Factors to preserve CpG-rich sequences in methylated CpG islands

Background

Mammalian CpG islands (CGIs) normally escape DNA methylation in all adult tissues and developmental stages. However, in our previous study we unexpectedly identified many methylated CGIs in human peripheral blood leukocytes. Methylated CpG dinucleotides convert to TpG dinucleotides through deaminization of their cytosine bases more frequently than hypomethylated CpG dinucleotides. Therefore, we wondered how methylated CGIs in germline or non-germline cells maintain their CpG-rich sequences. It is known that events such as germline hypomethylation, CpG selection, biased gene conversion (BGC), and frequent CpG fixation can contribute to the maintenance of CpG-rich sequences in methylated CGIs in germline or non-germline cells. However, it has not been investigated which of the processes maintain CpG-rich sequences of methylated CGIs in each genomic position.

Results

In this study, we comprehensively examined the contribution of the processes described above to the maintenance of CpG-rich sequences in methylated CGIs in germline and non-germline cells which were classified by genomic positions. Approximately 60–80% of CGIs with high methylation in H1 cell line (H1-HM) in all the genomic positions showed a low average CpG → TpG/CpA substitution rate. In contrast, fewer than half the numbers of CGIs with H1-HM in all the genomic positions showed a low average CpG → TpG/CpA substitution rate and low levels of methylation in sperm cells (SPM-LM). Furthermore, a small fraction of CGIs with a low average CpG → TpG/CpA substitution rate and high levels of methylation in sperm cells (SPM-HM) showed CpG selection.On the other hand, independent of the positions in genes, most CGIs with SPM-HM showed a slightly higher average TpG/CpA → CpG substitution rate compared with those with SPM-LM.

Conclusions

Relatively high numbers (approximately 60–80%) of CGIs with H1-HM in all the genomic positions preserve their CpG-rich sequences by a low CpG → TpG/CpA substitution rate caused mainly by their SPM-LM, and for those with SPM-HM partly by CpG selection and TpG/CpA → CpG fixation. BGC has little contribution to the maintenance of CpG-rich sequences of CGIs with SPM-HM which were classified by genomic positions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1286-x) contains supplementary material, which is available to authorized users.     

High-resolution mapping of DNA methylation in human genome using oligonucleotide tiling array

DNA methylation is an epigenetic mark crucial in regulation of gene expression. Aberrant DNA methylation causes silencing of tumor suppressor genes and promotes chromosomal instability in human cancers. Most of previous studies for DNA methylation have focused on limited genomic regions, such as selected genes or promoter CpG islands (CGIs) containing recognition sites of methylation-sensitive restriction enzymes. Here, we describe a method for high-resolution analysis of DNA methylation using oligonucleotide tiling arrays. The input material is methylated DNA immunoprecipitated with anti-methylcytosine antibodies. We examined the ENCODE region (∼1% of human genome) in three human colorectal cancer cell lines and identified over 700 candidate methylated sites (CMS), where 24 of 25 CMS selected randomly were subsequently verified by bisulfite sequencing. CMS were enriched in the 5′ regulatory regions and the 3′ regions of genes. We also compared DNA methylation patterns with histone H3 and H4 acetylation patterns in the HOXA cluster region. Our analysis revealed no acetylated histones in the hypermethylated region, demonstrating reciprocal relationship between DNA methylation and histone H3 and H4 acetylation. Our method recognizes DNA methylation with little bias by genomic location and, therefore, is useful for comprehensive high-resolution analysis of DNA methylation providing new findings in the epigenomics. Electronic supplementary material Supplementary material is available in the online version of this article at and is accessible for authorized users.     

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.     

Isolation and enrichment of human genomic CpG islands by methylation-sensitive mirror orientation selection

CpG islands (CGIs) in human genomic DNA are GC-rich fragments whose aberrant methylation is associated with human disease development. In the current study, methylation-sensitive mirror orientation selection (MS-MOS) was developed to efficiently isolate and enrich unmethylated CGIs from human genomic DNA. The unmethylated CGIs prepared by the MS-MOS procedure subsequently were used to construct a CGI library. Then the sequence characteristics of cloned inserts of the library were analyzed by bioinformatics tools, and the methylation status of CGI clones was analyzed by HpaII PCR. The results showed that the MS-MOS method could be used to isolate up to 0.001% of differentially existed unmethylated DNA fragments in two complex genomic DNA. In the CGI library, 34.1% of clones had insert sequences satisfying the minimal criteria for CGIs. Excluding duplicates, 22.0% of the 80,000 clones were unique CGI clones, representing 60% of all the predicted CGIs (about 29,000) in human genomic DNA, and most or all of the CGI clones were unmethylated in human normal cell DNA based on the HpaII PCR analysis results of randomly selected CGI clones. In conclusion, MS-MOS was an efficient way to isolate and enrich human genomic CGIs. The method has powerful potential application in the comprehensive identification of aberrantly methylated CGIs associated with human tumorigenesis to improve understanding of the epigenetic mechanisms involved.     

CpG islands: Algorithms and applications in methylation studies

Methylation occurs frequently at 5’-cytosine of the CpG dinucleotides in vertebrate genomes; however, this epigenetic feature is rarely observed in CpG islands (CGIs) or CpG clusters in the promoter regions of genes. Aberrant methylation of the promoter-associated CGIs might influence gene expression and cause carcinogenesis. Because of the functional importance, multiple algorithms have been available for identifying CGIs in a genome or a sequence. They can be categorized into the traditional algorithms (e.g., Gardiner-Garden and Frommer (1987), Takai and Jones (2002), and CpGPRoD (2002)) or statistical property based algorithms (CpGcluster (2006) and CG cluster (2007)). We reviewed the features of these algorithms and evaluated their performance on identifying functional CGIs using genome-wide methylation data. Moreover, identification of CGIs is an initial step in many recent studies for predicting methylation status as well as in the design of methylation detection platforms. We reviewed the benchmarks and features used in these studies.     

CpG_MI: a novel approach for identifying functional CpG islands in mammalian genomes

CpG islands (CGIs) are CpG-rich regions compared to CpG-depleted bulk DNA of mammalian genomes and are generally regarded as the epigenetic regulatory regions in association with unmethylation, promoter activity and histone modifications. Accurate identification of CpG islands with epigenetic regulatory function in bulk genomes is of wide interest. Here, the common features of functional CGIs are identified using an average mutual information method to differentiate functional CGIs from the remaining CGIs. A new approach (CpG mutual information, CpG_MI) was further explored to identify functional CGIs based on the cumulative mutual information of physical distances between two neighboring CpGs. Compared to current approaches, CpG_MI achieved the highest prediction accuracy. This approach also identified new functional CGIs overlapping with gene promoter regions which were missed by other algorithms. Nearly all CGIs identified by CpG_MI overlapped with histone modification marks. CpG_MI could also be used to identify potential functional CGIs in other mammalian genomes, as the CpG dinucleotide contents and cumulative mutual information distributions are almost the same among six mammalian genomes in our analysis. It is a reliable quantitative tool for the identification of functional CGIs from bulk genomes and helps in understanding the relationships between genomic functional elements and epigenomic modifications.     

Unmethylated state of 5′ upstream CpG islands may be necessary but not sufficient for the testis-enriched expression of ZNF230/Znf230

The testis-enriched genes ZNF230/Znf230 are located on human chromosome 11p15/mouse chromosome 7 near conserved imprinting control regions. Typical CpG islands (CGIs) extend from the promoter to the first exon in each of these genes. To investigate the correlation between the methylation status of the above CGIs and the expression patterns of the two genes, we performed bisulfite genomic sequencing of genomic DNA from human and mouse tissues and cells. The results showed that the CGIs of ZNF230/Znf230 were completely unmethylated in all selected tissues and cells, regardless of the expression levels of the two genes. Further experiments using Znf230-second-exon-knockout mice to investigate the imprinting status of Znf230 showed that its expression was not affected by genomic imprinting. However, an in vitro methylation assay illustrated that the methylation of these CpG sites could repress the expression of the luciferase reporter gene. Furthermore, chromatin immunoprecipitation with anti-Specificity protein 1 (Sp1) antibody showed that Sp1 could bind to the CGIs in the ZNF230/Znf230 gene promoter. Thus, we propose that the unmethylated state of ZNF230/Znf230 CGIs may be a prerequisite for their expression but not sufficient for their abundant expression in the testis, and that Sp1 binding may be one factor involved in preserving the methylation-free state of ZNF230/Znf230 CGIs.     

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/.