Emerging experimental and bioinformatic approaches in RNA interference-based pest control research

RNA interference (RNAi) has emerged as a promising strategy for species-specific and environmentally friendly pest control, offering an alternative to conventional chemical insecticides that are increasingly constrained by resistance development and ecological concerns. RNAi-based approaches involve oral delivery of double-stranded RNA (dsRNA), which is processed into RNA-induced silencing complex (RISC)-bound small interfering RNA (siRNA) to silence essential genes of pests. This review synthesizes recent advances in experimental and bioinformatic methodologies that are facilitating and enhancing RNAi research in insect pest management. Particular emphasis is placed on molecular validation techniques that move beyond phenotype-based bioassays, including RISC-bound small RNA sequencing to resolve dsRNA processing and guide strand selection, RNA degradomics to map siRNA-mediated transcript cleavage events and transcriptomic and proteomic profiling to characterize genome-wide responses and compensatory effects. In parallel, dsRNA visualization methods provide mechanistic insight into uptake, intracellular trafficking and degradation dynamics, clarifying barriers that distinguish responsive from recalcitrant species. Complementing these experimental developments, emerging computational platforms enable insect-optimized target selection, dsRNA design and environmentally informed off-target prediction. Together, these innovations support a transition toward more predictive and mechanistically grounded RNAi-based pest control applications. The integration of high-resolution molecular tools with specialized bioinformatic pipelines is expected to enhance efficacy, safety and reproducibility, advancing RNAi-based pest control toward practical and scalable agricultural deployment.