MethNet: a robust approach to identify regulatory hubs and their distal targets from cancer data.
Theodore SakellaropoulosCatherine DoGuimei JiangGiulia CovaPeter MeynDacia DimartinoSitharam RamaswamiAdriana HeguyAristotelis TsirigosJane A SkokPublished in: Nature communications (2024)
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.
Keyphrases
- genome wide
- dna methylation
- gene expression
- transcription factor
- copy number
- single cell
- genome wide identification
- electronic health record
- minimally invasive
- big data
- rna seq
- case report
- papillary thyroid
- physical activity
- squamous cell carcinoma
- mental health
- artificial intelligence
- cell free
- squamous cell
- nucleic acid
- childhood cancer
- machine learning
- single molecule
- crispr cas
- data analysis
- dna damage
- circulating tumor