qMAP decodes RNA fragmentation dynamics in development and disease

Area of Science:

• Molecular Biology
• Bioinformatics
• Genomics

Background:

• Noncanonical small RNAs, including tRNA-derived (tsRNAs) and rRNA-derived (rsRNAs) fragments, are generated through selective cleavage, not random degradation.
• Existing analytical methods primarily measure abundance and cannot systematically quantify differential RNA cleavage signals.

Purpose of the Study:

• To introduce qMAP, a computational framework for profiling differential RNA fragmentation from small RNA sequencing data.
• To enable systematic quantification of condition-specific fragmentation patterns and identify causative small RNA species.

Main Methods:

• qMAP integrates two complementary models to identify differential fragmentation patterns.
• A dedicated module within qMAP pinpoints specific small RNA species responsible for observed fragmentation differences.

Main Results:

• qMAP identified dynamic tRNA and rRNA fragmentation during mouse cell reprogramming.
• RNA fragmentation patterns were shown to classify human ulcerative colitis and predict recurrent implantation failure.
• Aging-associated RNA fragmentation was detected in sperm, highlighting its regulatory role beyond expression levels.

Conclusions:

• qMAP provides a foundational tool for exploring the regulatory "RNA fragmentome".
• RNA fragmentation represents a distinct regulatory dimension with significant potential for mechanistic discovery and translational applications.