{"doi":"10.3390/genes17010017","title":"ACmix-Swin Deep Learning of 4-Day-Old Apis mellifera Larval Transcriptomes Reveals Early Caste-Biased Regulatory Hubs","abstract":"<h4>Background/objectives</h4>Early larval development is critical for caste and sex differentiation in honeybees. This study investigates molecular divergence in 4-day-old <i>Apis mellifera</i> larvae and introduces a customized deep learning model for hub-gene discovery.<h4>Methods</h4>Genome-guided RNA-seq, DEGs, WGCNA, and splicing analyses were integrated. A hybrid convolution-attention model, ACmix-Swin, combined with WGAN-GP augmentation, was developed to classify larvae and prioritize caste-biased genes. Selected genes were validated by qPCR.<h4>Results</h4>Significant caste- and sex-specific divergence was detected in cuticle formation, hormone metabolism, and reproductive signaling. ACmix-Swin achieved the highest accuracy among baseline models and consistently identified key regulators, including <i>Vg</i>, <i>LOC725841</i>, <i>LOC412768</i>, and <i>LOC100576841</i>. qPCR confirmed RNA-seq trends.<h4>Conclusions</h4>Caste- and sex-specific transcriptional programs are established early in larval development. The ACmix-Swin framework provides an effective strategy for high-dimensional transcriptome interpretation and robust hub-gene identification.","journal":"Genes","year":2025,"id":7572,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.0637,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-12-25","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":68610,"name":"Jinyou Li","orcid":null,"position":1,"is_corresponding":false},{"id":68611,"name":"Weixue Tian","orcid":null,"position":2,"is_corresponding":false},{"id":68612,"name":"Xiang Ding","orcid":null,"position":3,"is_corresponding":false},{"id":68613,"name":"Runlang Su","orcid":"0009-0004-5028-4782","position":4,"is_corresponding":false},{"id":68614,"name":"Dan Yue","orcid":"0000-0002-2646-4386","position":5,"is_corresponding":false},{"id":68609,"name":"Peixun Gong","orcid":null,"position":0,"is_corresponding":true}],"reference_count":68,"raw_metadata":null,"created_at":"2026-03-01T18:20:47.508186Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}