A human CpG island randomly inserted into a plant genome is protected from methylation

In vertebrate genomes the dinucleotide CpG is heavily methylated, except in CpG islands, which are normally unmethylated. It is not clear why the CpG islands are such poor substrates for DNA methyltransferase. Plant genomes display methylation, but otherwise the genomes of plants and animals represent two very divergent evolutionary lines. To gain a further understanding of the resistance of CpG islands to methylation, we introduced a human CpG island from the proteasome-like subunit I gene into the genome of the plant Arabidopsis thaliana. Our results show that prevention of methylation is an intrinsic property of CpG islands, recognized even if a human CpG island is transferred to a plant genome. Two different parts of the human CpG island – the promoter region/ first exon and exon2–4 – both displayed resistance against methylation, but the promoter/ exon1 construct seemed to be most resistant. In contrast, certain sites in a plant CpG-rich region used as a control transgene were always methylated. The frequency of silencing of the adjacent nptII (Km^R) gene in the human CpG constructs was lower than observed for the plant CpG-rich region. These results have implications for understanding DNA methylation, and for construction of vectors that will reduce transgene silencing.     

Primate CpG islands are maintained by heterogeneous evolutionary regimes involving minimal selection

Mammalian CpG islands are key epigenomic elements that were first characterized experimentally as genomic fractions with low levels of DNA methylation. Currently, CpG islands are defined based on their genomic sequences alone. Here, we develop evolutionary models to show that several distinct evolutionary processes generate and maintain CpG islands. One central evolutionary regime resulting in enriched CpG content is driven by low levels of DNA methylation and consequentially low rates of CpG deamination. Another major force forming CpG islands is biased gene conversion that stabilizes constitutively methylated CpG islands by balancing rapid deamination with CpG fixation. Importantly, evolutionary analysis and population genetics data suggest that selection for high CpG content is not?a significant factor contributing to conservation of CpGs in differentially methylated regions. The heterogeneous, but not selective, origins of CpG islands have direct implications for the understanding of DNA methylation patterns in healthy and diseased cells.     

De novo quantitative bisulfite sequencing using the pyrosequencing technology

Current protocols for DNA methylation analysis are either labor intensive or limited to the measurement of only one or two CpG positions. Pyrosequencing is a real-time sequencing technology that can overcome these limitations and be used as an epigenotype-mapping tool. Initial experiments demonstrated reliable quantification of the degree of DNA methylation when 2-6 CpGs were analyzed. We sought to improve the sequencing protocol so as to analyze as many CpGs as possible in a single sequencing run. By using an improved enzyme mix and adding single-stranded DNA-binding protein to the reaction, we obtained reproducible results for as many as 10 successive CpGs in a single sequencing reaction spanning up to 75 nucleotides. A minimum amount of 10 ng of bisulfite-treated DNA is necessary to obtain good reproducibility and avoid preferential amplification. We applied the assay to the analysis of DNA methylation patterns in four CpG islands in the vicinity of IGF2 and H19 genes. This allowed accurate and quantitative de novo sequencing of the methylation state of each CpG, showing reproducible variations of methylation state in contiguous CpGs, and proved to be a useful adjunct to current technologies.     

CpG island methylation in human lymphocytes is highly correlated with DNA sequence, repeats, and predicted DNA structure

CpG island methylation plays an important role in epigenetic gene control during mammalian development and is frequently altered in disease situations such as cancer. The majority of CpG islands is normally unmethylated, but a sizeable fraction is prone to become methylated in various cell types and pathological situations. The goal of this study is to show that a computational epigenetics approach can discriminate between CpG islands that are prone to methylation from those that remain unmethylated. We develop a bioinformatics scoring and prediction method on the basis of a set of 1,184 DNA attributes, which refer to sequence, repeats, predicted structure, CpG islands, genes, predicted binding sites, conservation, and single nucleotide polymorphisms. These attributes are scored on 132 CpG islands across the entire human Chromosome 21, whose methylation status was previously established for normal human lymphocytes. Our results show that three groups of DNA attributes, namely certain sequence patterns, specific DNA repeats, and a particular DNA structure, are each highly correlated with CpG island methylation (correlation coefficients of 0.64, 0.66, and 0.49, respectively). We predicted, and subsequently experimentally examined 12 CpG islands from human Chromosome 21 with unknown methylation patterns and found more than 90% of our predictions to be correct. In addition, we applied our prediction method to analyzing Human Epigenome Project methylation data on human Chromosome 6 and again observed high prediction accuracy. In summary, our results suggest that DNA composition of CpG islands (sequence, repeats, and structure) plays a significant role in predisposing CpG islands for DNA methylation. This finding may have a strong impact on our understanding of changes in CpG island methylation in development and disease.     

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.     

A sensitive new method for rapid detection of abnormal methylation patterns in global DNA and within CpG islands.

To assess alterations in DNA methylation density in both global DNA and within CpG islands, we have developed a simple method based on the use of methylation-sensitive restriction endonucleases that leave a 5' guanine overhang after DNA cleavage, with subsequent single nucleotide extension with radiolabeled [(3)H]dCTP. The methylation-sensitive restriction enzymes HpaII and AciI have relatively frequent recognition sequences at CpG sites that occur randomly throughout the genome. BssHII is a methylation sensitive enzyme that similarly leaves a guanine overhang, but the recognition sequence is nonrandom and occurs predominantly at unmethylated CpG sites within CpG islands. The selective use of these enzymes can be used to screen for alterations in genome-wide methylation and CpG island methylation status, respectively. The extent of [(3)H]dCTP incorporation opposite the exposed guanine after restriction enzyme treatment is directly proportional to the number of unmethylated (cleaved) CpG sites. The "cytosine-extension assay" has several advantages over existing methods because (a) radiolabel incorporation is independent of the integrity of the DNA, (b) methylation detection does not require PCR amplification or DNA methylase reactions, and (c) it is applicable to ng quantities of DNA. Using DNA extracted from normal human liver and from human hepatocellular carcinoma, the applicability of the assay is demonstrated by the detection of an increase in genome-wide hypomethylation and CpG island hypermethylation in the tumor DNA.     

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/.     

Regionally Specific and Genome-Wide Analyses Conclusively Demonstrate the Absence of CpG Methylation in Human Mitochondrial DNA

Although CpG methylation clearly distributes genome-wide in vertebrate nuclear DNA, the state of methylation in the vertebrate mitochondrial genome has been unclear. Several recent reports using immunoprecipitation, mass spectrometry, and enzyme-linked immunosorbent assay methods concluded that human mitochondrial DNA (mtDNA) has much more than the 2 to 5% CpG methylation previously estimated. However, these methods do not provide information as to the sites or frequency of methylation at each CpG site. Here, we have used the more definitive bisulfite genomic sequencing method to examine CpG methylation in HCT116 human cells and primary human cells to independently answer these two questions. We found no evidence of CpG methylation at a biologically significant level in these regions of the human mitochondrial genome. Furthermore, unbiased next-generation sequencing of sodium bisulfite treated total DNA from HCT116 cells and analysis of genome-wide sodium bisulfite sequencing data sets from several other DNA sources confirmed this absence of CpG methylation in mtDNA. Based on our findings using regionally specific and genome-wide approaches with multiple human cell sources, we can definitively conclude that CpG methylation is absent in mtDNA. It is highly unlikely that CpG methylation plays any role in direct control of mitochondrial function.     

Methylation and sequence analysis around EagI sites: identification of 28 new CpG islands in XQ24-XQ28.

Thirty-two probes for CpG islands of the distal long arm of the human X chromosome have been identified. From a genomic library of DNA of the hamster-human cell hybrid X3000.1 digested with the rare cutter restriction enzyme EagI, 53 different human clones have been isolated and characterized by methylation and sequence analysis. The characteristic pattern of DNA methylation of CpG islands at the 5' end of genes of the X chromosome has been used to distinguish between EagI sites in CpG islands versus isolated EagI sites. The sequence analysis has confirmed and completed the characterization showing that sequences at the 5' end of known genes were among the clones defined CpG islands and that the non-CpG islands clones were mostly repetitive sequences with a non-methylated or variably methylated EagI site. Thus, since clones corresponding to repetitive sequences can be easily identified by sequencing, such libraries are a very good source of CpG islands. The methylation analysis of 28 different new probes allows to state that demethylation of CpG islands of the active X and methylation of those on the inactive X chromosome are the general rule. Moreover, the finding, in all instances, of methylation differences between male and female DNA is in very strong support of the notion that most genes of the distal long arm of the X chromosome are subject to X inactivation.     

Exploring genome-wide DNA methylation profiles altered in hepatocellular carcinoma using Infinium HumanMethylation 450 BeadChips

Hepatocellular carcinoma (HCC) incidence has increased in the US and also has one of the fastest growing death rates of any cancer. The purpose of the current study was to discover novel genome-wide aberrant DNA methylation patterns in HCC tumors that are predominantly HCV-related. Infinium HumanMethylation 450K BeadChip arrays were used to examine genome-wide DNA methylation profiles in 66 pairs of HCC tumor and adjacent non-tumor tissues. After Bonferroni adjustment, a total of 130,512 CpG sites significantly differed in methylation level in tumor compared with non-tumor tissues, with 28,017 CpG sites hypermethylated and 102,495 hypomethylated in tumor tissues. Absolute tumor/non-tumor methylation differences ≥ 20% were found in 24.9% of the hypermethylated and 43.1% of the hypomethylated CpG sites; almost 10,000 CpG sites have ≥ 30% DNA methylation differences. Most (60.1%) significantly hypermethylated CpG sites are located in CpG islands, with 21.6% in CpG shores and 3.6% in shelves. In contrast, only a small proportion (8.2%) of significantly hypomethylated CpG sites are situated in islands, while most are found in open sea (60.2%), shore (17.3%) or shelf (14.3%) regions. A total of 2,568 significant CpG sites (2,441 hypermethylated and 127 hypomethylated) covering 589 genes are located within 684 differentially methylated regions defined as regions with at least two significant CpG sites displaying > 20% methylation differences in the same direction within 250-bp. The top 500 significant CpG sites can significantly distinguish HCC tumor from adjacent tissues with one misclassification. Within adjacent non-tumor tissues, we also identified 75 CpG sites significantly associated with gender, 228 with HCV infection, 17,207 with cirrhosis, and 56 with both HCV infection and cirrhosis after multiple comparisons adjustment. Aberrant DNA methylation profiles across the genome were identified in tumor tissues from US HCC cases that are predominantly related to HCV infection. These results demonstrate the significance of aberrant DNA methylation in HCC tumorigenesis.