Abstract

Cells respond to external signals and stresses by activating transcription factors (TF), which induce gene expression changes. Prior work suggests that signal‐specific gene expression changes are partly achieved because different gene promoters exhibit distinct induction dynamics in response to the same TF input signal. Here, using high‐throughput quantitative single‐cell measurements and a novel statistical method, we systematically analyzed transcriptional responses to a large number of dynamic TF inputs. In particular, we quantified the scaling behavior among different transcriptional features extracted from the measured trajectories such as the gene activation delay or duration of promoter activity. Surprisingly, we found that even the same gene promoter can exhibit qualitatively distinct induction and scaling behaviors when exposed to different dynamic TF contexts. While it was previously known that promoters fall into distinct classes, here we show that the same promoter can switch between different classes depending on context. Thus, promoters can adopt context‐dependent “manifestations”. Our analysis suggests that the full complexity of signal processing by genetic circuits may be significantly underestimated when studied in only specific contexts.

Highlights

  • Exquisite regulation of gene expression underlies essentially all biological processes, including the remarkable ability of a single cell to develop into a fully formed organism

  • To study how genes respond to complex and dynamic transcription factors (TF) inputs, we focus on a large dataset that we previously generated (Fig EV1)

  • A large number of studies have shown that promoters fall into distinct classes and that different promoters decode dynamic stimuli differently (Stavreva et al, 2009; Suter et al, 2011; Hao & O’Shea, 2012; Sharon et al, 2012; Hansen & O’Shea, 2013; Hansen & O’Shea, 2015; Haberle & Stark, 2018; King et al, 2020)

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Summary

Introduction

Exquisite regulation of gene expression underlies essentially all biological processes, including the remarkable ability of a single cell to develop into a fully formed organism. Gene expression is primarily regulated at the level of promoter switching dynamics and initiation of transcription, which is associated with large cell-to-cell variability (Coulon et al, 2013). Gene expression is typically analyzed at the level of mRNAs (e.g., FISH) or proteins (e.g., immunofluorescence or GFP reporters) using bulk or single-cell approaches. Powerful, these data provide only partial and indirect information about the underlying promoter states and transcription initiation dynamics. Natural gene regulation is complex in both time (e.g., time-varying signals) and space (e.g., signaling gradients) (Li & Elowitz, 2019), experimental measurements tend to be limited to simple perturbations such as ON/ OFF or dose–response curves under steady-state conditions

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