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Generation and characterization of tools for target-specific de novo DNA methylat


The inability to manipulate DNA methylation or other epigenetic marks at will remains one of the biggest constrains in the field of epigenetics. Our goal is to overcome this limitation by designing an innovative approach for targeted manipulation of DNA methylation in a unique cellular system that also enables accurate measurements of such performance. Having the precise temporal and localized control over epigenetic marks will be essential for further dissecting their exact function(s) in genome regulation. The ability to write rather than just read epigenetic marks is the last missing piece t confidently and generally establish functional relationships, control the genome and will therefore have a wide impact on many fields. Over the past five years my lab has been one of the leading groups to map and manipulate DNA methylation at a genome-wide scale and we have accumulated likely the largest database of DNA methylation measurements at single base resolution. We have generated well over 2000 reduced representation bisulfite sequencing (RRBS) and more than 50 whole genome bisulfite sequencing (WGBS) datasets providing us with over a 100 billion CpG methylation measurements across more than a hundred mouse and human cell types. As a result we are confident to state that we know where in the genome DNA methylation can be found and how it is influenced by its genomic environment. Moreover we have created many mouse ES cells lines covering nearly every combination of loss and/or gain of function for the three catalytically active Dnmts (1, 3a and 3b) and their co-factor Dnmt3l. These in turn provide a unique foundation for this proposed study and enables us to most accurately determine efficiencies while controlling confounding factors. We strongly believe that simply engineering tools to write onto the genome without understanding the rules and principles on how this mark can be written in a genomic context will never provide a universal strategy.

Funded by the NIH National Center for Advancing Translational Sciences through its Clinical and Translational Science Awards Program, grant number UL1TR002541.