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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-...

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Autores principales: 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.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
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.
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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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