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          Institute: MPI für molekulare Biomedizin     Collection: Jahrbuch 2018 (publ. 2017, arch)     Display Documents



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ID: 744102.0, MPI für molekulare Biomedizin / Jahrbuch 2018 (publ. 2017, arch)
DNA methylation regulates discrimination of enhancers from promoters through a H3K4me1-H3K4me3 seesaw mechanism
Authors:Sharifi-Zarchi, A.; Gerovska, D.; Adachi, K.; Totonchi, M.; Pezeshk, H.; Taft, R. J.; Scholer, H. R.; Chitsaz, H.; Sadeghi, M.; Baharvand, H.; Arauzo-Bravo, M. J.
Date of Publication (YYYY-MM-DD):2017-12-12
Title of Journal:BMC Genomics
Volume:18
Issue / Number:1
Start Page:964
Review Status:Internal review
Audience:Not Specified
Abstract / Description:BACKGROUND: DNA methylation at promoters is largely correlated with inhibition of gene expression. However, the role of DNA methylation at enhancers is not fully understood, although a crosstalk with chromatin marks is expected. Actually, there exist contradictory reports about positive and negative correlations between DNA methylation and H3K4me1, a chromatin hallmark of enhancers. RESULTS: We investigated the relationship between DNA methylation and active chromatin marks through genome-wide correlations, and found anti-correlation between H3K4me1 and H3K4me3 enrichment at low and intermediate DNA methylation loci. We hypothesized "seesaw" dynamics between H3K4me1 and H3K4me3 in the low and intermediate DNA methylation range, in which DNA methylation discriminates between enhancers and promoters, marked by H3K4me1 and H3K4me3, respectively. Low methylated regions are H3K4me3 enriched, while those with intermediate DNA methylation levels are progressively H3K4me1 enriched. Additionally, the enrichment of H3K27ac, distinguishing active from primed enhancers, follows a plateau in the lower range of the intermediate DNA methylation level, corresponding to active enhancers, and decreases linearly in the higher range of the intermediate DNA methylation. Thus, the decrease of the DNA methylation switches smoothly the state of the enhancers from a primed to an active state. We summarize these observations into a rule of thumb of one-out-of-three methylation marks: "In each genomic region only one out of these three methylation marks {DNA methylation, H3K4me1, H3K4me3} is high. If it is the DNA methylation, the region is inactive. If it is H3K4me1, the region is an enhancer, and if it is H3K4me3, the region is a promoter". To test our model, we used available genome-wide datasets of H3K4 methyltransferases knockouts. Our analysis suggests that CXXC proteins, as readers of non-methylated CpGs would regulate the "seesaw" mechanism that focuses H3K4me3 to unmethylated sites, while being repulsed from H3K4me1 decorated enhancers and CpG island shores. CONCLUSIONS: Our results show that DNA methylation discriminates promoters from enhancers through H3K4me1-H3K4me3 seesaw mechanism, and suggest its possible function in the inheritance of chromatin marks after cell division. Our analyses suggest aberrant formation of promoter-like regions and ectopic transcription of hypomethylated regions of DNA. Such mechanism process can have important implications in biological process in where it has been reported abnormal DNA methylation status such as cancer and aging.
Free Keywords:Animals; Cytosine/metabolism; *DNA Methylation; DNA-Binding Proteins/chemistry/metabolism; *Enhancer Elements, Genetic; Gene Expression; *Histone Code; Histones/metabolism; Mice; *Promoter Regions, Genetic; Protein Domains; Computational epigenomics; DNA methylation; Enhancers; H3K4me1; H3K4me3; Histone modifications; Next generation sequencing; Promoters
External Publication Status:published
Document Type:Article
Communicated by:MPI für molekulare Biomedizin
Affiliations:MPI für molekulare Biomedizin
External Affiliations:Computer Science Department, Colorado State University, Fort Collins, CO, USA. Department of Stem Cells and Developmental Biology, Cell Science Research Center, Royan Institute for Stem Cell Biology and Technology, ACECR, Tehran, Iran. Department of Computer Engineering, Sharif University of Technology, Tehran, Iran. Computational Biology and Systems Biomedicine, Biodonostia Health Research Institute, 20014, San Sebastian, Spain. Department of Cell and Developmental Biology, Max Planck Institute for Molecular Biomedicine, Munster, Germany. School of Mathematics, Statistics and Computer Science, College of Science, University of Tehran, Tehran, Iran. School of Biological Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran. Illumina Inc., San Diego, USA. Medical Faculty, University of Munster, Munster, Germany. National Institute of Genetic Engineering and Biotechnology (NIGEB), Tehran, Iran. Department of Stem Cells and Developmental Biology, Cell Science Research Center, Royan Institute for Stem Cell Biology and Technology, ACECR, Tehran, Iran. baharvand@royaninstitute.org. Department of Developmental Biology, University of Science and Culture, Tehran, Iran. baharvand@royaninstitute.org. Computational Biology and Systems Biomedicine, Biodonostia Health Research Institute, 20014, San Sebastian, Spain. mararabra@yahoo.co.uk. Computational Biology and Bioinformatics Group, Max Planck Institute for Molecular Biomedicine, Munster, Germany. mararabra@yahoo.co.uk. IKERBASQUE, Basque Foundation for Science, 48011, Bilbao, Spain. mararabra@yahoo.co.uk.
Identifiers:ISSN:1471-2164 (Electronic) 1471-2164 (Linking) %R 10.1... [ID No:1]
URL:https://www.ncbi.nlm.nih.gov/pubmed/29233090 [ID No:2]
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