Well-TEMP-seq characterizes the temporal dynamics of single-cell gene expression

Single-cell RNA sequencing reveals the transcriptional heterogeneity of single cells, but offers static snapshots of gene expression and fails to reveal the temporal dynamics of transcription. Herein, we develop Well-TEMP-seq, a high-throughput, cost-effective, accurate, and efficient method for massively parallel profiling the time-resolved dynamics of single-cell gene expression. Well-TEMP-seq combines metabolic RNA labeling with our recently developed microwell-based single-cell RNA sequencing method (Well-Paired-seq) to distinguish newly transcribed RNAs marked by T-to-C substitutions from pre-existing RNAs in each of thousands of single cells. We further apply Well-TEMP-seq to profiling the dynamics of gene expression of colorectal cancer cells exposed to low-dose of 5-AZA-CdR, a clinically used DNA-demethylating anti-tumor drug. Well-TEMP-seq also for the first time reveals the activation of interferon responsive genes by 5-AZA-CdR induced viral mimicry in the first three days after treatment. Well-TEMP-seq will be broadly applicable to unveil the dynamics of single-cell gene expression in diverse biological processes. Overall design: mRNA profiles of K562 and HCT116