{"doi":"10.1101/2023.06.21.545966","title":"Impact of random 50-base sequences inserted into an intron on splicing in <i>Saccharomyces cerevisiae</i>","abstract":"ABSTRACT Intron splicing is a key regulatory step in gene expression in eukaryotes. Three sequence elements required for splicing – 5’ and 3’ splice sites and a branch point – are especially well- characterized in Saccharomyces cerevisiae , but our understanding of additional intron features that impact splicing in this organism is incomplete, due largely to its small number of introns. To overcome this limitation, we constructed a library in S. cerevisiae of random 50-nucleotide elements (N50) individually inserted into the intron of a reporter gene and quantified canonical splicing and the use of cryptic splice sites by sequencing analysis. More than 70% of approximately 140,000 N50 elements reduced splicing by at least 20% compared to the intron control. N50 features, including higher GC content, presence of GU repeats and stronger predicted secondary structure of its pre-mRNA, correlated with reduced splicing efficiency. A likely basis for the reduced splicing of such a large proportion of variants is the formation of RNA structures that pair N50 bases – such as the GU repeats – with other bases specifically within the reporter pre-mRNA analyzed. However, neither convolutional neural network nor linear models were able to explain more than a small fraction of the variance in splicing efficiency across the library, suggesting that complex non-linear interactions in RNA structures are not accurately captured by RNA structure prediction methods given the limited number of variants. Our results imply that the specific context of a pre-mRNA may determine the bases allowable in an intron to prevent secondary structures that reduce splicing.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2023,"id":408921,"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":0.9529,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1070623,"name":"Alexander Sasse","orcid":"0000-0001-7031-8848","position":1,"is_corresponding":false},{"id":5261,"name":"Sara Mostafavi","orcid":"0000-0003-4698-1177","position":2,"is_corresponding":false},{"id":87047,"name":"Stanley Fields","orcid":"0000-0001-5504-5925","position":3,"is_corresponding":false},{"id":554720,"name":"Josh T. Cuperus","orcid":"0000-0002-8019-7733","position":4,"is_corresponding":false},{"id":1126265,"name":"Molly Perchlik","orcid":"0000-0001-5158-9079","position":0,"is_corresponding":true}],"reference_count":65,"raw_metadata":null,"created_at":"2026-07-19T01:21:22.368387Z","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":[]}