Transcription factor binding process is the primary driver of noise in gene expression

Abstract

SummaryCellular processes driven by coordinated actions of individual genes generate cellular phenotypes. Stochastic variations in these processes lead to phenotypic heterogeneity that often has important implications for antibiotic persistence, mutation penetrance, cancer growth and anti-cancer drug resistance. However, the architecture of noise in cellular processes has remained largely unexplored even though expression noise in individual genes have been widely studied. Here we quantify noise in biological processes in yeast and through an integrated quantitative model show that the number of regulating transcription factors and their binding dynamics are the primary drivers of noise. Specifically, binding dynamics arising from competition and cooperation among TFs for promoter binding can predict a large fraction of noise variation. Our work reveals a novel mechanism of noise regulation that arises out of the dynamic nature of gene regulation and is not dependent on specific transcription factor or specific promoter sequence.

Transcription activator WCC recruits deacetylase HDA3 to control transcription dynamics and bursting in Neurospora

“…The active promoter state can be very short-lived, leading to transcription bursts interrupted by transcriptionally inactive phases which can be considerably long (2)(3)(4)(5)(6)(7)(8)(9)(10). TF binding dynamics are rate-limiting for the frequency of transcription initiation in many cases, and there is compelling evidence that the stochasticity of TF binding is a cause of transcriptional bursting (8,(11)(12)(13)(14)(15)(16).…”

Activation domains can decouple the mean and noise of gene expression

“…TFs are composed of DNA binding domains, which confer specificity for their target CREs, and activation domains (ADs), which recruit trans-acting cofactors that alter transcription once bound to DNA (Na ¨a ¨r et al, 2001;Govind et al, 2005). Fluctuations in TF binding are a major determinant of gene expression noise (Parab et al, 2021;Senecal et al, 2014;Pelet et al, 2011), but the effects of TF ADs on expression noise have not been determined. Because ADs vary widely in the cofactors they recruit and the contexts in which they are active (Blau et al, 1996;Brown et al, 1998;Duarte et al, 2016;Stampfel et al, 2015), we investigated whether ADs also vary in their effects on noise in gene expression.…”