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MethNet: a robust approach to identify regulatory hubs and their distal targets from cancer data

Author

Listed:
  • Theodore Sakellaropoulos

    (NYU Grossman School of Medicine
    NYU Langone Health)

  • Catherine Do

    (NYU Grossman School of Medicine
    NYU Langone Health)

  • Guimei Jiang

    (NYU Grossman School of Medicine
    NYU Langone Health)

  • Giulia Cova

    (NYU Grossman School of Medicine
    NYU Langone Health)

  • Peter Meyn

    (NYU Grossman School of Medicine)

  • Dacia Dimartino

    (NYU Grossman School of Medicine)

  • Sitharam Ramaswami

    (NYU Grossman School of Medicine)

  • Adriana Heguy

    (NYU Grossman School of Medicine)

  • Aristotelis Tsirigos

    (NYU Grossman School of Medicine
    NYU Langone Health
    NYU Grossman School of Medicine)

  • Jane A. Skok

    (NYU Grossman School of Medicine
    NYU Langone Health)

Abstract

Aberrations in the capacity of DNA/chromatin modifiers and transcription factors to bind non-coding regions can lead to changes in gene regulation and impact disease phenotypes. However, identifying distal regulatory elements and connecting them with their target genes remains challenging. Here, we present MethNet, a pipeline that integrates large-scale DNA methylation and gene expression data across multiple cancers, to uncover cis regulatory elements (CREs) in a 1 Mb region around every promoter in the genome. MethNet identifies clusters of highly ranked CREs, referred to as ‘hubs’, which contribute to the regulation of multiple genes and significantly affect patient survival. Promoter-capture Hi-C confirmed that highly ranked associations involve physical interactions between CREs and their gene targets, and CRISPR interference based single-cell RNA Perturb-seq validated the functional impact of CREs. Thus, MethNet-identified CREs represent a valuable resource for unraveling complex mechanisms underlying gene expression, and for prioritizing the verification of predicted non-coding disease hotspots.

Suggested Citation

  • Theodore Sakellaropoulos & Catherine Do & Guimei Jiang & Giulia Cova & Peter Meyn & Dacia Dimartino & Sitharam Ramaswami & Adriana Heguy & Aristotelis Tsirigos & Jane A. Skok, 2024. "MethNet: a robust approach to identify regulatory hubs and their distal targets from cancer data," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-50380-3
    DOI: 10.1038/s41467-024-50380-3
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