Tomás-Daza, LaureanoRovirosa, LlorençLópez-Martí, PaulaNieto-Aliseda, AndreaSerra, FrançoisPlanas-Riverola, AinoaMolina, ÒscarMcDonald, RebecaGhevaert, CedricCuatrecasas, EstherCosta, DolorsCamós Guijosa, MireiaBueno, ClaraMenéndez, PabloValencia, AlfonsoJavierre, Biola M.2025-02-052025-02-052023-01-172041-1723https://hdl.handle.net/2445/218536Long-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.16 p.application/pdfengcc-by (c) Tomás-Daza, L. et al., 2023http://creativecommons.org/licenses/by/4.0/Expressió gènicaGenoma humàCromatinaTranscripció genèticaGene expressionHuman genomeChromatinGenetic transcriptioninfo:eu-repo/semantics/article7527272025-02-05info:eu-repo/semantics/openAccess36650138