It has been ten years since the completion of the human genome project, but we are still far from understanding the mechanisms through which gene activities are regulated. It has been increasingly recognized that epigenetic mechanisms play an important role in cell-type specific gene regulation, and disruption of epigenetic regulation has been implicated in many diseases. However, our current knowledge has been limited to one-dimensional epigenetic patterns, whereas the three-dimensional chromatin structure remains poorly characterized. While it has been long recognized that chromatin interactions may play a critical role in long- range gene regulation, global investigations have been hampered by the technical difficulty to map genome-wide chromatin interactions at a high resolution. In this proposal, we will develop novel computational methods to systematically characterize the chromatin states from histone modification data, and to predict chromatin interactions from these states. We will leverage the large amount of histone modification data that are available in the public domain, and further validate our computational methods in the laboratories. Our proposed research will provide a much needed tool that can enable a guided approach to genome-wide interrogations of chromatin interactions, thereby greatly reducing the experimental cost to generate much needed data. Ultimately, the insights generated from these investigations will help elucidating the molecular pathways for a wide variety of diseases.
The proposed research will develop computational methods to prediction long-range chromatin interactions by leveraging the large amount of histone modification data generated by ENCODE and Roadmap Epigenomics Project. Our work will significantly facilitate genome-scale investigation of long-range gene regulatory mechanisms, which will in turn generate new insights into disease pathways and lead to new therapeutic approaches.
|Marco, Eugenio; Meuleman, Wouter; Huang, Jialiang et al. (2017) Multi-scale chromatin state annotation using a hierarchical hidden Markov model. Nat Commun 8:15011|
|Huang, Jialiang; Marco, Eugenio; Pinello, Luca et al. (2015) Predicting chromatin organization using histone marks. Genome Biol 16:162|
|Wu, Gengze; Cai, Jin; Han, Yu et al. (2014) LincRNA-p21 regulates neointima formation, vascular smooth muscle cell proliferation, apoptosis, and atherosclerosis by enhancing p53 activity. Circulation 130:1452-1465|
|Chipumuro, Edmond; Marco, Eugenio; Christensen, Camilla L et al. (2014) CDK7 inhibition suppresses super-enhancer-linked oncogenic transcription in MYCN-driven cancer. Cell 159:1126-1139|
|Marco, Eugenio; Karp, Robert L; Guo, Guoji et al. (2014) Bifurcation analysis of single-cell gene expression data reveals epigenetic landscape. Proc Natl Acad Sci U S A 111:E5643-50|
|Pinello, Luca; Xu, Jian; Orkin, Stuart H et al. (2014) Analysis of chromatin-state plasticity identifies cell-type-specific regulators of H3K27me3 patterns. Proc Natl Acad Sci U S A 111:E344-53|
|Larson, Jessica L; Huttenhower, Curtis; Quackenbush, John et al. (2013) A tiered hidden Markov model characterizes multi-scale chromatin states. Genomics 102:1-7|