Integrative epigenomic profiling by high-speed super-resolution imaging and deep learning reveals chromatin state biomarkers

Integrative epigenomic profiling by high-speed super-resolution imaging and deep learning reveals chromatin state biomarkers | 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 Research Article Integrative epigenomic profiling by high-speed super-resolution imaging and deep learning reveals chromatin state biomarkers Yicheng Wang, Nur Syatila Ab Ghani, Munmee Dutta, Shungo Adachi, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7787625/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Feb, 2026 Read the published version in Epigenetics & Chromatin → Version 1 posted 11 You are reading this latest preprint version Abstract Background Comprehensive profiling of epigenetic states is essential for understanding gene regulation and disease mechanisms. Sequencing-based methods such as ChIP-seq, Hi-C, and RNA-seq provide genome-wide views of histone modifications and 3D genome organization, but lack spatial resolution within single nuclei. Results Here we present an integrative framework that combines high-speed super-resolution microscopy with deep learning for image-based epigenetic profiling. Using models of (i) histone deacetylase inhibition in HEK293T cells and (ii) Rett syndrome iPS cells carrying MECP2 mutations, our approach accurately discriminated their epigenetic states (99.6% and 96.1% accuracy, respectively) and identified the nuclear periphery as a hotspot of H3K27ac and CTCF redistribution. Sequencing-based analyses confirmed compartment switching and lamina-associated domain alterations consistent with the image-based biomarkers. These results demonstrate that high-speed super-resolution imaging, when combined with deep learning, provides a powerful tool for epigenetic profiling. Conclusions Our framework offers a generalizable strategy for integrating imaging and genomics to uncover chromatin-level mechanisms in development, disease, and therapeutic response. image-based epigenomic profiling super-resolution microscopy deep learning histone deacetylase inhibitor Rett syndrome Full Text Additional Declarations No competing interests reported. Supplementary Files WangSyatilaSuppl1251004.pdf WangSyatilaSuppl2251004.xlsx Cite Share Download PDF Status: Published Journal Publication published 28 Feb, 2026 Read the published version in Epigenetics & Chromatin → Version 1 posted Editorial decision: Revision requested 19 Nov, 2025 Reviews received at journal 23 Oct, 2025 Reviews received at journal 22 Oct, 2025 Reviewers agreed at journal 09 Oct, 2025 Reviewers agreed at journal 09 Oct, 2025 Reviewers agreed at journal 09 Oct, 2025 Reviewers agreed at journal 09 Oct, 2025 Reviewers invited by journal 08 Oct, 2025 Editor assigned by journal 08 Oct, 2025 Submission checks completed at journal 07 Oct, 2025 First submitted to journal 05 Oct, 2025 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-7787625","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":529705013,"identity":"5ca11480-61bb-471c-8b72-071ac33c193c","order_by":0,"name":"Yicheng Wang","email":"","orcid":"","institution":"The University of Tokyo","correspondingAuthor":false,"prefix":"","firstName":"Yicheng","middleName":"","lastName":"Wang","suffix":""},{"id":529705016,"identity":"be789f35-3018-4100-9c2f-1a31291ac48c","order_by":1,"name":"Nur Syatila Ab Ghani","email":"","orcid":"","institution":"Kitasato 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biomarkers","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"epigenetics-and-chromatin","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"epch","sideBox":"Learn more about [Epigenetics \u0026 Chromatin](http://epigeneticsandchromatin.biomedcentral.com/)","snPcode":"13072","submissionUrl":"https://submission.nature.com/new-submission/13072/3","title":"Epigenetics \u0026 Chromatin","twitterHandle":"@EpigenChromatin","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"image-based epigenomic profiling, super-resolution microscopy, deep learning, histone deacetylase inhibitor, Rett syndrome","lastPublishedDoi":"10.21203/rs.3.rs-7787625/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7787625/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eComprehensive profiling of epigenetic states is essential for understanding gene regulation and disease mechanisms. Sequencing-based methods such as ChIP-seq, Hi-C, and RNA-seq provide genome-wide views of histone modifications and 3D genome organization, but lack spatial resolution within single nuclei.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eHere we present an integrative framework that combines high-speed super-resolution microscopy with deep learning for image-based epigenetic profiling. Using models of (i) histone deacetylase inhibition in HEK293T cells and (ii) Rett syndrome iPS cells carrying \u003cem\u003eMECP2\u003c/em\u003e mutations, our approach accurately discriminated their epigenetic states (99.6% and 96.1% accuracy, respectively) and identified the nuclear periphery as a hotspot of H3K27ac and CTCF redistribution. Sequencing-based analyses confirmed compartment switching and lamina-associated domain alterations consistent with the image-based biomarkers. These results demonstrate that high-speed super-resolution imaging, when combined with deep learning, provides a powerful tool for epigenetic profiling.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eOur framework offers a generalizable strategy for integrating imaging and genomics to uncover chromatin-level mechanisms in development, disease, and therapeutic response.\u003c/p\u003e","manuscriptTitle":"Integrative epigenomic profiling by high-speed super-resolution imaging and deep learning reveals chromatin state biomarkers","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-22 18:39:50","doi":"10.21203/rs.3.rs-7787625/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-19T14:32:06+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-23T20:09:20+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-22T23:11:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"115795601549094174573183433498541910465","date":"2025-10-09T20:55:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"290152248306126050132153084574023824437","date":"2025-10-09T20:27:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"9809583457952486778984966908104634966","date":"2025-10-09T08:00:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"202242952017328807909728305553789123293","date":"2025-10-09T04:54:14+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-09T03:13:44+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-08T06:13:37+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-07T04:00:49+00:00","index":"","fulltext":""},{"type":"submitted","content":"Epigenetics \u0026 Chromatin","date":"2025-10-06T03:28:01+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"epigenetics-and-chromatin","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"epch","sideBox":"Learn more about [Epigenetics \u0026 Chromatin](http://epigeneticsandchromatin.biomedcentral.com/)","snPcode":"13072","submissionUrl":"https://submission.nature.com/new-submission/13072/3","title":"Epigenetics \u0026 Chromatin","twitterHandle":"@EpigenChromatin","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d502f909-d127-4222-b896-9f91f516a770","owner":[],"postedDate":"October 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-02T16:03:07+00:00","versionOfRecord":{"articleIdentity":"rs-7787625","link":"https://doi.org/10.1186/s13072-026-00662-5","journal":{"identity":"epigenetics-and-chromatin","isVorOnly":false,"title":"Epigenetics \u0026 Chromatin"},"publishedOn":"2026-02-28 15:59:31","publishedOnDateReadable":"February 28th, 2026"},"versionCreatedAt":"2025-10-22 18:39:50","video":"","vorDoi":"10.1186/s13072-026-00662-5","vorDoiUrl":"https://doi.org/10.1186/s13072-026-00662-5","workflowStages":[]},"version":"v1","identity":"rs-7787625","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7787625","identity":"rs-7787625","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}