Abstract
Abstract
CRISPR/Cas9 genome editing provides a powerful framework for interrogating gene function in
Apis mellifera
. Yet, empirical application remains challenging due to biological constraints, including haplodiploid genetics, narrow embryonic injection window, and the social rearing requirements that complicate functional validation. These constraints necessitate in silico pre-screening to maximize editing success before resource-intensive wet-lab implementation. Within the omnigenic framework, which distinguishes core regulatory genes from peripheral loci buffered by network effects,
vitellogenin
(
Vg
) represents an optimal target which is ancestrally dedicated to yolk provisioning; it has been co-opted to orchestrate diverse non-reproductive functions including longevity, stress resistance, immunity, and social behavior. We developed a computational pipeline to design a list of 57 and 56 candidate guide RNAs (gRNA) for targeted
Vg
knockout, evaluating candidate sites in both functional exons 2 and 3 based on structural accessibility and frameshift efficiency. Comparative analysis revealed complementary strengths in two top-best candidates from initial target pool of predicted gRNAs. The gRNA targeting exon 2 exhibits weaker secondary structure (ΔG = –0.25 kcal/mol versus –2.10 kcal/mol for exon 3), aligning with empirical evidence that sites with ΔG > –1.0 kcal/mol achieve 2–5 × higher Cas9 binding efficiency. This site yielded moderate frameshift frequency (77.8%; 61.9 percentile). Conversely, the predicted editing outcome for the gRNA targeting exon 3, despite stronger structural constraints, demonstrated superior functional disruption metrics demonstrating very high frameshift frequency (88.3%; 95.2 percentile), high
in silico
editing precision, minimal microhomology-mediated repair bias, and reproducible outcomes wherein nearly all predicted indels disrupt the coding sequence. Protein structure and domain analyses further predict that frameshift edits will generate a truncated protein missing all downstream functional domains. We recommend parallel empirical validation of both exon 2 and exon 3 targets to resolve the trade-off between structural accessibility (favoring higher editing rates) and frameshift efficacy (favoring complete loss-of-function). This dual-target strategy accommodates uncertainty in in vivo performance while maximizing the probability of generating informative phenotypes. Our
in silico
framework enables rational CRISPR design in non-model organisms by computationally balancing biophysical accessibility with functional impact, accelerating functional genomics in species where empirical optimization faces substantial biological constraints.