{"doi":"10.1101/2025.01.20.633986","title":"Generative modeling for RNA splicing prediction and design","abstract":"Alternative splicing (AS) of pre-mRNA plays a crucial role in tissue-specific gene regulation, with disease implications due to splicing defects. Predicting and manipulating AS can therefore uncover new regulatory mechanisms and aid in therapeutics design. We introduce TrASPr+BOS, a generative AI model with Bayesian Optimization for predicting and designing RNA for tissue-specific splicing outcomes. TrASPr is a multi-transformer model that can handle different types of AS events and generalize to unseen cellular conditions. It then serves as an oracle, generating labeled data to train a Bayesian Optimization for Splicing (BOS) algorithm to design RNA for condition-specific splicing outcomes. We show TrASPr+BOS outperforms existing methods, enhancing tissue-specific AUPRC by up to 2.4 fold and capturing tissue-specific regulatory elements. We validate hundreds of predicted novel tissue-specific splicing variations and confirm new regulatory elements using dCas13. We envision TrASPr+BOS as a light yet accurate method researchers can probe or adopt for specific tasks.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2025,"id":555933,"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":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9533,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1454755,"name":"Natalie Maus","orcid":"0000-0002-6616-8506","position":1,"is_corresponding":false},{"id":286526,"name":"Anupama Jha","orcid":"0000-0003-3029-2086","position":2,"is_corresponding":false},{"id":1290784,"name":"Kevin Yang","orcid":"0000-0002-4897-3691","position":3,"is_corresponding":false},{"id":420675,"name":"Benjamin D Wales-McGrath","orcid":"0009-0006-4184-7875","position":4,"is_corresponding":false},{"id":1018595,"name":"San Jewell","orcid":"0000-0002-6494-8015","position":5,"is_corresponding":false},{"id":1455270,"name":"Anna Tangiyan","orcid":null,"position":6,"is_corresponding":false},{"id":695015,"name":"Peter S. Choi","orcid":"0000-0002-2820-3032","position":7,"is_corresponding":false},{"id":35398,"name":"Jacob R. Gardner","orcid":"0000-0003-1897-8384","position":8,"is_corresponding":false},{"id":281155,"name":"Yoseph Barash","orcid":"0000-0003-3005-5048","position":9,"is_corresponding":false},{"id":1290785,"name":"Di Wu","orcid":"0000-0002-9433-7725","position":0,"is_corresponding":true}],"reference_count":68,"raw_metadata":null,"created_at":"2026-07-19T02:55:03.976486Z","pmid":"39896553","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":[]}