Abstract
Crosstalk between epigenetic variables including histone modification produces diverse combinatorial patterns each of which has specific biological roles. Therefore, identification of causal relationships among epigenetic variables such as histone modifications, chromatin regulations, and DNA methylations has substantial impact on better understanding of complex epigenetic mechanisms. In this regard, development of effective and simple algorithms to recognize casual relationships among them is required. Here, we present a new method calculating maximal deletion effect (MDE) of one histone modification to determine whether two histone modifications have crosstalks. After combining genome-wide histone modification densities with gene expression changes in mutant strains that inhibit a specific modification, we evaluated MDE to examine causal relationships between histone H3 methylations and H4 acetylations. By calculating MDE of H4 acetyl sites, we identified new trans-crosstalks between H4 lysine 12th/16th acetylations and H3K79 tri-methylation, and these relationships were successfully confirmed by immunoblot analysis in Saccharomyces cerevisiae. Importantly, these trans-crosstalks showed correlative patterns with gene activation in both yeast and human CD4+ T cells. We expect that MDE can be generally applicable to identify various causal relationships among many epigenetic variables and useful for characterizing complex modification patterns.
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Acknowledgments
We thank Ali Shilatifard and his colleagues for the SHIMA library and Chul-Hwan Lee for technical advice on the wet experiments. This work was supported by Chung Moon Soul Center for BioInformation and BioElectronics (CMSC) and by the Ministry of Education, Science and Technology (Bioinformatics Pipeline for Stem Cell Epigenomics).
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The authors declare no conflict of interest.
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Inkyung Jung and Junseong Park have contributed equally to this work.
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Jung, I., Park, J., Choi, C. et al. Identification of novel trans-crosstalk between histone modifications via genome-wide analysis of maximal deletion effect. Genes Genom 37, 693–701 (2015). https://doi.org/10.1007/s13258-015-0298-x
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DOI: https://doi.org/10.1007/s13258-015-0298-x