Transcriptional Bursting Explains the Noise–Versus–Mean Relationship in mRNA and Protein Levels
Author(s) -
Roy D. Dar,
Sydney M. Shaffer,
Abhyudai Singh,
Brandon S. Razooky,
Michael L. Simpson,
Arjun Raj,
Leor S. Weinberger
Publication year - 2016
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0158298
Subject(s) - messenger rna , bursting , noise (video) , biology , physics , microbiology and biotechnology , statistics , genetics , mathematics , gene , computer science , neuroscience , image (mathematics) , artificial intelligence
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-to-cell 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. The data show that mRNA and protein noise decrease as mean expression increases, supporting the canonical inverse correlation between noise and mean.
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