GwEEP - A comprehensive approach for genome-wide efficiency profiling of DNA modifying enzymes

A precise understanding of DNA methylation dynamics on a genome wide scale is of great importance for the comprehensive investigation of a variety of biological processes such as reprogramming of somatic cells to iPSCs, cell differentiation and also cancer development. To date, a complex integration of multiple and distinct genome wide data sets is required to derive the global activity of DNA modifying enzymes. We present GwEEP - Genome-wide Epigenetic Efficiency Profiling as a versatile approach to infer dynamic efficiency changes of DNA modifying enzymes at base pair resolution on a genome wide scale. GwEEP relies on genome wide oxidative Hairpin Bisulfite sequencing (HPoxBS) data sets, which are translated by a sophisticated hidden Markov model into quantitative enzyme efficiencies with reported confidence around the estimates. GwEEP in its present form predicts de novo and maintenance methylation efficiencies of Dnmts, as well as the hydroxylation efficiency of Tets but its purposefully flexible design allows to capture further oxidation processes such as formylation and carboxylation given available data in the future. Applied to a well characterized ES cell model, GwEEP precisely predicts the complex epigenetic changes following a Serum-to-2i shift i.e., (i) instant reduction in maintenance efficiency (ii) gradually decreasing de novo methylation efficiency and (iii) increasing Tet efficiencies. In addition, a complementary analysis of Tet triple knock-out ES cells confirms the previous hypothesized mutual interference of Dnmts and Tets. GwEEP is applicable to a wide range of biological samples including cell lines, but also tissues and primary cell types. MOTIVATION Dynamic changes of DNA methylation patterns are a common phenomenon in epigenetics. Although a stable DNA methylation profile is essential for cell identity, developmental processes require the rearrangement of 5-methylcytosine in the genome. Stable methylation patterns are the result of balanced Dnmts and Tets activities, while methylome transformation results from a coordinated change in Dnmt and Tet efficiencies. Such transformations occur on a global scale, for example during the reprogramming of maternal and paternal methylation patterns and the establishment of novel cell type specific methylomes during embryonic development in vivo, but also in vitro during (re)programming of induced pluripotent stem cells, as well as somatic cells. In addition, local (de)methylation events are key for gene regulation during cell differentiation. A detailed understanding of Dnmt and Tet cooperation is essential for understanding natural epigenetic adaptation as well as optimization of in vitro (re)programming protocols. For this purpose, we developed a pipeline for quantitative and precise estimation of Dnmt and Tet activity. Using only double strand methylation information, GwEEP infers accurate maintenance and de novo methylation efficiency of Dnmts, as well as hydroxylation efficiency of Tets at single base resolution. Thus, we believe GwEEP provides a powerful tool for the investigation of methylome rearrangements in various systems.