagents (such as potassium arsenate) [25,26,27]. Such substitutes are unsuitable because their toxicological mechanisms, environmental persistence, and metabolic pathways differ fundamentally from those of RNAi molecules.
For instance, chlorpyrifos, a broad-spectrum neurotoxic insecticide, penetrates insects primarily through the cuticle and midgut, where it is metabolized into chlorpyrifos-oxon. This metabolite irreversibly inhibits acetylcholinesterase (AChE), leading to acetylcholine accumulation, neural dysfunction, paralysis, and ultimately death [28,29,30]. In contrast, RNAi silences insect genes through a sequence-specific degradation of mRNA triggered by exogenous dsRNA. After ingestion, dsRNA is absorbed in the insect midgut and distributed systemically via hemolymph circulation, with intercellular transfer facilitated by the membrane protein Sid-1. Once inside cells, dsRNA is processed by Dicer into 21–23 nt small interfering RNAs (siRNAs), which assemble with Argonaute proteins to form the RISC. Guided by base complementarity, RISC binds to target mRNAs and induces their degradation or translation inhibition, thereby suppressing gene expression and leading to specific phenotypic effects [31]. Meanwhile, dsRNA can be degraded both in the midgut lumen and within cells, mainly through the action of nucleases such as dsRNases and exoribonucleases (e.g., RNase T2), which break it down into nucleotides that enter normal metabolic pathways. Such fundamental mechanistic differences highlight why chemical pesticides cannot serve as mechanistically relevant positive controls for evaluating RNAi-specific effects [32].
Nevertheless, experimental studies in diverse insect species have confirmed that small RNAs remain biologically active and can regulate key physiological processes, thereby influencing growth, development, and survival [33]. Accumulating evidence indicates that siRNAs are functional in insects, where they play pivotal roles in regulating growth, development, and survival. For example, miR-92a in Drosophila regulates memory consolidation, likely through modulation of neuronal excitability [34]. In contrast, the Diap1 (Death-associated inhibitor of apoptosis 1) gene plays a crucial role in insect development by suppressing programmed cell death. The Diap1 protein encoded by this gene inhibits the proteolytic activity of effector caspases (e.g., Drone, DCP-1) through direct binding, thereby blocking apoptosis [35,36,37]. In studies on the Henosepilachna vigintioctopunctata, larvae fed with dsHvDiap1 exhibited acute feeding cessation within 24 h, with 100% larval mortality observed between 2 and 6 days post-feeding. Concurrently, the mRNA expression level of the Diap1 gene in these larvae was significantly reduced, dropping to only 38.4% of that in the control group [37]. In the western corn rootworm (WCR, Diabrotica virgifera virgifera), RNAi-mediated suppression of DvSnf7 expression induces protein deubiquitination and autophagy defects, ultimately resulting in larval mortality. Ultrastructural analyses reveal that silencing triggers endoplasmic reticulum dilation and mitophagic accumulation in WCR midgut cells [38]. Targeting genes such as Diap1 and Snf7 through RNAi has been shown to drastically reduce survival rate in H. vigintioctopunctata, Diabrotica virgifera virgifera producing lethal effects across larval and pupal stages [39,40]. Based on a comprehensive synthesis of existing research findings, the Diap1 and Snf7 genes can stably induce insect mortality following RNA interference (RNAi)-mediated silencing, and this key characteristic makes them ideal candidates for reliable positive controls in RNAi experiments.
It is crucial to test candidate positive controls in ecologically relevant non-target organisms. Insects belonging to the order Coleoptera exhibit high sensitivity to RNAi technology, which makes them ideal targets for pest control utilizing RNAi-based strategies [41,42]. Harmonia axyridis (Coleoptera: Coccinellidae), a widely distributed predatory beetle, plays a critical ecological role by effectively controlling populations of pests such as aphids, whiteflies, and psyllids [43,44]. Due to its broad habitat range, ecological significance, and frequent use in ecotoxicological and non-target organism studies, H. axyridis serves as an ideal representative species for assessing the environmental effects of RNAi-based crops. Its high adaptability, rapid reproductive rate, and broad diet range, further highlight its significance in biological pest management [45,46]. Our study utilizes H. axyridis as a model non-target organism to identify and confirm suitable positive controls for assessing the environmental safety of RNAi-based products. It aims to establish foundational methods and scientific references for standardized protocols in evaluating environmental risks.

2. Materials and Methods

2.1. Insect Strain and Rearing

The H. axyridis used in this experiment were collected from northeastern China in 2018 and reared in an artificial climate chamber with pea aphid, Acyrthosiphon pisum, as the food source. The rearing procedure was as follows: pea plants were cultivated to support pea aphid populations, and fresh pea seedlings infested with A. pisum were collected daily in adequate quantities to sustain H. axyridis feeding. Rearing conditions were maintained at a temperature of 25 ± 1 °C, a relative humidity of 70 ± 10%, and a photoperiod of 16 L: 8 D.

2.2. Isolation of Total RNA and cDNA Synthesis

Total RNA was extracted from H. axyridis specimens using TRlzol® Reagent (Invitrogen, Carlsbad, CA, USA) under strict RNase-free conditions. All procedures were conducted on ice to minimize RNA degradation, with RNase-free microcentrifuge tubes and pipette tips employed throughout the extraction. RNA concentration and purity were quantified using a NanoDrop™ 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA), and RNA integrity was verified by agarose gel electrophoresis. First-strand cDNA was synthesized using the TransScript® Uni All-in-One First-Strand cDNA Synthesis SuperMix (AT311, TransGen Biotech, Beijing, China) following the manufacturer’s protocol. The resulting cDNA products were stored at −80 °C for subsequent analyses.

2.3. miRNA Agomir, Mimics NC, dsRNA Preparation

The miR-92a agomir (sense strand: AUUGCACUAGUCCCGGCCUA, antisense strand: GGCCGGGACUAGUGCAAUUU), mimics negative control (mimics NC) (sense strand: UUGUACUACACAAAAGUACUG, antisense strand: GUACUUUUGUGUAGUACAAUU) were synthesized by Sangon Biotech Co., Ltd. (Shanghai, China).
The nucleic acid sequence of the H. axyridis HaSnf7 gene (NCBI accession number: XM_045627137.1) and the HaDiap1 gene [28] were entered into the SnapDragon—dsRNA Design platform (https://www.flyrnai.org/snapdragon, accession date: 9 September 2025) to identify highly targetable fragments suitable for RNA interference. The T7 promoter sequence (5′-TAATACGACTCACTATAGGG-3′) was added to the 5′ end of the designed primer sequences, and all primers were synthesized by Sangon Biotech Co., Ltd. (Shanghai, China). Enhanced green fluorescent protein (EGFP) was purchased from Shanghai Plant Science Biotechnology Co., Ltd. (Shanghai, China). All primer sequences are listed in Table 1.
The DNA template was amplified using a 2× Phanta Max Master Mix high-fidelity DNA polymerase (Vazyme Biotech Co., Ltd., Nanjing, China). The PCR products were then analyzed by agarose gel electrophoresis to verify their consistency with expected sizes. Target bands were excised and sent to Sangon Biotech Co., Ltd. (Shanghai, China) for Sanger sequencing. Following confirmation of successful sequencing, the validated PCR products were directly used as dsRNA templates and submitted to Shanghai Plant Science Biotechnology Co., Ltd. (Shanghai, China) for subsequent dsRNA synthesis.

2.4. Effects of miRNA and dsRNA on Larval Development

Second-instar larvae of H. axyridis were selected and transferred into plastic Petri dishes (60 mm diameter), and then anesthetized on ice for 5 min to ensure the insects remained sedated without obvious physiological damage during the operation. Each larva was injected with 20 nL of miRNA or dsRNA solution into the second abdominal segment using a digital microinjector system (Nanoject III, Drummond Scientific, Broomall, PA, USA).
Three treatment groups about miRNA were established: miR-92a agomir, mimics NC, and PBS, with each injected at a dosage of 60 ng per larva (3000 ng/μL, 20 nL). Three treatment groups related to dsRNA were established: dsHaDiap1, dsHaSnf7 and dsEGFP, with each injected at a dosage of 400 ng per larva (20 μg/μL, 20 nL).
Thirty larvae were included in each treatment group. Following dsRNA injection, larvae were reared according to the conditions described above. Larval survival was evaluated 12, 24, 36, 48, 60, 72, 84, 96, 108, and 120 h after the RNAi treatment.

2.5. Real-Time Quantitative PCR

The ribosomal protein 49 gene (RP49) was used as an internal reference gene to quantify the mRNA expression levels of HaDiap1 or HaSnf7 in H. axyridis larvae at 0, 2, and 4 days dsHaDiap1 or dsHaSnf7 post-injection. Each sample consisted of 10 larvae, and three biological replicates were performed. The reaction system was configured according to the protocol of the PerfectStart® Green qPCR SuperMix kit (AQ601, TransGen Biotech, Beijing, China), with the following thermal cycling conditions: 94 °C for 30 s (pre-denaturation), followed by 40 cycles of 94 °C for 5 s (denaturation), 60 °C for 30 s (extension). Gene expression levels were calculated using the 2−ΔΔCt method [47]. The primers used in the experiment were obtained through the following process: first, nucleic acid sequences were retrieved from the NCBI database, then the primers were designed using Primer Premier 6.0 software, and finally synthesized by Sangon Biotech Co., Ltd. (Shanghai, China). All qPCR primers are listed in Table 2.

2.6. Data Analysis

Survival data were analyzed using the Log-rank (Mantel–Cox) test. A t-test was performed to assess significant differences in the expression of H. axyridis target genes between dsEGFP and dsHaSnf7 or dsHaDiap1 treatment. All data analyses and graphs were performed and generated using GraphPad Prism v6.01 (GraphPad Software, La Jolla, CA, USA) [48].

3. Results

3.1. Effect of miRNA on Larval Survival Rate

Survival analysis demonstrated that administration of miR-92a did not significantly influence the survival probability of H. axyridis. Initial mortality was detected in the miR-92a group at 12 h post-injection, whereas mortality in the mimics NC and PBS groups was first observed at 60 h. At 120 h, survival remained relatively stable across treatments, with rates ranging from 87.5% to 97.06%. The Log-rank (Mantel–Cox) test revealed no statistically significant differences among the three groups (df = 2, p = 0.2947). Subsequent pairwise comparisons further confirmed the lack of significant survival variation (miR-92a vs. mimics NC: df = 1, p = 0.4049; miR-92a vs. PBS: df = 1, p = 0.1340; mimics NC vs. PBS: df = 1, p = 0.4875) (Figure 1).

3.2. Effect of dsRNA on Larval Survival Rate

Survival analysis revealed that injection of dsHaDiap1 or dsHaSnf7 significantly reduced the survival of H. axyridis larvae. Mortality in the dsHaDiap1 group reached 80% at 12 h and increased to 93% at 36 h. In the dsHaSnf7 group, larval mortality was 93% at 60 h and reached 100% at 72 h. In contrast, larvae injected with dsEGFP maintained a survival rate of approximately 80% at 120 h. A Log-rank (Mantel–Cox) test confirmed significant survival differences among groups (df = 2, p < 0.0001), with subsequent pairwise comparisons further validating these differences (dsEGFP vs. dsHaDiap1: df = 1, p < 0.0001; dsEGFP vs. dsHaSnf7: df = 1, p < 0.0001; dsHaDiap1 vs. dsHaSnf7: df = 1, p < 0.0001) (Figure 2).

3.3. The Expression Levels of Target Genes of dsRNA

To assess gene silencing efficiency, the relative transcript levels of Diap1 and Snf7 were quantified in H. axyridis using qPCR. Injection of dsHaDiap1 triggered a marked reduction in Diap1 expression at 2 h, 6 h, and 12 h post-injection (p = 0.0070, p = 0.0002, p = 0.0219) (Figure 3). Likewise, dsHaSnf7 administration induced a significant and sustained suppression of Snf7 expression, with downregulation observed at 2 h (p = 0.0016), 6 h (p = 0.0005), 12 h (p < 0.0001), 24 h (p = 0.0016), and 48 h (p = 0.0020) (Figure 4).

4. Discussion

The safety assessment of non-target organisms constitutes a crucial part of the environmental safety evaluation for RNAi products [49]. Among the key aspects of non-target organism safety assessment, the selection of positive controls is of particular importance. An ideal positive control should be characterized by a well-defined mechanism of action, as well as stable and reproducible biological effects [50,51,52]. As an important non-target organism, H. axyridis contributes to a more comprehensive evaluation of the environmental safety of RNAi products with respect to non-target organisms [53,54]. In this study, H. axyridis was used as the research object, and one miRNA (miR-92a) and two dsRNA (dsHaDiap1 and dsHaSnf7) were tested as potential positive controls to assess their impacts on the survival rate and target gene expression. This finding provides a scientific basis for the environmental safety evaluation of RNAi products and contribute to promoting sustainable agriculture. This study focused on H. axyridis, a representative predatory beetle of Coleoptera, with the primary aim of developing species-specific positive controls for RNAi-based environmental risk assessment; although the findings are currently limited to this species, the established experimental framework provides a useful reference for similar studies on other non-target insects, and future research will expand to additional insect taxa to identify and validate broader-spectrum RNAi positive controls, thereby improving the general applicability of the results. In the present study, dsRNA was administered to H. axyridis via injection rather than dietary exposure; we acknowledge that under realistic environmental conditions, non-target organisms primarily encounter RNAi molecules through ingesting plant material or spray residues, but the injection method was intentionally selected at this stage to verify the intrinsic gene-silencing activity and biological effectiveness of the dsRNA molecules themselves, as this approach minimizes variability in uptake efficiency, degradation, and stability that may occur in dietary assays. Although the injection method does not mimic the natural exposure pathway, it provides an effective and valuable means of verifying RNAi activity and serves as a practical strategy for establishing positive controls in non-target risk assessment studies.
Injection of miR-92a into H. axyridis larvae did not significantly affect survival rates, suggesting that miR-92a may not be suitable as a positive control for miRNA safety evaluation in this species. miR-92a plays an important role in the physiological and pathological processes of insects. In the mushroom body neurons of Drosophila, miR-92a target the kinesin Khc73 (a protein involved in synaptic vesicle transport), thereby inhibiting the formation of anesthesia-resistant memory (ARM). Studies have shown that inhibiting the expression of miR-92a significantly enhance the 3-h memory retention capacity [34]. While the underlying mechanisms remain unclear, we tentatively propose that miR-92a injection into H. axyridis could influence memory function without necessarily causing lethality. Thus, it is not suitable as a positive control for lethality tests.
Injection of dsHaDiap1 or dsHaSnf7 significantly reduced both larval survival and target gene expression. Specifically, dsHaDiap1-treated larvae exhibited 93% mortality within 36 h, while dsHaSnf7 treatment resulted in 100% mortality within 72 h. The approximately 20% mortality in the dsEGFP group aligns with the research results of Chen et al. Thus, this mortality is deemed a normal physiological response to the injection process, not an effect of dsEGFP [55]. These results demonstrate that dsHaDiap1 and dsHaSnf7 exert potent lethal effects on H. axyridis larvae, positioning them as suitable positive controls for RNAi products safety assessment. Diap1, a key member of the Inhibitor of Apoptosis Protein (IAP) family, can regulate insect growth, development, and immune responses by inhibiting cell apoptosis [56]. In Henosepilachna vigintioctopunctata (the 28-spotted potato ladybug), larvae fed with dsHvDiap1 showed acute cessation of feeding within 24 h, and all larvae died within 2–6 days; meanwhile, the mRNA level of Diap1 significantly decreased to 38.4% of that in the control group [37]. Other studies have demonstrated that when larvae of Musca domestica (housefly) and Delia radicum (cabbage root fly) were injected with different doses of dsHaDiap1, the lethal effect exhibited a dose-dependent manner; 24 h after injection, the mRNA level of Diap1 significantly dropped to less than 30% of that in the control group [36]. Our findings are consistent with those of the aforementioned studies.
Snf7, a key component of the endosomal sorting complex required for transport (ESCRT)-III, is involved in the formation of multivesicular bodies (MVBs) and protein transport processes [39]. Currently, studies on Snf7 in insects belonging to Coleoptera, Hemiptera, and Thysanoptera have been reported. In WCR, after larvae were fed with dsDvSnf7, the mRNA level of DvSnf7 in the larval midgut and fat body tissues significantly decreased, with the expression level in the midgut tissue downregulated by approximately 140-fold, and that in the fat body tissue by approximately 13-fold; meanwhile, the inhibition of dsDvSnf7 could lead to larval growth arrest and death within 5 days [39]. In the study on H. vigintioctopunctata, after larvae were fed with dsHvSnf7 at different concentrations (5, 10, and 50 ng/μL), the larval mortality significantly increased within 10 days in a dose-dependent manner, with the mortality rates of 78% in the 50 ng/μL group, 70% in the 10 ng/μL group, and 54% in the 5 ng/μL group; when the feeding concentration was 10 ng/μL, the expression level of HvSnf7 was inhibited by 19.32-fold and 9.99-fold on days 2 and 4, respectively [57]. In addition, after low-dose interference (injection and feeding methods) on NlSnf7 of Nilaparvata lugens (brown planthopper), the mRNA expression level of NlSnf7 significantly decreased, with the corrected mortality rate reaching 70% on day 13 after injection of 50 ng per insect and 48% on day 9 after feeding with 50 ng/μL; moreover, the protein level of NlSnf7 also significantly decreased on day 5 after injection of dsNlSnf7 [58]. Another study showed that after Thrips tabaci (onion thrips) was fed with dsSnf7, the mRNA level of the target gene decreased by 16.4-fold [59]. In Cylas formicarius (sweet potato weevil), when fed with dsSnf7 at a concentration of 1 μg/mL, the mortality rate could reach 69.1% [60]. Our research findings are in agreement with those of the aforementioned studies.
Snf7, a key component of the endosomal sorting complex required for transport (ESCRT)-III, is involved in the formation of multivesicular bodies (MVBs) and protein transport processes [39]. Currently, studies on Snf7 in insects belonging to Coleoptera, Hemiptera, and Thysanoptera have been reported. In WCR, after larvae were fed with dsDvSnf7, the mRNA level of DvSnf7 in the larval midgut and fat body tissues significantly decreased, with the expression level in the midgut tissue downregulated by approximately 140-fold, and that in the fat body tissue by approximately 13-fold; meanwhile, the inhibition of dsDvSnf7 could lead to larval growth arrest and death within 5 days [39]. In the study on H. vigintioctopunctata, after larvae were fed with dsHvSnf7 at different concentrations (5, 10, and 50 ng/μL), the larval mortality significantly increased within 10 days in a dose-dependent manner, with the mortality rates of 78% in the 50 ng/μL group, 70% in the 10 ng/μL group, and 54% in the 5 ng/μL group; when the feeding concentration was 10 ng/μL, the expression level of HvSnf7 was inhibited by 19.32-fold and 9.99-fold on days 2 and 4, respectively [57]. In addition, after low-dose interference (injection and feeding methods) on NlSnf7 of Nilaparvata lugens (brown planthopper), the mRNA expression level of NlSnf7 significantly decreased, with the corrected mortality rate reaching 70% on day 13 after injection of 50 ng per insect and 48% on day 9 after feeding with 50 ng/μL; moreover, the protein level of NlSnf7 also significantly decreased on day 5 after injection of dsNlSnf7 [58]. Another study showed that after Thrips tabaci (onion thrips) was fed with dsSnf7, the mRNA level of the target gene decreased by 16.4-fold [59]. In Cylas formicarius (sweet potato weevil), when fed with dsSnf7 at a concentration of 1 μg/mL, the mortality rate could reach 69.1% [60]. Our research findings are in agreement with those of the aforementioned studies.
For the above reasons, we selected these miRNAs and dsRNAs as candidate positive controls and tested their lethal effects on H. axyridis. H. axyridis is widely distributed in farmland ecosystems. Both adults and larvae of this species can prey on a variety of field pests. Additionally, due to their habit of feeding on pollen, they may come into direct or indirect contact with RNAi products. H. axyridis belongs to the order Coleoptera. Compared with insects of other orders, Coleoptera insects are generally more sensitive to RNAi products; thus, RNAi products may pose potential impacts on H. axyridis. As an important indicator insect for ESA, when conducting ESA of RNAi products for H. axyridis, the screening of positive controls is not only a necessary part of experimental design but also an important basis for ensuring the reliability of data and the scientific validity of conclusions. Based on this, this study focuses on screening positive controls suitable for the ESA of RNAi products, aiming to provide the necessary scientific basis for the ESA of RNAi products.
This study establishes key parameters for RNAi positive controls screening using H. axyridis as a model. Future research should expand gene screening to identify suitable microRNAs and experimentally validate their silencing efficiency, as well as develop feeding-based dsRNA positive control methods to enable oral delivery assessments. Together, these approaches will extend the present findings and contribute to more comprehensive risk evaluation frameworks for RNAi technologies.

5. Conclusions

This study identified dsHaDiap1 and dsHaSnf7 as effective positive controls for the safety assessment of RNAi products using H. axyridis as a representative non-target organism. Both dsRNAs produced strong gene-silencing and lethal effects, confirming their suitability for use as standard references in RNAi-based environmental risk assessment. In contrast, miR-92a did not significantly affect survival, suggesting it is unsuitable as a lethality control. Overall, the findings contribute to establishing standardized methodologies for environmental safety assessment of RNAi products and support the advancement of safe, sustainable applications of RNAi technologies in agriculture.

Author Contributions

Conceptualization, X.Y. and L.H.; methodology, X.Y., J.L. and Y.T.; formal analysis, K.D. and F.C.; investigation, K.D. and F.C.; data curation, K.D., F.C., G.C. and Q.Z.; writing—original draft preparation, K.D., F.C. and Q.Z.; writing—review and editing, X.Y., G.C., J.L., Y.T. and L.H.; supervision, X.Y. and J.L.; project administration, X.Y. and L.H.; funding acquisition, X.Y. and L.H. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Biological Breeding-Major Projects (2023ZD04062), and the Scientific and Technological Innovation Project of the Chinese Academy of Agricultural Science.

Data Availability Statement

The original contributions presented in the study are included in the article, and further inquiries can be directed to the corresponding authors.

Conflicts of Interest

The authors declare no conflicts of interest. The funding sources had no role in the study design, data collection, analysis, interpretation, manuscript writing, or the decision to submit this article for publication.

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Figure 1. Effect of miR-92a injection on larval survival in H. axyridis. Treatments included injection of miR-92a agomir (miR-92a), mimics negative control (mimics NC), and PBS. Kaplan–Meier survival curves were generated using GraphPad Prism, with the dotted line representing the 95% confidence interval (CI). Statistical significance was assessed using the log-rank (Mantel–Cox) test; ns indicates no significant difference.
Figure 1. Effect of miR-92a injection on larval survival in H. axyridis. Treatments included injection of miR-92a agomir (miR-92a), mimics negative control (mimics NC), and PBS. Kaplan–Meier survival curves were generated using GraphPad Prism, with the dotted line representing the 95% confidence interval (CI). Statistical significance was assessed using the log-rank (Mantel–Cox) test; ns indicates no significant difference.
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Figure 2. Survival rate of H. axyridis after dsRNA injection. Treatments included dsEGFP, dsHaDiap1, and dsHaSnf7. Kaplan–Meier survival curves were generated using GraphPad Prism, with the dotted line representing the 95% confidence interval (CI). Survival differences were analyzed using the log-rank (Mantel–Cox) test (***: p < 0.001).
Figure 2. Survival rate of H. axyridis after dsRNA injection. Treatments included dsEGFP, dsHaDiap1, and dsHaSnf7. Kaplan–Meier survival curves were generated using GraphPad Prism, with the dotted line representing the 95% confidence interval (CI). Survival differences were analyzed using the log-rank (Mantel–Cox) test (***: p < 0.001).
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Figure 3. Expression level of HaDiap1 gene after dsHaDiap1 injection. Note: dsEGFP: injection of dsEGFP; dsHaDiap1: injection of dsHaDiap1. Data are presented as means ± SE from n = 8 (dsEGFP and dsHaDiap1). Statistical significance between two groups at the same time was determined using t-test (*: p < 0.05, **: p < 0.01, ***: p < 0.001, ns: not significant).
Figure 3. Expression level of HaDiap1 gene after dsHaDiap1 injection. Note: dsEGFP: injection of dsEGFP; dsHaDiap1: injection of dsHaDiap1. Data are presented as means ± SE from n = 8 (dsEGFP and dsHaDiap1). Statistical significance between two groups at the same time was determined using t-test (*: p < 0.05, **: p < 0.01, ***: p < 0.001, ns: not significant).
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Figure 4. Expression level of HaSnf7 gene after dsHaSnf7 injection. Note: dsEGFP: injection of dsEGFP; dsHaSnf7: injection of dsHaSnf7. Data are presented as means ± SE from n = 8 (dsEGFP and dsHaSnf7). Statistical significance between two groups at the same time was determined using t-test (**: p < 0.01, ***: p < 0.001, ns: not significant).
Figure 4. Expression level of HaSnf7 gene after dsHaSnf7 injection. Note: dsEGFP: injection of dsEGFP; dsHaSnf7: injection of dsHaSnf7. Data are presented as means ± SE from n = 8 (dsEGFP and dsHaSnf7). Statistical significance between two groups at the same time was determined using t-test (**: p < 0.01, ***: p < 0.001, ns: not significant).
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Table 1. Primer sequences used in this study.
Table 1. Primer sequences used in this study.
Primer NameSequence (5′-3′)
HaSnf7-FT7-CGGATGAAGCACCAAGTACG
HaSnf7-RT7-TCAGGAAGTTTGTTTGTAGGCA
HaDiap1-FT7-AAACCCATAGACCTGGCTGC
HaDiap1-RT7-TCAAGGCTGACGCACAATCT
Note: T7 in the table represents sequence TAATACGACTCACTATAGGG.
Table 2. Primers for qPCR.
Table 2. Primers for qPCR.
Primer NameSequence (5′-3′)
HaSnf7-FTGGGCCTCATAAGGACAAAT
HaSnf7-RATTCATAATGAGGCAACGTTCT
HaDiap1-FGCAGCAGTACACTCATTCCT
HaDiap1-RGGTCTTCAGTCGGTCTATTGTT
HaRP49-FGCGATCGCTATGGAAAACTC
HaRP49-RTACGATTTTGCATCAACAGT
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Ding, K.; Yang, X.; Zhou, Q.; Chen, G.; Chen, F.; Tan, Y.; Li, J.; Han, L. Screening of Positive Controls for Environmental Safety Assessment of RNAi Products. Agronomy 2025, 15, 2399. https://doi.org/10.3390/agronomy15102399

AMA Style

Ding K, Yang X, Zhou Q, Chen G, Chen F, Tan Y, Li J, Han L. Screening of Positive Controls for Environmental Safety Assessment of RNAi Products. Agronomy. 2025; 15(10):2399. https://doi.org/10.3390/agronomy15102399

Chicago/Turabian Style

Ding, Kaixuan, Xiaowei Yang, Qinli Zhou, Geng Chen, Fengping Chen, Yao Tan, Jing Li, and Lanzhi Han. 2025. "Screening of Positive Controls for Environmental Safety Assessment of RNAi Products" Agronomy 15, no. 10: 2399. https://doi.org/10.3390/agronomy15102399

APA Style

Ding, K., Yang, X., Zhou, Q., Chen, G., Chen, F., Tan, Y., Li, J., & Han, L. (2025). Screening of Positive Controls for Environmental Safety Assessment of RNAi Products. Agronomy, 15(10), 2399. https://doi.org/10.3390/agronomy15102399

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