A bioinformatic ecological risk assessment framework for externally applied double-stranded RNA-based biopesticides

Area of Science:

• Environmental Science
• Biotechnology
• Genetics

Background:

• Double-stranded RNA (dsRNA)-based biopesticides utilize the RNA interference (RNAi) pathway for targeted pest control.
• This novel mode of action (MoA) offers potential environmental benefits due to high specificity.
• Evaluating potential off-target effects on non-target organisms (NTOs) is critical for regulatory review.

Purpose of the Study:

• To propose a bioinformatics framework for assessing sequence-specific off-target effects of dsRNA biopesticides on NTOs.
• To ensure robust ecological risk assessments for dsRNA-based pest management tools.

Main Methods:

• The framework recommends considering NTO exposure and susceptibility.
• Standardized analyses include searching for 21 nucleotide (nt) stretches of perfect and 80% identity between dsRNA and off-target transcripts.
• A three-pronged approach involves phylogenetic analysis, broad database searches, and full transcriptome analyses.

Main Results:

• The proposed framework standardizes the identification of potential off-target sequence similarities.
• It incorporates phylogenetic analysis to define taxonomic scope and broad database searches for unexpected similarities.
• Full transcriptome analyses are recommended for NTOs of particular concern.

Conclusions:

• The framework enables a comprehensive ecological risk assessment for dsRNA biopesticides.
• It provides a clear regulatory path forward for this innovative pest management technology.
• Integrating bioinformatics with risk characterization ensures the safe deployment of dsRNA biopesticides.