Cell-Cycle Dependence of Transcription Dominates Noise in Gene Expression
Author(s)
Maheshri, Narendra; Zopf, Christopher John; Quinn, Katie Julia; Zeidman, Joshua A.
DownloadZopf-2013-Cell-Cycle Dependenc.pdf (1.270Mb)
PUBLISHER_CC
Publisher with Creative Commons License
Creative Commons Attribution
Terms of use
Metadata
Show full item recordAbstract
The large variability in mRNA and protein levels found from both static and dynamic measurements in single cells has been largely attributed to random periods of transcription, often occurring in bursts. The cell cycle has a pronounced global role in affecting transcriptional and translational output, but how this influences transcriptional statistics from noisy promoters is unknown and generally ignored by current stochastic models. Here we show that variable transcription from the synthetic tetO promoter in S. cerevisiae is dominated by its dependence on the cell cycle. Real-time measurements of fluorescent protein at high expression levels indicate tetO promoters increase transcription rate ~2-fold in S/G2/M similar to constitutive genes. At low expression levels, where tetO promoters are thought to generate infrequent bursts of transcription, we observe random pulses of expression restricted to S/G2/M, which are correlated between homologous promoters present in the same cell. The analysis of static, single-cell mRNA measurements at different points along the cell cycle corroborates these findings. Our results demonstrate that highly variable mRNA distributions in yeast are not solely the result of randomly switching between periods of active and inactive gene expression, but instead largely driven by differences in transcriptional activity between G1 and S/G2/M.
Date issued
2013-07Department
Massachusetts Institute of Technology. Department of Chemical EngineeringJournal
PLoS Computational Biology
Publisher
Public Library of Science
Citation
Zopf, C. J., Katie Quinn, Joshua Zeidman, and Narendra Maheshri. “Cell-Cycle Dependence of Transcription Dominates Noise in Gene Expression.” Edited by Jane Kondev. PLoS Computational Biology 9, no. 7 (July 25, 2013): e1003161.
Version: Final published version
ISSN
1553-7358
1553-734X