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Quantitative modelling predicts the impact of DNA methylation on RNA polymerase II traffic

View ORCID ProfileJustyna Cholewa-Waclaw, View ORCID ProfileRuth Shah, View ORCID ProfileShaun Webb, View ORCID ProfileKashyap Chhatbar, Bernard Ramsahoye, View ORCID ProfileOliver Pusch, Miao Yu, View ORCID ProfilePhilip Greulich, View ORCID ProfileBartlomiej Waclaw, View ORCID ProfileAdrian Bird
doi: https://doi.org/10.1101/391904
Justyna Cholewa-Waclaw
1The Wellcome Centre for Cell Biology, The King’s Buildings, University of Edinburgh, Max Born Crescent, Edinburgh, EH9 3BF, UK
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Ruth Shah
1The Wellcome Centre for Cell Biology, The King’s Buildings, University of Edinburgh, Max Born Crescent, Edinburgh, EH9 3BF, UK
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Shaun Webb
1The Wellcome Centre for Cell Biology, The King’s Buildings, University of Edinburgh, Max Born Crescent, Edinburgh, EH9 3BF, UK
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Kashyap Chhatbar
1The Wellcome Centre for Cell Biology, The King’s Buildings, University of Edinburgh, Max Born Crescent, Edinburgh, EH9 3BF, UK
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Bernard Ramsahoye
2Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital Campus, Crewe Road, Edinburgh, EH4 2XU, UK
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Oliver Pusch
3Center for Anatomy and Cell Biology, Medical University of Vienna, Schwarzspanierstrasse 17, Vienna, 1090, Austria
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Miao Yu
4Ludwig Institute for Cancer Research, La Jolla, California, 92093 USA
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Philip Greulich
5Mathematical Sciences, University of Southampton, Southampton, SO17 1BJ, UK
6Institute for Life Sciences, University of Southampton, Southampton, SO17 1BJ, UK
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Bartlomiej Waclaw
7School of Physics and Astronomy, University of Edinburgh, James Clerk Maxwell Building, Peter Guthrie Tait Road, Edinburgh, EH9 3FD, UK
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  • For correspondence: a.bird@ed.ac.uk bwaclaw@ph.ed.ac.uk
Adrian Bird
1The Wellcome Centre for Cell Biology, The King’s Buildings, University of Edinburgh, Max Born Crescent, Edinburgh, EH9 3BF, UK
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  • For correspondence: a.bird@ed.ac.uk bwaclaw@ph.ed.ac.uk
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Abstract

Patterns of gene expression are primarily determined by proteins that locally enhance or repress transcription. While many transcription factors target a restricted number of genes, others appear to modulate transcription levels globally. An example is MeCP2, an abundant methylated-DNA binding protein that is mutated in the neurological disorder Rett Syndrome. Despite much research, the molecular mechanism by which MeCP2 regulates gene expression is not fully resolved. Here we integrate quantitative, multi-dimensional experimental analysis and mathematical modelling to show that MeCP2 is a novel type of global transcriptional regulator whose binding to DNA creates "slow sites" in gene bodies. Waves of slowed-down RNA polymerase II formed behind these sites travel backward and indirectly affect initiation, reminiscent of defect-induced shock waves in non-equilibrium physics transport models. This mechanism differs from conventional gene regulation mechanisms, which often involve direct modulation of transcription initiation. Our findings uncover a genome-wide function of DNA methylation that may account for the reversibility of Rett syndrome in mice. Moreover, our combined theoretical and experimental approach provides a general method for understanding how global gene expression patterns are choreographed.

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Posted February 28, 2019.
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Quantitative modelling predicts the impact of DNA methylation on RNA polymerase II traffic
Justyna Cholewa-Waclaw, Ruth Shah, Shaun Webb, Kashyap Chhatbar, Bernard Ramsahoye, Oliver Pusch, Miao Yu, Philip Greulich, Bartlomiej Waclaw, Adrian Bird
bioRxiv 391904; doi: https://doi.org/10.1101/391904
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Quantitative modelling predicts the impact of DNA methylation on RNA polymerase II traffic
Justyna Cholewa-Waclaw, Ruth Shah, Shaun Webb, Kashyap Chhatbar, Bernard Ramsahoye, Oliver Pusch, Miao Yu, Philip Greulich, Bartlomiej Waclaw, Adrian Bird
bioRxiv 391904; doi: https://doi.org/10.1101/391904

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