Pseudouridine (Ψ) is an abundant mRNA modification in mammalian transcriptome, but its functions have remained elusive due to the difficulty of transcriptome-wide mapping. We develop a nanopore native RNA sequencing method for quantitative Ψ prediction (NanoPsu) that utilizes native content training, machine learning modeling, and single-read linkage analysis. Biologically, we find interferon inducible Ψ modifications in interferon-stimulated gene transcripts which are consistent with a role of Ψ in enabling efficacy of mRNA vaccines.
Keywords: Interferon; Machine learning; Nanopore sequencing; Pseudouridine.
© 2021. The Author(s).