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Low input capture Hi-C (liCHi-C) identifies promoter-enhancer interactions at high-resolution

Author

Listed:
  • Laureano Tomás-Daza

    (Josep Carreras Leukaemia Research Institute
    Barcelona Supercomputing Center)

  • Llorenç Rovirosa

    (Josep Carreras Leukaemia Research Institute)

  • Paula López-Martí

    (Josep Carreras Leukaemia Research Institute
    Barcelona Supercomputing Center)

  • Andrea Nieto-Aliseda

    (Josep Carreras Leukaemia Research Institute)

  • François Serra

    (Josep Carreras Leukaemia Research Institute)

  • Ainoa Planas-Riverola

    (Josep Carreras Leukaemia Research Institute)

  • Oscar Molina

    (Josep Carreras Leukaemia Research Institute)

  • Rebecca McDonald

    (Wellcome-MRC Cambridge Stem Cell Institute)

  • Cedric Ghevaert

    (Wellcome-MRC Cambridge Stem Cell Institute
    NHS Blood and Transplant)

  • Esther Cuatrecasas

    (Sant Joan de Déu Hospital, Esplugues de Llobregat)

  • Dolors Costa

    (Hospital Clinic
    Institute of Biomedical Research August Pi i Sunyer
    Cancer Network Biomedical Research Center)

  • Mireia Camós

    (Sant Joan de Déu Research Institute, Esplugues de Llobregat
    Sant Joan de Déu Hospital, Esplugues de Llobregat
    Carlos III Health Institute)

  • Clara Bueno

    (Josep Carreras Leukaemia Research Institute)

  • Pablo Menéndez

    (Josep Carreras Leukaemia Research Institute
    Catalan Institution for Research and Advanced Studies (ICREA))

  • Alfonso Valencia

    (Barcelona Supercomputing Center
    Catalan Institution for Research and Advanced Studies (ICREA))

  • Biola M. Javierre

    (Josep Carreras Leukaemia Research Institute
    Institute for Health Science Research Germans Trias i Pujol)

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.

Suggested Citation

  • Laureano Tomás-Daza & Llorenç Rovirosa & Paula López-Martí & Andrea Nieto-Aliseda & François Serra & Ainoa Planas-Riverola & Oscar Molina & Rebecca McDonald & Cedric Ghevaert & Esther Cuatrecasas & Do, 2023. "Low input capture Hi-C (liCHi-C) identifies promoter-enhancer interactions at high-resolution," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-35911-8
    DOI: 10.1038/s41467-023-35911-8
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