RNA interference (RNAi) is a promising next generation technology for the development of species-specific pest management. The key to successful RNAi based-plant protection is dependent in part on data-driven target gene selection, a challenging task due to the absence of laboratory strains and the seasonality of most pest species. In this study, we aimed to identify novel target genes by performing a knowledge-based approach in order to expand the spectrum of known potent RNAi targets. Recently, the protein-coding genes ncm, Rop, RPII-140, and dre4 have been identified as sensitive RNAi targets for pest control. Based on these potent RNAi targets, we constructed an interaction network and analyzed a selection of 30 genes in the model beetle Tribolium castaneum via injection of dsRNA synthesized by in vitro transcription. Nineteen of these targets induced significant mortality of over 70%, including six that caused 100% lethality. Orthologs of active T. castaneum RNAi targets were verified in the economically important coleopteran pests Diabrotica virgifera virgifera and Brassicogethes aeneus. Knockdown of D. v. virgifera genes coding for transcription factor Spt5, Spt6, and RNA polymerase II subunit RPII-33 caused over 90% mortality in larval feeding assays. Injection of dsRNA constructs targeting RPII-215 or the pre-mRNA-processing factor Prp19 into adult B. aeneus resulted in high lethality rates of 93 and 87%, respectively. In summary, the demonstrated knowledge-based approaches increased the probability of identifying novel lethal RNAi target genes from 2% (whole genome) to 36% (transcription- and splicing-related genes). In addition, performing RNAi pre-screening in a model insect increased also the probability of the identification essential genes in the difficult-to-work-with pest species D. v. virgifera and B. aeneus.
In vitro safety pharmacology evaluation of 2-hydroxybenzylamine acetate
