Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/218536
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dc.contributor.authorTomás-Daza, Laureano-
dc.contributor.authorRovirosa, Llorenç-
dc.contributor.authorLópez-Martí, Paula-
dc.contributor.authorNieto-Aliseda, Andrea-
dc.contributor.authorSerra, François-
dc.contributor.authorPlanas-Riverola, Ainoa-
dc.contributor.authorMolina, Òscar-
dc.contributor.authorMcDonald, Rebeca-
dc.contributor.authorGhevaert, Cedric-
dc.contributor.authorCuatrecasas, Esther-
dc.contributor.authorCosta, Dolors-
dc.contributor.authorCamós Guijosa, Mireia-
dc.contributor.authorBueno, Clara-
dc.contributor.authorMenéndez, Pablo-
dc.contributor.authorValencia, Alfonso-
dc.contributor.authorJavierre, Biola M.-
dc.date.accessioned2025-02-05T16:17:45Z-
dc.date.available2025-02-05T16:17:45Z-
dc.date.issued2023-01-17-
dc.identifier.issn2041-1723-
dc.identifier.urihttps://hdl.handle.net/2445/218536-
dc.description.abstractLong-range interactions between regulatory elements and promoters are key in gene transcriptional control; however, their study requires large amounts of starting material, which is not compatible with clinical scenarios nor the study of rare cell populations. Here we introduce low input capture Hi-C (liCHi-C) as a cost-effective, flexible method to map and robustly compare promoter interactomes at high resolution. As proof of its broad applicability, we implement liCHi-C to study normal and malignant human hematopoietic hierarchy in clinical samples. We demonstrate that the dynamic promoter architecture identifies developmental trajectories and orchestrates transcriptional transitions during cell-state commitment. Moreover, liCHi-C enables the identification of disease-relevant cell types, genes and pathways potentially deregulated by non-coding alterations at distal regulatory elements. Finally, we show that liCHi-C can be harnessed to uncover genome-wide structural variants, resolve their breakpoints and infer their pathogenic effects. Collectively, our optimized liCHi-C method expands the study of 3D chromatin organization to unique, low-abundance cell populations, and offers an opportunity to uncover factors and regulatory networks involved in disease pathogenesis.-
dc.format.extent16 p.-
dc.format.mimetypeapplication/pdf-
dc.language.isoeng-
dc.publisherNature Publishing Group-
dc.relation.isformatofReproducció del document publicat a: https://doi.org/10.1038/s41467-023-35911-8-
dc.relation.ispartofNature Communications, 2023, vol. 14-
dc.relation.urihttps://doi.org/10.1038/s41467-023-35911-8-
dc.rightscc-by (c) Tomás-Daza, L. et al., 2023-
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/-
dc.sourceArticles publicats en revistes (Ciències Fisiològiques)-
dc.subject.classificationExpressió gènica-
dc.subject.classificationGenoma humà-
dc.subject.classificationCromatina-
dc.subject.classificationTranscripció genètica-
dc.subject.otherGene expression-
dc.subject.otherHuman genome-
dc.subject.otherChromatin-
dc.subject.otherGenetic transcription-
dc.titleLow input capture Hi-C (liCHi-C) identifies promoter-enhancer interactions at high-resolution-
dc.typeinfo:eu-repo/semantics/article-
dc.typeinfo:eu-repo/semantics/publishedVersion-
dc.identifier.idgrec752727-
dc.date.updated2025-02-05T16:17:45Z-
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess-
dc.identifier.pmid36650138-
Appears in Collections:Articles publicats en revistes (Ciències Fisiològiques)

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