PeerJ (Dec 2017)

In silico identification of off-target pesticidal dsRNA binding in honey bees (Apis mellifera)

  • Christina L. Mogren,
  • Jonathan Gary Lundgren

DOI
https://doi.org/10.7717/peerj.4131
Journal volume & issue
Vol. 5
p. e4131

Abstract

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Background Pesticidal RNAs that silence 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 double stranded RNAs (dsRNAs) were collated into a database. The target gene sequences for these pesticidal RNAs were determined, and the degree of similarity with sequences in the honey bee genome were evaluated statistically. Results We identified 101 insecticidal RNAs sharing high sequence similarity with genomic regions in honey bees. The likelihood that off-target sequences were similar increased with the number of nucleotides in the dsRNA molecule. The similarities of non-target genes to the pesticidal RNA 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 similarity with pesticidal RNAs relative to other areas of the genome. Discussion Although sequence similarity does not itself guarantee a significant phenotypic effect in honey bees by the primary dsRNA, in silico screening may help to identify appropriate experimental endpoints within a risk assessment framework for pesticidal RNAi.

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