Phenotypic Consequences of Promoter-Mediated Transcriptional Noise

Abstract

A more complete understanding of the causes and effects of cell-cell variability in gene expression is needed to elucidate whether the resulting phenotypes are disadvantageous or confer some adaptive advantage. Here we show that increased variability in gene expression, affected by the sequence of the TATA box, can be beneficial after an acute change in environmental conditions. We rationally introduce mutations within the TATA region of an engineered Saccharomyces cerevisiae GAL1 promoter and measure promoter responses that can be characterized as being either highly variable and rapid or steady and slow. We computationally illustrate how a stable transcription scaffold can result in "bursts" of gene expression, enabling rapid individual cell responses in the transient and increased cell-cell variability at steady state. We experimentally verify computational predictions that the rapid response and increased cell-cell variability enabled by TATA-containing promoters confer a clear benefit in the face of an acute environmental stress.

Phenotypic Diversity Using Bimodal and Unimodal Expression of Stress Response Proteins

“…In contrast to the bimodal case, there are not distinct phenotypic states. An example of unimodal distributions comes from TATA box-containing genes associated with stress response in Saccharomyces cerevisiae, which exhibit large levels of variability that protect against future environmental changes (14). Similarly, increased population heterogeneity has been shown to enhance survival of stress in S. cerevisiae (15).…”

Modeling the effect of transcriptional noise on switching in gene networks in a genetic bistable switch

“…Such complexity can be introduced by varying the strength, number, and position of the transcription factor binding sites and also the strength of the repressors or activators. It has been reported earlier both in experiments and in theoretical studies that the promoter architecture of the gene regulatory network affects cell-to-cell variability in gene expression [32][33][34][35]. Thermodynamic models of gene expression have been used earlier to calculate the mean mRNA number and the protein copy number per cell [36][37][38].…”

Disparity between microRNA levels and promoter strength is associated with initiation rate and Pol II pausing

“…Transcription directed by TATA-box promoters, but not through TATA-less promoters, is produced through re-initiation 32 or bursts 33 . This raises the possibility that a high frequency of transcription initiation is incompatible with efficient miRNA expression.…”