DOI: 10.1101/486852Jan 21, 2019Paper

scSLAM-seq reveals core features of transcription dynamics in single cells

BioRxiv : the Preprint Server for Biology
Florian ErhardLars Doelken

Abstract

Current single-cell RNA sequencing approaches gives a snapshot of a cellular phenotype but convey no information on the temporal dynamics of transcription. Moreover, the stochastic nature of transcription at molecular level is not recovered. Here, we present single-cell SLAM-seq (scSLAM-seq), which integrates metabolic RNA labeling, biochemical nucleoside conversion and single-cell RNA-seq to directly measure total transcript levels and transcriptional activity by differentiating newly synthesized from pre-existing RNA for thousands of genes per single cell. scSLAM-seq recovers the earliest virus-induced changes in cytomegalovirus infection and reveals a so far hidden phase of viral gene expression comprising promiscuous transcription of all kinetic classes. It depicts the stochastic nature of transcription and demonstrates extensive gene-specific differences. These range from stable transcription rates to on-off dynamics which coincide with gene-/promoter-intrinsic features (Tbp-TATA-box interactions and DNA methylation). Gene but not cell-specific features thus explain the heterogeneity in transcriptomes between individual cells and the transcriptional response to perturbations.

Related Concepts

Cytomegalovirus Infections
Genes
Nucleosides
RNA
Transcription, Genetic
Virus
Promoter
Transcriptional Activation
DNA Methylation
RNA Metabolism

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