Histone methylation marks play important roles in predicting the methylation status of CpG islands

The methylation status of CpG islands is highly correlated with gene expression. Current methods for computational prediction of DNA methylation only utilize DNA sequence features. In this study, besides 35 DNA sequence features, we added four histone methylation marks to predict the methylation status of CpG islands, and improved the accuracy to 89.94%. Also we applied our model to predict the methylation pattern of all the CpG islands in the human genome, and the results are consistent with the previous reports. Our results imply the important roles of histone methylation marks in affecting the methylation status of CpG islands. H3K4me enriched in the methylation-resistant CpG islands could disrupt the contacts between nucleosomes, unravel chromatin and make DNA sequences accessible. And the established open environment may be a prerequisite for or a consequence of the function implementation of zinc finger proteins that could protect CpG islands from DNA methylation. © 2008 Elsevier Inc. All rights reserved

Trisomy 21 alters DNA methylation in parent-of-origin-dependent and independent manners

The supernumerary chromosome 21 in Down syndrome differentially affects the methylation statuses at CpG dinucleotide sites and creates genome-wide transcriptional dysregulation of parental alleles, ultimately causing diverse pathologies. At present, it is unknown whether those effects are dependent or independent of the parental origin of the nondis-joined chromosome 21. Linkage analysis is a standard method for the determination of the parental origin of this aneuploidy, although it is inadequate in cases with deficiency of samples from the progenitors. Here, we assessed the reliability of the epigenetic 5(m)CpG imprints resulting in the maternally (oocyte)-derived allele methylation at a differentially methylated region (DMR) of the candidate imprinted WRB gene for asserting the parental origin of chromosome 21. We developed a methylation-sensitive restriction enzyme-specific PCR assay, based on the WRB DMR, across single nucleotide polymorphisms (SNPs) to examine the methylation statuses in the parental alleles. In genomic DNA from blood cells of either disomic or trisomic subjects, the maternal alleles were consistently methylated, while the paternal alleles were unmethylated. However, the supernumerary chromosome 21 did alter the methylation patterns at the RUNX1 (chromosome 21) and TMEM131 (chromosome 2) CpG sites in a parent-of-origin-independent manner. To evaluate the 5(m)CpG imprints, we conducted a computational comparative epigenomic analysis of transcriptome RNA sequencing (RNA-Seq) and histone modification expression patterns. We found allele fractions consistent with the transcriptional biallelic expression of WRB and ten neighboring genes, despite the similarities in the confluence of both a 17-histone modification activation backbone module and a 5-histone modification repressive module between the WRB DMR and the DMRs of six imprinted genes. We concluded that the maternally inherited 5(m)CpG imprints at the WRB DMR are uncoupled from the parental allele expression of WRB and ten neighboring genes in several tissues and that trisomy 21 alters DNA methylation in parent-of-origin-dependent and -independent manners

Methylation status of Dnmt1 promoter depends on poly(ADP-ribosy)lation

Research is focused on CpG islands and on the mechanism that poly(ADP-ribosyl)ation uses to defend the unmethylated state of these important DNA sequences which are located in the promoter regions of the housekeeping genes having a role of transcription regulators. Data here reported show that inhibition of PARP activity allows the diffuse insertion of methyl groups onto some CpG islands and in particular on the CpG island which is located in the promoter region of Dnmt1 gene. Hence, following inhibition of PARPs activity, this promoter loses its protection against methylation becoming silenced through methylation as shown by analyses with Methylation Sensitive PCR (MS-PCR) and sequencing after bisulphite treatment. Analyses of Western Blotting, RT-PCR and Real-time RT-PCR confirm that the gene has undergone silencing. The role of ADP-ribose polymers in silencing Dnmt1 has been demonstrated by additional experiments in which overexpression of poly(ADP-ribose) glycohydrolase leads to reduction of ADP-ribose polymers in nuclei associated to a sharp decrease of Dnmt1 level respect to control. A parallel genome-wide methyl-sensitive restriction assay demonstrates that the variation of Dnmt1 level is followed by a bimodal alteration of DNA methylation pattern. In fact, the inhibition of poly(ADP-ribosyl)ation initially causes an increase in methyl-group insertion onto DNA while this phenomenon is reversed after prolonged treatments and demethylation is detected within Alu sequences. Considering the important role played by Dnmt1 in the epigenetic scenario, these data lead us to think about what happens in tumor cells where both anomalous methylation of some CpG islands and diffuse hypomethylation are present. These findings open up a new path into epigenetic research in tumors. What is remarkable is that the demethylated pattern found in Alu sequences after treatment of cells with 3-ABA for 96 hours is very similar to the one found on DNA from cells treated with 5-AZA for the same time. The discovery of a DNA demethylating activity dependent on the use of inhibitors of poly(ADP-ribosyl)ation process increases the knowledge of mechanism by which these inhibitors enhance the cytotoxicity of other anticancer agents

Comparative (computational) analysis of the DNA methylation status of trinucleotide repeat expansion diseases

Copyright © 2013 Mohammadmersad Ghorbani et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.This article has been made available through the Brunel Open Access Publishing Fund.Previous studies have examined DNA methylation in different trinucleotide repeat diseases. We have combined this data and used a pattern searching algorithm to identify motifs in the DNA surrounding aberrantly methylated CpGs found in the DNA of patients with one of the three trinucleotide repeat (TNR) expansion diseases: fragile X syndrome (FRAXA), myotonic dystrophy type I (DM1), or Friedreich’s ataxia (FRDA). We examined sequences surrounding both the variably methylated (VM) CpGs, which are hypermethylated in patients compared with unaffected controls, and the nonvariably methylated CpGs which remain either always methylated (AM) or never methylated (NM) in both patients and controls. Using the J48 algorithm of WEKA analysis, we identified that two patterns are all that is necessary to classify our three regions CCGG* which is found in VM and not in AM regions and AATT* which distinguished between NM and VM + AM using proportional frequency. Furthermore, comparing our software with MEME software, we have demonstrated that our software identifies more patterns than MEME in these short DNA sequences. Thus, we present evidence that the DNA sequence surrounding CpG can influence its susceptibility to be de novo methylated in a disease state associated with a trinucleotide repeat.European Union Seventh Framework Programme and The Brunel University Graduate Program

Methylation status of Dnmt1 promoter depends on poly(ADP-ribosy)lation

Research is focused on CpG islands and on the mechanism that poly(ADP-ribosyl)ation uses to defend the unmethylated state of these important DNA sequences which are located in the promoter regions of the housekeeping genes having a role of transcription regulators. Data here reported show that inhibition of PARP activity allows the diffuse insertion of methyl groups onto some CpG islands and in particular on the CpG island which is located in the promoter region of Dnmt1 gene. Hence, following inhibition of PARPs activity, this promoter loses its protection against methylation becoming silenced through methylation as shown by analyses with Methylation Sensitive PCR (MS-PCR) and sequencing after bisulphite treatment. Analyses of Western Blotting, RT-PCR and Real-time RT-PCR confirm that the gene has undergone silencing. The role of ADP-ribose polymers in silencing Dnmt1 has been demonstrated by additional experiments in which overexpression of poly(ADP-ribose) glycohydrolase leads to reduction of ADP-ribose polymers in nuclei associated to a sharp decrease of Dnmt1 level respect to control. A parallel genome-wide methyl-sensitive restriction assay demonstrates that the variation of Dnmt1 level is followed by a bimodal alteration of DNA methylation pattern. In fact, the inhibition of poly(ADP-ribosyl)ation initially causes an increase in methyl-group insertion onto DNA while this phenomenon is reversed after prolonged treatments and demethylation is detected within Alu sequences. Considering the important role played by Dnmt1 in the epigenetic scenario, these data lead us to think about what happens in tumor cells where both anomalous methylation of some CpG islands and diffuse hypomethylation are present. These findings open up a new path into epigenetic research in tumors. What is remarkable is that the demethylated pattern found in Alu sequences after treatment of cells with 3-ABA for 96 hours is very similar to the one found on DNA from cells treated with 5-AZA for the same time. The discovery of a DNA demethylating activity dependent on the use of inhibitors of poly(ADP-ribosyl)ation process increases the knowledge of mechanism by which these inhibitors enhance the cytotoxicity of other anticancer agents

Restriction landmark genomic scanning (RLGS) spot identification by second generation virtual RLGS in multiple genomes with multiple enzyme combinations.

BackgroundRestriction landmark genomic scanning (RLGS) is one of the most successfully applied methods for the identification of aberrant CpG island hypermethylation in cancer, as well as the identification of tissue specific methylation of CpG islands. However, a limitation to the utility of this method has been the ability to assign specific genomic sequences to RLGS spots, a process commonly referred to as "RLGS spot cloning."ResultsWe report the development of a virtual RLGS method (vRLGS) that allows for RLGS spot identification in any sequenced genome and with any enzyme combination. We report significant improvements in predicting DNA fragment migration patterns by incorporating sequence information into the migration models, and demonstrate a median Euclidian distance between actual and predicted spot migration of 0.18 centimeters for the most complex human RLGS pattern. We report the confirmed identification of 795 human and 530 mouse RLGS spots for the most commonly used enzyme combinations. We also developed a method to filter the virtual spots to reduce the number of extra spots seen on a virtual profile for both the mouse and human genomes. We demonstrate use of this filter to simplify spot cloning and to assist in the identification of spots exhibiting tissue-specific methylation.ConclusionThe new vRLGS system reported here is highly robust for the identification of novel RLGS spots. The migration models developed are not specific to the genome being studied or the enzyme combination being used, making this tool broadly applicable. The identification of hundreds of mouse and human RLGS spot loci confirms the strong bias of RLGS studies to focus on CpG islands and provides a valuable resource to rapidly study their methylation

Linking the Epigenome to the Genome: Correlation of Different Features to DNA Methylation of CpG Islands

DNA methylation of CpG islands plays a crucial role in the regulation of gene expression. More than half of all human promoters contain CpG islands with a tissue-specific methylation pattern in differentiated cells. Still today, the whole process of how DNA methyltransferases determine which region should be methylated is not completely revealed. There are many hypotheses of which genomic features are correlated to the epigenome that have not yet been evaluated. Furthermore, many explorative approaches of measuring DNA methylation are limited to a subset of the genome and thus, cannot be employed, e.g., for genome-wide biomarker prediction methods. In this study, we evaluated the correlation of genetic, epigenetic and hypothesis-driven features to DNA methylation of CpG islands. To this end, various binary classifiers were trained and evaluated by cross-validation on a dataset comprising DNA methylation data for 190 CpG islands in HEPG2, HEK293, fibroblasts and leukocytes. We achieved an accuracy of up to 91% with an MCC of 0.8 using ten-fold cross-validation and ten repetitions. With these models, we extended the existing dataset to the whole genome and thus, predicted the methylation landscape for the given cell types. The method used for these predictions is also validated on another external whole-genome dataset. Our results reveal features correlated to DNA methylation and confirm or disprove various hypotheses of DNA methylation related features. This study confirms correlations between DNA methylation and histone modifications, DNA structure, DNA sequence, genomic attributes and CpG island properties. Furthermore, the method has been validated on a genome-wide dataset from the ENCODE consortium. The developed software, as well as the predicted datasets and a web-service to compare methylation states of CpG islands are available at http://www.cogsys.cs.uni-tuebingen.de/software/dna-methylation/

Chromosome-wide DNA methylation analysis predicts human tissue-specific X inactivation

X-chromosome inactivation (XCI) results in the differential marking of the active and inactive X with epigenetic modifications including DNA methylation. Consistent with the previous studies showing that CpG island-containing promoters of genes subject to XCI are approximately 50% methylated in females and unmethylated in males while genes which escape XCI are unmethylated in both sexes; our chromosome-wide (Methylated DNA ImmunoPrecipitation) and promoter-targeted methylation analyses (Illumina Infinium HumanMethylation27 array) showed the largest methylation difference (D = 0.12, p < 2.2 E−16) between male and female blood at X-linked CpG islands promoters. We used the methylation differences between males and females to predict XCI statuses in blood and found that 81% had the same XCI status as previously determined using expression data. Most genes (83%) showed the same XCI status across tissues (blood, fetal: muscle, kidney and nerual); however, the methylation of a subset of genes predicted different XCI statuses in different tissues. Using previously published expression data the effect of transcription on gene-body methylation was investigated and while X-linked introns of highly expressed genes were more methylated than the introns of lowly expressed genes, exonic methylation did not differ based on expression level. We conclude that the XCI status predicted using methylation of X-linked promoters with CpG islands was usually the same as determined by expression analysis and that 12% of X-linked genes examined show tissue-specific XCI whereby a gene has a different XCI status in at least one of the four tissues examined

DNA methylation dynamics in aging: How far are we from understanding the mechanisms?

DNA methylation is currently the most promising molecular marker for monitoring aging and predicting life expectancy. However, the mechanisms underlying age-related DNA methylation changes remain mostly undiscovered.Here we discuss the current knowledge of the dynamic nature of DNA epigenome landscape in mammals, and propose putative molecular mechanisms for aging-associated DNA epigenetic changes. Specifically, we describe age-related variations of methylcytosine and its oxidative derivatives in relation to the dynamics of chromatin structure, histone post-translational modifications and their modulators.Finally, we are proposing a conceptual framework that could explain the complex nature of the effects of age on DNA methylation patterns. This combines the accumulation of DNA methylation noise and also all of the predictable, site-specific DNA methylation changes.Gathering information in this area would pave the way for future investigation aimed at establishing a possible causative role of epigenetic mechanisms in aging