Estimation of splicing metrics for NMD-sensitive transcripts

Corrected splicing metrics reveal distinct NMD-sensitive and NMD-evading transcript classes with improved accuracy from short-read RNA-seq data.

• Why it matters: Accurate quantification of alternative splicing is hindered by NMD targeting, which biases traditional PSI measurements and obscures true splicing rates, impacting understanding of gene regulation.
• What they did: The authors developed an analytical framework and statistical models, including Gaussian mixture models, to distinguish NMD-sensitive from NMD-evading splicing events and incorporate decay rates for correction, using data from short-read RNA-seq.
• The result: Incorporating event-specific decay rates enhances interpretation of differential splicing, with NMD-evading transcripts showing higher coding potential and translation signals, enabling more precise splicing analysis in NMD-targeted transcripts.