The present study outlines an in-silico pipeline for CRISPR/Cas9-mediated editing of the vitellogenin (Vg) gene in Apis mellifera, a gene integral to honeybee reproduction, immunity, and social behavior. From an initial pool of 116 gRNA candidates, we applied stringent filters for on-target efficiency, minimal off-target potential, and optimal GC content (40–60%), followed by manual verification of PAM sites within critical exonic regions and BLAST screening against the honeybee genome. The top-ranked guide, CTGGACACCGAAAATGATGGCGG (NC_037641.1:5031500, – strand), exhibited 50% GC content, zero self-complementarity, no off-target hits (MM0–MM3), and a predicted cleavage efficiency of 78.91%. Thermodynamic ensemble analysis via RNAfold revealed a free energy of –1.40 kcal/mol, an MFE structure frequency of 52.15%, and ensemble diversity of 3.69, indicating a dominant yet moderately flexible conformation favorable for Cas9 binding. inDelphi simulations forecast predominately 1–2 bp deletions yielding frameshifts, highlighting strong knockout potential, while the guide’s clean target context suggests high-fidelity knock-in via HDR. Secondary-structure insights—open loops and minimal hairpins in the spacer region—further support robust editing performance. This comprehensive computational framework attempts to provide high-confidence gRNAs for functional Vg editing using a low-cost, in silico approach, and encompasses applications including behavioral biology, disease resistance, and selective breeding in honey bee populations
