CpG island mapping of a mouse double-minute chromosome.

The development of double-minute chromosomes (DMs) and subsequent gene amplification are important genomic alterations resulting in increased oncogene expression in a variety of tumors. The molecular mechanisms mediating the development of these acentric extrachromosomal elements have not been completely defined. To elucidate the mechanisms involved in DM formation, we have developed strategies to map amplified circular DM DNA. In this study, we present a long-range restriction map of a 980-kb DM. A cell line cloned from mouse EMT-6 cells was developed by stepwise selection for resistance to methotrexate. This cloned cell line contains multiple copies of the 980-kb DM carrying the dihydrofolate reductase (DHFR) gene. A long-range restriction map was developed in which a hypomethylated CpG-rich region near the DHFR gene served as a landmark. This strategy was combined with plasmid-like analysis of ethidium bromide-stained pulsed-field gels and indicated that a single copy of the DHFR gene was located near a hypomethylated region containing SsII and NotI sites. At least 490 kb of this DM appears to be composed of unrearranged chromosomal DNA.     

CpG island chromatin

The majority of mammalian gene promoters are encompassed within regions of the genome called CpG islands that have an elevated level of non-methylated CpG dinucleotides. Despite over 20 years of study, the precise mechanisms by which CpG islands contribute to regulatory element function remain poorly understood. Recently it has been demonstrated that specific histone modifying enzymes are recruited directly to CpG islands through recognition of non-methylated CpG dinucleotide sequence. These enzymes then impose unique chromatin architecture on CpG islands that distinguish them from the surrounding genome. In the context of this work we discuss how CpG island elements may contribute to the function of gene regulatory elements through the utilization of chromatin and epigenetic processes.     

DNA motifs associated with aberrant CpG island methylation

Epigenetic silencing involving the aberrant methylation of promoter region CpG islands is widely recognized as a tumor suppressor silencing mechanism in cancer. However, the molecular pathways underlying aberrant DNA methylation remain elusive. Recently we showed that, on a genome-wide level, CpG island loci differ in their intrinsic susceptibility to aberrant methylation and that this susceptibility can be predicted based on underlying sequence context. These data suggest that there are sequence/structural features that contribute to the protection from or susceptibility to aberrant methylation. Here we use motif elicitation coupled with classification techniques to identify DNA sequence motifs that selectively define methylation-prone or methylation-resistant CpG islands. Motifs common to 28 methylation-prone or 47 methylation-resistant CpG island-containing genomic fragments were determined using the MEME and MAST algorithms (). The five most discriminatory motifs derived from methylation-prone sequences were found to be associated with CpG islands in general and were nonrandomly distributed throughout the genome. In contrast, the eight most discriminatory motifs derived from the methylation-resistant CpG islands were randomly distributed throughout the genome. Interestingly, this latter group tended to associate with Alu and other repetitive sequences. Used together, the frequency of occurrence of these motifs successfully discriminated methylation-prone and methylation-resistant CpG island groups with an accuracy of 87% after 10-fold cross-validation. The motifs identified here are candidate methylation-targeting or methylation-protection DNA sequences.     

CpG island methylation in precursors of gastrointestinal malignancies

Gastrointestinal malignancies account for about 20% of all cancers worldwide. It is widely accepted that cancer evolves through several stepwise morphological stages such as the adenoma-carcinoma and hyperplastic polyp-serrated adenoma-carcinoma sequences in colorectal cancers, and the metaplasia-dysplasia-carcinoma sequences in esophageal and gastric cancers. The morphological progression is associated with the accumulation of multiple genetic and epigenetic events. It is now recognized that epigenetic silencing of gene expression by CpG island methylation is an important alternative mechanism of inactivating tumor suppressor genes. Inflammatory conditions of the gastrointestinal and pancreaticobiliary tracts and liver such as Barrett esophagus, Helicobacter pylori gastritis, inflammatory bowel disease and viral hepatitis, are associated with increased frequency of malignancies and CpG methylation. In addition, CpG methylation is present in aberrant crypt foci and pancreatic intraepithelial neoplasia that are considered putative precursors of colon and pancreatic carcinomas, respectively. Understanding of these early genetic and epigenetic changes allows for the discoveries of potential screening, monitoring and therapeutic strategies. Targeting of the epigenetic changes that occur before the development of frank malignancy offers a potential chemopreventive strategy.     

Tissue-specific methylation of a CpG island in transgenic mice.

Clustering of CpG dinucleotides in CpG-rich islands is a characteristic feature of mammalian genomes. Such CpG islands are frequently associated with genes and usually hypomethylated, regardless of the gene activity. This is the case for the CpG island of the murine Thy-1 gene. A transgenic line containing multiple copies of a truncated, concatemeric CpG island from the Thy-1.1 allele (Thy-1.2 background) showed that a stable fraction (approx. 0.20) became fully methylated in somatic tissues of homozygous mice with respect to testable restriction sites, while the remaining copies were methylation-free, i.e., this methylation appears to be an 'all-or-none' phenomenon. DNA from extraembryonic tissues (placenta and yolk sac) and epididymal sperm showed, however, an even higher degree of methylation in two distinct patterns. In the extraembryonic tissue, partial methylation of each copy was seen, whereas in sperm a high degree of 'all-or-none' methylation (greater than 0.35) was observed.     

Evaluation of single CpG sites as proxies of CpG island methylation states at the genome scale

Methylation of a CpG island is a faithful marker of silencing of its associated gene. Different approaches report the methylation status of a CpG island based on the determination of one or a few CpG sites by assuming the homogeneity of methylation along the element. This strategy is frequently applied in both locus-specific and genome-wide studies, but often without a validation of the representativeness of the interrogated CpG site compared with the whole element. We have evaluated the predictive informativeness of the HpaII sites located in CpG islands using data from high-resolution methylome maps, which offer the possibility to assess the methylation homogeneity of each CpG island and to determine the reporter accuracy of single sites as surrogate markers. An excellent correlation was observed between the HpaII and CpG island methylation levels (r > 0.93). At the qualitative level, the predictive sensitivity of HpaII was >95% with >92% specificity for methylated CpG islands and >90% sensitivity with >95% specificity for unmethylated CpG islands. This analysis provides a global validation framework for strategies based on the use of the methylation-sensitive HpaII restriction enzyme.     

Human epigenome data reveal increased CpG methylation in alternatively spliced sites and putative exonic splicing enhancers

The role of gene body methylation, which represents a major part of methylation in DNA, remains mostly unknown. Evidence based on the CpG distribution associates its presence with nucleosome positioning and alternative splicing. Recently, it was also shown that cytosine methylation influences splicing. However, to date, there is no methylation-based data on the association of methylation with alternative splicing and the distribution in exonic splicing enhancers (ESEs). We presently report that, based on the computational analysis of the Human Epigenome Project data, CpG hypermethylation (>80%) is frequent in alternatively spliced sites (particularly in noncanonical) but not in alternate promoters. The methylation frequency increases in sequences containing multiple putative ESEs. However, significant differences in the extent of methylation are observed among different ESEs. Specifically, moderate levels of methylation, ranging from 20% to 80%, are frequent in SRp55-binding elements, which are associated with response to extracellular conditions, but not in SF2/ASF, primarily responsible for alternative splicing, or in CpG islands. Finally, methylation is more frequent in the presence of AT repeats and CpGs separated by 10 nucleotides and lower in adjacent CpGs, probably indicating its dependence on helical formations and on the presence of nucleosome positioning-related sequences. In conclusion, our results show the regulation of methylation in ESEs and support its involvement in alternative splicing.     

Inter-individual variation of DNA methylation and its implications for large-scale epigenome mapping

Genomic DNA methylation profiles exhibit substantial variation within the human population, with important functional implications for gene regulation. So far little is known about the characteristics and determinants of DNA methylation variation among healthy individuals. We performed bioinformatic analysis of high-resolution methylation profiles from multiple individuals, uncovering complex patterns of inter-individual variation that are strongly correlated with the local DNA sequence. CpG-rich regions exhibit low and relatively similar levels of DNA methylation in all individuals, but the sequential order of the (few) methylated among the (many) unmethylated CpGs differs randomly across individuals. In contrast, CpG-poor regions exhibit substantially elevated levels of inter-individual variation, but also significant conservation of specific DNA methylation patterns between unrelated individuals. This observation has important implications for experimental analysis of DNA methylation, e.g. in the context of epigenome projects. First, DNA methylation mapping at single-CpG resolution is expected to uncover informative DNA methylation patterns for the CpG-poor bulk of the human genome. Second, for CpG-rich regions it will be sufficient to measure average methylation levels rather than assaying every single CpG. We substantiate these conclusions by an in silico benchmarking study of six widely used methods for DNA methylation mapping. Based on our findings, we propose a cost-optimized two-track strategy for mammalian methylome projects.     

Tissue of origin determines cancer-associated CpG island promoter hypermethylation patterns

Background

Aberrant CpG island promoter DNA hypermethylation is frequently observed in cancer and is believed to contribute to tumor progression by silencing the expression of tumor suppressor genes. Previously, we observed that promoter hypermethylation in breast cancer reflects cell lineage rather than tumor progression and occurs at genes that are already repressed in a lineage-specific manner. To investigate the generality of our observation we analyzed the methylation profiles of 1,154 cancers from 7 different tissue types.

Results

We find that 1,009 genes are prone to hypermethylation in these 7 types of cancer. Nearly half of these genes varied in their susceptibility to hypermethylation between different cancer types. We show that the expression status of hypermethylation prone genes in the originator tissue determines their propensity to become hypermethylated in cancer; specifically, genes that are normally repressed in a tissue are prone to hypermethylation in cancers derived from that tissue. We also show that the promoter regions of hypermethylation-prone genes are depleted of repetitive elements and that DNA sequence around the same promoters is evolutionarily conserved. We propose that these two characteristics reflect tissue-specific gene promoter architecture regulating the expression of these hypermethylation prone genes in normal tissues.

Conclusions

As aberrantly hypermethylated genes are already repressed in pre-cancerous tissue, we suggest that their hypermethylation does not directly contribute to cancer development via silencing. Instead aberrant hypermethylation reflects developmental history and the perturbation of epigenetic mechanisms maintaining these repressed promoters in a hypomethylated state in normal cells.     

PIPS: pathogenicity island prediction software

The adaptability of pathogenic bacteria to hosts is influenced by the genomic plasticity of the bacteria, which can be increased by such mechanisms as horizontal gene transfer. Pathogenicity islands play a major role in this type of gene transfer because they are large, horizontally acquired regions that harbor clusters of virulence genes that mediate the adhesion, colonization, invasion, immune system evasion, and toxigenic properties of the acceptor organism. Currently, pathogenicity islands are mainly identified in silico based on various characteristic features: (1) deviations in codon usage, G+C content or dinucleotide frequency and (2) insertion sequences and/or tRNA genetic flanking regions together with transposase coding genes. Several computational techniques for identifying pathogenicity islands exist. However, most of these techniques are only directed at the detection of horizontally transferred genes and/or the absence of certain genomic regions of the pathogenic bacterium in closely related non-pathogenic species. Here, we present a novel software suite designed for the prediction of pathogenicity islands (pathogenicity island prediction software, or PIPS). In contrast to other existing tools, our approach is capable of utilizing multiple features for pathogenicity island detection in an integrative manner. We show that PIPS provides better accuracy than other available software packages. As an example, we used PIPS to study the veterinary pathogen Corynebacterium pseudotuberculosis, in which we identified seven putative pathogenicity islands.     

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/.