Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 70,754 bioRxiv papers from 308,923 authors.
Cells respond to external signals and stresses by activating transcription factors (TF), which induce gene expression changes. Previous work suggests that signal-specific gene expression changes are partly achieved because different gene promoters exhibit varying 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 transcription in individual cells 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. That is, 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 specific contexts only.
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