{"doi":"10.1101/2023.04.26.538501","title":"Analysis of single-cell CRISPR perturbations indicates that enhancers act multiplicatively and provides limited evidence for epistatic-like interactions","abstract":"Summary A single gene may have multiple enhancers, but how they work in concert to regulate transcription is poorly understood. To analyze enhancer interactions throughout the genome, we developed a generalized linear modeling framework, GLiMMIRS, for interrogating enhancer effects from single-cell CRISPR experiments. We applied GLiMMIRS to a published dataset and tested for interactions between 46,166 enhancer pairs and corresponding genes, including 264 ’high-confidence’ enhancer pairs. We found that enhancer effects combine multiplicatively but with limited evidence for further interactions. Only 31 enhancer pairs exhibited significant interactions (FDR < 0.1), of which none came from the high confidence subset and 20 were driven by outlier expression values. Additional analyses of a second CRISPR dataset and in silico enhancer perturbations with Enformer both support a multiplicative model of enhancer effects without interactions. Altogether, our results indicate that enhancer interactions are uncommon or have small effects that are difficult to detect. Highlights Analysis of a large single-cell CRISPRi screen finds limited evidence for synergistic or redundant interactions between enhancers The collective action of multiple enhancers on a common target gene follows a multiplicative model of activity A new statistical framework for simulating and modeling data from single-cell CRISPRi screens","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2023,"id":392335,"datarank":0.26876392038420827,"base_score":1.791759469228055,"endowment":1.791759469228055,"self_citation_contribution":0.26876392038420827,"citation_network_contribution":0.0,"self_endowment_contribution":0.26876392038420827,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":5,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.5002,"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":1003622,"name":"Karthik Guruvayurappan","orcid":"0000-0003-3791-8387","position":1,"is_corresponding":false},{"id":775740,"name":"Shushan Toneyan","orcid":"0000-0002-1365-3241","position":2,"is_corresponding":false},{"id":51507,"name":"Hsiuyi V. Chen","orcid":"0000-0002-5216-6710","position":3,"is_corresponding":false},{"id":424421,"name":"Aaron R. Chen","orcid":"0000-0003-4938-3834","position":4,"is_corresponding":false},{"id":298873,"name":"Peter K. Koo","orcid":"0000-0001-8722-0038","position":5,"is_corresponding":false},{"id":43077,"name":"Graham McVicker","orcid":"0000-0003-0991-0951","position":6,"is_corresponding":false},{"id":58765,"name":"Jessica Zhou","orcid":"0000-0002-4131-0756","position":0,"is_corresponding":true}],"reference_count":49,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T01:18:52.232318Z","pmid":"37163096","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":[]}