Single-cell analysis of transcription kinetics across the cell cycle

Samuel O. Skinner, Heng Xu, Sonal Nagarkar-Jaiswal, Pablo R. Freire, Thomas P. Zwaka, Ido Golding

Research output: Contribution to journalArticlepeer-review

Abstract

Transcription is a highly stochastic process. To infer transcription kinetics for a gene-of-interest, researchers commonly compare the distribution of mRNA copy-number to the prediction of a theoretical model. However, the reliability of this procedure is limited because the measured mRNA numbers represent integration over the mRNA lifetime, contribution from multiple gene copies, and mixing of cells from different cell-cycle phases. We address these limitations by simultaneously quantifying nascent and mature mRNA in individual cells, and incorporating cell-cycle effects in the analysis of mRNA statistics. We demonstrate our approach on Oct4 and Nanog in mouse embryonic stem cells. Both genes follow similar two-state kinetics. However, Nanog exhibits slower ON/OFF switching, resulting in increased cell-to-cell variability in mRNA levels. Early in the cell cycle, the two copies of each gene exhibit independent activity. After gene replication, the probability of each gene copy to be active diminishes, resulting in dosage compensation.

Original languageEnglish (US)
Article numbere12175
JournaleLife
Volume5
Issue numberJANUARY2016
DOIs
StatePublished - Jan 29 2016
Externally publishedYes

ASJC Scopus subject areas

  • Neuroscience(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)

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