Assessing Environmental RNAi in a Non-Model Organism
Mondal, M.; Peter, J.; Scarbrough, O.; Flynt, A. S.
Show abstract
RNA interference (RNAi) regulates gene expression in most multicellular organisms through binding of small RNA effectors to target transcripts. Exploiting this process is a popular strategy for genetic manipulation in invertebrates and has applications that includes control of pests. Successful RNAi technologies are dependent on delivery method. The most convenient method is likely feeding which is effective in some animals while others are insensitive. Thus, there is a need to develop RNAi technology on a per-species basis, which will require a comprehensive approach for assessing small RNA production from synthetic nucleic acids. Using a biochemical and sequencing approaches we investigated the metabolism of ingested RNAs using the two-spotted spider mite, Tetranychus urticae, as a model for RNAi insensitivity. This chelicerae arthropod shows only modest response to oral RNAi and has biogenesis pathways distinct from model organisms. To identify RNAi substrates in T. urticae we characterized processing of synthetic RNAs and those derived from plant transcripts ingested during feeding. Through characterization of read size length and overlaps of small RNA reads, visualization methods were developed that facilitate distinguish trans-acting small RNAs from degradation fragments. Using a strategy that delineates small RNA classes, we found a variety of RNA species are gated into spider mite RNAi pathways, however, potential mature trans-acting RNAs appear very unstable and rare. This suggests spider mite RNAi pathway products that originate as ingested materials may be preferentially metabolized instead of converted into regulators of gene expression. Spider mites infest a variety of plants, and it would be maladaptive to generate diverse gene regulators from dietary RNAs. This study provides a framework for assessing RNAi technology in organisms where genetic and biochemical tools are absent and benefit rationale design of RNAi triggers.
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