RISC-Bound Small RNA Sequencing Provides Insights into Guide Strand Selection and siRNA Trimming and Tailing Following Insecticidal dsRNA Delivery
Guney, G.; Plathner, P.; Scholten, S.; Cedden, D.
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RNA interference (RNAi) offers a sequence-specific approach to pest control. In insects, Dicer-2 processes double-stranded RNA (dsRNA) into small interfering RNA (siRNA) duplexes, from which the RNA-induced silencing complex (RISC) retains a guide strand. Only antisense-loaded RISC can mediate cleavage of the target transcript. However, how sequence features shape the RISC-bound siRNA pool in pests remains poorly understood, limiting opportunities for sequence optimization. Here, we profiled RISC-bound siRNAs following injection of 34 insecticidal dsRNAs targeting 11 essential genes in Tribolium castaneum larvae. We computationally reconstructed 7,879 siRNA pairs and examined associations between sequence features and strand bias. Differences in GC identity at terminal paired positions 1 to 5, used as a proxy for local thermodynamic asymmetry, correlated with strand bias, with the strongest correlations at the first two paired positions. ORF targeting and reduced predicted antisense self-folding were also associated with higher antisense fractions. Analysis of non-templated terminal additions revealed predominantly 3-prime uridylation, a known signature of small RNA turnover, along with putative 3-prime trimming. Among ORF-associated siRNA pairs, sense strands showed higher relative U-tailing abundance, based on 3-prime uridylated and putatively trimmed-and-3-prime-uridylated reads relative to perfect 21-nt reads, than antisense strands. Antisense strands with the least predicted self-folding also showed low relative U-tailing abundance. These observations are consistent with sequence-dependent contributions from both guide-strand selection and differential post-RISC-loading siRNA retention, although a causal link remains to be established. The identified associations provide a basis for testing whether dsRNA sequence optimization can improve pest control efficacy and reduce off-target activity.
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