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Nature. 2019 Jan;565(7738):251-254. doi: 10.1038/s41586-018-0836-1. Epub 2019 Jan 2.

Genomic encoding of transcriptional burst kinetics.

Author information

1
Department of Cell and Molecular Biology, Karolinska Institutet, Stockholm, Sweden.
2
Ludwig Institute for Cancer Research, Stockholm, Sweden.
3
Integrated Cardio Metabolic Center (ICMC), Karolinska Institutet, Stockholm, Sweden.
4
Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden.
5
Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
6
Ludwig Institute for Cancer Research, San Diego, CA, USA.
7
Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA.
8
Department of Cell and Molecular Biology, Karolinska Institutet, Stockholm, Sweden. rickard.sandberg@ki.se.
9
Ludwig Institute for Cancer Research, Stockholm, Sweden. rickard.sandberg@ki.se.
10
Integrated Cardio Metabolic Center (ICMC), Karolinska Institutet, Stockholm, Sweden. rickard.sandberg@ki.se.

Abstract

Mammalian gene expression is inherently stochastic1,2, and results in discrete bursts of RNA molecules that are synthesized from each allele3-7. Although transcription is known to be regulated by promoters and enhancers, it is unclear how cis-regulatory sequences encode transcriptional burst kinetics. Characterization of transcriptional bursting, including the burst size and frequency, has mainly relied on live-cell4,6,8 or single-molecule RNA fluorescence in situ hybridization3,5,8,9 recordings of selected loci. Here we determine transcriptome-wide burst frequencies and sizes for endogenous mouse and human genes using allele-sensitive single-cell RNA sequencing. We show that core promoter elements affect burst size and uncover synergistic effects between TATA and initiator elements, which were masked at mean expression levels. Notably, we provide transcriptome-wide evidence that enhancers control burst frequencies, and demonstrate that cell-type-specific gene expression is primarily shaped by changes in burst frequencies. Together, our data show that burst frequency is primarily encoded in enhancers and burst size in core promoters, and that allelic single-cell RNA sequencing is a powerful model for investigating transcriptional kinetics.

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PMID:
30602787
DOI:
10.1038/s41586-018-0836-1
[Indexed for MEDLINE]

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