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Nat Commun. 2016 Feb 4;7:10528. doi: 10.1038/ncomms10528.

Probabilistic modelling of chromatin code landscape reveals functional diversity of enhancer-like chromatin states.

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Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey 08540, USA.
Graduate Program in Quantitative and Computational Biology, Princeton University, Princeton, New Jersey 08540, USA.
242 Carl Icahn Laboratory, Department of Computer Science, Princeton University, Princeton, New Jersey 08540, USA.
Simons Center for Data Analysis, Simons Foundation, New York, New York 10010, USA.


Interpreting the functional state of chromatin from the combinatorial binding patterns of chromatin factors, that is, the chromatin codes, is crucial for decoding the epigenetic state of the cell. Here we present a systematic map of Drosophila chromatin states derived from data-driven probabilistic modelling of dependencies between chromatin factors. Our model not only recapitulates enhancer-like chromatin states as indicated by widely used enhancer marks but also divides these states into three functionally distinct groups, of which only one specific group possesses active enhancer activity. Moreover, we discover a strong association between one specific enhancer state and RNA Polymerase II pausing, linking transcription regulatory potential and chromatin organization. We also observe that with the exception of long-intron genes, chromatin state transition positions in transcriptionally active genes align with an absolute distance to their corresponding transcription start site, regardless of gene length. Using our method, we provide a resource that helps elucidate the functional and spatial organization of the chromatin code landscape.

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