Time-resolved single-cell RNA-seq using metabolic RNA labelling

Abstract

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. Using 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 the 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 (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.

bakR: uncovering differential RNA synthesis and degradation kinetics transcriptome-wide with Bayesian hierarchical modeling

“…bakR uses Bayesian hierarchical modeling to effectively share information across transcripts, increasing its statistical power while maintaining the desired level of specificity. Applying bakR's analysis strategy to the growing list of extensions of NR-seq could provide similar benefits (Erhard et al 2019;Battich et al 2020;Cao et al 2020;Qiu et al 2020;Zimmer et al 2021;Erhard et al 2022;Qiu et al 2022;Smalec et al 2022). We anticipate that broad implementation of bakR to analyze NR-seq datasets will provide new insights into the regulated kinetics of gene expression.…”

Determining RNA Natural Modifications and Nucleoside Analog-Labeled Sites by a Chemical/Enzyme-Induced Base Mutation Principle

“…4SU has become the most widely used uridine analog for studying RNA dynamics because of its great biocompatibility for metabolic labeling of RNA and its capability to specifically react with thiols and to be reversibly biotinylated for enrichment. 4SU is readily taken up by mammalian cells and converted to 4SUTP via the endogenous nucleotide salvage pathway [ 99 ]. For example, the major uridine transporter proteins SLC29A1 and SLC29A2 are abundantly expressed in HEK293 and HeLa cell lines, thus 4SU is rapidly incorporated into newly transcribed RNA [ 100 , 101 , 102 ].…”

Flexible and scalable control of T cell memory by a reversible epigenetic switch

“…1), we analyzed ex vivo activated cells using the temporally-resolved single-cell transcriptome sequencing method, sci-fate 22 . Here, metabolic labeling of newly-synthesized transcripts reveals a cell’s current activity state apart from its history 22,23 (Fig. 2A).…”