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• W3034348519 startingPage "e1008572" @default.
• W3034348519 abstract "The study of transcription remains one of the centerpieces of modern biology with implications in settings from development to metabolism to evolution to disease. Precision measurements using a host of different techniques including fluorescence and sequencing readouts have raised the bar for what it means to quantitatively understand transcriptional regulation. In particular our understanding of the simplest genetic circuit is sufficiently refined both experimentally and theoretically that it has become possible to carefully discriminate between different conceptual pictures of how this regulatory system works. This regulatory motif, originally posited by Jacob and Monod in the 1960s, consists of a single transcriptional repressor binding to a promoter site and inhibiting transcription. In this paper, we show how seven distinct models of this so-called simple-repression motif, based both on thermodynamic and kinetic thinking, can be used to derive the predicted levels of gene expression and shed light on the often surprising past success of the thermodynamic models. These different models are then invoked to confront a variety of different data on mean, variance and full gene expression distributions, illustrating the extent to which such models can and cannot be distinguished, and suggesting a two-state model with a distribution of burst sizes as the most potent of the seven for describing the simple-repression motif." @default.
• W3034348519 created "2020-06-19" @default.
• W3034348519 creator A5029612834 @default.
• W3034348519 creator A5056139482 @default.
• W3034348519 creator A5073123449 @default.
• W3034348519 date "2021-01-19" @default.
• W3034348519 modified "2023-10-16" @default.
• W3034348519 title "Reconciling kinetic and thermodynamic models of bacterial transcription" @default.
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• W3034348519 doi "https://doi.org/10.1371/journal.pcbi.1008572" @default.
• W3034348519 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7845990" @default.
• W3034348519 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/33465069" @default.
• W3034348519 hasPublicationYear "2021" @default.
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