Massively parallel and time-resolved RNA sequencing in single cells with scNT-Seq

Single-cell RNA sequencing offers snapshots of whole transcriptomes but obscures the temporal RNA dynamics. Here we present single-cell metabolically labeled new RNA tagging sequencing (scNT-Seq), a method for massively parallel analysis of newly-transcribed and pre-existing mRNAs from the same cell. This droplet microfluidics-based method enables high-throughput chemical conversion on barcoded beads, efficiently marking newly-transcribed mRNAs with T-to-C substitutions. With scNT-Seq, we jointly profiled new and old transcriptomes in ~55,000 single cells. These data revealed time-resolved transcription factor activities and cell state trajectories at single-cell level in response to neuronal activation. We further determined rates of RNA biogenesis and decay to uncover RNA regulatory strategies during stepwise conversion between pluripotent and rare totipotent two-cell-embryo-like (2C-like) stem cell states. Finally, integrating scNT-Seq with genetic perturbation identifies DNA methylcytosine dioxygenases as an epigenetic barrier into 2C-like cell state. Time-resolved single-cell transcriptomic analysis thus opens new lines of inquiry regarding cell-type-specific RNA regulatory mechanisms. Single-cell metabolically labeled new RNA tagging sequencing