Interpretable machine learning enables de novo mapping of cell type-specific RNA splicing regulation from scRNA-seq data

Interpretable machine learning enables de novo mapping of cell type-specific RNA splicing regulation from scRNA-seq data | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Interpretable machine learning enables de novo mapping of cell type-specific RNA splicing regulation from scRNA-seq data Xuerui Yang, Xianke Xiang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9148958/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Context-dependent regulation of alternative splicing (AS), largely mediated by RNA-binding proteins (RBPs), is a key post-transcriptional mechanism shaping diverse biological processes. Experimental approaches for probing splicing regulation, such as CLIP-based assays and RBP perturbations, suffer from low throughput, poor physiological relevance, and bulk resolution that overlooks cellular heterogeneity. Here, we present CASREL (cell-specific alternative splicing regulation inference via explainable learning), a machine learning framework that reconstructs RBP-AS regulatory circuitry directly from single-cell RNA sequencing data without reliance on prior RBP-RNA binding annotations. CASREL integrates ensemble learning with SHAP-based interpretation to uncover RBP-AS associations, leveraging unique features of single-cell splicing profiles, including polarized isoform usage, minimal averaging of regulatory programs, and resilience to expression noise. Applications across diverse tissues and cell types demonstrate its robustness, accuracy, and biological relevance, establishing CASREL as a powerful method for de novo mapping of cell-specific RNA splicing regulation in physiological contexts. Biological sciences/Biological techniques/Bioinformatics Biological sciences/Computational biology and bioinformatics/Machine learning Biological sciences/Genetics/RNA splicing Biological sciences/Computational biology and bioinformatics/Data mining Biological sciences/Biotechnology/Genomics/Transcriptomics single-cell RNA sequencing alternative splicing splicing regulation RNA-binding protein (RBP) ensemble learning interpretable machine learning Full Text Additional Declarations There is NO Competing Interest. Supplementary Files CASRELSupplFigv3.3.docx Supplementary Figures SupplTable.docx Supplementary Table Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9148958","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":608382356,"identity":"8e9b999c-0bd9-487e-894b-60ef8ff66e9b","order_by":0,"name":"Xuerui Yang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFklEQVRIie3RsUrDQBjA8S8cZLq0a7qoj/CVQqAo6aukBJIlaKfMKYWbfIBIX8JO4nZyQ5barBk6pIuLGRIczKDopVOHs+omeH/uOPi4HxwcgE73pyOEA+B+ycwfEXOa/JIAHSbd8S3B7FE8W+ziCjP6umtnW/fO9kuoYwH9ZaIm68tgfMOC8a2wVguKT/59GqCRbgTYW64mPHKwYQKxI4DCx8JDYjEBaHtqklcOTtmHJHQ3b/ckrMn7MVJEo7JhvCNGQlG4coLEOEIGReXIl/s4EOZwKYmH62r2cL0JqV2oSS+PRi80drGXi7Jp38QEs3BVtvH5ST9VkzMOpn04kP8JwOWmyvuy0wRIfTiYfHVTp9Pp/m+fLlhm70JcG/0AAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-7731-2147","institution":"Tsinghua University","correspondingAuthor":true,"prefix":"","firstName":"Xuerui","middleName":"","lastName":"Yang","suffix":""},{"id":608382357,"identity":"1f95b485-1b37-4989-9687-9123252f121d","order_by":1,"name":"Xianke Xiang","email":"","orcid":"","institution":"Chongqing University","correspondingAuthor":false,"prefix":"","firstName":"Xianke","middleName":"","lastName":"Xiang","suffix":""}],"badges":[],"createdAt":"2026-03-17 12:53:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9148958/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9148958/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105035251,"identity":"f26b0e65-2f18-4045-b8c7-4c002c25fefd","added_by":"auto","created_at":"2026-03-20 07:25:44","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1039761,"visible":true,"origin":"","legend":"","description":"","filename":"CASRELv3.3.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9148958/v1_covered_95963c4a-05a9-4249-b3e1-0bc33b4cb7d3.pdf"},{"id":104958441,"identity":"15d2d070-a999-44b8-a45f-e7e6051425e9","added_by":"auto","created_at":"2026-03-19 08:28:16","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1583098,"visible":true,"origin":"","legend":"Supplementary Figures","description":"","filename":"CASRELSupplFigv3.3.docx","url":"https://assets-eu.researchsquare.com/files/rs-9148958/v1/617630d776735aed2d6bb96c.docx"},{"id":104958442,"identity":"2eae53f5-ab0e-4fd5-88f8-0e57889d3c04","added_by":"auto","created_at":"2026-03-19 08:28:16","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":33326,"visible":true,"origin":"","legend":"Supplementary Table","description":"","filename":"SupplTable.docx","url":"https://assets-eu.researchsquare.com/files/rs-9148958/v1/867f7c96dd4022ce78fd141f.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Interpretable machine learning enables de novo mapping of cell type-specific RNA splicing regulation from scRNA-seq data","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"single-cell RNA sequencing, alternative splicing, splicing regulation, RNA-binding protein (RBP), ensemble learning, interpretable machine learning","lastPublishedDoi":"10.21203/rs.3.rs-9148958/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9148958/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Context-dependent regulation of alternative splicing (AS), largely mediated by RNA-binding proteins (RBPs), is a key post-transcriptional mechanism shaping diverse biological processes. 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