bioRxivMolecular BiologyPreprint
Chromatin remodelling enables enhancer resetting to facilitate the ERK transcriptional response
Ramy RaghebiD, Nicola ReynoldsiD, Devina ShahiD, Mark Louie D. LopeziD, Jennifer BalmeriD, Nikolaos Markozanis, Prajakta Gade, Andria KoulleiD, Oluwaseun OgundeleiD, Robin FloydiD, Ernest D. LaueiD, Brian HendrichiD
Abstract
During development, cellular identity is ultimately determined by transcriptional output: lineage-specific genes must be activated, while genes associated with alternative fates must be repressed. This process depends on the activity of chromatin remodelling complexes, which regulate the accessibility of transcription factors to chromatin regulatory elements. In addition, cellular identity is shaped by exposure to intercellular signals. Understanding the mechanisms by which extracellular signals are translated into changes in the transcriptional program is essential for understanding cell fate decisions during development, as well as in disease conditions such as cancer. Here we describe a rapid and widespread enhancer resetting event in response to ERK signalling in mouse ES cells. This process occurs in two distinct phases: an immediate, genome-wide alteration in transcription factor binding dynamics at regulatory regions which is dependent on the release of paused RNA Polymerase II, followed by the re-establishment of a context appropriate, stable chromatin state. We demonstrate that the chromatin remodelling complex NuRD is required for this reestablishment phase and for the appropriate transcriptional response to ERK signalling. We propose that enhancer resetting places genomic regulatory regions in a state which is permissive to the exchange of transcription factors in order to establish a new, stable enhancer topology enabling rapid yet precise transcriptional response to extracellular signals.
- organism: mouse
- assay: ChIP-seq
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: cell type annotation
- approach: statistical model
- approach: experimental assay
- Citations
- 0
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