Integrating WGCNA, TCN, and Alternative Splicing to Map Early Caste Programs in Day-2 Honeybee Larvae.

BACKGROUND/OBJECTIVES: The larval stage plays a pivotal role in determining caste and sex in Apis mellifera. This study integrates RNA-seq, WGCNA, and alternative splicing analyses to explore gene expression differences among 2-day-old worker, drone, and queen larvae. METHODS: RNA-seq was conducted on 2-day-old larvae from all three castes. Differential expression, WGCNA, and alternative splicing patterns were investigated. A deep learning TCN model was trained using WGCNA-derived modules and demonstrated high classification accuracy. RESULTS: The TCN model highlighted a top-10 gene set, including PDHB, Fibroin3, and LOC724161. Significant caste- and sex-specific splicing events were detected in Tk, Csd, and Fem, with AF events being most prevalent. Splicing differences between sexes exceeded those observed among castes. CONCLUSIONS: The 2-day-old larval stage is crucial for both caste and sex differentiation in honeybees. This study identifies key genes and splicing events, offering new insights into the molecular mechanisms underlying caste formation and sex determination.