Framework for microRNA variant annotation and prioritization using human population and disease datasets.

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• MicroRNA (miRNA) expression is often altered in human diseases.
• Mutations within miRNAs that contribute to disease remain largely unexplored.
• A systematic approach is needed to identify and prioritize disease-relevant miRNA variants.

Purpose of the Study:

• To develop Annotative Database of miRNA Elements (ADmiRE) for annotating and prioritizing miRNA genetic variation.
• To analyze miRNA variant patterns across large-scale sequencing datasets.
• To identify disease-associated miRNA variants, particularly in cancer.

Main Methods:

• Integrated existing and novel biological annotations into ADmiRE.
• Annotated over 10,000 mature miRNA variants from gnomAD datasets.
• Performed conservation analysis across 100 vertebrates.
• Applied ADmiRE to TCGA PanCancerAtlas Whole Exome Sequencing data.

Main Results:

• MiRNA variant patterns resemble protein-coding exonic regions; highly confident miRNAs show greater sequence constraint.
• Identified 765 highly conserved miRNAs with limited genetic variation.
• Annotated 1,267 germline and 1,492 somatic miRNA variants in TCGA PanCancerAtlas.
• Discovered novel somatic miR-21 mutations in esophageal cancers.

Conclusions:

• ADmiRE provides a framework for annotating and prioritizing miRNA variation in disease.
• MiRNA variant patterns suggest functional constraint similar to coding regions.
• Identified specific miRNA mutations, like miR-21 in esophageal cancer, with potential disease impact.