Protein complex scaffolding predicted as a prevalent function of long non-coding RNAs

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Thousands of long non-coding RNAs (lncRNAs) exist in the human transcriptome, but their functions remain largely uncharacterized.
• A growing hypothesis suggests lncRNAs function as protein scaffolds, organizing protein complexes (ribonucleoproteins).
• The prevalence and scale of lncRNA scaffolding function are currently unknown.

Purpose of the Study:

• To develop and apply the first large-scale computational approach for predicting scaffolding long non-coding RNAs.
• To investigate the potential prevalence of RNA-mediated protein scaffolding in human cells.
• To explore the link between lncRNA scaffolding and disease association.

Main Methods:

• Utilized the catRAPID omics algorithm to predict a comprehensive human lncRNA-protein interaction network.
• Integrated tissue expression data and statistical analyses to identify candidate scaffolding lncRNAs.
• Analyzed the predicted network to assess the coverage of known protein complexes and network modules by scaffolding lncRNAs.

Main Results:

• Predicted the largest human lncRNA-protein interaction network to date.
• Identified 847 long non-coding RNAs (approximately 5% of the lncRNA transcriptome) as potential scaffolds.
• These predicted scaffolding lncRNAs are implicated in organizing roughly half of known protein complexes and network modules.
• Demonstrated a potential link between the scaffolding ability of certain lncRNAs and their association with diseases.

Conclusions:

• RNA-mediated scaffolding of protein complexes and modules may represent a widespread and fundamental mechanism in human cellular biology.
• The developed computational approach enables large-scale prediction and characterization of scaffolding lncRNAs.
• This finding opens new avenues for understanding lncRNA function, regulation, and their roles in health and disease.