Transcriptional bursting explains the noise–versus–mean relationship in mRNA and protein levels
- Univ. of Illinois Urbana-Champaign, Urbana, IL (United States)
- Univ. of Pennsylvania, Philadelphia, PA (United States)
- Univ. of Delaware, Newark, DE (United States)
- Rockefeller Univ., New York, NY (United States)
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Univ. of Tennessee, Knoxville, TN (United States)
- Gladstone Institutes, San Francisco, CA (United States); Univ. of California San Francisco, San Francisco, CA (United States)
Recent analysis demonstrates that the HIV-1 Long Terminal Repeat (HIV LTR) promoter exhibits a range of possible transcriptional burst sizes and frequencies for any mean-expression level. However, these results have also been interpreted as demonstrating that cell-tocell expression variability (noise) and mean are uncorrelated, a significant deviation from previous results. Here, we re-examine the available mRNA and protein abundance data for the HIV LTR and find that noise in mRNA and protein expression scales inversely with the mean along analytically predicted transcriptional burst-size manifolds. We then experimentally perturb transcriptional activity to test a prediction of the multiple burst-size model: that increasing burst frequency will cause mRNA noise to decrease along given burst-size lines as mRNA levels increase. In conclusion, the data show that mRNA and protein noise decrease as mean expression increases, supporting the canonical inverse correlation between noise and mean.
- Research Organization:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Joint Institute for Biological Sciences (JIBS)
- Sponsoring Organization:
- USDOE Laboratory Directed Research and Development (LDRD) Program
- Grant/Contract Number:
- AC05-00OR22725
- OSTI ID:
- 1279452
- Journal Information:
- PLoS ONE, Vol. 11, Issue 7; ISSN 1932-6203
- Publisher:
- Public Library of ScienceCopyright Statement
- Country of Publication:
- United States
- Language:
- English
Web of Science
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