DNA Methylation: Site-Specific Methylations Cause Gene Inactivation

In the molecular biology of eukaryotic organisms, the elucidation of mechanisms involved in the regulation of gene expression has assumed an important role. All cells of an organism carry the same genes, but differ in the patterns of genes they express. There is an increasing amount of evidence that cancer cells exhibit a pattern of gene expression which can be very different from that of normal cells. One of the molecular signals that has been recognized in the regulation of gene expression in eukaryotes is the modified nucleotide 5-methylcytosine (5-mC). Through experiments in well-characterized eukaryotic systems, evidence has been adduced that the introduction of 5-mC into highly specific sequences, particularly into the 5′ and promoter regions of a gene, can cause gene inactivation. Viral and other eukaryotic systems have helped in the recognition of this cause-and-effect relationship. Inactive genes are frequently hypermethylated in the promoter region; active genes are hypomethylated. However, these correlations are not always as simple and straightforward. The biochemical mechanisms by which site-specific DNA methylations cause gene inactivation have not yet been determined. It is plausible to postulate that promoter methylations could somehow affect the binding of cellular enzymes involved in recognizing the promoter of a gene. Structural alterations of DNA promoter sequences arising from DNA methylations could also be important. DNA methylation is likely to represent a long-term inactivation signal, since it is presently thought that patterns of DNA methylation can be changed only by DNA replication and specific inhibition of post-replicative maintenance methylation.     

Determining the global DNA methylation status of rat according to the identifier repetitive elements

A large portion of the genome represents repetitive elements. Identifier (ID) elements, the major elements of short interspersed repetitive elements, are widespread with about 150 000 copies in the rat genome. Each ID element contains six CpG dinucleotides, which might account for the global methylation status of rat. We validated the CpG methylation of the ID elements by various methods. The methylation of one CpG site (CpG-3) of the ID element was investigated by performing pyrosequencing. The methylation percentage of the CpG-3 site was 53.6% (SD = 2.2) on average from six rat tissues with blood, but 24.6% (SD = 1.0) in rat pheochromocytoma, PC-12, cell line. This CpG-3 methylation was further verified by whole genome amplification (WGA), 5-azacytidine treatment, and proportional mixing of rat WGA genomic DNA (gDNA) with liver gDNA. Methylation-sensitive restriction enzyme PCR method showed that three other CpG sites (CpG-1, CpG-4, and CpG-5) within the ID element were also methylated (about 60%) in rat gDNA, but not in WGA gDNA. The ID elements may be good candidates for routine analysis of the global DNA methylation changes of rat for pharmaceutical treatment and their use can make basic epigenetic research possible with high accuracy.     

面向DNA甲基化修饰分析的质谱技术

DNA甲基化作为表观遗传修饰中一种重要的调控方式,通过调控基因的表达,从而影响机体内一系列的生物学过程。色谱-质谱法是研究DNA甲基化修饰的重要研究手段。随着对哺乳动物DNA甲基化的生物学功能的深入研究,应用于研究表观遗传修饰的手段与仪器设备越来越先进。为了对DNA修饰进行定性与定量的分析检测,除了高效液相色谱整合不同种类质量分析器的质谱联用（HPLC-MS）技术外,目前还开发应用了基质辅助激光解析质谱技术（MALDI-ToF-MS）和气相色谱-质谱联用技术（GC-MS）,从而极大拓展了DNA甲基化修饰研究的手段。本文对分析表观遗传DNA甲基化修饰的质谱技术发展进行综述,希望为DNA甲基化修饰分析提供有价值的研究策略。     

Restriction landmark genome scanning method using isoschizomers (MspI/HpaII) for DNA methylation analysis

Restriction landmark genome scanning (RLGS) is a 2-DE of genomic DNA, which visualizes thousands of loci. In a conventional RLGS method for methylation analysis, we have used a methylation sensitive restriction enzyme, NotI as a landmark. However, it was unable to discriminate methylation polymorphism from sequence polymorphism. Here, we report an improved RLGS method to detect methylated sites directly. We employed isoschizomers, MspI and HpaII, that recognize the same sequence (CCGG) but have different methylation sensitivity. We carried out the RLGS analysis of Arabidopsis thaliana ecotype Columbia, and obtained a pair of spot patterns with MspI and HpaII. We detected 22 spots in both patterns. In comparison of them, 18% of the spots were polymorphic, which indicated the methylation of C(5m)CGG sites. Further analyses revealed an additional methylated site of NotI. Moreover, 52 and 54 restriction enzyme sites were also analyzed in two other ecotypes, Wassilewskija and Landsberg erecta, respectively. Consequently, 15% of the 52 common sites showed methylation polymorphism among the three ecotypes. The restriction sites analyzed in this study were located in or near genes, and contribute new data about the correlation between methylation status and gene expression. Therefore, this result strongly indicates that the improved RLGS method is readily applicable to practical analyses of methylation dynamics, and provides clues to the relationship between methylation and gene expression.     

Label‐Free Quantification of 5‐Azacytidines Directly in the Genome

Azacytidines (AzaC and AzadC) are clinically relevant pharmaceuticals that operate at the epigenetic level. They are integrated into the genome as antimetabolites to block DNA methylation events. This leads to a reduction of the 5‐methyl‐2′‐deoxycytidine (m⁵dC) level in the genome, which can activate epigenetically silenced genes. Because of the inherent chemical instability of Aza(d)Cs, their incorporation levels in DNA and RNA are difficult to determine, which hinders correlation of therapeutic effects with incorporation and removal processes. Existing methods involve radioactive labeling and are therefore unsuitable to monitor levels from patients. We report here a new direct chemical method that allows absolute quantification of the levels of incorporated AzaC and AzadC in both RNA and DNA. Furthermore, it clarifies that Aza(d)C accumulates to high levels (up to 12.9 million bases per genome). Although RNA‐based antimetabolites are often 2′‐deoxygenated in vivo and incorporated into DNA, for AzaC we see only limited incorporation into DNA. It accumulates predominantly in RNA where it, however, only leads to insignificant demethylation.     

Identification of methylated regions with peak search based on Poisson model from massively parallel methylated DNA immunoprecipitation-sequencing data

DNA methylation is one of the most important epigenetic modification types, which plays a critical role in gene expression. High efficient surveying of whole genome DNA methylation has been aims of many researchers for long. Recently, the rapidly developed massively parallel DNA‐sequencing technologies open the floodgates to vast volumes of sequence data, enabling a paradigm shift in profiling the whole genome methylation. Here, we describe a strategy, combining methylated DNA immunoprecipitation sequencing with peak search to identify methylated regions on a whole‐genome scale. Massively parallel methylated DNA immunoprecipitation sequencing combined with methylation DNA immunoprecipitation was adopted to obtain methylated DNA sequence data from human leukemia cell line K562, and the methylated regions were identified by peak search based on Poison model. From our result, 140 958 non‐overlapping methylated regions have been identified in the whole genome. Also, the credibility of result has been proved by its strong correlation with bisulfite‐sequencing data (Pearson R²=0.92). It suggests that this method provides a reliable and high‐throughput strategy for whole genome methylation identification.     

Predicting methylation status of human DNA sequences by pseudo-trinucleotide composition

DNA methylation plays a key role in the regulation of gene expression. The most common type of DNA modification consists of the methylation of cytosine in the CpG dinucleotide. The detections of DNA methylation have been determined mostly by experimental methods; however, these methods were time-consuming, expensive, and difficult to meet the requirements of modern large-scale sequencing technology. Accordingly, it is necessary to develop automatic and reliable prediction methods for DNA methylation.In this study, the pseudo-trinucleotide composition was proposed, and a novel method was developed by support vector machine (SVM) with the pseudo-trinucleotide composition as input parameter to represent DNA sequence for DNA methylation prediction. The model was evaluated on two datasets, including a dataset of Rollins (dataset_1) and a dataset collected healthy human records from the MethDB database (dataset_2). For dataset_1, the Matthews correlation coefficient (MCC) and accuracy (ACC) by jackknife validation were 0.8051 and 0.6098, respectively. For dataset_2, the MCC and ACC were 0.8500 and 0.7203, respectively. The good prediction results reveal that the pseudo-trinucleotide composition is an effective representation method for DNA sequence and plays a very important role in the prediction of DNA function.     

Genetic analyzer-dependent DNA methylation detection and its application to existing age prediction models

DNA methylation is the most promising biomarker for estimating human age. There are various methods used for analyzing DNA methylation. Among those, the SNaPshot assay-based method provides a semi-quantitative measurement of DNA methylation using capillary electrophoresis on genetic analyzers. However, DNA methylation measures produced using different types of genetic analyzers have never been compared, although differences in methylation values can directly affect age estimates. To evaluate the differences between the results generated by different genetic analyzers, we analyzed the same blood, saliva, and control methylated DNA using three genetic analyzers—the Applied Biosystems 3130, 3500, and SeqStudio—and compared the methylation values at five CpG sites: ELOVL2, FHL2, KLF14, MIR29B2C, and TRIM59. The methylation value at each of the five CpG sites decreased in the order 3130, 3500, and SeqStudio. The differences in the results produced by the different genetic analyzers resulted in significant errors when applying the 3500 and SeqStudio data to a previous age estimation model constructed using the 3130 Genetic Analyzer data. Therefore, DNA methylation measurements from 3500 and SeqStudio were corrected using the regression functions obtained by plotting the DNA methylation data of one instrument versus the other to facilitate the application of DNA methylation data from one instrument to the age prediction model based on other instruments. The age prediction accuracy obtained by applying corrected 3500 and SeqStudio data to the existing age estimation model was as high as observed in the 3130 data.     

Direct Sensing of 5‐Methylcytosine by Polymerase Chain Reaction

The epigenetic control of genes by the methylation of cytosine resulting in 5‐methylcytosine (5mC) has fundamental implications for human development and disease. Analysis of alterations in DNA methylation patterns is an emerging tool for cancer diagnostics and prognostics. Here we report that two thermostable DNA polymerases, namely the DNA polymerase KlenTaq derived from Thermus aquaticus and the KOD DNA polymerase from Thermococcus kodakaraensis, are able to extend 3′‐mismatched primer strands more efficiently from 5 mC than from unmethylated C. This feature was advanced by generating a DNA polymerase mutant with further improved 5mC/C discrimination properties and its successful application in a novel methylation‐specific PCR approach directly from untreated human genomic DNA.     

Discovering DNA methylation patterns for long non-coding RNAs associated with cancer subtypes

Despite growing evidence demonstrates that the long non-coding ribonucleic acids (lncRNAs) are critical modulators for cancers, the knowledge about the DNA methylation patterns of lncRNAs is quite limited. We develop a systematic analysis pipeline to discover DNA methylation patterns for lncRNAs across multiple cancer subtypes from probe, gene and network levels. By using The Cancer Genome Atlas (TCGA) breast cancer methylation data, the pipeline discovers various DNA methylation patterns for lncRNAs across four major subtypes such as luminal A, luminal B, her2-enriched as well as basal-like. On the probe and gene level, we find that both differentially methylated probes and lncRNAs are subtype specific, while the lncRNAs are not as specific as probes. On the network level, the pipeline constructs differential co-methylation lncRNA network for each subtype. Then, it identifies both subtype specific and common lncRNA modules by simultaneously analyzing multiple networks. We show that the lncRNAs in subtype specific and common modules differ greatly in terms of topological structure, sequence conservation as well as expression. Furthermore, the subtype specific lncRNA modules serve as biomarkers to improve significantly the accuracy of breast cancer subtypes prediction. Finally, the common lncRNA modules associate with survival time of patients, which is critical for cancer therapy.     

Quantitative Detection of Gene Methylated Level of Stool Samples Based on Invader Assay Coupled with Real-time Polymerase Chain Reaction and Its Application in Non-invasive Screening of Colorectal Cancer

Methylation of bone morphogenetic protein 3 (BMP3) in stool DNA is an effective biomarker for non-invasive screening of colorectal cancer. However, a highly sensitive and specific detection method is required. Here, a quantification method for BMP3 methylation was developed by combining real-time polymerase chain reaction (PCR) with invader assay using Beta-actin (ACTB) as a reference. Amplification efficiencies of BMP3 and ACTB were close to 100% after optimizing the concentration of detection probes, FEN1 enzyme and Taq polymerase, and the relative quantification of BMP3 methylation was achieved accurately by ΔCT algorithms. Ten copies and 0.01% of BMP3 methylation level could be successfully detected and non-specific signal was generated from non-methylated template, indicating that the method was highly sensitive and specific. The method was successfully applied to detect BMP3 methylation in fecal DNA from 16 colorectal cancer patients, 7 adenoma patients and 19 healthy volunteers. The results indicated that BMP3 methylation occurred in 5 of 16 cancer patients and 2 of 7 adenoma patients, but was not observed in 19 of healthy volunteers. Therefore, this method could be used to quantify methylation of gene in stool samples, providing an effective technique for non-invasive screening of colorectal cancer.     

Quantitative analysis of DNA methylation in the promoter region of the methylguanine‐O6‐DNA‐methyltransferase gene by COBRA and subsequent native capillary gel electrophoresis

Along with histone modifications, RNA interference and delayed replication timing, DNA methylation belongs to the key processes in epigenetic regulation of gene expression. Therefore, reliable information about the methylation level of particular DNA fragments is of major interest. Herein the methylation level at two positions of the promoter region of the gene methylguanine‐O⁶‐DNA‐Methyltransferase (MGMT) was investigated. Previously, it was demonstrated that the epigenetic status of this DNA region correlates with response to alkylating anticancer agents. An automated CGE method with LIF detection was established to separate the six DNA fragments resulting from combined bisulfite restriction analysis of the methylated and non‐methylated MGMT promoter. In COBRA, the DNA was treated with bisulfite converting cytosine into uracil. During PCR uracil pairs with adenine, which changes the original recognition site of the restriction enzyme Taql. Artificial probes generated by mixing appropriate amounts of DNA after bisulfite treatment and PCR amplification were used for validation of the method. The methylation levels of these samples could be determined with high accuracy and precision. DNA samples prepared by mixing the corresponding clones first and then performing PCR amplification led to non‐linear correlation between the corrected peak areas and the methylation levels. This effect is explained by slightly different PCR amplification of DNA with different sequences present in the mixture. The superiority of CGE over PAGE was clearly demonstrated. Finally, the established method was used to analyze the methylation levels of human brain tumor tissue samples.     

Genome-scale DNA methylation pattern profiling of human bone marrow mesenchymal stem cells in long-term culture

Human bone marrow mesenchymal stem cells (MSCs) expanded in vitro exhibit not only a tendency to lose their proliferative potential, homing ability and telomere length but also genetic or epigenetic modifications, resulting in senescence. We compared differential methylation patterns of genes and miRNAs between early-passage [passage 5 (P5)] and late-passage (P15) cells and estimated the relationship between senescence and DNA methylation patterns. When we examined hypermethylated genes (methylation peak ≥ 2) at P5 or P15, 2,739 genes, including those related to fructose and mannose metabolism and calcium signaling pathways, and 2,587 genes, including those related to DNA replication, cell cycle and the PPAR signaling pathway, were hypermethylated at P5 and P15, respectively. There was common hypermethylation of 1,205 genes at both P5 and P15. In addition, genes that were hypermethylated at P5 (CPEB1, GMPPA, CDKN1A, TBX2, SMAD9 and MCM2) showed lower mRNA expression than did those hypermethylated at P15, whereas genes that were hypermethylated at P15 (MAML2, FEN1 and CDK4) showed lower mRNA expression than did those that were hypermethylated at P5, demonstrating that hypermethylation at DNA promoter regions inhibited gene expression and that hypomethylation increased gene expression. In the case of hypermethylation on miRNA, 27 miRNAs were hypermethylated at P5, whereas 44 miRNAs were hypermethylated at P15. These results show that hypermethylation increases at genes related to DNA replication, cell cycle and adipogenic differentiation due to long-term culture, which may in part affect MSC senescence.     

Global DNA Methylation Level Monitoring by methyl-CpG Binding Domain-Fused Luciferase

DNA methylation is an epigenetic modification that represses gene expression. In cancer cells, alterations of the DNA methylation state in promoter regions and repetitive DNA sequences are observed; therefore, DNA methyltransferase inhibitors have been the focus of interest as potential anticancer drugs. We previously reported a simple global DNA methylation level-sensing assay using methyl-CpG binding domain (MBD) fused to luciferase (MBD-luciferase). In the assay, the MBD-luciferase binds to methyl-CpG sites on genomic DNA. Subsequently, bioluminescence resonance energy transfer (BRET) between the luciferase and a fluorescent DNA intercalating dye generates a signal that is dependent on DNA methylation level. In this study, we investigated whether global DNA hypomethylation induced by a DNA methyltransferase inhibitor or nutrient can be monitored by the BRET assay. 5-Aza-2′-deoxycytidine and folic acid were utilized as the DNA-methyltransferase inhibitor and nutrient that affect DNA methylation in cells. The HeLa cells were cultured with the inhibitor or in folic acid-deficient medium and their global DNA methylation levels measured. Both time- and concentration-dependent hypomethylation were detected by the BRET assay. These results demonstrate that global DNA hypomethylation can be monitored by the BRET assay, indicating that the assay is applicable to cell-based screening of DNA-methyltransferase inhibitors.     

DNA methylation-regulated microRNA pathways in ovarian serous cystadenocarcinoma: A meta-analysis

Epigenetic regulation has been linked to the initiation and progression of cancer. Aberrant expression of microRNAs (miRNAs) is one such mechanism that can activate or silence oncogenes (OCGs) and tumor suppressor genes (TSGs) in cells. A growing number of studies suggest that miRNA expression can be regulated by methylation modification, thus triggering cancer development. However, there is no comprehensive in silico study concerning miRNA regulation by direct DNA methylation in cancer. Ovarian serous cystadenocarcinoma (OSC) was therefore chosen as a tumor model for the present work.Twelve batches of OSC data, with at least 35 patient samples in each batch, were obtained from The Cancer Genome Atlas (TCGA) database. The Spearman rank correlation coefficient (SRCC) was used to quantify the correlation between the CpG DNA methylation level and miRNA expression level. Meta-analysis was performed to reduce the effects of biological heterogeneity among different batches. MiRNA-target interactions were also inferred by computing SRCC and meta-analysis to assess the correlation between miRNA expression and cancer-associated gene expression and the interactions were further validated by a query against the miRTarBase database.A total of 26 potential epigenetic-regulated miRNA genes that can target OCGs or TSGs in OSC were found to show biological relevance between DNA methylation and miRNA gene expression. Furthermore, some of the identified DNA-methylated miRNA genes; for instance, the miR-200 family, were previously identified as epigenetic-regulated miRNAs and correlated with poor survival of ovarian cancer. We also found that several miRNA target genes, BTG3, NDN, HTRA3, CDC25A, and HMGA2 were also related to the poor outcomes in ovarian cancer.The present study proposed a systematic strategy to construct highly confident epigenetic-regulated miRNA pathways for OSC. The findings are validated and are in line with the literature. The inclusion of direct DNA methylated miRNA events may offer another layer of explanation that along with genetics can give a better understanding of the carcinogenesis process.     

Genomic Imprinting—The Struggle of the Genders at the Molecular Level

Genomic imprinting, the parent of origin‐dependent expression of genes, has been discovered as a fascinating example of the control of gene expression by epigenetic processes in the human body. It affects about 100 genes, which are often involved in growth and development. In this Review, we discuss the mechanisms leading to the generation of gender‐specific imprints in form of DNA methylation marks, their preservation during growth and development of the organism, and the processes that translate parental methylation marks into monoallelic gene expression. We discuss the gender‐specific dimorphic nature of imprints from an evolutionary point of view and present the prevalent model that molecular imprinting mediates a conflict of interest between the parents that occurs in viviparous animals. Finally, we summarize the relevance of parental imprinting for human health.     

Mechanistic study on DNA mutation of the cytosine methylation reaction at C5 position

DNA methylation is a crucial epigenetic mark connected to conventionally changing the DNA bases, typically by adding methyl groups into DNA bases. Methylation of cytosine at the C5 position (5-methylcytosine) occurs mostly in the context of cytosine-phosphate-guanine dinucleotides, the methylation of which has important impacts on gene regulation and expression. However, the mechanistic details of this reaction are still debatable concerning the concertedness of the key reaction steps and the roles played by the base that abstracts the proton in the β-elimination and water molecules at the active site. To gain a deeper insight into the formation of 5-mehtylcytosine, an extensive density functional theory (DFT) study was performed with the B3LYP functional in conjunction with different basis sets. Our study has clearly established the mechanistic details of this methylation approach, based on which the roles of conserved active site residues, such as glutamic acid and waters, are well understood. Our results show that the reaction of 5-methylcytosine follows a concerted mechanism in which water molecules are critically involved. Moreover, arginine and alanine give more significant catalytic effects than glutamic acid on the 5-methylcytosine process. Considering the effect of Alanine, Arginine, and one water bridging molecule, the activation energy is 31 kJ mol^?1 calculated at B3LYP/6-31G(d) level of theory.