Environmental RNA interference in two-spotted spider mite, Tetranychus urticae, reveals dsRNA processing requirements for efficient RNAi response

Abstract

Comprehensive understanding of pleiotropic roles of RNAi machinery highlighted the conserved chromosomal functions of RNA interference. The consequences of the evolutionary variation in the core RNAi pathway genes are mostly unknown, but may lead to the species-specific functions associated with gene silencing. The two-spotted spider mite, Tetranychus urticae, is a major polyphagous chelicerate pest capable of feeding on over 1100 plant species and developing resistance to pesticides used for its control. A well annotated genome, susceptibility to RNAi and economic importance, make T. urticae an excellent candidate for development of an RNAi protocol that enables high-throughput genetic screens and RNAi-based pest control. Here, we show that the length of the exogenous dsRNA critically determines its processivity and ability to induce RNAi in vivo. A combination of the long dsRNAs and the use of dye to trace the ingestion of dsRNA enabled the identification of genes involved in membrane transport and 26S proteasome degradation as sensitive RNAi targets. Our data demonstrate that environmental RNAi can be an efficient reverse genetics and pest control tool in T. urticae. In addition, the species-specific properties together with the variation in the components of the RNAi machinery make T. urticae a potent experimental system to study the evolution of RNAi pathways.

Introduction

The ability of double-stranded RNA (dsRNA) to inhibit the expression of a complementary target gene in a process named RNA interference (RNAi) was first demonstrated in plants and Caenorhabditis elegans^1,2 and was since discovered in a wide range of organisms^3–5. The RNAi is guided by small RNAs that can be generated from different precursor RNA molecules. Short interfering RNAs (siRNAs) are generated from dsRNAs. They interfere with the expression of viral and transposon-originating transcripts or direct chromatin modifications that are essential for proper chromosomal functions^6,7. Micro-RNAs (miRNAs) are processed from genome-encoded hairpins that contain local stem-loop structures. These precursor RNAs undergo a series of maturation steps to generate Argonaute-associated miRNAs that primarily silence protein-coding mRNAs through either translational inhibition or mRNA degradation. Finally, single-stranded RNA (ssRNA) precursors, transcribed from chromosomal loci that mostly consist of remnants of transposable element sequences, give rise to PIWI-interacting RNAs (piRNAs). They are mainly active in germ-line tissues, where they transcriptionally silence transposable elements⁷.

Understanding of the siRNA RNAi pathway led to the use of the exogenously supplied dsRNA to trigger RNAi (termed environmental RNAi⁸). This opened possibilities to develop RNAi as a reverse genetics tool^9–13 and more recently as an environmentally friendly strategy for pest control^14,15. The stability of the exogenous dsRNAs in body fluids, their cellular uptake, and spread to distal tissues that were not in direct contact with the initially delivered dsRNA were identified as key elements for the efficient environmental RNAi. However, the variability in the gut pH and the presence of dsRNases in gut and/or hemolymph that lead to dsRNA hydrolysis and degradation, limit the use of RNAi in many insect clades (reviewed in Cooper et al.¹⁶). Consequently, many arthropods (e.g. some lepidopterans) are refractory to the environmental RNAi. Others (such as some coleopterans, blattodeans and orthopterans) can induce the environmental RNAi only by the injection of dsRNA, restricting its use to reverse genetics. Finally, only a subset of arthropods that respond to the orally delivered dsRNAs are potential candidate species for whom environmental RNAi can be used as a reverse genetics and a pest control tool¹⁶.

The two-spotted spider mite, Tetranychus urticae, is an important agricultural pest that feeds on more than a thousand plant species including over 150 crops¹⁷. Consistent with its outstanding xenobiotic resistance against plant allelochemicals, T. urticae populations can rapidly develop resistance to pesticides used for its control¹⁸, hindering the control of mite infestations in agricultural settings. T. urticae is also a model chelicerate whose genome is well annotated and constantly updated¹⁹. In addition, numerous datasets describing mite transcriptional changes associated with developmental progression, pesticide resistance, or upon host-shift, are available^19–24. Furthermore, the candidate loci underlying mite physiological processes (e.g. diapause, carotenoid biosynthesis) and pesticide resistance using forward genetic approaches have been recently identified^25,26. However, the assessment of the in vivo function of candidate loci, at the level of an otherwise unperturbed whole organism, is so far lacking. In the absence of well-established reverse genetics tools, a demonstration that proteins encoded by candidate loci have capabilities to modify mite physiology rely on the expression of candidate genes in heterologous systems or on in vitro assays. Thus, the development of reverse genetics tools is essential for the understanding of gene function and the unique features of T. urticae biology.

The analysis of the T. urticae genome identified significant variation in RNAi core machinery compared with other arthropods¹⁹. T. urticae harbours a single copy of pasha and drosha genes, two dicer homologs, seven argonaute and seven piwi genes. T. urticae lacks R2D2 that is a co-factor of Dicer-2 in Drosophila, however, it contains two copies of loquacious gene. Finally, unlike in insects and crustaceans, the mite genome contains five homologs of RNA dependent RNA polymerase (RdRP) genes¹⁹. Pleiotropic roles of RNAi in gene silencing and chromosomal functions (reviewed in Gutbrod and Martienssen⁶), together with the contribution of core RNAi proteins to more than one RNAi pathway, confines an understanding of the functional implications of the diversity and evolutionary variation in RNAi machinery^7,16,27,28. Regardless, it has been demonstrated that maternal injections of dsRNA and siRNA, and oral delivery of dsRNA can induce environmental RNAi in T. urticae^29–32. Here, we investigated the effect of sequence composition and length of the exogenous dsRNA on the efficiency of RNAi and its processivity by Dicer using both in vivo and in vitro analysis. Understanding the length requirement of the exogenous dsRNA and utilization of tracer dye to control the variability in dsRNA ingestion led to the development of a highly efficient RNAi protocol. The protocol was rigorously tested against twelve T. urticae homologs of Tribolium castaneum sensitive RNAi targets³³, demonstrating that environmental RNAi can be an efficient reverse genetics and pest control tool in T. urticae. In addition, the species-specific properties together with the variation in the complement of RNAi pathway genes identified in the T. urticae genome make the two-spotted spider mite a potent experimental system to study the evolution of RNAi pathways.

Results

TuCOPB2 is a sensitive target for RNAi

We previously identified TuVATPase as a sensitive RNAi target. However, only about 50% of treated mites responded to the application of dsRNA and developed RNAi-associated phenotype³². To ensure that the improvement of the RNAi protocol is independent of the target gene and results in the general enhancement of RNAi efficiency, we first identified an additional target whose silencing leads to a trackable phenotype. Previously, Kwon et al.^30,31 identified TuCOPB2 as a sensitive RNAi target following leaf-disc mediated delivery of dsRNA. To test the ability of dsRNA-TuCOPB2 to induce RNAi-associated phenotypic changes, we designed two independent dsRNA-TuCOPB2 fragments (fragment A of 308 bp and B of 513 bp (DNA sequences used for the generation of dsRNA-TuCOPB2-A and dsRNA-TuCOPB2-B are shown in Fig. 1A)) and delivered them at a concentration of 160 ng/µL to mites using the soaking method^32,34. As a control, we used the dsRNA-NC (382 bp in length) that has complementarity against the non-transcribed intergenic region of the T. urticae genomic scaffold 12, Fig. 1A. Two days post dsRNA treatment, 62% and 51% of mites treated with dsRNA-TuCOPB2-A and -B, respectively, exhibited smaller size and a light red–orange color, referred to as a spotless phenotype (Fig. 1B; spotless). Mites treated with dsRNA-NC invariably displayed the two distinctive black spots (Fig. 1B; normal). To ensure that the spotless phenotype is associated with the RNAi response, we grouped mites post dsRNA-TuCOPB2 treatment based on their body phenotype and characterized mite fitness parameters and the expression of the TuCOPB2 in these mite subpopulations separately. The survivorship and the fecundity of mites treated with dsRNA-TuCOPB2-A or -B, displaying the normal body phenotype, were similar to these fitness parameters observed in mites treated with dsRNA-NC (Fig. 1C,D; normal body phenotype). However, mites treated with dsRNA-TuCOPB2-A or -B, displaying the spotless phenotype, had significantly lower survivorship and dramatically reduced fecundity (≥ 90% reduction) compared to the control (Fig. 1C,D; spotless body phenotype). Furthermore, the expression level of the endogenous TuCOPB2 transcripts was significantly reduced (by about 50%) in spotless mites relative to mites treated with dsRNA-NC (Fig. 1E). Thus, reminiscent of the effectiveness of dsRNA-TuVATPase, dsRNA-TuCOPB2 induced strong RNAi in approximately 50% of treated mites. The silencing of TuCOPB2 resulted in a trackable phenotype, identifying an independent target gene that can be used together with TuVATPase for the improvement of RNAi efficiency in T. urticae.

Figure 1.

dsRNA-TuCOPB2 induces a spotless body phenotype in a portion of treated adult female mites. (A) Schematics of the TuCOPB2 locus depicting DNA sequences used for the generation of dsRNA-TuCOPB2-A and dsRNA-TuCOPB2-B. The part of the scaffold 12 of T. urticae genome depicting the location of the 382 bp fragment that was used to synthesize dsRNA-NC. (B) Female mites showing the normal and spotless phenotypes, and the proportion of mites displaying the spotless phenotype after soaking mites in the solution of dsRNA-NC, dsRNA-TuCOPB2-A, and dsRNA-TuCOPB2-B (160 ng/µL). The bars represent the proportion of mites displaying phenotype and error bars represent 95% CI of the proportion. Data were analyzed with Fisher’s exact test followed by Bonferroni correction for multiple comparisons. Different letters indicate significant differences, P < 0.05. (C) Adult mite survivorship over 10 days after 24 h soaking in the solution of TuCOPB2-A, dsRNA-TuCOPB2-B, or dsRNA-NC (160 ng/µL). Survival curves of normal and spotless mites were plotted using the Kaplan–Meier method and compared using the log-rank test with Bonferroni correction (**P < 0.01; ***P < 0.001). (D) Fecundity of normal and spotless mites after 24 h soaking in the solution of TuCOPB2-A, dsRNA-TuCOPB2-B, or dsRNA-NC. Statistical analysis was performed using the Wilcoxon–Mann–Whitney test with Bonferroni correction (*P < 0.05; ***P < 0.001). (E) TuCOPB2 expression levels were normalized to the expression of the reference genes RP49 and CycA and were shown relative to the expression in the negative control (NC). Data are represented as a mean ± SEM. Data were analyzed with one way-ANOVA followed by Dunnett’s test (**P < 0.01). All experiments were performed in 3 independent experimental trials.

Long dsRNAs are required for the efficient RNAi in T. urticae

The length of dsRNAs has been shown to be an important parameter affecting the efficiency of RNAi in a wide range of organisms^35–38. To test the effect of dsRNA size on RNAi efficiency in T. urticae, a series of nested dsRNA fragments against TuVATPase and TuCOPB2 were evaluated for their ability to induce RNAi-associated mite phenotypes (dark-body phenotype upon the application of dsRNAs targeting the TuVATPase and spotless phenotype upon the application of dsRNAs against the TuCOPB2), Fig. 2A. The longest fragment had 600 bp (shown in red), while shorter fragments (400, 200, and 100 bp) were overlapping at either the 5′ (shown in green) or the 3′ (shown in blue) ends of the 600 bp-fragment. The effectiveness of dsRNAs fell in two classes: (a) short dsRNAs, 100 and 200 bp in length, induced limited RNAi responses (≤ 4.4% and ≤ 19% of treated mites developed RNAi-associated phenotypes when treated with 100 bp and 200 bp dsRNA fragments, respectively); and (b) dsRNA fragments of 400 and 600 bp had similar RNAi efficiency and induced RNAi-associated phenotypes in ≥ 46% of treated mites, Fig. 2A.

Figure 2.

Long dsRNAs are required for the efficient processing of dsRNAs and RNAi. (A) The effect of dsRNAs length on RNAi efficacy. Sizes and positions of dsRNAs targeting TuCOPB2 and TuVATPase are shown in red for the longest dsRNAs (600 bp), in green for the shorter overlapping fragments (400, 200 and 100 bp) positioned at the 5′ ends of the 600 bp-fragment, and in blue for the shorter fragments positioned at the 3′ ends of the 600 bp-fragment. RNAi efficacy is measured as the frequency of spotless (after treatment with dsRNA-COPB2) and dark-body (after treatment with dsRNA-TuVATPase) phenotypes. (B) Frequency of dark mites upon the application of dsRNAs of different lengths and sequence coverage. dsRNA-TuVATPase fragments spanning 200 bp at either the 5′ or 3′ end of the 600 bp-fragment were applied individually or as a mix. A 400-5′ bp dsRNA-TuVATPase fragment was used as a control. (C) Frequency of dark mites upon treatment with the dsRNA-TuVATPase 100-5′ and the chimeric dsRNA fragment that is composed of 100-5′ bp TuVATPase fragment and 385 bp fragment corresponding to dsRNA-NC sequence. Application of dsRNA-TuVATPase 600 bp was used as a control. (A–C) All fragments were applied at 160 ng/µL. Data represent the 95% confidence interval of the proportion of mites displaying phenotype. Data were analyzed with Fisher’s exact test followed by Bonferroni correction for multiple comparisons. Different letters indicate significant differences, P < 0.05. (D) Dicing (dsRNA-cleaving) activities of crude mite extracts incubated with ³²P-labeled dsRNA-TuVATPase of different lengths (600, 400, 200, and 100 bp) at 22 °C for 2 h. Long dsRNAs and processed small RNAs were detected by autoradiography. No crude extract was used as the negative control. M indicates a size marker (21 nt). (E) The radioactive intensity of siRNA products relative to the total intensity. Data were analyzed with one-way ANOVA followed by Tukey’s HSD test. Different letters indicate significant differences, P < 0.05. All data were collected from three independent experimental runs.

The greater efficiency of longer dsRNA fragments could be due to greater target sequence coverage of siRNAs generated from dsRNA precursor or can arise from greater efficiency of cellular uptake and/or processing. To differentiate between these possibilities, we first compared the RNAi efficacy of a mix of two dsRNAs of 200 bp in length relative to the application of a single dsRNA of 400 bp. If uptake and processing of these dsRNAs are similar, then these treatments are expected to have similar RNAi efficiency as they are expected to generate a similar complement of siRNAs. However, if the uptake and/or processing of dsRNAs of different lengths differ, the RNAi efficacy of long dsRNA is expected to be greater than that of short dsRNAs. As shown in Fig. 2B, dsRNAs of 200 bp in length, either individually or as a mix, had significantly lower ability to induce RNAi-associated phenotype relative to the 400 bp fragment, suggesting that the ineffectiveness of short dsRNAs is not due to the lack of sequence variation. To further understand the contribution of dsRNA length on the effectiveness of RNAi, we prepared the chimeric dsRNA fragment consisting of a 100-5′ sequence complementary to TuVATPase (Fig. 2A) and 382 bp of non-transcribed sequence used in the dsRNA-NC (Fig. 1A). Comparison of RNAi responses triggered by the 100-5′dsRNA-TuVATPase and the chimeric fragment revealed that the chimeric fragment was about 11 times more efficient, Fig. 2C. As these fragments are expected to give rise to similar pools of effective siRNAs, the differential effectiveness of these dsRNAs indicates that their uptake or processivity may differ.

To directly test if the processivity of dsRNAs is dependent on the length of dsRNAs, we established a biochemical method to monitor the Dicer dsRNA-cleaving activity in mite cell-free extracts. By mixing the crude mite protein extract with ³²P-labeled dsRNAs of different lengths as substrates, we were able to visualize the cleaved RNA products using denaturing polyacrylamide gel electrophoresis (PAGE) and autoradiography. As seen in Fig. 2D,E, and Supplemental Fig. 2³², P-labeled small RNAs tightly correlated with the progressive increase of dsRNA length. These results demonstrate that Dicer preferentially cleaves long dsRNAs in T. urticae. Thus, dsRNAs of ≥ 400 bp in length are required for the efficient processing of dsRNAs and RNAi in T. urticae.

Tracing the dsRNA ingestion increases RNAi responsiveness to > 90% in treated mite populations

Even the length-optimized dsRNAs induced RNAi only in a subset of treated mites, Fig. 2. A variation in dsRNA uptake, tracked by the addition of dye into dsRNA solution, was previously reported for aphids³⁹. To test if mites soaked in dsRNA solution ingest dsRNA differentially, we used a 6% blue food dye that can be easily visualized in mite posterior midgut, Fig. 3A, and mixed it in dsRNA solution. Upon soaking, 64% and 66% of the total mites treated with dsRNA-TuVATPase-B and dsRNA-TuCOPB2-B showed blue color in the posterior midgut, respectively. When mites were preselected for the presence of blue dye in their gut, the proportion of mites displaying the RNAi-associated phenotypes was greater than 90% (94% and 95% of mites treated with dsRNA-TuVATPase-B and dsRNA-TuCOPB2-B displayed dark-body and spotless phenotypes, respectively (Fig. 3B)). Mites without the visible accumulation of dye had a significantly lower frequency of body phenotypes associated with RNAi responses (Fig. 3B). Thus, the blue dye could be used as a dsRNA tracer, securing the RNAi responsiveness in the majority of treated mites.

Figure 3.

Blue dye can be used as a tracer to correct for the variability in dsRNA ingestion. (A) Representative images showing absence (white) or accumulation of tracer dye (blue) in the posterior midgut after mite treatment with a solution containing 6% blue dye. (B) Frequency of dark and spotless mites upon mite soaking in the solution of blue dye that was mixed with dsRNA-TuVATPase or dsRNA-TuCOPB2, respectively. Data represent the 95% confidence interval of the proportion of mites displaying dark-body (on the left) and spotless (on right) phenotypes. Statistical analysis was performed using Fisher’s exact test. ***P < 0.001.

The effect of dsRNA concentration on RNAi efficacy

Several application methods for the oral delivery of dsRNA to T. urticae have been developed^30,32,38. These methods use a wide range of dsRNA concentrations, from 40 up to 1 µg/µL. To determine the effective dsRNA concentrations and the potential toxicity of high concentrations of dsRNAs due to the possible oversaturation of the RNAi machinery, we applied dsRNA-TuVATPase, dsRNA-TuCOPB2 and dsRNA-NC in the range of 20 to 1280 ng/µL and scored mite survivorship, Fig. 4. At 20 ng/µL, individual dsRNAs against TuVATPase and TuCOPB2 did not affect mite mortality, Fig. 4A. However, the mixture of these dsRNAs (at the concentration of 20 ng/µL each) acted synergistically and resulted in a significant decrease of mite survivorship, Fig. 4B. dsRNA-TuVATPase and dsRNA-TuCOPB2 induced significant mite mortality (80%) at 40 and 80 ng/µL, respectively, and their responses were saturated at 160 ng/µL, Fig. 4A. Therefore, even though the effective concentrations of dsRNA may vary dependent on the target, the concentration of 160 ng/µL of dsRNA appears to be sufficient to induce the full RNAi response and was used in subsequent experiments. High concentrations of dsRNAs, at 1280 ng/µL, did not affect mite mortality (Fig. 4C), indicating that dsRNA at this concentration was not toxic to mites and did not oversaturate the RNAi machinery.

Figure 4.

RNAi dose–response curves following dsRNA treatment. (A) Adult survivorship following mite treatment with dsRNA-TuVATPase and dsRNA-TuCOPB2 at 20, 40, 80, 160, and 320 ng/µL. (B) Synergistic effect of combined application of dsRNA-TuVATPase and dsRNA-TuCOPB2 at 20 ng/µL each, on adult survivorship. (C) Adult survivorship following treatment with dsRNA-NC at 20, 160, and 1280 ng/µL. All experiments were performed in 3 independent trials. Survival curves were plotted using the Kaplan–Meier method and compared using the log-rank test with Bonferroni correction (not significant, P > 0.05; ***P < 0.001).

Testing the effectiveness of RNAi on a broad range of gene targets

Almost complete RNAi responsiveness of mite populations to dsRNA-TuVATPase and dsRNA-TuCOPB2 using the optimized method raises a possibility to use RNAi as a reverse genetics tool in T. urticae. However, the use of RNAi as a tool to induce loss-of-function phenotypes requires a demonstration of RNAi effectiveness on a broader range of target genes. Previously, Ulrich et al.³³ performed an RNAi screen of 5,000 randomly selected Tribolium castaneum genes and identified eleven highly efficient RNAi targets whose silencing led to 100% mortality of Tribolium larvae. These genes are predicted to encode conserved proteins that perform essential cellular functions involved in membrane transport, degradation of ubiquitinated proteins through 26S proteasome, protein folding and secretion, and regulation of gene expression, Table 1, and were proposed to be conserved candidate RNAi targets across arthropods. Thus, to test the efficiency of the optimized RNAi protocol on a greater number of genes, we identified T. urticae orthologs of Tribolium RNAi targets, Table 1. The search of T. urticae orthologs revealed that T. urticae genome contains two copies of Pp1a-96a locus, both of which were included in our analysis. Pp1a-96a orthologs share 78% CDS sequence identity (95% aa identity) and are further referred to as TuPp1α-96a-A and TuPp1α-96a-B.

Table 1.

List of T. urticae orthologs of Tribolium RNAi sensitive genes.

Name	Tc-gene	Tu-ortholog	Gene symbol	Cellular function
Ras opposite	TC011120	tetur13g00570	TuRop	SNARE binding
Alpha soluble NSF attachment protein	TC013571	tetur06g05400	TuSnap α	Vesicular transport
Shirbire	TC011058	tetur07g07190	TuShi	Actin and microtubule binding activity
Regulatory particle triple-A ATPase 3	TC007999	tetur32g01800	TuRpt3	Subunit of the 26S proteasome
Regulatory particle non-ATPase 7	TC006375	tetur33g01390	TuRpn7	Subunit of the 26S proteasome
Heat shock 70-kDa protein cognate 3	TC004425	tetur08g01320	TuHsc70-3	Protein folding
Signal recognition particle protein 54 k	TC002574	tetur17g03110	TuSrp54	Protein secretion
Cactus	TC002003	tetur14g01540	TuCac	Regulation of gene expression
Inverse regulator a	TC008263	tetur04g01220	TuInr-a	RNA cleavage and polyadenylation factor
Gawky	TC006679	tetur05g07970	TuGw	miRNAs mediated gene silencing
Protein phosphatase 1alpha at 96a	TC015321	tetur15g03360	TuPp1α-96a-A	Phosphatase, regulation of gene expression
		tetur04g05120	TuPp1α-96a-B
Coatomer subunit beta 2	–	tetur24g00150	TuCOPB2	Vesicular trafficking
Vacuolar-type H+-ATPase	–	tetur09g04140	TuVATPase	Proton pump, regulation of pH in organelle

dsRNA treatments targeting TuRpn7, TuSnapα, TuRop, and TuSrp54 resulted in a dark-body phenotype previously observed in dsRNA-TuVATPase treated mites, Fig. 5. In addition, mites treated with dsRNAs against TuRpt3 and TuHsc70-3 displayed a spotless phenotype characteristic for mites treated with dsRNA-TuCOPB2. dsRNAs against TuInr-a, TuGw, TuShi, TuPp1α-96a-A, and TuPp1α-96a-B yielded mite populations whose body phenotypes were indistinguishable from mites treated with dsRNA-NC, Fig. 5 and not shown. The body phenotypes were visible 2 days post-treatment, except for mites treated with dsRNAs against TuRpt3 and TuHsc70-3 that required 4 to 5 days post dsRNA treatment for the establishment of the body-color change. The appearance and the timing of body color phenotypes were the same upon application of two independent dsRNA fragments, Supplemental Table 1, indicating that these phenotypes are associated with the RNAi of their corresponding targets.

Figure 5.

Mite RNAi-associated phenotypes upon the application of dsRNA against T. urticae orthologs of Tribolium RNAi sensitive targets. Gene targets are listed at the upper left corner. NC, mites were soaked in the solution of dsRNA-NC.

To assess the efficiency of RNAi upon application of these dsRNAs, we determined mite survivorship over 10 days (Fig. 6 and Supplemental Fig. 1) and fecundity over 3 days (Fig. 7) post dsRNA treatments. Even though the silencing of all tested target genes resulted in 100% mortality in Tribolium³³, in T. urticae, their effectiveness was variable. dsRNAs targeting TuSrp54, TuRop, TuSnap α, TuRpn7, TuRpt3, TuInr-a and TuGw caused > 80% mortality of adult female mites, Fig. 6. However, mites treated with dsRNA-TuShi, dsRNA-TuHsc70-3, and a mixture of dsRNAs against TuPp1α-96a-A and TuPp1α-96a-B had a modest increase in mortality (~ 20% more than mites treated with the dsRNA-NC that was used as a negative control), while dsRNA targeting TuCac and TuPp1α-96a-A and TuPp1α-96a-B genes individually had no effect on mite survivorship, Fig. 6. Reproducibility of RNAi phenotypes upon the application of a second non-overlapping dsRNA for each gene rigorously confirms that the observed phenotypes are specific to the RNAi of target genes, making off-target effects improbable (Supplemental Fig. 1).

Figure 6.

Survival curves of adult female mites after treatment with dsRNAs targeting T. urticae orthologs of Tribolium RNAi sensitive genes. dsRNAs were applied at 160 ng/µL. Survival curves were plotted using the Kaplan–Meier method and compared using the log-rank test with Bonferroni correction (not significant, P > 0.05; ***P < 0.001). All experiments were performed in 3 independent trials.

Figure 7.

Fecundity of adult female mites after treatment with dsRNAs targeting T. urticae orthologs of Tribolium RNAi sensitive genes. dsRNAs were applied at 160 ng/µL. Fecundity is represented as the average number of eggs per female per day laid over 3 days. Significant differences relative to dsRNA-NC were determined by repeated-measures ANOVA followed by pairwise comparisons of treatment estimated marginal means with a Tukey p-value adjustment. (not significant, P > 0.05; *P < 0.05; ***P < 0.001). All experiments were performed in 3 independent trials.

Besides mortality, mite fecundity was also affected by the application of dsRNA, Fig. 7. Mites treated with dsRNA against TuRop and TuSnap α had dramatically reduced fecundity, laying on average 0.4 and 0.7 eggs/female/day, relative to mites treated with dsRNA-NC that laid 5.2 eggs/female/day. Most other treatments resulted in a ~ 50% reduction of fecundity, while dsRNAs targeting TuShi, TuInr-a, TuGw, TuPp1α-96a-A, and TuPp1α-96a-B did not significantly affect mite egg deposition. Overall, our data demonstrate that RNAi is effective to silence a range of gene targets in T. urticae.

Discussion

The use of RNAi as a reverse genetics tool requires efficient silencing of the expression of the target gene(s) and the responsiveness of the majority of treated individuals. In addition, the ability of ingested dsRNA to silence the target pest gene, resulting in pest mortality or reduced fitness, is a prerequisite for the development of RNAi-based pest control strategies. Many economically important lepidopteran, orthopteran, blattodean, and some coleopteran pests are recalcitrant to RNAi silencing by feeding that impedes the development of RNAi-based tools for their control¹⁶. The ability of orally delivered dsRNA to induce RNAi in T. urticae has been previously established^30–32, making this species a potential model for the development of RNAi-based pest controls. In this work, we optimized the dsRNA design and tested the utilization of dye as a marker for dsRNA ingestion. These modifications resulted in almost 100% RNAi efficiency. Using the optimized protocol, we demonstrated that sensitive RNAi targets identified in one organism are not directly transferable to another. Rather, the identification of RNAi targets has to be species-specific. The optimized RNAi protocol developed and used in this study, in conjunction with high quality T. urticae genome, paves the way for the high-throughput genetic analysis of gene function, for the identification of RNAi targets for mite pest control, and for dissection of RNAi processing machinery in this model pest.

The power of RNAi as a reverse genetics strategy is best illustrated by the genome-wide RNAi screens performed in Tribolium castaneum¹², Drosophila melanogaster¹¹, and Caenorhabditis elegans^9,10. The optimized RNAi protocol used in this study can be scaled up and used for the whole-genome functional analysis of T. urticae genes. Such screen would be particularly useful in identifying RNAi target genes for mite pest control, deciphering the function of > 4 k orphan genes that are unique to T. urticae/Chelicerates, or the analysis of candidate genes that were identified in studies of mite-plant host interactions^19–24 and pesticide resistance^26,40. Design of the gene-specific dsRNA is facilitated by the high quality of T. urticae genome sequence and high RNAi efficacy of chimeric dsRNAs, where only a small portion of the dsRNA sequence produces effective siRNAs (Fig. 2C). However, to claim the loss-of-function phenotype to a target gene and to eliminate the possibility of the off-target RNAi effects, a demonstration that second non-overlapping dsRNA causes the same phenotype is required, Supplemental Fig. 1. Furthermore, the ability of a mixture of dsRNAs to simultaneously induce RNAi in several genes enables knock-down of multiple processes (e.g. silencing of TuVATPase and TuCOPB2, Fig. 4B), and the analysis of genes that act redundantly (e.g. TuPp1α-96a-A and TuPp1α-96a-B, Figs. 6, 7). The CRISPR-Cas9 system is an alternative reverse genetics method for the generation of the loss-of-function phenotypes. The initial demonstration of CRISPR-Cas9 in T. urticae has been recently reported⁴¹, however, it will require a substantial increase in method efficiency to be useful in the generation of mutant alleles. Even when the CRISPR-Cas9 method becomes available, the RNAi approach may be preferred for the generation of loss-of-function phenotypes. RNAi protocols are easy to perform and do not require maintenance of mutant populations. RNAi enables testing of the effects of several genes simultaneously simply by combining multiple dsRNAs, which is particularly beneficial in pathway analysis. In addition, RNAi induced decreased gene function can be monitored in a time and dose-dependent manner. However, the other genome editing capabilities of CRISPR-Cas9, e.g. generation of larger deletions or gain-of-function alleles, will be important additional tools for understanding gene functions in T. urticae.

The ability of the ingested dsRNA to trigger RNAi in T. urticae opens a possibility to develop RNAi-based strategies for its control. As mites easily develop resistance to chemical pesticides¹⁸, the RNAi-based controls that have an independent mode of action relative to the existing pesticides could be an important tool for mite pesticide resistance management. Here, we tested the ability of twelve T. urticae orthologs of Tribolium genes that were identified as highly efficient RNAi targets³³ for their ability to induce RNAi and reduce mite fitness. Though not all candidate genes were confirmed as sensitive RNAi targets in T. urticae, silencing of 9 out of 14 genes resulted in a highly significant reduction in fecundity and survivorship (mortality ≥ 75%), Figs. 6, 7, 8. These genes represent processes and protein complexes that are particularly susceptible to environmental RNAi in T. urticae. Highly effective RNAi targets in T. urticae are involved in membrane transport and 26S proteasome degradation of ubiquitinated proteins, Fig. 8. In addition, targets involved in the general control of gene expression, TuGw (required for gene silencing mediated by miRNAs) and TuInr-a/Pcf11 (required for the transcriptional termination and 3′ end processing), as well as TuSRP54 (required for protein secretion) were also sensitive to RNAi in T. urticae, Fig. 8. In addition to these processes, Kwon et al.^30,31 identified the aquaporins (AQPs) and the regulation of the water balance as the essential process that is sensitive to manipulation by RNAi in T. urticae. The high level of mortality and decreased fecundity in mites treated with dsRNAs targeting TuSNAP α, TuRop, and TuCOPB2 transcripts (Figs. 1, 4, 8), predicted to dramatically reduce the size of a T. urticae population, demonstrate that these or similar RNAi targets can be developed as a tool for mite pest control in agriculture. In addition, dsRNAs targeting mite pesticide resistance genes were demonstrated to act as synergists to the existing pesticides^42–45—prolonging their efficiency against mite populations. Identification of additional sensitive gene targets, an understanding of the gut environment that can affect dsRNA stability, as well as mechanisms of dsRNA cellular uptake and spread to target tissues are required for the development of effective RNAi-based crop protection strategies against T. urticae. Although these processes are not limiting the efficacy of environmental RNAi in T. urticae, they could be the basis of the development of mite resistance to dsRNA. For example, the impairment of luminal uptake of dsRNA led to the development of dsRNA-resistant western corn rootworm⁴⁶. In insects, SID-1 and SID-1-like (SIL) proteins that encode transmembrane channel proteins, and receptor-mediated clathrin-dependent endocytosis^16,47–49 were implicated in the cellular uptake of dsRNA. The dsRNA cell import has not been investigated in T. urticae. However, in the absence of hemolymph⁵⁰, dsRNA uptake from the gut lumen and transporters that enable intercellular dsRNA movement are expected to profoundly affect the efficiency and the spread of the RNAi in T. urticae.

Figure 8.

Relationship between mite survivorship rate and fecundity for different classes of target genes. Mite survival rate on day 10 is as shown in Fig. 6. Mite fecundity is the mean number of eggs per female per day laid over 3 days as shown in Fig. 7.

An understanding of the evolutionary variation in the core RNAi machinery is an important factor in the development of RNAi-based tools. Gene losses and gains, and mutations in individual genes encoding proteins of the core RNAi machinery are expected to lead to species-specific modifications of RNAi pathways. For example, core proteins of the siRNA RNAi pathway include Argonaute-2, Dicer-2, and R2D2. Furthermore, the core proteins of the miRNA pathway in insects include Argonaute-1, Dicer-1, Loquacious, Drosha, and Pasha⁵¹.

Many beetles have duplicated R2D2 gene that is associated with efficient environmental RNAi²⁷. However, T. urticae, like primary wingless insects and some Lepidopteran species²⁷, lacks the homolog of R2D2. It has been hypothesized that Loquacious could act as a co-factor for both Dicer-1 and Dicer-2²⁷, enabling the processing of dsRNAs and the generation of siRNAs. Interestingly, T. urticae has two copies of loquacious gene¹⁹, raising the possibility of potential diversification of Loquacious functions in the generation of siRNAs and miRNAs. In addition to two copies of loquacious gene¹⁹, the miRNA pathway is further expanded in T. urticae and contains two dicer homologs (with unclear homology to Drosophila dicer-1 or -2 genes), seven argonaute genes, pasha and drosha. Finally, unlike in insects and crustaceans, the T. urticae genome contains five homologs of RNA dependent RNA polymerase (RdRP) genes that in C. elegans are implicated in systemic RNAi response⁵². As the conserved function of RNAi machinery is in the modulation of chromosome segregation, dosage response, and repair of DNA damage⁶, these changes in gene complement may reflect the variations in the generation and gene silencing function of small RNAs. Indeed, we showed that short dsRNAs (≤ 200 bp) had a low ability to induce the RNAi-associated phenotypes and that long dsRNAs (≥ 300 bp) are required for the efficient RNAi in T. urticae. A similar relationship between the length of the dsRNA and RNAi efficacy was observed in other organisms^35,36,53,54, however, the length of dsRNA required for efficient RNAi differs. For example, unlike in T. urticae, dsRNAs of 100–200 bp in length induce highly efficient RNAi in Tribolium^36,55, western corn rootworm^53,54, Drosophila S2 cells⁴⁷ and the nematode C. elegans³⁵. However, while in T. urticae the in vivo effects of dsRNAs of different length on RNAi efficacy tightly correlated with the processivity of dsRNA by Dicer in vitro assay, Fig. 2D and E, in Drosophila S2 cells, the length of dsRNA affected its cellular uptake and not the processivity⁴⁷, indicating differences in the RNAi machinery. With the establishment of an efficient RNAi protocol and the identification of sensitive RNAi targets, we are now in a position to dissect and characterize RNAi machinery in T. urticae and identify evolutionary changes in RNAi genetic pathways that are critical for efficient environmental RNAi.

In summary, we characterized the properties of dsRNA that are essential for the efficient environmental RNAi and demonstrated that RNAi can be used as a reverse genetics and pest control tool in T. urticae. In addition, we identified a causality between the length of dsRNA and its processivity, that warrants further dissection of RNAi processing machinery in this model pest.

Materials and methods

Mite rearing conditions

The London strain of T. urticae was maintained on beans (Phaseolus vulgaris ‘California Red Kidney’; Stokes, Thorold, ON) grown in soil (Pro-Mix BX Mycorrhizae; Premier Tech, Rivière-du-Loup, QC), at 26 °C under 100–150 μmol m⁻² s⁻¹ cool-white fluorescent light and a 16/8 h light/dark photoperiod.

dsRNA synthesis

The RNeasy Mini Kit (Qiagen, Valencia, CA) and the SuperScript II cDNA Synthesis Kit (Thermo Fisher Scientific, Waltham, MA) were used for total RNA extraction and synthesis of cDNA. Template preparation for dsRNA synthesis was performed by polymerase chain reaction (PCR) amplification using specific forward and reverse primers with a minimal T7 promoter sequence at their 5′ ends (see list of primers in the Supplemental Table 1). The dsRNA-NC (382 bp) has complementarity against non-transcribed intergenic region 1,690,614–1,690,995 of the T. urticae genomic scaffold 12, Fig. 1A. A 500 bp-chimeric dsRNA fragment was synthesized using an overlap-extension assembly PCR, resulting in the fusion between the 100-5′dsRNA-TuVATPase (118 bp) and the dsRNA-NC (382 bp) fragments. Briefly, both fragments were individually amplified using primers listed in Supplemental Table 1. Approximately 50 ng of both PCR products (purified by Qiagen PCR purification kit) were combined and a PCR was performed for 7 cycles to combine PCR fragments into one. These PCR products were then used as a template to perform a second PCR using end primers (forward primer of TuVATPase and reverse primer of NC) for the final amplification of chimeric fragment. Amplified fragments were purified with the Gel/PCR DNA Fragments Extraction Kit (Geneaid Biotech, New Taipei, Taiwan) and were sequenced to confirm their identity. dsRNAs were synthesized as described in Suzuki et al.³².

Preparation of ³²P-labeled dsRNA fragments

A 1 µL aliquot of 3.3 nM ³²P-α-UTP (Perkin Elmer) was added to the 20-µL reaction mixture of in vitro transcription containing 4 mM ATP, 4 mM GTP, 4 mM CTP and 0.1 mM UTP (final concentration). 2-nt 3′ overhang of dsRNAs was made using RNase T1, and DNA templates were digested by RNase-free DNase I (Takara Bio, Shiga, Japan).

dsRNA-cleaving assay

To detect the activity of Dicer complex in mites, we used the method previously described by Fukudome et al.⁵⁶ and Nagano et al.⁵⁷. Adult female mites (20 mg in weight) were collected with an air pump-based sucking system⁵⁸ and were transferred to a 1.5-mL polypropylene tube. Mites were homogenized in 20 mL/g of extraction buffer containing 20 mM Tris-HCl (pH 7.5), 4 mM MgCl₂, 5 mM DTT, 1 mM phenylmethylsulfonyl fluoride (PMSF), 1 mg/mL leupeptin, and 1 mg/mL pepstatin A. Homogenates were centrifuged twice at 20,000 g for 10 to 15 min to remove debris, and the supernatant containing the protein crude extract was collected and tested for the dsRNA-cleaving activity. A 1 µL aliquot of ³²P-labeled dsRNAs (approximately 10 ng) was incubated with 15 µL of crude protein extracts and 4 µl of 5 × dicing buffer containing 100 mM Tris–HCl (pH 7.5), 250 mM NaCl, 25 mM MgCl₂ and 25 mM ATP with 0.1 μL of an RNase inhibitor (2313A; Takara Bio) that inhibits the enzymatic activity of RNase A but not of Dicer (RNase III), at 22 °C for 2 h. Upon incubation, the cleaved products were purified by phenol/chloroform, precipitated by ethanol, separated by 15% denaturing PAGE with 8 M urea, and detected by autoradiography. The relative band intensities of the small RNA products were quantified by a Typhoon FLA 7000 image analyzer (GE Healthcare, Chicago, IL). The dsRNA-cleaving activity was calculated as the relative band intensity corresponding to the small RNAs in comparison with the total intensity of all bands in each lane. The experiment was conducted in 3 independent trials.

dsRNA oral delivery

dsRNA was delivered to mites using the soaking method described by Suzuki et al.^32,34. Briefly, fifty newly-emerged adult female mites were soaked in 50 μL of dsRNA solution (160 ng/μL, unless stated otherwise; 0.1% v/v Tween 20) at 20 °C for 24 h. Subsequently, mites were washed in 100 μL of double distilled water and were transferred onto either bean leaf or bean leaf discs placed on water-soaked cotton kept at 26 °C, 16/8 h light/dark photoperiod, and 50% RH.

Application of a tracer dye to monitor the uptake of dsRNA solution

Fifty newly-emerged adult female mites were soaked in 50 μL of dsRNA solution (160 ng/μL; 0.1% v/v Tween 20) mixed with 6% of blue food dye (erioglaucine; McCormick, Sparks Glencoe, MD) and were incubated at 20 °C for 24 h. After soaking, mites were washed in 100 μL of double distilled water and separated according to their color (blue or transparent) onto a bean leaf that was incubated at 26 °C, 16/8 h light/dark, photoperiod and 50% RH.) The experiment was conducted in 3 independent trials. The counts of dark-body and spotless mite phenotypes upon treatment with dsRNA-TuVATPase-600 and dsRNA-TuCOPB2-B, respectively, after “blue” and “white” mite separation, were analyzed using the R software environment⁵⁹ and the Fisher’s exact test (Fisher test function, R package ‘stats’). Confidence intervals of proportions were determined using the Clopper–Pearson method⁶⁰.

Selection of RNAi target genes in T. urticae

To determine T. urticae homologs of T. castaneum sensitive RNAi targets³³ we used the bidirectional best hit (BBH) approach⁶¹, and reciprocal blastp searches⁶² were conducted using amino acid sequences of targets against protein databases of D. melanogaster, T. castaneum, and T. urticae (Supplemental File 1).

Determination of mite RNAi-induced body phenotype

Two days post soaking, mite body-color associated with the application of dsRNAs was counted and frequencies calculated, except for mites treated with dsRNAs against TuRpt3 and TuHsc70-3 that required 4 to 5 days post dsRNA treatment for the establishment of the body-color change. A significant difference in the proportion of color phenotype, spotless, black, or normal was analyzed with Fisher’s exact test (Fisher test function, R package ‘stats’). For multiple comparisons of phenotype proportions between treatments Fisher’s exact test was used (fisher multcomp function, R package ‘RVAideMemoire’) and a Bonferroni correction of p-values was applied. Confidence intervals of proportions were determined using Clopper–Pearson method⁵⁹. Images of mite body phenotypes were taken using a Canon EOS Rebel T5i camera (Canon, Japan) fitted on an upright dissecting microscope (Leica, Germany). The experiment was conducted in 3 independent trials.

Mite survivorship

Mite survivorship was determined as described by Suzuki et al.³². Approximately 30 dsRNA treated adult female mites were placed on a detached bean leaf and mortality was recorded over 10 days. The experiment was performed in 3 independent trials. Survival curves were calculated with the Kaplan–Meier method (function survfit, R package ‘survival’) with comparisons performed based on the log-rank test (function survdiff, R package ‘survival’).

Mite fecundity

Mite fecundity upon the treatment with dsRNA-TuCOPB2 was performed as described in Suzuki et al.³². The fecundity of individual adult female mites was recorded over 10 days and mites were moved every other day onto a fresh bean disc (10 mm). The experiment was performed in 3 independents trials. A Wilcoxon–Mann–Whitney test was run to check the differences in fecundity between treatments (Wilcox test function in native stats package of R) with Bonferroni correction of p-values. For the fecundity assays of mites treated with dsRNAs against Tribolium orthologous genes, mites were recovered on a bean leaf for one-day post-treatment. On the second day, 10 mites were moved from the bean leaf and placed on a bean leaf disk (15 mm) and the number of eggs laid by a group of 10 adult females was recorded over 3 days. Mites were moved every other day onto a fresh bean disc. The target genes were distributed in four groups and experiments were performed in 3 independent trials. dsRNA-NC control treatment was included within each group. Differences in the mean number of eggs laid between the gene target dsRNA and dsRNA-NC treatments for each group were modelled using linear mixed-effects models with trial, treatment, and timepoint as fixed effects, using leaf-disk as the repeated measures random component and an autocorrelation structure using timepoint/leaf-disk (lme and corAR1 functions, R package ‘nlme’). The ACF function in the ‘nlme’ package was used to determine the autocorrelation for a lag of 1 in the timepoint variable. The models were validated by interrogating the qq plots of residuals (normality assumption) and ‘fitted’ versus ‘residuals’ plots to verify equal variance and linearity. The ANOVA function (R package ‘car’) was used to conduct an analysis of deviance and test hypotheses regarding fixed effects. Following a significant effect of treatment (and no confounding interactions of biological relevance), estimated marginal means and subsequent multiple comparisons between treatments were determined using the emmeans function (R package ‘emmeans’) with the application of the Tukey method of p-value adjustment. For plotting the mean of eggs laid per mite per day from a group of 10 mites was calculated and individual group data were adjusted towards an overall mean of dsRNA-NC treatment.

Real-time quantitative reverse transcription-PCR analysis of TuCOPB2

For the TuCOPB2 gene expression post dsRNA treatments, RNA was extracted from a batch of 30 adult mites in 3 independent experimental trials using the RNeasy Mini Kit (Qiagen). One microgram of RNA was reverse transcribed with the Maxima First Strand cDNA Synthesis Kit for RT-qPCR (Thermo Fisher Scientific). The reference genes RP49 (tetur18g03590), coding for a ribosomal protein, and CycA (tetur01g12670) coding for the protein Cyclophilin A were used as the internal control. The RT-qPCR was performed using forward and reverse primers (shown in the Supplementary Table 1D) that amplified fragment that does not overlap by the dsRNA sequence. Cycle Threshold (Ct) values were averaged from 3 technical replicates. Expression values for the TuCOPB2 were normalized to the average of the reference genes RP49 and CycA. The values were normalized to a mean of the control group treated with dsRNA-NC. Differences in the mean of normalized values between the control and treatments were analyzed with one-way ANOVA followed by Dunnett’s test (function glht, R package ‘multcomp’). Differences were considered significant at P < 0.05 for all analyses.

Author contributions

N.B., T.S., T.F., S.G., R.N., M.G. and V.G. conceived and planned the study. N.B., S.D., M.T., M.M., D.L., M.A., P.J. and Y.A. performed experimental procedures and collected data. N.B., V.Z., T.S., K.B., M.G. and V.G. performed analysis and wrote the manuscript.

Competing interests

The authors declare no competing interests.

Supplementary information

is available for this paper at 10.1038/s41598-020-75682-6.