TITLE

Predicting the probability of H3K4me3 occupation at a base pair from the genome sequence context

AUTHOR(S)
Ha, Misook; Hong, Soondo; Li, Wen-Hsiung
PUB. DATE
May 2013
SOURCE
Bioinformatics;May2013, Vol. 29 Issue 9, p1199
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
Motivation: Histone modifications regulate chromatin structure and gene expression. Although nucleosome formation is known to be affected by primary DNA sequence composition, no sequence signature has been identified for histone modifications. It is known that dense H3K4me3 nucleosome sites are accompanied by a low density of other nucleosomes and are associated with gene activation. This observation suggests a different sequence composition of H3K4me3 from other nucleosomes.Approach: To understand the relationship between genome sequence and chromatin structure, we studied DNA sequences at histone modification sites in various human cell types. We found sequence specificity for H3K4me3, but not for other histone modifications. Using the sequence specificities of H3 and H3K4me3 nucleosomes, we developed a model that computes the probability of H3K4me3 occupation at each base pair from the genome sequence context.Results: A comparison of our predictions with experimental data suggests a high performance of our method, revealing a strong association between H3K4me3 and specific genomic DNA context. The high probability of H3K4me3 occupation occurs at transcription start and termination sites, exon boundaries and binding sites of transcription regulators involved in chromatin modification activities, including histone acetylases and enhancer- and insulator-associated factors. Thus, the human genome sequence contains signatures for chromatin modifications essential for gene regulation and development. Our method may be applied to find new sequence elements functioning by chromatin modulation.Availability: Software and supplementary data are available at Bioinformatics online.Contact: misook.ha@samsung.com or wli@uchicago.eduSupplementary information: Supplementary data are available at Bioinformatics online.
ACCESSION #
87375798

 

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