- Open Access
Establishing RNAi for basic research and pest control and identification of the most efficient target genes for pest control: a brief guide
Frontiers in Zoology volume 18, Article number: 60 (2021)
RNA interference (RNAi) has emerged as a powerful tool for knocking-down gene function in diverse taxa including arthropods for both basic biological research and application in pest control. The conservation of the RNAi mechanism in eukaryotes suggested that it should—in principle—be applicable to most arthropods. However, practical hurdles have been limiting the application in many taxa. For instance, species differ considerably with respect to efficiency of dsRNA uptake from the hemolymph or the gut. Here, we review some of the most frequently encountered technical obstacles when establishing RNAi and suggest a robust procedure for establishing this technique in insect species with special reference to pests. Finally, we present an approach to identify the most effective target genes for the potential control of agricultural and public health pests by RNAi.
RNA interference in research and pest control
For a long time, studying gene function was restricted to highly developed model organisms such as Drosophila melanogaster, where genetic screens and the maintenance of mutants were eased by an elaborate genetic toolkit. The advent of reverse genetics based on RNA interference (RNAi) paved the way for selectively silencing genes outside established model organisms and has broadened the scope of gene function studies. The high conservation of this process throughout eukaryotes and the ease of application of double-stranded RNA (dsRNA) by injection without the need of elaborate genetic tools promise—in principle—to study gene function in any animal. However, significant hurdles have to be overcome to realize this potential and it has turned out that practical restrictions often hamper the establishment of the technique in organisms—both for basic research and pest control purposes. We review some of these hurdles and give hints that help establishing RNAi in a novel organism to foster the broad application of this technique.
RNAi is an ancestral immune response of eukaryotic organisms to combat viral infections, transposable elements and to regulate expression of endogenous genes [1,2,3]. It was first discovered in petunia plants where overexpression of an anthocyanin biosynthesis enzyme led to white or spotted flowers instead of the expected increase of color intensity . Subsequently, spreading RNA was found to deplete homologous mRNA termed “posttranscriptional gene silencing” and showed its importance in virus resistance [4,5,6,7,8]. Similar observations in fungi were termed “quelling” [9, 10]. The identification of dsRNA as causative agent in Caenorhabditis elegans  and Trypanosoma brucei  led to the detailed molecular characterization of the RNAi mechanism, its ramifications and diversification between taxa [1,2,3, 13].
Here, we focus mainly on the application of RNAi in insects, where the gene inventory of RNAi components is highly conserved, indicating that—in theory—any insect should be amenable to this technique [13,14,15] but the same applies to other arthropods. Indeed, RNAi has been widely adopted to study gene function for purposes of basic research in arthropod species ranging from spiders and early branching hexapods to holometabolous insects [16,17,18,19,20,21,22] thereby opening new fields of research. For example, in the red flour beetle Tribolium castaneum, where RNAi is strong and easy to apply, a wide range of topics has been studied in terms of gene function ranging from embryonic and postembryonic development, evolution and physiology [16, 23,24,25,26,27,28,29,30,31,32,33].
Besides studying gene function in basic research, RNAi is being harnessed for eco-friendly and species-specific pest control [34,35,36]. Pre-and postharvest damage of agricultural crops by insect pests are thought to reduce yields by 18% despite preventive measures and economic losses are even expected to increase due to global warming [37,38,39]. So far, pest insect control has largely relied on chemical insecticides and BT toxin based approaches, yet the appearance of insecticide resistance and environmental and toxicological concerns called for the development of insecticides with novel modes of action and environmental benign profiles [38, 40,41,42,43,44,45]. RNAi has been successfully tested as means for controlling a number of pest species, particularly coleopteran pests [34,35,36, 46, 47].
Three main issues have emerged in endeavors to apply this technique: First, some insect clades appear to be less amenable to RNAi or RNAi via feeding than others and species-specific differences within clades are rather the rule than the exception. Second, efforts to establish RNAi have led to conflicting reports on whether RNAi works in a given species or not. It has remained unclear, in how far the divergent observations are due to biologically relevant strain-specific differences in RNAi susceptibility or whether technical issues have led to false positive reports. Third, dsRNA remains an expensive slowly acting chemical with often lower efficacy than classical pesticides. Hence, it is of crucial importance to identify the most efficient target genes and the best sequences targeting them. Based on success in one species, several RNAi target genes have been tested in different species for use in pest control. However, it has become clear recently that orthologous genes differ with respect to their efficacy between species [27, 48,49,50,51,52,53,54,55]. Alternative approaches are the prediction of essential genes supported by artificial intelligence  or large scale RNAi screens in model organisms and subsequent transfer to pest species [27, 32, 33].
Here, we first provide a brief overview on some of the reasons for differences of susceptibility to RNAi including biological variation and experimental issues. Based on this, we outline an approach to establish RNAi as a method in yet untested model species or insect pests. Then, we provide an efficient workflow for selecting most efficient RNAi target genes for pest control. Finally, we argue that optimizing the dsRNA fragment applied in pest control may further increase efficacy.
Variability and experimental difficulties encountered with RNAi
Delivery of dsRNA—environmental RNAi and putative dsRNA receptors
RNAi emerged early in evolution of eukaryotes as immune response against viruses and transposons and the core components of the RNAi machinery are widely conserved [1, 11,12,13,14, 57,58,59,60]. Therefore, it is expected that most if not all animal species will mount an RNAi response once dsRNA has reached the cytoplasm of their cells. However, the macromolecular dsRNA does not enter cells by itself calling for efficient delivery methods. Direct injection of dsRNA into cells is very efficient but feasible only during the first embryonic stages (often called embryonic RNAi) when the cells are still large. Application at later stages requires that dsRNA enters the cells after e.g. injection into the insect hemolymph. This can be advanced experimentally to some degree for instance by electroporation [61, 62] or by packaging the dsRNA into nanoparticles that facilitate entry into cells [48, 63,64,65,66,67,68,69].
A much more robust response is observed in species with an endogenous mechanism for dsRNA uptake, which is the basis for “environmental RNAi”, i.e. the uptake of dsRNA from the fluid surrounding cells . If this feature is present, dsRNA can be injected into the hemolymph of any insect life stage and subsequent knock-down in most or all cells can be expected. Depending on the injected life stage, the application of dsRNA is often called “larval” or “pupal” or “adult RNAi” [71, 72]. Another option opened by environmental RNAi is “in vitro RNAi” knocking down gene function by soaking cells in culture . In the nematode C. elegans, the molecular basis of environmental RNAi has been studied thoroughly [74,75,76,77] while in the fly D. melanogaster, environmental uptake of dsRNA appeared to be restricted to specific cell types and was studied in cell culture [78,79,80,81]. In other insect species, in contrast, environmental RNAi works efficiently [71, 82,83,84,85]. While the nature of the insect receptors remains disputed (see below) they appear to require dsRNAs with a minimum length of around 60 base pairs [86,87,88,89].
In the nematode C. elegans the membrane-spanning dsRNA-specific channel systemic RNAi defective1 (SID1) was found to be essential for dsRNA uptake [74, 76, 90, 91]. However, no direct SID1 ortholog was found in insects  while the identified insect SID1-like (Sil) proteins showed more homology to the C. elegans Tag-130 / ChUP1 protein which, however, does not contribute to the RNAi response in C. elegans [13, 92]. Nevertheless, some Sil homologs were tested for their impact on systemic RNAi in a number of insect species—with varying results. In Apis mellifera, a Sil-protein was upregulated after dsRNA exposure  and in Leptinotarsa decemlineata, minor contribution to systemic RNAi were attributed to one of its Sil proteins (SilC but not SilA) [94, 95] while strong participation was found in Diabrotica virgifera virgifera [87, 96]. In T. castaneum, all three identified Sil proteins were irrelevant for systemic RNAi  and similar results were obtained for Schistocerca gregaria , Plutella xylostella  and Locusta migratoria . Hence, Sid-1 like genes do not or at least not exclusively explain dsRNA uptake in insects.
Clathrin-dependent endocytosis is required for dsRNA uptake as well, for instance as part of the mechanism for SID2 mediated dsRNA entry from the gut lumen in C. elegans  and in a D. melanogaster cell line [80, 81]. This was confirmed for several insect species such as L. decemlineata , Bactrocera dorsalis , T. castaneum , D. v. virgifera  and S. gregaria . Additional dsRNA receptors were proposed including pattern-recognition receptors  previously only associated with bacterial infections in D. melanogaster, and the scavenger receptors (SR) SR-CI and Eater [81, 102, 103]. Indeed, SRs were also found to be relevant for RNAi in S. gregaria and L. decemlineata [92, 95] and were upregulated after dsRNA exposure in honey bees [104, 105]. The fact that environmental RNAi does not appear to work in D. melanogaster  despite the presence of the endocytosis pathway indicates that another, yet unknown dsRNA receptor may exist in insects.
Variability of RNAi: population specific differences or false positive reports?
For the application in pest control, environmental RNAi is a prerequisite because dsRNA needs to be taken up from the gut after oral uptake. However, trials with oral uptake of dsRNA often have limited success, and bioavailability of dsRNA remains the most critical issue for its application in pest control. Amenability to oral RNAi appears to be a species-specific property where species of some clades appear to be amenable to RNAi via feeding with higher likelihood than others. For example, a number of beetles exhibit a robust RNAi response after oral dsRNA uptake [27, 34, 51, 55, 106]. In contrast, many Lepidopterans were found to be quite resistant to environmental RNAi [86, 107]. There are positive reports for several stinkbugs [52, 108,109,110] while there are more mixed reports with respect to whiteflies [65, 111,112,113,114], aphids [115,116,117,118,119,120] and spider mites [121, 122]. Though RNAi was shown to work in several hemipteran pest species, its commercial use to target these species is currently out of scope due to the high concentrations of dsRNA necessary for a rather moderate response. Similarly, major constraints on the potential of RNAi to control mosquito vectors of human diseases such as anopheline species transmitting malaria were reported, particularly due to the need of rather high doses of dsRNA required for successful RNAi under applied conditions . But even within a certain clade the efficiency can vary. For instance, embryonic injection of dsRNA leads to a quite robust response in Bombyx mori but fails to do so in Spodoptera exigua and hemolymph dsRNA injection led to effects in Saturniidae but not in Papilionoidae . One exception within beetles are weevils, where several species such as the cotton boll weevil proved resilient to oral RNAi mediated control [124,125,126,127]. The picture is further complicated by contradicting reports on RNAi after oral uptake for closely related or even identical species. For instance, RNAi after oral feeding of dsRNA was reported for the red flour beetle T. castaneum in several studies [120, 128,129,130] while respective attempts in a number of other labs remained unsuccessful (G.B., Ernst A. Wimmer and Yoshinori Tomoyasu, personal information). Likewise, successful RNAi by feeding in aphids was reported [131, 132] while other work shows that dsRNA endonucleases in gut and hemolymph hamper efficient RNAi  and finally, RNAi by feeding was reported to work in honey bee larvae  while others found low efficiency when feeding larvae .
These observations could reflect either biological divergence among populations of one species or false positive data. Biological variability between strains of the same species would have important bearings on application. Most importantly, such genetic diversity would represent material from which resistance against dsRNA as pesticide could develop. Unfortunately, only few studies focus on this aspect. For instance, susceptibility to oral RNAi was compared among 14 European populations of the Colorado potato beetle revealing a degree of variability. However, this variability was comparably small and would probably not compromise RNAi efficacy under applied conditions—depending on recommended label rates . Further, it was shown that RNAi resistance conferred by the inhibition of dsRNA uptake could be selected in field populations of the Western corn rootworm (Coleoptera) . Unfortunately, this resistance mechanism most likely confers cross-resistance to any dsRNA, and would render the entire technology useless. A recent study in the pea aphid found high variability among strains and a subsequent genome wide association study revealed a number of unexpected candidate genes that might contribute to these differences . In contrast, in the red flour beetle T. castaneum, similar strength of the RNAi response upon injection was found in several lab strains and in field strains [138, 139]. Taken together, some biological variability of dsRNA susceptibility can be expected between taxa and sometimes even among strains of one taxon but it does probably not explain the dramatic differences in reported RNAi efficacy.
False positive reports may be an alternative explanation for some diverging reports on RNAi efficiency. One reason is that that many studies on RNAi in pest control use lethality as readout for the RNAi treatment. However, this is a quite unspecific phenotype, which can occur due to many factors unrelated to RNAi treatment. For instance, problems with maintaining the insects, hidden infection with parasites, different age of the treated individuals, quality and purity of the injection needles, toxic substances remaining from dsRNA preparations etc., all increase the variability of the background lethality between experiments, therefore appropriate control treatments are of utmost importance. Indeed, sudden instances of increased lethality are observed even in well-established cultures of model insects from time to time. Pest species are often more difficult to maintain in the lab or even need to be collected from the field, adding an additional level of variability on any measure of survival. Even in the absence of a lethal effect of a given dsRNA treatment, this experimental variability combined with the unspecific nature of the readout will almost certainly lead to increased death in some experimental settings, which might be interpreted as positive results. Given their sometimes crucial relevance for publication and funding, the wish for positive results may sometimes be stronger than the tightness of the experimental controls. Therefore, we suggest using specific phenotypes to establish RNAi as a method and applying stringent controls that reveal confounding effects when studying lethality after RNAi (see below).
Possible mechanisms leading to variability of the RNAi response
Research on the lack of RNAi after oral application has unveiled several possible modes of resistance. First, the midgut of lepidopteran insects, along with several orthopteran or hymenopteran species, is alkaline which destabilizes dsRNA and thus facilitates degradation [140,141,142]. Additionally, Lepidoptera-specific RNAi efficiency-related nucleases (REase) and other dsRNA nucleases expressed in the midgut degrade dsRNA before it can be taken up and processed by the RNAi machinery [143,144,145,146,147]. Quite often, dsRNA is eliminated in the hemolymph of Lepidoptera, Hemiptera and Orthoptera, or the saliva of Hemiptera. In many cases nucleases are suggested to be the primary cause of RNAi tolerance [52, 112, 117, 118, 130, 148,149,150,151,152,153]. In contrast, dsRNA was shown to be relatively stable in midgut and hemolymph of Dictyopterans, e.g. cockroaches [149, 154]. Finally, dsRNA was shown to be trapped in endosomes of Heliothis virescens and Spodoptera frugiperda cell lines and tissues, thus blocking further cleavage to small-interfering RNAs (siRNAs) [150, 155]. Several creative approaches have been developed to overcome dsRNA degradation in the gut . For instance, liposomes have been used in Drosophilids and a stink bug [120, 156], cationic nanoparticles were used in Ostrinia furnacalis , chitosan nanoparticles enhanced the RNAi effect in the Anopheles gambiae and Aedes aegypti gut [69, 158], cell penetrating peptides fused to dsRNA binding domains were applied in Anthonomus grandis  while endosymbiont bacteria in the gut were used successfully to produce a stable dsRNA supply .
Viral infections are discussed as an additional mechanism leading to RNAi insensitivity. Some viruses have evolved protein effectors that suppress the RNAi response of their host. Persistent viral infection caused for example by the flock house virus, Drosophila C virus or Nora virus inhibited the RNAi machinery assembly or activity [161,162,163,164]. Moreover, the RNAi machinery could be overloaded or diverted by the expression of excess viral RNA thereby reducing the RNAi response to external dsRNAs [165, 166].
Another factor possibly influencing variability in oral dsRNA uptake could be the microbiome. In P. versicolora, RNAi efficiency was increased when bacteria inhabited their alimentary tract . Especially Pseudomonas putida profited from the additional nutrition provided by dsRNA degradation products causing overgrowth and infection of the beetle . The disruption of gut epithelia and translocation of bacteria accelerated the RNAi-induced mortality  and in L. migratoria, the gut microbiome was altered upon dsRNA injection .
Establishing RNAi in a novel model organism or pest species
Establishing a robust procedure for the application of RNAi is of crucial importance for basic research in novel model organisms and for the development of RNAi-based pest control in pest species. In this section we present an approach that is based on our experience with these endeavors in beetles.
The dsRNA fragment: length, selection, production, concentration
The length of the dsRNA fragment might be chosen between 500 and 1,000 bp. One reason is the cellular uptake mechanism, which in insects appears to require a certain minimal length of the dsRNA. For instance, 21mers or fragments of 31 bp length injected into the hemocoel did not elicit RNAi in the red flour beetle while fragments of 69 bp induced RNAi and dsRNA with the length of 520 bp was even more efficient . In the Western corn root worm a dsRNA length of > 60 bp was required for an RNAi response after oral uptake [46, 89]. While dsRNA targeting β-actin of 60 bp length reduced target gene transcript levels in Colorado potato beetle, it was not sufficient to induce mortality which was only achieved by dsRNA fragments of > 200 bp length . Whereas dsRNA uptake determines the minimum size there are also reasons for an upper limit. Fragments longer than 1.5 kb do sometimes anneal with low efficiency, such that the effective concentration of dsRNA may be low despite high concentration of RNA (G.B. unpublished observation). Besides, a length above 500 bp promises a more efficient in vitro dsRNA production (Ambion MEGAscript Kit manual).
In the cell, long dsRNA is processed into different siRNAs and depending on their sequence characteristics, some siRNAs have been shown to be more efficient than others. There are computational tools that predict the portion of efficient siRNAs and the portion of potential off target siRNAs and based on these data, the optimal fragment can be selected. The Deqor algorithm  was used in our large scale screen in Tribolium  and we indeed found that the optimized fragments in many cases resulted in stronger phenotypes compared to other fragments targeting the same gene (unquantified observation). An online version of the tool is found at https://www.eupheria.com/tools-resources/deqor/.
In vitro dsRNA production is usually performed from a PCR template that has T7 promoter sequences at both ends. These T7 promoter sequences can be added by including them into the respective primers. However, in PCR reactions from complex DNA mixtures (like genomic DNA or cDNA), PCR artifact products are often produced along with the desired product. Such artifacts will be transcribed to dsRNA as well and will thereby reduce the effective amount of dsRNA and add off target effects to the specific effect of the target dsRNA. Therefore, a two-step process is advisable, where the target sequence is purified and sequenced (Fig. 1A). One option is to clone the fragment into a plasmid and confirm its correctness by sequencing before doing a secondary PCR with primers including T7 promoter sequences. Alternatively, the PCR product with linker sequences is excised from a gel, sequenced and stored (the linker used in the iBeetle screen was a partial T7 promoter: 5’-CTCACTATAGGGAGA-3’). In a secondary PCR, this template is amplified using primers that bind to the linker and contain T7 sequences . This product is purified and used for an in vitro transcription (e.g. MEGAscript). Note that LiCl used for precipitating dsRNA is interfering with the Hedgehog pathway and can therefore be toxic and induce phenotypes. Therefore, the respective washing steps need to be performed very carefully—especially when lethality is the expected phenotype.
A portion of the RNA already anneals during the in vitro reaction but single stranded RNA will be present as well. In order to maximize the presence of double stranded RNA, a specific annealing reaction is recommended, the effect of which should be monitored on a gel (e.g. place reaction for 5 min in a 94 °C heating block, take out block and let cool at room temperature for 40 min). Due to secondary structures, RNA fragments behave differently from DNA on standard agarose gels. Nevertheless, differences before and after annealing are usually visible. Please contact the authors for a protocol.
Usually, the strength of the phenotype correlates with the amount of injected dsRNA. Therefore, the initial experiments should include maximum dsRNA concentrations (e.g. 2–3 µg/µl—higher dsRNA concentrations are often more difficult to obtain and dsRNA viscosity increases with concentration). Once a phenotype is observed, the concentration can be reduced empirically to reduce potential unspecific lethality or secondary effects. Note that standard procedures measuring DNA or RNA do not work well for determining effective dsRNA concentrations because most of these techniques detect single stranded RNA and/or nucleotides as well. Actually, nucleotides are not reliably removed by LiCl precipitation and residual nucleotides may indicate a higher concentration in measurements than actually present.
Commercially produced dsRNA is an alternative especially when many different genes are to be tested and/or molecular biology is not well established in the lab (e.g. Eupheria Biotech GmbH, Dresden, Germany—see competing interest section).
Target genes for establishing RNAi
Given the risk of false positive results when using lethality as a readout, it is advisable to establish and optimize the RNAi technique based on a gene with a specific phenotypic response. A convincing case for an RNAi response can be made by observing an expected specific visible but non-lethal phenotype after silencing a gene. Pigmentation genes are good candidates for that purpose. For instance, laccase is an enzyme involved in melanin-related cuticle tanning and its knock-down led to reduced pigmentation in a number of insects [24, 170,171,172,173]. Another option is the ebony gene, which upon knock-down led to darkened cuticle in Tribolium and other insects [87, 174, 175]. Another kind of specific phenotypes is expected after knocking down certain developmental regulatory genes. For instance, Distal-less is a homeobox gene required for the development of distal parts of appendages in many arthropods and upon downregulation the distal parts of appendages are defective [71, 176,177,178]. Ultrabithorax is a homeobox gene, the knock-down of which led to clearly visible abnormalities in the trunk region of insects and crustaceans [179,180,181]. Of note, the duplication of genes may lead to mutual compensation such that the knock-down of one paralog may not elicit a full phenotype or none at all. Hence, the presence of only one copy of the target gene should be confirmed before it is used for establishing RNAi.
Most if not all animals mount an RNAi response once dsRNA has entered the cells. Hence, the limitation is actually getting the dsRNA into the cells. Unfortunately for application in pest control, RNAi after feeding is the method with least likelihood to work and usually the one with weakest phenotypic outcome. Therefore, we suggest establishing RNAi with more robust dsRNA delivery methods, first.
Direct injection of dsRNA into cells is restricted to the freshly laid eggs because they are still comparably large. Moreover, before cellularization, the dsRNA does not have to pass membranes to distribute. After injection of dsRNA into the one- or two-cell stage or into the syncytial phase of early insect development, it is very likely that dsRNA will elicit a response. The above-mentioned developmental genes are excellent test genes for embryonic phenotypes while pigmentation of the freshly eclosed larvae may not always be strong enough to be seen. The main hurdle in this procedure is that-depending on the species-it may be a real challenge to establish a protocol for collection and treatment of early embryos such that they survive injection. Actually, establishing embryonic injection is the crucial hurdle not only for RNAi targeting of early stages but also for other key applications in gene function studies such as transposon-mediated transgenesis or genome editing.
Many but not all arthropods show environmental RNAi, i.e. cells take up dsRNA from the surrounding medium. This uptake process is well studied in the nematode C. elegans [74,75,76,77, 91, 182] but it remains open in how far those processes are similar in insects. To test for environmental RNAi, dsRNA is injected into larvae or pupae and the phenotype is observed subsequently in the injected animal. Pigmentation phenotypes are an excellent choice for testing postembryonic stages but the phenotypes of the mentioned developmental genes in most cases affect morphology of pupae or adults as well. Due to the species-specific lag between time of injection and knock-down effect, and the difference in protein stability of different genes, it is advisable to perform time series injections in order to empirically determine the optimal timing for injection.
In some species, the knock-down effect is transmitted even to the offspring of injected females (parental RNAi) [71, 82, 83, 85, 183]. Once environmental RNAi has been shown to work by the above-mentioned experiment, this aspect can be tested by injection of female pupae or adults with dsRNA targeting developmental regulatory genes and scoring the hatchlings for morphological phenotypes. Note that hatchlings may not be pigmented enough to reliably score pigmentation genes and that injection of males has not led to transfer to the offspring so far .
Quantification of the knock-down by qPCR or by the phenotypic readout?
qPCR is often used to confirm that the target gene is indeed downregulated. However, a number of issues limit the value of this control. First, there is no clearly defined relationship between the level of knock-down that has to be reached to elicit a phenotype—and the respective value varies from gene to gene. Actually, most genes are viable in a genetically heterozygous state, which means that 50% knock-down of transcripts is usually well tolerated or compensated for. As a rule of thumb, it is difficult to knock-down the transcript below 10–20% of residual mRNA while values above 30–40% residual mRNA may still lead to a strong phenotype, depending on the gene.
Second, many genes are part of regulatory feedback loops such that the transcript level will be determined by the primary downregulation by RNAi and modification by secondary effects. For instance, compensatory upregulation of paralogs or the targeted gene itself were observed after RNAi  (and unpublished observations V.H.). Compensatory upregulation of the transcript in the nucleus may increase the level of RNA detected by qPCR while downregulation in the cytoplasm may still be sufficient for a strong phenotype. For instance, we observed a very strong phenotype after RNAi targeting a developmental gene but surprisingly, qPCR indicated no strong modification of expression levels. However, qPCR measuring the intron of that gene indeed showed dramatic upregulation (unpublished observation). Likewise, we noted complex and unexpected patterns of down- and up-regulation with respect to several other genes after RNAi and these highly depended on the time between injection and qPCR.
Given these uncertainties regarding the interpretation of qPCR results, quantification of the phenotypic readout may still represent the most meaningful readout to answer the question of whether RNAi is an adequate tool for a specific gene in a given process.
Sine qua non: off target controls
The result of any RNAi experiment can be blurred by off target effects. This means that the injected dsRNA does not exclusively target the intended transcript but may hit other transcripts as well. The presence of very short stretches of sequence identity (19 or more nucleotides) with an unrelated mRNA may already lead to efficient knock-down of that off-target mRNA . The resulting phenotype then represents a combination of the intended effect and an off-target effect. Actually, in our large scale iBeetle screen (T. castaneum), we found qualitatively different phenotypes in 14% of all treatments even though bioinformatically optimized sequences were used . Therefore, off target controls are absolutely essential in order to minimize the likelihood of erroneously assigning functions to certain genes. One measure is to identify sequences with identity to other mRNAs of 19 bp length by bioinformatics means and exclude them. Some online tools allow for checking long dsRNAs for off target effects (e.g. dsCheck, Deqor, SnapDragon, E-RNAi) but often the number of species is limited with E-RNAi having the highest number of species included [169, 185]. An essential control is in any case that the target mRNA is knocked down in an additional experiment with a second, non-overlapping fragment. Qualitatively coinciding phenotypes in both treatments indicate the absence of (at least strong) off target effects, while some degree of quantitative differences between fragments can occur.
How to find the best RNAi target genes for pest control
Varying efficacy of RNAi target genes across species
About 40% of all genes in an insect genome are essential, i.e. their knock-down leads to lethality of the animal at any stage [32, 186]. Hence, the problem is not to find an essential gene—the challenge is to identify one that leads to death most quickly at lowest doses of dsRNA. Some genes have been selected based on the assumption that they should be essential. Indeed, orthologs of some of these knowledge-based target genes have been used successfully tested in a number of different species (e.g. V-ATPase, Act, tubulin) [34, 49, 52, 113, 120]. However, our knowledge may not suffice to make reliable predictions on the best target genes for pest control. Efficacy is modulated by several unknown factors like stability of the protein (which is not affected by RNAi) and compensatory upregulation of the target gene or functionally related paralogs. Likewise, it is not clear, what cells should be targeted to induce most efficient death. Given these uncertainties, unbiased approaches can be used, where many genes are tested for their usability in pest control independent of assumptions. Due to the ease of rearing and application of RNAi, we have used the genetic model organism T. castaneum (red flour beetle) to score for lethality after RNAi of all genes in a completely unbiased approach [32, 33], providing a good base for the initial selection of target genes. Recent data showed that the efficacy of orthologous target genes can differ between taxa. For instance, RNAi in the red flour beetle silencing the previously used target genes copi coatamere and V-ATPase did induce lethality, but efficacy remained clearly below the level of the top 11 genes identified in that unbiased RNAi screen . Meanwhile these top 11 genes have been tested in a number of other pest species to identify the most efficient target genes [27, 48,49,50,51,52,53,54,55]. The picture emerging from these studies (summarized in Table 1) is that usually at least one of the target genes efficient in one species turned out to be decent target genes in other pests as well.
Challenges when testing RNAi by feeding
For application in pest control, dsRNA needs to be taken up by feeding. Hence, the target genes have ultimately to be tested in a feeding assay often using larvae as the most destructive life stage, at least for many chewing pests. Establishing a robust test is of key importance to avoid false positive results. First, the assay needs to ensure a baseline lethality of the treated insects, which is as low as possible and rather constant. Hence, an artificial diet must be developed that is based on well-defined components (for reproducibility), supports the regular development of the animals and does not interfere with dsRNA stability. For instance, culturing red flour beetle larvae in viscous flour-liquid mix can lead to increased death because these animals are adapted to dry habitats (unpublished observation). Herbivorous pest insects are best tested for RNAi efficacy using the respective host or test plants or parts thereof, e.g. by the spray application of dsRNA to leaf-discs as recently shown for mustard beetle larvae .
Second, degradation of dsRNA in the medium needs to be considered and ways to replenish the dsRNA have to be designed where necessary. Of note, dsRNA has been shown to be effective on leaves for up to several weeks under greenhouse conditions . In our experiments using Phaedon cochleariae as a chrysomelid model beetle, we developed a spraying system that allowed administering defined amounts of dsRNA on leaves. Once the treated leaf-disc was consumed we supplied untreated leaf-discs .
Design of the experiment and the controls
Orthologous target genes differ in their efficacy in different species (see above) and reliable predictors for the transferability of RNAi responses across species are still lacking. Therefore, it is advisable to start with a primary screen testing as many target genes as technically feasible (20 to 50 depending on the ease of application) at comparably high dsRNA concentrations. Based on the results of this primary screen, a smaller number of candidates (for instance the top 5 to 10) funnel into a secondary screen. Here, they are tested in extensive titration experiments where different concentrations of dsRNA are applied and the phenotypic effects are documented for an extended period of time. The most important phenotype is lethality, which is recorded over time to reveal the dynamics of the response. Additional parameters to document might include the number of molts, feeding behavior, weight, etc. The experiment could be complemented by qPCR analyses documenting the degree of knock-down. While the primary screen may still be based on a comparably low number of animals per treatment (depending on the baseline lethality e.g. 10 to 15), the subsequent experiments should be based on numbers that allow for statistical analyses, for instance at least three biological replicates with 9 or more animals per treatment. The concentrations should cover a broad range, which depends on the mode of application. For instance, we administered 3 µg, 1 µg and 0.3 µg per leaf-disc which was not completely consumed by several mustard beetle larvae feeding on it . For the primary screen by injection in T. castaneum, we used five concentrations between 1 µg/µl to 3 ng/µl.
Given the likelihood of false positive results when using lethality as readout, a number of controls are essential. First, a dsRNA preparation of an non-endogenous gene (e.g. EGFP) should be used as negative control. This controls for unwanted effects by the dsRNA preparation and other technical factors (still, the dsRNA production of a target gene could be contaminated with LiCl or other toxic substances). Moreover, such a treatment controls for unspecific lethality induced by dsRNA (and its solvents) or by the artificial diet. Increased lethality can emerge from technical issues like toxic substances in the dsRNA preparation, infections of the animals or other problems with the culture (albeit less common). Hence, reproducing the result with an independent dsRNA preparation in an independent replicate is required to minimize false positive results. For the genes analyzed in detail, off-target effect with a non-overlapping fragment targeting the same gene need to be performed. Only genes that pass these controls should be considered for the laborious titrating experiment.
Catalogue of potential target genes
The challenge of identifying the best RNAi target genes is restricted on the one hand by the limited level of transferability from one species to the other (see above). On the other hand, large scale screens are difficult to perform in most pest species. Hence, we suggest to perform a mini-screen with a selection of RNAi target genes identified in other studies [27, 32, 33, 187]. Depending on the experimental amenability of the species, a number of genes successfully shown to be lethal across a number of species (at least 10 but better 30–50 genes) should be tested to identify efficient target genes. A list of very good candidate genes based on a large scale RNAi screen in T. castaneum  and results of respective tests in other insects are given in Table 1. Meanwhile, we have completed this screen to cover the entire T. castaneum genome and the best target genes from this effort will be published in due time. Other genes frequently used targets are V-ATPase (although this turned out to be less efficient than the target genes identified in the screen) and Actin, while genes so far targeted in commercial products include SSJ1 and Snf7 [188, 189].
Optimization of the target fragment for pest control
Besides the parameters for selection of a dsRNA fragment discussed above, there are additional considerations when it comes to the design of fragments for pest control. The fragment has to specifically target the pest but should not affect other species. Initial hopes to find species specific genes for pest control did not realize—because the most efficient target genes are highly conserved. Further, assuming 19 bp homology as the minimal sequence that would allow for knock-down, almost every long dsRNA sequence will have off target siRNAs that target other mRNAs. These off target sites are not restricted to the conserved regions of the protein . Hence, for application in the field, the target mRNA should be searched for sequence stretches that do not show off-target sequences in non-target insects living in the same habitat. Alternatively, one might try to find stretches that target a number of related pest species while avoiding effects to non-target species. This could be especially relevant in integrated pest management programs, when dsRNA treatment is combined with the application of beneficial insectivorous species e.g. of the Coccinellidae (lady beetles) family. Tests on bee pollinators are mandatory for registration of insecticides  and are likely to become mandatory for insecticidal dsRNAs as well. Ecotoxicological effects on honey bees were evaluated as part of the risk assessment for Western corn rootworm dssnf7 used in the first GM-crop with insecticidal dsRNA-traits approved by USA authorities [189, 191, 192]. However, accounts on RNAi efficiency e.g. in the honey bee A. mellifera are quite variable. It was shown that different dsRNA amounts were necessary to achieve knockdown of target genes with various effectiveness, an observation partially explained by differences in tissue susceptibility [93, 193, 194]. When choosing a worst case scenario with dsvATPaseA from Western corn rootworm with the highest homology to honey bee, no adverse effects were found . In fact, even in case of full sequence identity with honey bee vATPaseA, survival of A. mellifera larvae and adults was not affected after dsRNA feeding .
In our hands, combining dsRNAs targeting different lethal genes lead to no synergistic effect. Our pairwise combinations of the top 11 target genes rather revealed additive effects . However, co-administration of hsc70-3 and shi dsRNA in A. planipennis larvae and adults suggested a synergistic effect on mortality , albeit at low levels.
Unfortunately, systematic work on designing and tinkering the optimal dsRNA sequence is still missing and potentially, ways of increasing efficacy remain to be discovered.
Outlook: where might RNAi help in pest control?
The great promise of RNAi in pest control is the very species-specific action combined with the fact that dsRNA is a natural compound that quickly degrades in nature. So far, insect pest control by insecticidal dsRNAs is still on the verge of commercialization. To date, only one product, the transgenic GM-maize SmartStax PRO expressing double stranded RNA targeting Dv-snf7 and Bacillus thuringiensis (Bt) insecticidal proteins (Head et al., 2017), gained approval and awaits its launch in the United States of America . Another transgenic product based on RNAi mediated knock-down of the Dv-SSJ1 gene has been tested [188, 195]. An alternative approach is the non-transgenic sprayable RNAi, which circumvents several problems of GM crops particularly in the EU such as lacking public support, long registration processes or difficulties in the efficient generation of transgenic plants . Considering the fast and complete degradation of dsRNA in the environment suggest low environmental and health risks [197,198,199], this might be especially attractive for organic farming.
Unfortunately, there are also issues that hamper RNAi applications. First, RNAi as a control strategy, is comparably slow and taking several days, during which the insects can still damage the crop or transmit diseases. For this reason, dsRNA is less suitable for insect control in ornamental plant or cut flower cultures where pristine appearance is desired. Another drawback is the limited number of insect species that are amenable to RNAi by feeding. Formulations of dsRNA with nanoparticles aimed to improve oral delivery [48, 63, 64, 69, 157, 200]. While these formulations show some promise, they may not be available to organic farming and need to be tested for safety.
dsRNA products are still considered rather expensive compared to chemical insecticides. Advances in the production of long dsRNA considerably dropped production costs below 0.5$/g  and the results from  indicated that field rates of 10 g/ha may be enough leading to an estimation of production costs of at least 5$ per hectare (Note that this estimation does not cover development, distribution and profit). Additional costs will have to be covered by the price of the marketed product. This is high when for example compared to the chemical insecticide “Decis forte” formulation with the pyrethroid deltamethrin as active ingredient, which costs approximately 50–60 €/l depending on the vendor (e.g. [202, 203]). This corresponds to roughly 3–4 € per hectare at a field application rate of 5–7.5 g/ha [204,205,206]. On the other hand, the price of dsRNA insecticides will be competitive with other products like the Bt toxin-based “Xentari”, which costs about 20–40 € per hectare and needs application rates of at least 324 g per hectare on cabbage, root vegetable or tomato [207,208,209,210,211]. The issue of fast degradation of dsRNA may be less of an issue in greenhouse-grown crops because one predominant source of degradation—UV light—is strongly reduced. Hence, sprayable dsRNA products could be competitive in high value crop applications.
Taken together, the future of sprayable RNAi in agriculture is difficult to predict and the balance can still tip either way. It continues to face many limitations and therefore might end up as a niche product for specific pest control problems or as a resistance-management tool in agronomic settings with pest species, which developed high levels of resistance to conventional insecticides. Being a natural compound, the focus of insecticidal RNAi might well shift from agriculture to domestic insect nuisances such as ants and termites [212,213,214] and to mosquitoes as vectors of human diseases [215,216,217]. Hence, depending on the development of political and regulatory frameworks in Europe and other regions, RNAi may contribute to some agricultural and horticultural production systems and domestic uses as an alternative to chemical insecticides.
RNAi has become a key technique for studying gene function outside the classic model organisms and it can be harnessed for species-specific and eco-friendly pest control. However, the optimal mode of dsRNA delivery, the strength of the gene knock-down and the degree of environmental uptake and systemic spread differ dramatically between taxa. Therefore, we present a guideline on how to establish the method in a careful and well-controlled way. In order to render RNAi mediated pest control economically interesting, it is essential to identify the most efficient target genes. We suggest that testing a moderate number of candidate target genes is required to find an optimal one.
Availability of data and materials
RNAi efficiency-related nuclease
Meister G, Tuschl T. Mechanisms of gene silencing by double-stranded RNA. Nature. 2004;16(431):343–9.
Wilson RC, Doudna JA. Molecular mechanisms of RNA interference. Annu Rev Biophys. 2013;42(1):217–39.
Shabalina SA, Koonin EV. Origins and evolution of eukaryotic RNA interference. Trends Ecol Evol. 2008;23(10):578–87.
Napoli C, Lemieux C, Jorgensen R. Introduction of a chimeric chalcone synthase gene into petunia results in reversible co-suppression of homologous genes in trans. Plant Cell. 1990;2(4):279–89.
Angell SM, Baulcombe DC. Consistent gene silencing in transgenic plants expressing a replicating potato virus X RNA. EMBO J. 1997;16(12):3675–84.
Palauqui J-C, Elmayan T, Pollien J-M, Vaucheret H. Systemic acquired silencing: transgene-specific post-transcriptional silencing is transmitted by grafting from silenced stocks to non-silenced scions. EMBO J. 1997;16(15):4738–45.
Voinnet O, Vain P, Angell S, Baulcombe DC. Systemic spread of sequence-specific transgene RNA degradation in plants is initiated by localized introduction of ectopic promoterless DNA. Cell. 1998;95(2):177–87.
Waterhouse PM, Graham MW, Wang M-B. Virus resistance and gene silencing in plants can be induced by simultaneous expression of sense and antisense RNA. Proc Natl Acad Sci. 1998;95(23):13959–64.
Cogoni C, Romano N, Macino G. Suppression of gene expression by homologous transgenes. Antonie Van Leeuwenhoek. 1994;65(3):205–9.
Cogoni C, Macino G. Isolation of quelling-defective (qde) mutants impaired in posttranscriptional transgene-induced gene silencing in Neurospora crassa. PNAS. 1997;94(19):10233–8.
Fire A, Xu S, Montgomery MK, Kostas SA, Driver SE, Mello CC. Potent and specific genetic interference by double-stranded RNA in Caenorhabditis elegans. Nature. 1998;391(6669):806–11.
Ngô H, Tschudi C, Gull K, Ullu E. Double-stranded RNA induces mRNA degradation in Trypanosoma brucei. Proc Natl Acad Sci U S A. 1998;95(25):14687–92.
Tomoyasu Y, Miller SC, Tomita S, Schoppmeier M, Grossmann D, Bucher G. Exploring systemic RNA interference in insects: a genome-wide survey for RNAi genes in Tribolium. Genome Biol. 2008;9:R10.
Dowling D, Pauli T, Donath A, Meusemann K, Podsiadlowski L, Petersen M, et al. Phylogenetic origin and diversification of RNAi pathway genes in insects. Genome Biol Evol. 2016;8(12):3784–93.
Mongelli V, Saleh M-C. Bugs are not to be silenced: small RNA pathways and antiviral responses in insects. Ann Rev Virol. 2016;3(1):573–89.
Brown SJ, Mahaffey JP, Lorenzen MD, Denell RE, Mahaffey JW. Using RNAi to investigate orthologous homeotic gene function during development of distantly related insects. Evol Dev. 1999;1:11–5.
Dong Y, Friedrich M. Enforcing biphasic eye development in a directly developing insect by transient knockdown of single eye selector genes. J Exp Zool B Mol Dev Evol. 2010;314B(2):104–14.
Elias-Neto M, Belles X. Tergal and pleural structures contribute to the formation of ectopic prothoracic wings in cockroaches. R Soc Open Sci. 2016;3(8):160347.
Hughes CL, Kaufman TC. RNAi analysis of Deformed, proboscipedia and Sex combs reduced in the milkweed bug Oncopeltus fasciatus: novel roles for Hox genes in the hemipteran head. Development. 2000;127(17):3683–94.
Khila A, Abouheif E, Rowe L. Function, developmental genetics, and fitness consequences of a sexually antagonistic trait. Science. 2012;336(6081):585–9.
Konopova B, Akam M. The Hox genes Ultrabithorax and abdominal-A specify three different types of abdominal appendage in the springtail Orchesella cincta (Collembola). EvoDevo. 2014;5(1):2.
Miyawaki K, Mito T, Sarashina I, Zhang H, Shinmyo Y, Ohuchi H, et al. Involvement of wingless/armadillo signaling in the posterior sequential segmentation in the cricket, gryllus bimaculatus (Orthoptera), as revealed by RNAi analysis. Mech Dev. 2004;121(2):119–30.
Ansari S, Troelenberg N, Dao VA, Richter T, Bucher G, Klingler M. Double abdomen in a short-germ insect: Zygotic control of axis formation revealed in the beetle Tribolium castaneum. PNAS. 2018;115(8):1819–24.
Arakane Y, Muthukrishnan S, Beeman RW, Kanost MR, Kramer KJ. Laccase 2 is the phenoloxidase gene required for beetle cuticle tanning. PNAS. 2005;102(32):11337–42.
Fu J, Posnien N, Bolognesi R, Fischer TD, Rayl P, Oberhofer G, et al. Asymmetrically expressed axin required for anterior development in Tribolium. PNAS. 2012;109(20):7782–6.
Jacobs CGC, Spaink HP, van der Zee M. The extraembryonic serosa is a frontier epithelium providing the insect egg with a full-range innate immune response. Medzhitov R, editor. eLife. 2014;3:e04111.
Knorr E, Fishilevich E, Tenbusch L, Frey MLF, Rangasamy M, Billion A, et al. Gene silencing in Tribolium castaneum as a tool for the targeted identification of candidate RNAi targets in crop pests. Sci Rep. 2018;8(1):2061.
Konopova B, Jindra M. Juvenile hormone resistance gene Methoprene-tolerant controls entry into metamorphosis in the beetle Tribolium castaneum. PNAS. 2007;104(25):10488–93.
Linz DM, Tomoyasu Y. Dual evolutionary origin of insect wings supported by an investigation of the abdominal wing serial homologs in Tribolium. PNAS. 2018;115(4):E658–67.
Nunes da Fonseca R, von Levetzow C, Kalscheuer P, Basal A, van der Zee M, Roth S. Self-regulatory circuits in dorsoventral axis formation of the short-germ beetle Tribolium castaneum. Dev Cell. 2008;14(4):605–15.
Rösner J, Tietmeyer J, Merzendorfer H. Functional analysis of ABCG and ABCH transporters from the red flour beetle. Tribolium castaneum Pest Management Science. 2021;77(6):2955–63.
Schmitt-Engel C, Schultheis D, Schwirz J, Ströhlein N, Troelenberg N, Majumdar U, et al. The iBeetle large-scale RNAi screen reveals gene functions for insect development and physiology. Nat Commun. 2015;28(6):7822.
Ulrich J, Dao VA, Majumdar U, Schmitt-Engel C, Schwirz J, Schultheis D, et al. Large scale RNAi screen in Tribolium reveals novel target genes for pest control and the proteasome as prime target. BMC Genomics [Internet]. 2015 Dec [cited 2016 Jun 15];16(1). Available from: http://0-www-biomedcentral-com.brum.beds.ac.uk/1471-2164/16/674
Baum JA, Bogaert T, Clinton W, Heck GR, Feldmann P, Ilagan O, et al. Control of coleopteran insect pests through RNA interference. Nat Biotechnol. 2007;25(11):1322–6.
Liu S, Jaouannet M, Dempsey DA, Imani J, Coustau C, Kogel K-H. RNA-based technologies for insect control in plant production. Biotechnology Advances. 2020 Mar 1;39:107463.
Mao Y-B, Cai W-J, Wang J-W, Hong G-J, Tao X-Y, Wang L-J, et al. Silencing a cotton bollworm P450 monooxygenase gene by plant-mediated RNAi impairs larval tolerance of gossypol. Nat Biotechnol. 2007;25(11):1307–13.
Bradshaw CJA, Leroy B, Bellard C, Roiz D, Albert C, Fournier A, et al. Massive yet grossly underestimated global costs of invasive insects. Nat Commun. 2016;7(1):1–8.
Oerke E-C. Crop losses to pests. J Agric Sci. 2006;144(1):31–43.
Lehmann P, Ammunét T, Barton M, Battisti A, Eigenbrode SD, Jepsen JU, et al. Complex responses of global insect pests to climate warming. Frontiers in Ecology and the Environment [Internet]. 2020 Feb 3 [cited 2020 Mar 11];n/a(n/a). Available from: https://0-esajournals-onlinelibrary-wiley-com.brum.beds.ac.uk/doi/abs/https://0-doi-org.brum.beds.ac.uk/10.1002/fee.2160
Borel B. CRISPR, microbes and more are joining the war against crop killers. Nature News. 2017;543(7645):302.
Casida JE, Bryant RJ. The ABCs of pesticide toxicology: amounts, biology, and chemistry. Toxicol Res. 2017;6(6):755–63.
Sparks TC, Wessels FJ, Lorsbach BA, Nugent BM, Watson GB. The new age of insecticide discovery-the crop protection industry and the impact of natural products. Pestic Biochem Physiol. 2019;1(161):12–22.
Sparks TC, Nauen R. IRAC: Mode of action classification and insecticide resistance management. Pestic Biochem Physiol. 2015;1(121):122–8.
Tabashnik BE, Carrière Y. Surge in insect resistance to transgenic crops and prospects for sustainability. Nat Biotechnol. 2017;35(10):926–35.
Nauen R, Jeschke P, Velten R, Beck ME, Ebbinghaus-Kintscher U, Thielert W, et al. Flupyradifurone: a brief profile of a new butenolide insecticide. Pest Manag Sci. 2015;71(6):850–62.
San Miguel K, Scott JG. The next generation of insecticides: dsRNA is stable as a foliar-applied insecticide. Pest Manag Sci. 2016;72(4):801–9.
Christiaens O, Whyard S, Vélez AM, Smagghe G. Double-stranded RNA technology to control insect pests: current status and challenges. Front Plant Sci. 2020;11:451.
Castellanos NL, Smagghe G, Sharma R, Oliveira EE, Christiaens O. Liposome encapsulation and EDTA formulation of dsRNA targeting essential genes increase oral RNAi-caused mortality in the Neotropical stink bug Euschistus heros. Pest Manag Sci. 2019;75(2):537–48.
Dhandapani RK, Gurusamy D, Duan JJ, Palli SR. RNAi for management of Asian long-horned beetle, Anoplophora glabripennis: identification of target genes. J Pest Sci. 2020;93(2):823–32.
Kyre BR, Rodrigues TB, Rieske LK. RNA interference and validation of reference genes for gene expression analyses using qPCR in southern pine beetle. Dendroctonus frontalis Sci Rep. 2019;9(1):1–8.
Mehlhorn S, Ulrich J, Baden CU, Buer B, Maiwald F, Lueke B, et al. The mustard leaf beetle, Phaedon cochleariae, as a screening model for exogenous RNAi-based control of coleopteran pests. Pesticide Biochemistry and Physiology. 2021 Jul 1;176:104870.
Mogilicherla K, Howell JL, Palli SR. Improving RNAi in the brown marmorated stink bug: identification of target genes and reference genes for RT-qPCR. Sci Rep. 2018;8(1):1–9.
Rodrigues TB, Duan JJ, Palli SR, Rieske LK. Identification of highly effective target genes for RNAi-mediated control of emerald ash borer Agrilus planipennis. Sci Rep. 2018;8(1):1–9.
Xu L, Xu S, Sun L, Zhang Y, Luo J, Bock R, et al. Synergism of gut microbiota to double-stranded RNAs in RNA interference of a leaf beetle. bioRxiv. 2019 Oct 31;824581.
Zhang Y, Xu L, Li S, Zhang J. Bacteria-mediated RNA interference for management of plagiodera versicolora (Coleoptera: Chrysomelidae). Insects. 2019;10(12):415.
Beder T, Aromolaran O, Dönitz J, Tapanelli S, Adedeji EO, Adebiyi E, et al. Identifying essential genes across eukaryotes by machine learning. bioRxiv. 2021 Apr 15;2021.04.15.439934.
Billmyre RB, Calo S, Feretzaki M, Wang X, Heitman J. RNAi function, diversity, and loss in the fungal kingdom. Chromosome Res. 2013;21(6):561–72.
Kavi HH, Fernandez H, Xie W, Birchler JA. Genetics and Biochemistry of RNAi in Drosophila. In: Paddison PJ, Vogt PK, editors. RNA Interference [Internet]. Berlin, Heidelberg: Springer; 2008 [cited 2021 Jul 6]. p. 37–75. (Current Topics in Microbiology and Immunology). Available from: https://0-doi-org.brum.beds.ac.uk/10.1007/978-3-540-75157-1_3
Tijsterman M, Ketting RF, Plasterk RHA. The genetics of RNA silencing. Annu Rev Genet. 2002;36(1):489–519.
Ullu E, Tschudi C, Chakraborty T. RNA interference in protozoan parasites. Cell Microbiol. 2004;6(6):509–19.
Ando T, Fujiwara H. Electroporation-mediated somatic transgenesis for rapid functional analysis in insects. Development. 2013;140(2):454–8.
Okude G, Fukatsu T, Futahashi R. Electroporation-mediated RNA Interference Method in Odonata. J Vis Exp. 2021 Feb 6;(168).
Avila LA, Chandrasekar R, Wilkinson KE, Balthazor J, Heerman M, Bechard J, et al. Delivery of lethal dsRNAs in insect diets by branched amphiphilic peptide capsules. J Control Release. 2018;10(273):139–46.
Christiaens O, Tardajos MG, Martinez Reyna ZL, Dash M, Dubruel P, Smagghe G. Increased RNAi Efficacy in Spodoptera exigua via the Formulation of dsRNA With Guanylated Polymers. Front Physiol [Internet]. 2018 [cited 2019 Dec 17];9. Available from: https://www.frontiersin.org/articles/https://0-doi-org.brum.beds.ac.uk/10.3389/fphys.2018.00316/full
Kaur R, Gupta M, Singh S, Joshi N, Sharma A. Enhancing RNAi Efficiency to Decipher the Functional Response of Potential Genes in Bemisia tabaci AsiaII-1 (Gennadius) Through dsRNA Feeding Assays. Front Physiol [Internet]. 2020 [cited 2021 Jul 6];11. Available from: https://www.frontiersin.org/articles/https://0-doi-org.brum.beds.ac.uk/10.3389/fphys.2020.00123/full#B86
Kunte N, McGraw E, Bell S, Held D, Avila L-A. Prospects, challenges and current status of RNAi through insect feeding. Pest Manag Sci. 2020;76(1):26–41.
Yan S, Qian J, Cai C, Ma Z, Li J, Yin M, et al. Spray method application of transdermal dsRNA delivery system for efficient gene silencing and pest control on soybean aphid Aphis glycines. J Pest Sci. 2020;93(1):449–59.
Yan S, Ren B-Y, Shen J. Nanoparticle-mediated double-stranded RNA delivery system: a promising approach for sustainable pest management. Insect Science. 2021;28(1):21–34.
Zhang X, Zhang J, Zhu KY. Chitosan/double-stranded RNA nanoparticle-mediated RNA interference to silence chitin synthase genes through larval feeding in the African malaria mosquito (Anopheles gambiae). Insect Mol Biol. 2010;19(5):683–93.
Whangbo JS, Hunter CP. Environmental RNA interference. Trends Genet. 2008;24(6):297–305.
Bucher G, Scholten J, Klingler M. Parental RNAi in Tribolium (Coleoptera). Curr Biol. 2002;12(3):R85–6.
Tomoyasu Y, Denell RE. Larval RNAi in Tribolium (Coleoptera) for analyzing adult development. Dev Genes Evol. 2004;214:575–8.
Hahn N, Knorr DY, Liebig J, Wüstefeld L, Peters K, Büscher M, et al. The Insect Ortholog of the Human Orphan Cytokine Receptor CRLF3 Is a Neuroprotective Erythropoietin Receptor. Front Mol Neurosci [Internet]. 2017 [cited 2021 Jul 6];10. Available from: https://www.frontiersin.org/articles/https://0-doi-org.brum.beds.ac.uk/10.3389/fnmol.2017.00223/full
Feinberg EH, Hunter CP. Transport of dsRNA into Cells by the Transmembrane Protein SID-1. Science. 2003;301:1545–7.
Hinas A, Wright AJ, Hunter CP. SID-5 is an endosome-associated protein required for efficient systemic RNAi in C elegans. Curr Biol. 2012;22(20):1938–43.
Winston WM, Molodowitch C, Hunter CP. Systemic RNAi in C. elegans requires the putative transmembrane protein SID-1. Science. 2002;295:2456–9.
Winston WM, Sutherlin M, Wright AJ, Feinberg EH, Hunter CP. Caenorhabditis elegans SID-2 is required for environmental RNA interference. PNAS. 2007;104(25):10565–70.
Miller SC, Brown SJ, Tomoyasu Y. Larval RNAi in Drosophila? Dev Genes Evol. 2008;218:505–10.
Roignant J-Y, Carré C, Mugat B, Szymczak D, Lepesant J-A, Antoniewski C. Absence of transitive and systemic pathways allows cell-specific and isoform-specific RNAi in Drosophila. RNA. 2003;9(3):299–308.
Saleh M-C, van Rij RP, Hekele A, Gillis A, Foley E, O’Farrell PH, et al. The endocytic pathway mediates cell entry of dsRNA to induce RNAi silencing. Nat Cell Biol. 2006;8(8):793–802.
Ulvila J, Parikka M, Kleino A, Sormunen R, Ezekowitz RA, Kocks C, et al. Double-stranded RNA Is Internalized by Scavenger Receptor-mediated Endocytosis in Drosophila S2 Cells. J Biol Chem. 2006;281(20):14370–5.
Khajuria C, Vélez AM, Rangasamy M, Wang H, Fishilevich E, Frey MLF, et al. Parental RNA interference of genes involved in embryonic development of the western corn rootworm, Diabrotica virgifera virgifera LeConte. Insect Biochem Mol Biol. 2015;1(63):54–62.
Shakeel M, Du J, Li S-W, Zhou Y-J, Sarwar N, Bukhari SAH. Characterization, Knockdown and Parental Effect of Hexokinase Gene of Cnaphalocrocis medinalis (Lepidoptera: Pyralidae) Revealed by RNA Interference. Genes (Basel). 2020;11(11):E1258.
Simonet P, Gaget K, Parisot N, Duport G, Rey M, Febvay G, et al. Disruption of phenylalanine hydroxylase reduces adult lifespan and fecundity, and impairs embryonic development in parthenogenetic pea aphids. Sci Rep. 2016;6(1):34321.
Yoshiyama N, Tojo K, Hatakeyama M. A survey of the effectiveness of non-cell autonomous RNAi throughout development in the sawfly, Athalia rosae (Hymenoptera). J Insect Physiol. 2013;59(4):400–7.
Ivashuta S, Zhang Y, Wiggins BE, Ramaseshadri P, Segers GC, Johnson S, et al. Environmental RNAi in herbivorous insects. RNA. 2015;21(5):840–50.
Miyata K, Ramaseshadri P, Zhang Y, Segers G, Bolognesi R, Tomoyasu Y. Establishing an in vivo assay system to identify components involved in environmental RNA interference in the western corn rootworm. PLoS One. 2014;9(7):e101661.
Miller SC, Miyata K, Brown SJ, Tomoyasu Y. Dissecting systemic RNA interference in the red flour beetle Tribolium castaneum: parameters affecting the efficiency of RNAi. PLoS ONE. 2012;7(10):e47431.
Bolognesi R, Ramaseshadri P, Anderson J, Bachman P, Clinton W, Flannagan R, et al. Characterizing the mechanism of action of double-stranded RNA activity against western corn rootworm (Diabrotica virgifera virgifera LeConte). PLoS One. 2012;7(10):e47534.
Li W, Koutmou KS, Leahy DJ, Li M. Systemic RNA interference deficiency-1 (SID-1) extracellular domain selectively binds long double-stranded RNA and Is required for RNA transport by SID-1. J Biol Chem. 2015;290(31):18904–13.
Shih JD, Hunter CP. SID-1 is a dsRNA-selective dsRNA-gated channel. RNA. 2011;17(6):1057–65.
Wynant N, Santos D, Wielendaele PV, Broeck JV. Scavenger receptor-mediated endocytosis facilitates RNA interference in the desert locust. Schistocerca gregaria Insect Molecular Biology. 2014;23(3):320–9.
Aronstein K, Pankiw T, Saldivar E. SID-I is implicated in systemic gene silencing in the honey bee. J Apic Res. 2006;45(1):20–4.
Cappelle K, de Oliveira CFR, Eynde BV, Christiaens O, Smagghe G. The involvement of clathrin-mediated endocytosis and two Sid-1-like transmembrane proteins in double-stranded RNA uptake in the Colorado potato beetle midgut. Insect Mol Biol. 2016;25(3):315–23.
Yoon J-S, Shukla JN, Gong ZJ, Mogilicherla K, Palli SR. RNA interference in the Colorado potato beetle, Leptinotarsa decemlineata: Identification of key contributors. Insect Biochem Mol Biol. 2016;1(78):78–88.
Pinheiro DH, Vélez AM, Fishilevich E, Wang H, Carneiro NP, Valencia-Jiménez A, et al. Clathrin-dependent endocytosis is associated with RNAi response in the western corn rootworm, Diabrotica virgifera virgifera LeConte. PLOS ONE. 2018 Aug 9;13(8):e0201849.
Wang H, Gong L, Qi J, Hu M, Zhong G, Gong L. Molecular cloning and characterization of A SID-1-LIKE GENE IN Plutella xylostella. Arch Insect Biochem Physiol. 2014;87(3):164–76.
Luo Y, Wang X, Yu D, Kang L. The SID-1 double-stranded RNA transporter is not required for systemic RNAi in the migratory locust. RNA Biol. 2012;9(5):663–71.
McEwan DL, Weisman AS, Hunter CP. Uptake of extracellular double-stranded RNA by SID-2. Mol Cell. 2012;47(5):746–54.
Li X, Dong X, Zou C, Zhang H. Endocytic pathway mediates refractoriness of insect Bactrocera dorsalis to RNA interference. Sci Rep. 2015;5(1):1–8.
Xiao D, Gao X, Xu J, Liang X, Li Q, Yao J, et al. Clathrin-dependent endocytosis plays a predominant role in cellular uptake of double-stranded RNA in the red flour beetle. Insect Biochem Mol Biol. 2015;1(60):68–77.
Kocks C, Cho JH, Nehme N, Ulvila J, Pearson AM, Meister M, et al. Eater, a transmembrane protein mediating phagocytosis of bacterial pathogens in drosophila. Cell. 2005;123(2):335–46.
Rämet M, Pearson A, Manfruelli P, Li X, Koziel H, Göbel V, et al. Drosophila scavenger receptor CI Is a pattern recognition receptor for bacteria. Immunity. 2001;15(6):1027–38.
Brutscher LM, Daughenbaugh KF, Flenniken ML. Virus and dsRNA-triggered transcriptional responses reveal key components of honey bee antiviral defense. Sci Rep. 2017;7(1):1–15.
Flenniken ML, Andino R. Non-Specific dsRNA-Mediated Antiviral Response in the Honey Bee. PLOS ONE. 2013;8(10):e77263.
Zhang J, Khan SA, Hasse C, Ruf S, Heckel DG, Bock R. Full crop protection from an insect pest by expression of long double-stranded RNAs in plastids. Science. 2015;347(6225):991–4.
Terenius O, Papanicolaou A, Garbutt JS, Eleftherianos I, Huvenne H, Kanginakudru S, et al. RNA interference in Lepidoptera: an overview of successful and unsuccessful studies and implications for experimental design. J Insect Physiol. 2011;57(2):231–45.
Ghosh SKB, Hunter WB, Park AL, Gundersen-Rindal DE. Double strand RNA delivery system for plant-sap-feeding insects. PLOS ONE. 2017 Feb 9;12(2):e0171861.
Gurusamy D, Howell JL, Chereddy SCRR, Mogilicherla K, Palli SR. Improving RNA interference in the southern green stink bug. Nezara viridula J Pest Sci. 2021. https://0-doi-org.brum.beds.ac.uk/10.1007/s10340-021-01358-3.
Sharma R, Christiaens O, Taning CN, Smagghe G. RNAi-mediated mortality in southern green stinkbug Nezara viridula by oral delivery of dsRNA. Pest Manag Sci. 2021;77(1):77–84.
Luan J-B, Ghanim M, Liu S-S, Czosnek H. Silencing the ecdysone synthesis and signaling pathway genes disrupts nymphal development in the whitefly. Insect Biochem Mol Biol. 2013;43(8):740–6.
Luo Y, Chen Q, Luan J, Chung SH, Van Eck J, Turgeon R, et al. Towards an understanding of the molecular basis of effective RNAi against a global insect pest, the whitefly Bemisia tabaci. Insect Biochem Mol Biol. 2017;1(88):21–9.
Upadhyay SK, Chandrashekar K, Thakur N, Verma PC, Borgio JF, Singh PK, et al. RNA interference for the control of whiteflies (Bemisia tabaci) by oral route. J Biosci. 2011;36(1):153–61.
Vyas M, Raza A, Ali MY, Ashraf MA, Mansoor S, Shahid AA, et al. Knock down of Whitefly Gut Gene Expression and Mortality by Orally Delivered Gut Gene-Specific dsRNAs. PLOS ONE. 2017 Jan 3;12(1):e0168921.
Andrade EC, Hunter WB. RNAi feeding bioassay: development of a non-transgenic approach to control Asian citrus psyllid and other hemipterans. Entomol Exp Appl. 2017;162(3):389–96.
Christiaens O, Smagghe G. The challenge of RNAi-mediated control of hemipterans. Curr Opin Insect Sci. 2014;6:15–21.
Christiaens O, Swevers L, Smagghe G. DsRNA degradation in the pea aphid (Acyrthosiphon pisum) associated with lack of response in RNAi feeding and injection assay. Peptides. 2014;53:307–14.
Ghodke AB, Good RT, Golz JF, Russell DA, Edwards O, Robin C. Extracellular endonucleases in the midgut of Myzus persicae may limit the efficacy of orally delivered RNAi. Sci Rep. 2019;9(1):1–14.
Mutti NS, Park Y, Reese JC, Reeck GR. RNAi knockdown of a salivary transcript leading to lethality in the pea aphid, Acyrthosiphon pisum. J Insect Sci [Internet]. 2006 Jan 1 [cited 2020 Apr 20];6(1). Available from: https://0-academic-oup-com.brum.beds.ac.uk/jinsectscience/article/6/1/38/871156
Whyard S, Singh AD, Wong S. Ingested double-stranded RNAs can act as species-specific insecticides. Insect Biochem Mol Biol. 2009;39(11):824–32.
Mondal M, Peter J, Scarbrough O, Flynt A. Environmental RNAi pathways in the two-spotted spider mite. BMC Genomics. 2021;22(1):42.
Yoon J-S, Sahoo DK, Maiti IB, Palli SR. Identification of target genes for RNAi-mediated control of the Twospotted Spider Mite. Sci Rep. 2018;8(1):14687.
Balakrishna Pillai A, Nagarajan U, Mitra A, Krishnan U, Rajendran S, Hoti SL, et al. RNA interference in mosquito: understanding immune responses, double-stranded RNA delivery systems and potential applications in vector control. Insect Mol Biol. 2017;26(2):127–39.
Garcia RA, Macedo LLP, Nascimento DC do, Gillet F-X, Moreira-Pinto CE, Faheem M, et al. Nucleases as a barrier to gene silencing in the cotton boll weevil, Anthonomus grandis. PLOS ONE. 2017 Dec 20;12(12):e0189600.
Prentice K, Christiaens O, Pertry I, Bailey A, Niblett C, Ghislain M, et al. RNAi-based gene silencing through dsRNA injection or ingestion against the African sweet potato weevil Cylas puncticollis (Coleoptera: Brentidae). Pest Manag Sci. 2017;73(1):44–52.
Prentice K, Smagghe G, Gheysen G, Christiaens O. Nuclease activity decreases the RNAi response in the sweetpotato weevil Cylas puncticollis. Insect Biochem Mol Biol. 2019;1(110):80–9.
Wu K, Taylor CE, Pinheiro DH, Skelley LH, McAuslane HJ, Siegfried BD. Lethal RNA interference response in the pepper weevil. J Appl Entomol. 2019;143(7):699–705.
Abd El Halim HM, Alshukri BMH, Ahmad MS, Nakasu EYT, Awwad MH, Salama EM, et al. RNAi-mediated knockdown of the voltage gated sodium ion channel TcNa v causes mortality in Tribolium castaneum. Scientific Reports. 2016;6(1):29301.
Cao M, Gatehouse JA, Fitches EC. A Systematic Study of RNAi Effects and dsRNA Stability in Tribolium castaneum and Acyrthosiphon pisum, Following Injection and Ingestion of Analogous dsRNAs. Int J Mol Sci. 2018;19(4).
Peng Y, Wang K, Chen J, Wang J, Zhang H, Ze L, et al. Identification of a double-stranded RNA-degrading nuclease influencing both ingestion and injection RNA interference efficiency in the red flour beetle Tribolium castaneum. Insect Biochem Mol Biol. 2020;125:103440.
Will T, Vilcinskas A. The structural sheath protein of aphids is required for phloem feeding. Insect Biochem Mol Biol. 2015;1(57):34–40.
Ye C, Jiang Y-D, An X, Yang L, Shang F, Niu J, et al. Effects of RNAi-based silencing of chitin synthase gene on moulting and fecundity in pea aphids ( Acyrthosiphon pisum ). Sci Rep. 2019;9(1):3694.
Nunes FMF, Simões ZLP. A non-invasive method for silencing gene transcription in honeybees maintained under natural conditions. Insect Biochem Mol Biol. 2009;39(2):157–60.
Vélez AM, Jurzenski J, Matz N, Zhou X, Wang H, Ellis M, et al. Developing an in vivo toxicity assay for RNAi risk assessment in honey bees Apis mellifera L. Chemosphere. 2016;144:1083–90.
Mehlhorn SG, Geibel S, Bucher G, Nauen R. Profiling of RNAi sensitivity after foliar dsRNA exposure in different European populations of Colorado potato beetle reveals a robust response with minor variability. Pesticide Biochemistry and Physiology. 2020;104569.
Khajuria C, Ivashuta S, Wiggins E, Flagel L, Moar W, Pleau M, et al. Development and characterization of the first dsRNA-resistant insect population from western corn rootworm, Diabrotica virgifera virgifera LeConte. PLOS ONE. 2018;13(5):e0197059.
Yoon J-S, Tian H, McMullen JG, Chung SH, Douglas AE. Candidate genetic determinants of intraspecific variation in pea aphid susceptibility to RNA interference. Insect Biochemistry and Molecular Biology. 2020;123:103408.
Kitzmann P, Schwirz J, Schmitt-Engel C, Bucher G. RNAi phenotypes are influenced by the genetic background of the injected strain. BMC Genomics. 2013;14:5.
Wang H, Zhang J, Zhao S, Zhu KY, Wu Y. Limited variations in susceptibility to an insecticidal double-stranded RNA (dsvATPaseE) among a laboratory strain and seven genetically differentiated field populations of Tribolium castaneum. Pestic Biochem Physiol. 2018;1(149):143–8.
Dow JA. pH GRADIENTS IN LEPIDOPTERAN MIDGUT. J Exp Biol. 1992;172(1):355–75.
Ortego F. Physiological adaptations of the insect gut to herbivory. In: Smagghe G, Diaz I, editors. Arthropod-plant interactions: novel insights and approaches for IPM [Internet]. Dordrecht: Springer Netherlands; 2012 [cited 2019 Dec 19]. p. 75–88. (Progress in Biological Control). Available from: https://0-doi-org.brum.beds.ac.uk/10.1007/978-94-007-3873-7_3
Wu K, Yang B, Huang W, Dobens L, Song H, Ling E. Gut immunity in Lepidopteran insects. Dev Comp Immunol. 2016;1(64):65–74.
Arimatsu Y, Kotani E, Sugimura Y, Furusawa T. Molecular characterization of a cDNA encoding extracellular dsRNase and its expression in the silkworm, Bombyx mori. Insect Biochem Mol Biol. 2007;37(2):176–83.
Furusawa T, Takayama E, Ishihara R, Hayashi Y. Double-stranded ribonuclease activity in the digestive juice and midgut of the silkworm, Bombyx mori. Comp Biochem Physiol Part B Comp Biochem. 1993;104(4):795–801.
Guan R, Hu S, Li H, Shi Z, Miao X. The in vivo dsRNA cleavage has sequence preference in insects. Front Physiol. 2018 Dec 10 [cited 2019 Nov 28];9. Available from: https://0-www-ncbi-nlm-nih-gov.brum.beds.ac.uk/pmc/articles/PMC6295558/
Guan R-B, Li H-C, Fan Y-J, Hu S-R, Christiaens O, Smagghe G, et al. A nuclease specific to lepidopteran insects suppresses RNAi. J Biol Chem. 2018 2;jbc.RA117.001553.
Liu J, Swevers L, Iatrou K, Huvenne H, Smagghe G. Bombyx mori DNA/RNA non-specific nuclease: Expression of isoforms in insect culture cells, subcellular localization and functional assays. J Insect Physiol. 2012;58(8):1166–76.
Allen ML, Walker WB. Saliva of Lygus lineolaris digests double stranded ribonucleic acids. J Insect Physiol. 2012;58(3):391–6.
Garbutt JS, Bellés X, Richards EH, Reynolds SE. Persistence of double-stranded RNA in insect hemolymph as a potential determiner of RNA interference success: Evidence from Manduca sexta and Blattella germanica. J Insect Physiol. 2013;59(2):171–8.
Shukla JN, Kalsi M, Sethi A, Narva KE, Fishilevich E, Singh S, et al. Reduced stability and intracellular transport of dsRNA contribute to poor RNAi response in lepidopteran insects. RNA Biol. 2016;13(7):656–69.
Singh IK, Singh S, Mogilicherla K, Shukla JN, Palli SR. Comparative analysis of double-stranded RNA degradation and processing in insects. Sci Rep. 2017;7(1):1–12.
Vatanparast M, Kim Y. Optimization of recombinant bacteria expressing dsRNA to enhance insecticidal activity against a lepidopteran insect, Spodoptera exigua. PLOS ONE. 2017 Aug 11;12(8):e0183054.
Wynant N, Santos D, Verdonck R, Spit J, Van Wielendaele P, Vanden BJ. Identification, functional characterization and phylogenetic analysis of double stranded RNA degrading enzymes present in the gut of the desert locust, Schistocerca gregaria. Insect Biochem Mol Biol. 2014;1(46):1–8.
Wang K, Peng Y, Pu J, Fu W, Wang J, Han Z. Variation in RNAi efficacy among insect species is attributable to dsRNA degradation in vivo. Insect Biochem Mol Biol. 2016;1(77):1–9.
Yoon J-S, Gurusamy D, Palli SR. Accumulation of dsRNA in endosomes contributes to inefficient RNA interference in the fall armyworm, Spodoptera frugiperda. Insect Biochem Mol Biol. 2017;1(90):53–60.
Castellanos NL, Smagghe G, Sharma R, Oliveira EE, Christiaens O. Liposome encapsulation and EDTA formulation of dsRNA targeting essential genes increase oral RNAi-caused mortality in the Neotropical stink bug Euschistus heros. Pest Manag Sci. 2019;75(2):537–48.
He B, Chu Y, Yin M, Müllen K, An C, Shen J. Fluorescent nanoparticle delivered dsRNA toward genetic control of insect pests. Adv Mater. 2013;25(33):4580–4.
Mysore K, Flannery EM, Tomchaney M, Severson DW, Duman-Scheel M. Disruption of Aedes aegypti olfactory system development through chitosan/siRNA nanoparticle targeting of semaphorin-1a. PLoS Negl Trop Dis. 2013;7(5):e2215.
Gillet F-X, Garcia RA, Macedo LLP, Albuquerque EVS, Silva MCM, Grossi-de-Sa MF. Investigating engineered ribonucleoprotein particles to improve Oral RNAi delivery in crop insect pests. Front Physiol. 2017;8:256.
Whitten MMA, Facey PD, Del Sol R, Fernández-Martínez LT, Evans MC, Mitchell JJ, et al. Symbiont-mediated RNA interference in insects. Proc Biol Sci. 2016;283(1825):20160042.
Berry B, Deddouche S, Kirschner D, Imler J-L, Antoniewski C. Viral Suppressors of RNA Silencing Hinder Exogenous and Endogenous Small RNA Pathways in Drosophila. PLOS ONE. 2009 Jun 10;4(6):e5866.
Li H, Li WX, Ding SW. Induction and suppression of RNA silencing by an animal virus. Science. 2002;296(5571):1319–21.
Nayak A, Berry B, Tassetto M, Kunitomi M, Acevedo A, Deng C, et al. Cricket paralysis virus antagonizes Argonaute 2 to modulate antiviral defense in Drosophila. Nat Struct Mol Biol. 2010;17(5):547–54.
van Mierlo JT, Bronkhorst AW, Overheul GJ, Sadanandan SA, Ekström J-O, Heestermans M, et al. Convergent Evolution of Argonaute-2 Slicer Antagonism in Two Distinct Insect RNA Viruses. PLOS Pathogens. 2012;8(8):e1002872.
Flynt A, Liu N, Martin R, Lai EC. Dicing of viral replication intermediates during silencing of latent Drosophila viruses. PNAS [Internet]. 2009 Feb 26 [cited 2020 Apr 20]; Available from: https://www.pnas.org/content/early/2009/02/26/0813412106
Goic B, Vodovar N, Mondotte JA, Monot C, Frangeul L, Blanc H, et al. RNA-mediated interference and reverse transcription control the persistence of RNA viruses in the insect model Drosophila. Nat Immunol. 2013;14(4):396–403.
Xie J, Li S, Zhang W, Xia Y. RNAi-knockdown of the Locusta migratoria nuclear export factor protein results in insect mortality and alterations in gut microbiome. Pest Manag Sci. 2019;75(5):1383–90.
He W, Xu W, Xu L, Fu K, Guo W, Bock R, et al. Length-dependent accumulation of double-stranded RNAs in plastids affects RNA interference efficiency in the Colorado potato beetle. J Exp Bot. 2020;71(9):2670–7.
Henschel A, Buchholz F, Habermann B. DEQOR: a web-based tool for the design and quality control of siRNAs. Nucleic Acids Res. 2004;1(32):W113–20.
Du M-H, Yan Z-W, Hao Y-J, Yan Z-T, Si F-L, Chen B, et al. Suppression of Laccase 2 severely impairs cuticle tanning and pathogen resistance during the pupal metamorphosis of Anopheles sinensis (Diptera: Culicidae). Parasit Vectors. 2017;10(1):171.
Elias-Neto M, Soares MPM, Simões ZLP, Hartfelder K, Bitondi MMG. Developmental characterization, function and regulation of a Laccase2 encoding gene in the honey bee, Apis mellifera (Hymenoptera, Apinae). Insect Biochem Mol Biol. 2010;40(3):241–51.
Futahashi R, Tanaka K, Matsuura Y, Tanahashi M, Kikuchi Y, Fukatsu T. Laccase2 is required for cuticular pigmentation in stinkbugs. Insect Biochem Mol Biol. 2011;41(3):191–6.
Nishide Y, Kageyama D, Hatakeyama M, Yokoi K, Jouraku A, Tanaka H, et al. Diversity and function of multicopper oxidase genes in the stinkbug Plautia stali. Sci Rep. 2020;10(1):3464.
Liu J, Lemonds TR, Marden JH, Popadić A. A pathway analysis of melanin patterning in a hemimetabolous insect. Genetics. 2016;203(1):403–13.
Tomoyasu Y, Arakane Y, Kramer KJ, Denell RE. Repeated co-options of exoskeleton formation during wing-to-elytron evolution in beetles. Curr Biol. 2009;19(24):2057–65.
Kato Y, Shiga Y, Kobayashi K, Tokishita S, Yamagata H, Iguchi T, et al. Development of an RNA interference method in the cladoceran crustacean Daphnia magna. Dev Genes Evol. 2011;220(11):337–45.
Ohde T (Nagoya U (Japan)), Masumoto M, Yaginuma T, Niimi T. Embryonic RNAi analysis in the firebrat, Thermobia domestica [Zygentoma: Lepismatidae]: Distal-less is required to form caudal filament. Journal of Insect Biotechnology and Sericology (Japan). 2009;78(2):99–105.
Schoppmeier M, Damen WG. Double-stranded RNA interference in the spider Cupiennius salei: the role of Distal-less is evolutionarily conserved in arthropod appendage formation. Dev Genes Evol. 2001;211(2):76–82.
Martin A, Serano JM, Jarvis E, Bruce HS, Wang J, Ray S, et al. CRISPR/Cas9 mutagenesis reveals versatile roles of hox genes in crustacean limb specification and evolution. Curr Biol. 2016;26(1):14–26.
Refki PN, Armisén D, Crumière AJJ, Viala S, Khila A. Emergence of tissue sensitivity to Hox protein levels underlies the evolution of an adaptive morphological trait. Dev Biol. 2014;392(2):441–53.
Tomoyasu Y, Wheeler SR, Denell RE. Ultrabithorax is required for membranous wing identity in the beetle Tribolium castaneum. Nature. 2005;433(7026):643–7.
Jose AM, Kim YA, Leal-Ekman S, Hunter CP. Conserved tyrosine kinase promotes the import of silencing RNA into Caenorhabditis elegans cells. Proc Natl Acad Sci U S A. 2012;109(36):14520–5.
Schaeper ND, Prpic N-M, Wimmer EA. A conserved function of the zinc finger transcription factor Sp8/9 in allometric appendage growth in the milkweed bug Oncopeltus fasciatus. Dev Genes Evol. 2009;219(8):427.
Kulkarni MM, Booker M, Silver SJ, Friedman A, Hong P, Perrimon N, et al. Evidence of off-target effects associated with long dsRNAs in Drosophila melanogaster cell-based assays. Nat Methods. 2006;3(10):833–8.
Horn T, Boutros M. E-RNAi: a web application for the multi-species design of RNAi reagents–2010 update. Nucleic Acids Res. 2010;38:W332–9.
Nüsslein-Volhard C. Of flies and fishes. Science. 1994;266(5185):572–4.
Knorr E, Bingsohn L, Kanost MR, Vilcinskas A. Tribolium castaneum as a Model for High-Throughput RNAi Screening. In: Vilcinskas A, editor. Yellow Biotechnology II: Insect Biotechnology in Plant Protection and Industry [Internet]. Berlin, Heidelberg: Springer; 2013 [cited 2021 Jul 6]. p. 163–78. (Advances in Biochemical Engineering/Biotechnology). Available from: https://0-doi-org.brum.beds.ac.uk/10.1007/10_2013_208
Anderson JA, Mickelson J, Challender M, Moellring E, Sult T, TeRonde S, et al. Agronomic and compositional assessment of genetically modified DP23211 maize for corn rootworm control. GM Crops Food. 2020;11(4):206–14.
Head GP, Carroll MW, Evans SP, Rule DM, Willse AR, Clark TL, et al. Evaluation of SmartStax and SmartStax PRO maize against western corn rootworm and northern corn rootworm: efficacy and resistance management. Pest Manag Sci. 2017;73(9):1883–99.
EFSA. Guidance on the risk assessment of plant protection products on bees (Apis mellifera, Bombus spp. and solitary bees). EFSA Journal. 2013;11(7):3295.
ISAAA website. GM Crop Events List - GM Approval Database | ISAAA.org [Internet]. 2020 [cited 2020 Apr 22]. Available from: http://www.isaaa.org/gmapprovaldatabase/eventslist/default.asp
Tan J, Levine SL, Bachman PM, Jensen PD, Mueller GM, Uffman JP, et al. No impact of DvSnf7 RNA on honey bee (Apis mellifera L.) adults and larvae in dietary feeding tests. Environmental Toxicology and Chemistry. 2016;35(2):287–94.
Guo X, Wang Y, Sinakevitch I, Lei H, Smith BH. Comparison of RNAi knockdown effect of tyramine receptor 1 induced by dsRNA and siRNA in brains of the honey bee, Apis mellifera. J Insect Physiol. 2018;1(111):47–52.
Jarosch A, Moritz RFA. Systemic RNA-interference in the honeybee Apis mellifera: tissue dependent uptake of fluorescent siRNA after intra-abdominal application observed by laser-scanning microscopy. J Insect Physiol. 2011;57(7):851–7.
Hu X, Boeckman CJ, Cong B, Steimel JP, Richtman NM, Sturtz K, et al. Characterization of DvSSJ1 transcripts targeting the smooth septate junction (SSJ) of western corn rootworm ( Diabrotica virgifera virgifera ). Sci Rep. 2020;10(1):11139.
Altpeter F, Springer NM, Bartley LE, Blechl AE, Brutnell TP, Citovsky V, et al. Advancing crop transformation in the era of genome editing. Plant Cell. 2016;28(7):1510–20.
Aliabadi HM, Landry B, Sun C, Tang T, Uludağ H. Supramolecular assemblies in functional siRNA delivery: Where do we stand? Biomaterials. 2012;33(8):2546–69.
Petrick JS, Moore WM, Heydens WF, Koch MS, Sherman JH, Lemke SL. A 28-day oral toxicity evaluation of small interfering RNAs and a long double-stranded RNA targeting vacuolar ATPase in mice. Regul Toxicol Pharmacol. 2015;71(1):8–23.
Witwer KW, Hirschi KD. Transfer and functional consequences of dietary microRNAs in vertebrates: Concepts in search of corroboration: Negative results challenge the hypothesis that dietary xenomiRs cross the gut and regulate genes in ingesting vertebrates, but important questions per. BioEssays. 2014;36(4):394–406.
Parsons KH, Mondal MH, McCormick CL, Flynt AS. Guanidinium-functionalized interpolyelectrolyte complexes enabling RNAi in resistant insect pests. Biomacromol. 2018;19(4):1111–7.
Maxwell B, Ramachandriya K, Abshire J, Cobb C. Enabling the RNA revolution; Cell-free dsRNA production and control of Colorado potato beetle [Internet]. p. 1. Available from: http://www.globalengage.co.uk/pgc/docs/PosterMaxwell.pdf
Avagrar. Decis forte [Internet]. Avagrar. 2020 [cited 2020 May 3]. Available from: https://avagrar.de/pflanzenschutzmittel/raps/insektizide/3/decis-forte
myAGRAR. myAGRAR Onlineshop | Decis forte 1 l | online kaufen [Internet]. https://www.myagrar.de/. 2020 [cited 2020 May 3]. Available from: https://www.myagrar.de/Pflanzenschutzmittel/Kulturen/Sonderkulturen/Decis-forte-1-l.html
BVL. Datenblatt PSM - Decis forte [Internet]. Bundesamt für Verbraucherschutz und Lebensmittelsicherheit. 2020 [cited 2020 May 3]. Available from: https://apps2.bvl.bund.de/psm/jsp/DatenBlatt.jsp?kennr=007418-00
BVL. PSM- Datenblatt Anwendungen Decis forte - Getreide [Internet]. Bundesamt für Verbraucherschutz und Lebensmittelsicherheit. 2020 [cited 2020 May 3]. Available from: https://apps2.bvl.bund.de/psm/jsp/BlattAnwendg.jsp?awg_id=007418-00/00-001&kennr=007418-00
BVL. PSM- Datenblatt Anwendungen Decis forte - Kartoffel [Internet]. Bundesamt für Verbraucherschutz und Lebensmittelsicherheit. 2020 [cited 2020 May 3]. Available from: https://apps2.bvl.bund.de/psm/jsp/BlattAnwendg.jsp?awg_id=007418-00/00-006&kennr=007418-00
Avagrar. XenTari (0,5kg) [Internet]. Avagrar. 2020 [cited 2020 May 3]. Available from: https://avagrar.de/pflanzenschutzmittel/sonderkulturen/insektizide-und-akarizide/366/xentari-0-5kg
BVL. Datenblatt PSM - XenTari [Internet]. Bundesamt für Verbraucherschutz und Lebensmittelsicherheit. 2020 [cited 2020 May 3]. Available from: https://apps2.bvl.bund.de/psm/jsp/DatenBlatt.jsp?kennr=024426-00
BVL. PSM- Datenblatt Anwendungen XenTari - Kohlgemüse [Internet]. Bundesamt für Verbraucherschutz und Lebensmittelsicherheit. 2020 [cited 2020 May 3]. Available from: https://apps2.bvl.bund.de/psm/jsp/BlattAnwendg.jsp?awg_id=024426-00/00-007&kennr=024426-00
BVL. PSM- Datenblatt Anwendungen XenTari - Wurzel- und Knollengemüse [Internet]. Bundesamt für Verbraucherschutz und Lebensmittelsicherheit. 2020 [cited 2020 May 3]. Available from: https://apps2.bvl.bund.de/psm/jsp/BlattAnwendg.jsp?awg_id=024426-00/06-001&kennr=024426-00
BVL. PSM- Datenblatt Anwendungen XenTari - Tomate, Aubergine [Internet]. Bundesamt für Verbraucherschutz und Lebensmittelsicherheit. 2020 [cited 2020 May 3]. Available from: https://apps2.bvl.bund.de/psm/jsp/BlattAnwendg.jsp?awg_id=024426-00/09-002&kennr=024426-00
Choi M-Y, Vander Meer RK, Coy M, Scharf ME. Phenotypic impacts of PBAN RNA interference in an ant, Solenopsis invicta, and a moth, Helicoverpa zea. J Insect Physiol. 2012;58(8):1159–65.
Raje KR, Peterson BF, Scharf ME. Screening of 57 candidate double-stranded RNAs for insecticidal activity against the pest termite reticulitermes flavipes (Isoptera: Rhinotermitidae). J Econ Entomol. 2018;111(6):2782–7.
Zhou X, Wheeler MM, Oi FM, Scharf ME. RNA interference in the termite reticulitermes flavipes through ingestion of double-stranded RNA. Insect Biochem Mol Biol. 2008;38(8):805–15.
Hapairai LK, Mysore K, Chen Y, Harper EI, Scheel MP, Lesnik AM, et al. Lure-and-kill yeast interfering RNA larvicides targeting neural genes in the human disease vector mosquito aedes aegypti. Sci Rep. 2017;7(1):1–11.
Kumar A, Wang S, Ou R, Samrakandi M, Beerntsen BT, Sayre RT. Development of an RNAi based microalgal larvicide to control mosquitoes. 2013;4(6):7.
Mysore K, Li P, Wang C-W, Hapairai LK, Scheel ND, Realey JS, et al. Characterization of a broad-based mosquito yeast interfering RNA larvicide with a conserved target site in mosquito semaphorin-1a genes. Parasit Vectors [Internet]. 2019 May 22 [cited 2020 Apr 24];12. Available from: https://0-www-ncbi-nlm-nih-gov.brum.beds.ac.uk/pmc/articles/PMC6532267/
Open Access funding enabled and organized by Projekt DEAL. We thank Deutsche Forschungsgemeinschaft (DFG) for funding Te 1380/1 and BU 1443/17.
Ethics approval and consent to participate
Consent for publication
The Georg-August-University and G.B. profit from sales of Eupheria with respect to Tribolium dsRNAs. G.B., S.G., S.M., and R.N. and Bayer CropScience applied for a patent on optimal RNAi target sequences for pest control.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
About this article
Cite this article
Mehlhorn, S., Hunnekuhl, V.S., Geibel, S. et al. Establishing RNAi for basic research and pest control and identification of the most efficient target genes for pest control: a brief guide. Front Zool 18, 60 (2021). https://0-doi-org.brum.beds.ac.uk/10.1186/s12983-021-00444-7
- RNA interference
- Establishment of RNAi
- Off target control
- Pest control