This Article Full Text Full Text (PDF) Supplemental Research Data All Versions of this Article: gr.073080.107v1 gr.073080.107v2 18/8/1314    most recent Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Google Scholar Articles by Yu, H. Articles by Han, J.-D. J. PubMed PubMed Citation Articles by Yu, H. Articles by Han, J.-D. J. Social Bookmarking                   What's this?

Methods

Inferring causal relationships among different histone modifications and gene expression

Chinese Academy of Sciences Key Laboratory of Molecular Developmental Biology, Center for Molecular Systems Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Datun Road, Beijing, 100101, China

Histone modifications are major epigenetic factors regulating gene expression. They play important roles in maintaining stem cell pluripotency and in cancer pathogenesis. Different modifications may combine to form complex "histone codes." Recent high-throughput technologies, such as "ChIP-chip" and "ChIP-seq," have generated high-resolution maps for many histone modifications on the human genome. Here we use these maps to build a Bayesian network to infer causal and combinatorial relationships among histone modifications and gene expression. A pilot network derived by the same method among polycomb group (PcG) genes and H3K27 trimethylation is accurately supported by current literature. Our unbiased network model among histone modifications is also well supported by cross-validation results. It not only confirmed already known relationships, such as those of H3K27me3 to gene silencing, H3K4me3 to gene activation and the effect of bivalent modification of both H3K4me3 and H3K27me3, but also identified many other relationships that may predict new epigenetic interactions important in epigenetic gene regulation. Our automated inference method, which is potentially applicable to other ChIP-chip or ChIP-seq data analyses, provides a much-needed guide to deciphering the complex histone codes.

² Corresponding author.

E-mail jdhan{at}genetics.ac.cn; fax 86-10-64845797.

[Supplemental material is available online at www.genome.org.]

Article published online before print. Article and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.073080.107.

CiteULike    Connotea    Del.icio.us    Digg    Reddit    Technorati    What's this?