2008 NIH Director's New Innovator Award Program (DP2) 10 Quantitative and Computational Biology Investigating Developmental Potential Based on Genome- wide Chromatin Status Abstract While the epigenetic state of chromatin is thought to play an important role in regulating and maintaining gene expression programs during development, the general principles by which this occurs are only beginning to emerge. Recent advances in quantitative genomic approaches such as ChIP-chip and ChIP-seq provide a unique opportunity to elucidate the general rules by which chromatin states accompany and regulate developmental programs in vivo. However, generating sufficient high quality data to elucidate these rules is still challenging in mammalian systems because of the cell-type heterogeneity of embryos and the large amounts of cells required with current techniques. The goal of this proposal is to use genomic approaches to investigate the role of chromatin status during the development of Drosophila. Specifically, we are interested in identifying chromatin states that can predict which genes are likely to be activated in future gene expression programs and thus reflect the developmental potential of a cell. We have previously demonstrated the value of such approach by establishing ChIP-chip in Drosophila and by identifying stalled RNA polymerase II as a hallmark of developmental genes that are poised for activation. Here we test more generally the predictive value of stalled RNA polymerase II and chromatin states implicated in determining developmental potential, cellular memory and the response to signaling. Chromatin states to be tested include Polycomb group protein occupancy, specific histone modifications, nucleosome density and core promoter elements. All chromatin states will be analyzed across a developmental time-course and across specific cell lineages, both singly and in combination. Follow-up experiments with traditional Drosophila genetics will be used to test emerging hypotheses. Because chromatin states in Drosophila are likely to have similar predictive value in mammalian cells, this study will provide an important framework for understanding and predicting the development of normal and diseased cells in humans.
