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Low input capture Hi-C (liCHi-C) identifies promoter-enhancer interactions at high-resolution
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-...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9845235/ https://www.ncbi.nlm.nih.gov/pubmed/36650138 http://dx.doi.org/10.1038/s41467-023-35911-8 |
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author | Tomás-Daza, Laureano Rovirosa, Llorenç López-Martí, Paula Nieto-Aliseda, Andrea Serra, François Planas-Riverola, Ainoa Molina, Oscar McDonald, Rebecca Ghevaert, Cedric Cuatrecasas, Esther Costa, Dolors Camós, Mireia Bueno, Clara Menéndez, Pablo Valencia, Alfonso Javierre, Biola M. |
author_facet | Tomás-Daza, Laureano Rovirosa, Llorenç López-Martí, Paula Nieto-Aliseda, Andrea Serra, François Planas-Riverola, Ainoa Molina, Oscar McDonald, Rebecca Ghevaert, Cedric Cuatrecasas, Esther Costa, Dolors Camós, Mireia Bueno, Clara Menéndez, Pablo Valencia, Alfonso Javierre, Biola M. |
author_sort | Tomás-Daza, Laureano |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9845235 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-98452352023-01-19 Low input capture Hi-C (liCHi-C) identifies promoter-enhancer interactions at high-resolution Tomás-Daza, Laureano Rovirosa, Llorenç López-Martí, Paula Nieto-Aliseda, Andrea Serra, François Planas-Riverola, Ainoa Molina, Oscar McDonald, Rebecca Ghevaert, Cedric Cuatrecasas, Esther Costa, Dolors Camós, Mireia Bueno, Clara Menéndez, Pablo Valencia, Alfonso Javierre, Biola M. Nat Commun Article 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. Nature Publishing Group UK 2023-01-17 /pmc/articles/PMC9845235/ /pubmed/36650138 http://dx.doi.org/10.1038/s41467-023-35911-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Tomás-Daza, Laureano Rovirosa, Llorenç López-Martí, Paula Nieto-Aliseda, Andrea Serra, François Planas-Riverola, Ainoa Molina, Oscar McDonald, Rebecca Ghevaert, Cedric Cuatrecasas, Esther Costa, Dolors Camós, Mireia Bueno, Clara Menéndez, Pablo Valencia, Alfonso Javierre, Biola M. Low input capture Hi-C (liCHi-C) identifies promoter-enhancer interactions at high-resolution |
title | Low input capture Hi-C (liCHi-C) identifies promoter-enhancer interactions at high-resolution |
title_full | Low input capture Hi-C (liCHi-C) identifies promoter-enhancer interactions at high-resolution |
title_fullStr | Low input capture Hi-C (liCHi-C) identifies promoter-enhancer interactions at high-resolution |
title_full_unstemmed | Low input capture Hi-C (liCHi-C) identifies promoter-enhancer interactions at high-resolution |
title_short | Low input capture Hi-C (liCHi-C) identifies promoter-enhancer interactions at high-resolution |
title_sort | low input capture hi-c (lichi-c) identifies promoter-enhancer interactions at high-resolution |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9845235/ https://www.ncbi.nlm.nih.gov/pubmed/36650138 http://dx.doi.org/10.1038/s41467-023-35911-8 |
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