Project description:RNA internal modifications play critical role in development of multicellular organisms and their response to environmental cues. Using nanopore direct RNA sequencing (DRS), we constructed a large in vitro epitranscriptome (IVET) resource from plant cDNA library labeled with m6A, m1A and m5C respectively. Furthermore, after transfer learning, the pre-trained model was used to detect additional RNA internal modification such as m1A, hm5C, m7G and Ψ modification. Finally, we illustrated a global view of epitranscriptome with m6A, m1A, m5C, m7G and Ψ modification in rice seedlings under normal and high salinity environment. In summary, we provided a strategy for creating IVET resource from cDNA library and developed a computational method that use IVET-based transfer learning termed TandemMod for profiling epitranscriptome landscape with co-occupancy of multiple types of RNA modification in plants responsive to environmental signal.
Project description:5-methylcytosine (5mC) is an important type of epigenetic modification. In this study, we enhanced 5mC detection using SMRT sequencing by holistically analyzing kinetic signals of a DNA polymerase and sequence context for every base within a measurement window. We employed a convolutional neural network to train a methylation classification model. This methodology has provided a system for simultaneous genome-wide genetic and epigenetic analyses.ÂÂ
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.