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. Researchers from the University of Pennsylvania have developed 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.

Using scNT-seq, the researchers jointly profiled new and old transcriptomes in ~55,000 single cells. These data revealed time-resolved transcription factor activities and cell-state trajectories at the single-cell level in response to neuronal activation. They further determined rates of RNA biogenesis and decay to uncover RNA regulatory strategies during stepwise conversion between pluripotent and rare totipotent two-cell embryo (2C)-like stem cell states. Finally, integrating scNT-seq with genetic perturbation identifies DNA methylcytosine dioxygenase as an epigenetic barrier into the 2C-like cell state. Time-resolved single-cell transcriptomic analysis thus opens new lines of inquiry regarding cell-type-specific RNA regulatory mechanisms.

Development and validation of scNT-seq

a, Overview of scNT-seq. TSO, template switch oligo. b, Species-mixing experiment benchmarks the performance of TFEA/NaIO₄– and IAA-based chemical conversion reactions on pooled beads in scNT-seq, by sequencing a mix (1:1) of human K562 cells and mESCs. The scatterplot shows the number of transcripts (UMIs) mapped to the mouse (y axis) or human (x axis) genome for each cell (dot) that is colored by its identity (human, blue; mouse, red; mixed, green). c, Bar plot showing nucleotide substitution rates in 4sU-labeled K562 cells. Untreated, control cells that were not chemically treated were used. d, Box plots showing the fraction of 4sU-labeled transcripts (UMI) per cell in untreated (n = 193 cells) and TFEA/NaIO₄-treated (n = 202 cells) K562 cells.