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Probabilistic modelling of chromatin code landscape reveals functional diversity
of enhancer-like chromatin states
#MMPMID26841971
Zhou J
; Troyanskaya OG
Nat Commun
2016[Feb]; 7
(?): 10528
PMID26841971
show ga
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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