Promoters adopt distinct dynamic manifestations depending on transcription factor context
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 respons...
Main Authors: | , |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2021-02-01
|
Series: | Molecular Systems Biology |
Subjects: | |
Online Access: | https://doi.org/10.15252/msb.20209821 |
id |
doaj-96fd96158ac24282a2c0a6047b324891 |
---|---|
record_format |
Article |
spelling |
doaj-96fd96158ac24282a2c0a6047b3248912021-08-02T16:04:06ZengWileyMolecular Systems Biology1744-42922021-02-01172n/an/a10.15252/msb.20209821Promoters adopt distinct dynamic manifestations depending on transcription factor contextAnders S Hansen0Christoph Zechner1Department of Biological Engineering Massachusetts Institute of Technology Cambridge MA USAMax Planck Institute of Molecular Cell Biology & Genetics Dresden GermanyAbstract 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.https://doi.org/10.15252/msb.20209821Bayesian inferencemanifestationMsn2promoter class switchingtranscription factor dynamics |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Anders S Hansen Christoph Zechner |
spellingShingle |
Anders S Hansen Christoph Zechner Promoters adopt distinct dynamic manifestations depending on transcription factor context Molecular Systems Biology Bayesian inference manifestation Msn2 promoter class switching transcription factor dynamics |
author_facet |
Anders S Hansen Christoph Zechner |
author_sort |
Anders S Hansen |
title |
Promoters adopt distinct dynamic manifestations depending on transcription factor context |
title_short |
Promoters adopt distinct dynamic manifestations depending on transcription factor context |
title_full |
Promoters adopt distinct dynamic manifestations depending on transcription factor context |
title_fullStr |
Promoters adopt distinct dynamic manifestations depending on transcription factor context |
title_full_unstemmed |
Promoters adopt distinct dynamic manifestations depending on transcription factor context |
title_sort |
promoters adopt distinct dynamic manifestations depending on transcription factor context |
publisher |
Wiley |
series |
Molecular Systems Biology |
issn |
1744-4292 |
publishDate |
2021-02-01 |
description |
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. |
topic |
Bayesian inference manifestation Msn2 promoter class switching transcription factor dynamics |
url |
https://doi.org/10.15252/msb.20209821 |
work_keys_str_mv |
AT andersshansen promotersadoptdistinctdynamicmanifestationsdependingontranscriptionfactorcontext AT christophzechner promotersadoptdistinctdynamicmanifestationsdependingontranscriptionfactorcontext |
_version_ |
1721230143995772928 |