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

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 prote...

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Published inProceedings of the National Academy of Sciences - PNAS Vol. 116; no. 30; pp. 14995 - 15000
Main Authors Cholewa-Waclaw, Justyna, Shah, Ruth, Webb, Shaun, Chhatbar, Kashyap, Ramsahoye, Bernard, Pusch, Oliver, Yu, Miao, Greulich, Philip, Waclaw, Bartlomiej, Bird, Adrian P.
Format Journal Article
LanguageEnglish
Published United States National Academy of Sciences 23.07.2019
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Summary: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, multidimensional experimental analysis and mathematical modeling to indicate that MeCP2 is a global transcriptional regulator whose binding to DNA creates “slow sites” in gene bodies. We hypothesize that waves of slowed-down RNA polymerase II formed behind these sites travel backward and indirectly affect initiation, reminiscent of defect-induced shockwaves in nonequilibrium physics transport models. This mechanism differs from conventional gene-regulation mechanisms, which often involve direct modulation of transcription initiation. Our findings point to 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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Author contributions: J.C.-W., R.S., B.W., and A.P.B. designed research; J.C.-W., R.S., B.R., and M.Y. performed research; J.C.-W., R.S., and O.P. contributed new reagents/analytic tools; J.C.-W., R.S., S.W., K.C., P.G., B.W., and A.P.B. analyzed data; and J.C.-W., R.S., B.W., and A.P.B. wrote the paper.
Contributed by Adrian P. Bird, June 4, 2019 (sent for review March 1, 2019; reviewed by Martin Howard, Amos Tanay, and Pieter Rein ten Wolde)
1J.C.-W. and R.S. contributed equally to this work.
Reviewers: M.H., John Innes Centre; A.T., Weizmann Institute; and P.R.t.W., University of Amsterdam.
ISSN:0027-8424
1091-6490
DOI:10.1073/pnas.1903549116