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

TitleProbabilistic modelling of chromatin code landscape reveals functional diversity of enhancer-like chromatin states.
Publication TypeJournal Article
Year of Publication2016
AuthorsZhou, J, Troyanskaya, OG
JournalNat Commun
Volume7
Pagination10528
Date Published2016 Feb 04
ISSN2041-1723
KeywordsAnimals, Chromatin, Chromatin Immunoprecipitation, Drosophila melanogaster, Epigenesis, Genetic, Gene Expression Regulation, Models, Statistical, RNA Polymerase II, Transcription Initiation Site
Abstract

<p>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. </p>

DOI10.1038/ncomms10528
Alternate JournalNat Commun
PubMed ID26841971
PubMed Central IDPMC4742914
Grant ListP50 GM071508 / GM / NIGMS NIH HHS / United States
R01 GM071966 / GM / NIGMS NIH HHS / United States
R01 HG005998 / HG / NHGRI NIH HHS / United States
T32 HG003284 / HG / NHGRI NIH HHS / United States