Methylation of cytosines is an essential epigenetic modification in mammalian genomes, yet the rules that govern methylation patterns remain largely elusive. To gain insights into this process, we generated base-pair-resolution mouse methylomes in stem cells and neuronal progenitors. Advanced quantitative analysis identified low-methylated regions (LMRs) with an average methylation of 30%. These represent CpG-poor distal regulatory regions as evidenced by location, DNase I hypersensitivity, presence of enhancer chromatin marks and enhancer activity in reporter assays. LMRs are occupied by DNA-binding factors and their binding is necessary and sufficient to create LMRs. A comparison of neuronal and stem-cell methylomes confirms this dependency, as cell-type-specific LMRs are occupied by cell-type-specific transcription factors. This study provides methylome references for the mouse and shows that DNA-binding factors locally influence DNA methylation, enabling the identification of active regulatory regions.

Recently, we described a machine learning approach for classification of central nervous system tumors based on the analysis of genome-wide DNA methylation patterns [6]. Here, we report on DNA methylation-based central nervous system (CNS) tumor diagnostics conducted in our institution between the years 2015 and 2018. In this period, more than 1000 tumors from the neurosurgical departments in Heidelberg and Mannheim and more than 1000 tumors referred from external institutions were subjected to DNA methylation analysis for diagnostic purposes. We describe our current approach to the integrated diagnosis of CNS tumors with a focus on constellations with conflicts between morphological and molecular genetic findings. We further describe the benefit of integrating DNA copy-number alterations into diagnostic considerations and provide a catalog of copy-number changes for individual DNA methylation classes. We also point to several pitfalls accompanying the diagnostic implementation of DNA methylation profiling and give practical suggestions for recurring diagnostic scenarios.Electronic supplementary materialThe online version of this article (10.1007/s00401-018-1879-y) contains supplementary material, which is available to authorized users.