Abstract

DNA methylation is considered a stable epigenetic mark, yet methylation patterns can vary during differentiation and in diseases such as cancer. Local levels of DNA methylation result from opposing enzymatic activities, the rates of which remain largely unknown. Here we developed a theoretical and experimental framework enabling us to infer methylation and demethylation rates at 860,404 CpGs in mouse embryonic stem cells. We find that enzymatic rates can vary as much as two orders of magnitude between CpGs with identical steady-state DNA methylation. Unexpectedly, de novo and maintenance methylation activity is reduced at transcription factor binding sites, while methylation turnover is elevated in transcribed gene bodies. Furthermore, we show that TET activity contributes substantially more than passive demethylation to establishing low methylation levels at distal enhancers. Taken together, our work unveils a genome-scale map of methylation kinetics, revealing highly variable and context-specific activity for the DNA methylation machinery.

Local activity of the DNA methylation machinery remains poorly understood. Here, the authors present a theoretical and experimental framework to infer methylation and demethylation rates at genome scale in mouse embryonic stem cells, finding that maintenance methylation activity is reduced at transcription factor binding sites, while methylation turnover is elevated in transcribed gene bodies.

Details

Title
A genome-scale map of DNA methylation turnover identifies site-specific dependencies of DNMT and TET activity
Author
Ginno, Paul Adrian 1   VIAFID ORCID Logo  ; Gaidatzis Dimos 2 ; Feldmann Angelika 3 ; Hoerner, Leslie 1 ; Imanci Dilek 4 ; Burger, Lukas 2   VIAFID ORCID Logo  ; Zilbermann Frederic 1 ; Peters Antoine H F M 5 ; Edenhofer, Frank 6 ; Smallwood, Sébastien A 1 ; Krebs, Arnaud R 7 ; Schübeler Dirk 5   VIAFID ORCID Logo 

 Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland (GRID:grid.482245.d) (ISNI:0000 0001 2110 3787) 
 Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland (GRID:grid.482245.d) (ISNI:0000 0001 2110 3787); Swiss Institute of Bioinformatics, Basel, Switzerland (GRID:grid.419765.8) (ISNI:0000 0001 2223 3006) 
 Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland (GRID:grid.482245.d) (ISNI:0000 0001 2110 3787); Department of Biochemistry, University of Oxford, Oxford, UK (GRID:grid.4991.5) (ISNI:0000 0004 1936 8948) 
 Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland (GRID:grid.482245.d) (ISNI:0000 0001 2110 3787); Novartis Institutes for Biomedical Research, Basel, Switzerland (GRID:grid.419481.1) (ISNI:0000 0001 1515 9979) 
 Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland (GRID:grid.482245.d) (ISNI:0000 0001 2110 3787); University of Basel, Faculty of Sciences, Basel, Switzerland (GRID:grid.6612.3) (ISNI:0000 0004 1937 0642) 
 Leopold-Franzens-University Innsbruck & CMBI, Innsbruck, Austria (GRID:grid.5771.4) (ISNI:0000 0001 2151 8122) 
 Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland (GRID:grid.482245.d) (ISNI:0000 0001 2110 3787); EMBL Heidelberg, Heidelberg, Germany (GRID:grid.4709.a) (ISNI:0000 0004 0495 846X) 
Publication year
2020
Publication date
2020
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2407755909
Copyright
© The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.