Low input capture Hi-C (liCHi-C) identifies promoter-enhancer interactions at high-resolution
| dc.contributor.author | Tomás-Daza, Laureano | |
| dc.contributor.author | Rovirosa, Llorenç | |
| dc.contributor.author | López-Martí, Paula | |
| dc.contributor.author | Nieto-Aliseda, Andrea | |
| dc.contributor.author | Serra, François | |
| dc.contributor.author | Planas-Riverola, Ainoa | |
| dc.contributor.author | Molina, Òscar | |
| dc.contributor.author | McDonald, Rebeca | |
| dc.contributor.author | Ghevaert, Cedric | |
| dc.contributor.author | Cuatrecasas, Esther | |
| dc.contributor.author | Costa, Dolors | |
| dc.contributor.author | Camós Guijosa, Mireia | |
| dc.contributor.author | Bueno, Clara | |
| dc.contributor.author | Menéndez, Pablo | |
| dc.contributor.author | Valencia, Alfonso | |
| dc.contributor.author | Javierre, Biola M. | |
| dc.date.accessioned | 2025-02-05T16:17:45Z | |
| dc.date.available | 2025-02-05T16:17:45Z | |
| dc.date.issued | 2023-01-17 | |
| dc.date.updated | 2025-02-05T16:17:45Z | |
| dc.description.abstract | Long-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.extent | 16 p. | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.idgrec | 752727 | |
| dc.identifier.issn | 2041-1723 | |
| dc.identifier.pmid | 36650138 | |
| dc.identifier.uri | https://hdl.handle.net/2445/218536 | |
| dc.language.iso | eng | |
| dc.publisher | Nature Publishing Group | |
| dc.relation.isformatof | Reproducció del document publicat a: https://doi.org/10.1038/s41467-023-35911-8 | |
| dc.relation.ispartof | Nature Communications, 2023, vol. 14 | |
| dc.relation.uri | https://doi.org/10.1038/s41467-023-35911-8 | |
| dc.rights | cc-by (c) Tomás-Daza, L. et al., 2023 | |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.source | Articles publicats en revistes (Ciències Fisiològiques) | |
| dc.subject.classification | Expressió gènica | |
| dc.subject.classification | Genoma humà | |
| dc.subject.classification | Cromatina | |
| dc.subject.classification | Transcripció genètica | |
| dc.subject.other | Gene expression | |
| dc.subject.other | Human genome | |
| dc.subject.other | Chromatin | |
| dc.subject.other | Genetic transcription | |
| dc.title | Low input capture Hi-C (liCHi-C) identifies promoter-enhancer interactions at high-resolution | |
| dc.type | info:eu-repo/semantics/article | |
| dc.type | info:eu-repo/semantics/publishedVersion |
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