Comparative analysis of double-stranded RNA degradation and processing in insects

Abstract

RNA interference (RNAi) based methods are being developed for pest management. A few products for control of coleopteran pests are expected to be commercialized soon. However, variability in RNAi efficiency among insects is preventing the widespread use of this technology. In this study, we conducted research to identify reasons for variability in RNAi efficiency among thirty-seven (37) insects belonging to five orders. Studies on double-stranded RNA (dsRNA) degradation by dsRNases and processing of labeled dsRNA to siRNA showed that both dsRNA degradation and processing are variable among insects belonging to different orders as well as among different insect species within the same order. We identified homologs of key RNAi genes in the genomes of some of these insects and studied their domain architecture. These data suggest that dsRNA digestion by dsRNases and its processing to siRNAs in the cells are among the major factors contributing to differential RNAi efficiency reported among insects.

Enhancing RNAi Efficiency to Decipher the Functional Response of Potential Genes in Bemisia tabaci AsiaII-1 (Gennadius) Through dsRNA Feeding Assays

“…When hemolymph was isolated from dsRNases knockdown whitefly, the incubated dsRNA didn't showed notable degradation of dsRNA till 5 h (Figures 1D-F), which signifies the role of nucleases (dsRNases) in the hindrance of RNAi in whitefly. Various earlier reports also suggests the degradation of dsRNA in the insect belonging to lepidoptera, hemiptera, coleoptera and orthoptera orders due the presence of dsRNA specific nucleases in the gut or hemolymph (Singh et al, 2017;Peng et al, 2018;Prentice et al, 2019;Singh et al, 2019;Song et al, 2019). The conjugation of dsRNA with CQD was confirmed through gel retardation assay, which clearly indicated that an optimum concentration of CQD was required to conjugate the dsRNA (Figure 2A).…”

“…This is because the success and efficacy of RNAi depends upon several factors which include presence of core RNAi machinery, dose of dsRNA, the mode of RNAi delivery (Roignant et al, 2003), and the genes being targeted (Kitzmann et al, 2013). RNAi response is highly variable among insect species with lepidopteran being toward the lowest side and coleopterans showing highest efficiency (Shukla et al, 2016;Singh et al, 2017). The variability may be due to several factors, but majorly an impaired or slow cellular uptake of dsRNA in the gut and degradation of dsRNA in the insect body lead to deficient RNAi response.…”

Delivery of gene‐specific dsRNA by microinjection and feeding induces RNAi response in Sri Lanka weevil, Myllocerus undecimpustulatus undatus Marshall

“…7,9,10 Although the RNAi mechanism has been demonstrated in many insect orders, including Coleoptera, Hemiptera, Diptera, Hymenoptera and Lepidoptera, its efficiency among different insect taxa is extremely variable. 11,12 The level of sensitivity to RNAi, especially that induced by orally delivered dsRNA, may be a limiting factor for the application of RNAi as an insect control method since most of the RNAi-based crop protection strategies require ingestion of dsRNA by the insect pests. 13,14 Therefore, evaluation of RNAi efficiency is the first step toward determining the feasibility of using RNAi-based gene silencing for controlling a target insect.…”

Key factors determining variations in RNA interference efficacy mediated by different double‐stranded RNA lengths in Tribolium castaneum

“…This suggests that dsRNA degradation in T. castaneum varies with molecular length, and among the dsRNAs absorbable by the cells the shorter molecules are more easily degraded. Recent studies have shown that rapid dsRNA degradation by some nucleases can cause differences in dsRNA sensitivity among organisms (Wang et al, 2016;Singh et al, 2017). The two types of nuclease that are likely to be involved in dsRNA degradation are exonucleases and endonucleases (Kupsco et al, 2006;Gabel and Ruvkun, 2008;Ramachandran and Chen, 2008;Garbutt et al, 2013;Wynant et al, 2014;Garcia et al, 2017;Song et al, 2017;Cao et al, 2018;Guan et al, 2018).…”