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

Erhard F, Baptista MAP, Krammer T, Hennig T, Lange M, Arampatzi P, Juerges CS, Theis FJ, Saliba AE, Doelken L (2019)

Publication Type: Journal article

Publication year: 2019

Journal

Nature Nature Research

Book Volume: 571

Pages Range: 419-423

Journal Issue: 7765

DOI: 10.1038/s41586-019-1369-y

Abstract

Single-cell RNA sequencing (scRNA-seq) has highlighted the important role of intercellular heterogeneity in phenotype variability in both health and disease1. However, current scRNA-seq approaches provide only a snapshot of gene expression and convey little information on the true temporal dynamics and stochastic nature of transcription. A further key limitation of scRNA-seq analysis is that the RNA profile of each individual cell can be analysed only once. Here we introduce single-cell, thiol-(SH)-linked alkylation of RNA for metabolic labelling sequencing (scSLAM-seq), which integrates metabolic RNA labelling2, biochemical nucleoside conversion3 and scRNA-seq to record transcriptional activity directly by differentiating between new and old RNA for thousands of genes per single cell. We use scSLAM-seq to study the onset of infection with lytic cytomegalovirus in single mouse fibroblasts. The cell-cycle state and dose of infection deduced from old RNA enable dose–response analysis based on new RNA. scSLAM-seq thereby both visualizes and explains differences in transcriptional activity at the single-cell level. Furthermore, it depicts ‘on–off’ switches and transcriptional burst kinetics in host gene expression with extensive gene-specific differences that correlate with promoter-intrinsic features (TBP–TATA-box interactions and DNA methylation). Thus, gene-specific, and not cell-specific, features explain the heterogeneity in transcriptomes between individual cells and the transcriptional response to perturbations.

Involved external institutions

Julius-Maximilians-Universität Würzburg DE Germany (DE) Helmholtz-Zentrum für Infektionsforschung (HZI) DE Germany (DE) Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt (HMGU) / Helmholtz Munich DE Germany (DE)

How to cite

APA:

Erhard, F., Baptista, M.A.P., Krammer, T., Hennig, T., Lange, M., Arampatzi, P.,... Doelken, L. (2019). scSLAM-seq reveals core features of transcription dynamics in single cells. Nature, 571(7765), 419-423. https://doi.org/10.1038/s41586-019-1369-y

MLA:

Erhard, Florian, et al. "scSLAM-seq reveals core features of transcription dynamics in single cells." Nature 571.7765 (2019): 419-423.

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