Project description:Pseudouridine (Ψ) is an abundant mRNA modification in the mammalian transcriptome, but its function has remained elusive due to the difficulty of transcriptome-wide mapping. We develop nanopore native RNA sequencing for quantitative Ψ analysis that utilizes native content training, machine learning model prediction, and single read coordination. We find interferon inducible Ψ modifications in the interferon stimulated gene transcripts, consistent with a role of Ψ in the efficacy of mRNA vaccines.
Project description:Pseudouridine (Ψ) is an abundant mRNA modification in the mammalian transcriptome, but its function has remained elusive due to the difficulty of transcriptome-wide mapping. We develop nanopore native RNA sequencing for quantitative Ψ analysis that utilizes native content training, machine learning model prediction, and single read coordination. We find interferon inducible Ψ modifications in the interferon stimulated gene transcripts, consistent with a role of Ψ in the efficacy of mRNA vaccines.
Project description:N6-methyladenosine (m6A) and pseudouridine (Ψ) are the two most abundant modifications in mammalian mRNA, but the coordination of their biological functions remains poorly understood. We develop a machine learning-based nanopore direct RNA sequencing method (NanoSPA) that simultaneously analyzes m6A and Ψ in the human transcriptome. Applying NanoSPA to polysome profiling, we reveal opposing transcriptomic co-occurrence of m6A and Ψ and synergistic, hierarchical effects of m6A and Ψ on the polysome.