In silico identification of off-target pesticidal dsRNA binding in honey bees (Apis mellifera)
- Subject Areas
- Biotechnology, Ecology, Entomology, Toxicology, Ecotoxicology
- RNAi, non-target, risk assessment, transgenic crops
- © 2017 Mogren et al.
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2017. In silico identification of off-target pesticidal dsRNA binding in honey bees (Apis mellifera) PeerJ Preprints 5:e3287v1 https://doi.org/10.7287/peerj.preprints.3287v1
Background. Pesticidal RNAs silencing critical gene function have great potential in pest management, but the benefits of this technology must be weighed against non-target organism risks. Methods. Published studies that developed pesticidal dsRNAs were collated into a database. The target gene sequences for these pesticidal RNAs were determined, and the degree of sequence homology with the honey bee genome were evaluated statistically for each. Results. We identified 101 insecticidal dsRNAs sharing high sequence homology with genomic regions in honey bees. The likelihood of off-target sequence homology increased with the parent dsRNA length. Non-target gene binding was unaffected by taxonomic relatedness of the target insect to honey bees, contrary to previous assertions. Gene groups active during honey bee development had disproportionately high sequence homology with pesticidal RNAs relative to other areas of the genome. Discussion. Although sequence homology does not itself guarantee a significant phenotypic effect in honey bees, in silico screening may help to identify appropriate experimental endpoints within a risk assessment framework for pesticidal RNAi.
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This excel sheet contains the necessary information for rerunning all of our analyses in this paper