scSLAM-seq reveals core features of transcription dynamics in single cells.
Nature
; 571(7765): 419-423, 2019 07.
Article
em En
| MEDLINE
| ID: mdl-31292545
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.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Transcrição Gênica
/
Regulação da Expressão Gênica
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Análise de Sequência de RNA
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Análise de Célula Única
Limite:
Animals
Idioma:
En
Ano de publicação:
2019
Tipo de documento:
Article