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- Title
Low input capture Hi-C (liCHi-C) identifies promoter-enhancer interactions at high-resolution.
- Authors
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.
- 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. Here the authors present the low input capture Hi-C (liCHi-C) method, a cost-effective, flexible method to map and robustly compare promoter interactomes at high resolution. liCHi-C identifies new disease-associated genes and structural variants to ultimately illuminate their pathogenic effects.
- Subjects
CELL populations; GENETIC variation; GENE regulatory networks; CHROMATIN
- Publication
Nature Communications, 2023, Vol 14, Issue 1, p1
- ISSN
2041-1723
- Publication type
Article
- DOI
10.1038/s41467-023-35911-8