Deciphering and modifying the rules of epigenetic regulation in chromatin – EPIGENEREG

One of the unsolved challenges of synthetic and systems biology is bottom-up prediction of gene expression from molecular interactions of regulatory molecules with the genome. Current high-throughput experiments allow generating large data sets for retrieving the DNA sequence preferences of transcription factors (TF) and other chromosomal proteins throughout the complete genome, as well as the maps of DNA methylation, histone variant incorporation and histone modifications. Due to the high combinatorial complexity of possible chromatin states an experimental determination of genome-wide maps for all possible sets of epigenetic parameters is not possible. Thus, quantitative descriptions are needed that relate molecular binding events to epigenetic states as determined from a limited number of key features. In the project proposed here, we set out to develop such a framework to predict and manipulate changes in gene expression caused by transcription factor and nucleosome rearrangements, starting from a known set of epigenetic marks that define a given cell state. To parameterize the models, we will use high-throughput sequencing data for mouse embryonic stem cell development. To validate the models, we will study the effects of novel epigenetic modulators in the same system. The resulting quantitative description will connect molecular binding events to the changes in epigenetic states at functional genomic elements during stem cell differentiation. The theoretico-experimental framework developed here will have general implications for in silico drug testing and construction of synthetic cis-regulatory modules with defined properties.