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

Theodore Sakellaropoulos, Catherine Do, Guimei Jiang, Giulia Cova, Peter Meyn, Dacia Dimartino, Sitharam Ramaswami, Adriana Heguy, Aristotelis Tsirigos () and Jane A. Skok ()
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Theodore Sakellaropoulos: NYU Grossman School of Medicine
Catherine Do: NYU Grossman School of Medicine
Guimei Jiang: NYU Grossman School of Medicine
Giulia Cova: NYU Grossman School of Medicine
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
Jane A. Skok: NYU Grossman School of Medicine

Nature Communications, 2024, vol. 15, issue 1, 1-15

Abstract: 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.

Date: 2024
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DOI: 10.1038/s41467-024-50380-3

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