Simple screening method for differentially methylated regions of the genome using a small number of cells

Genomic DNA methylation is a major epigenetic mechanism controlling the expression of genetic information. Therefore, identifying regions of the genome that are differentially methylated in different cells is a useful strategy for the study of biological phenomena. To date, several useful screening methods have been established for identifying differentially methylated genomic regions. However, it is impossible to use these methods in fields of study in which it is difficult to obtain a large number of uniform cells, because considerable amounts of genomic DNA are required. Given this situation, we developed a method for preparing large genomic DNA from a small number of cells, and a simple and highly sensitive method for screening for differentially methylated sites. Combined, these two methods comprise a simple screening method, which we named "Differential Methylation Site Scanning" (DMSS), for identifying differentially methylated regions of the genome from a small number of cells. Just 10 cells are sufficient for the method described here.     

Identification of differentially methylated sites within unmethylated DNA domains in normal and cancer cells

Altered DNA methylation has been linked to neoplastic cell transformation and is a hallmark of cancer progression. Therefore, the screening for differentially methylated sequences as tumor biomarkers has a significant implication in the clinical setting. To determine the cancer-linked alterations in DNA methylation pattern, we have applied an endonuclease, McrBC, to the existing methylation-sensitive arbitrarily primed polymerase chain reaction (msAP-PCR) method and developed McrBC-msAP-PCR. This modified approach allows detection of differentially methylated sites within unmethylated DNA domains enriched by regulatory sequences and CpG islands. In this method, we used digestion of DNA with the McrBC methylation-sensitive endonuclease to selectively exclude the methylated fraction of DNA, which comprises interspersed and tandem-repeated sequences and exons other than first exons, from analysis. The subsequent digestion of unmethylated DNA fragments with SmaI and HpaII methylation-sensitive restriction endonucleases followed by AP-PCR amplification resulted in the detection of unknown unique sequences associated with cancer-linked methylation changes in genomic DNA. Hypermethylation and hypomethylation are visualized by the increase or decrease in the band intensity of DNA fingerprints. By using this technique, we were able to differentiate clearly, identify, and characterize a number of novel unique DNA sequences with differentially methylated sites in normal and breast cancer cell lines and in normal and rat tumor liver tissues.     

Methylated site display (MSD)-AFLP,a sensitive and affordable method for analysis of CpG methylation profiles

Background

It has been pointed out that environmental factors or chemicals can cause diseases that are developmental in origin. To detect abnormal epigenetic alterations in DNA methylation, convenient and cost-effective methods are required for such research, in which multiple samples are processed simultaneously. We here present methylated site display (MSD), a unique technique for the preparation of DNA libraries. By combining it with amplified fragment length polymorphism (AFLP) analysis, we developed a new method, MSD-AFLP.

Results

Methylated site display libraries consist of only DNAs derived from DNA fragments that are CpG methylated at the 5′ end in the original genomic DNA sample. To test the effectiveness of this method, CpG methylation levels in liver, kidney, and hippocampal tissues of mice were compared to examine if MSD-AFLP can detect subtle differences in the levels of tissue-specific differentially methylated CpGs. As a result, many CpG sites suspected to be tissue-specific differentially methylated were detected. Nucleotide sequences adjacent to these methyl-CpG sites were identified and we determined the methylation level by methylation-sensitive restriction endonuclease (MSRE)-PCR analysis to confirm the accuracy of AFLP analysis. The differences of the methylation level among tissues were almost identical among these methods. By MSD-AFLP analysis, we detected many CpGs showing less than 5% statistically significant tissue-specific difference and less than 10% degree of variability. Additionally, MSD-AFLP analysis could be used to identify CpG methylation sites in other organisms including humans.

Conclusion

MSD-AFLP analysis can potentially be used to measure slight changes in CpG methylation level. Regarding the remarkable precision, sensitivity, and throughput of MSD-AFLP analysis studies, this method will be advantageous in a variety of epigenetics-based research.

     

Identification of New Differentially Methylated Genes That Have Potential Functional Consequences in Prostate Cancer

Many differentially methylated genes have been identified in prostate cancer (PCa), primarily using candidate gene-based assays. Recently, several global DNA methylation profiles have been reported in PCa, however, each of these has weaknesses in terms of ability to observe global DNA methylation alterations in PCa. We hypothesize that there remains unidentified aberrant DNA methylation in PCa, which may be identified using higher resolution assay methods. We used the newly developed Illumina HumanMethylation450 BeadChip in PCa (n = 19) and adjacent normal tissues (n = 4) and combined these with gene expression data for identifying new DNA methylation that may have functional consequences in PCa development and progression. We also confirmed our methylation results in an independent data set. Two aberrant DNA methylation genes were validated among an additional 56 PCa samples and 55 adjacent normal tissues. A total 28,735 CpG sites showed significant differences in DNA methylation (FDR adjusted P<0.05), defined as a mean methylation difference of at least 20% between PCa and normal samples. Furthermore, a total of 122 genes had more than one differentially methylated CpG site in their promoter region and a gene expression pattern that was inverse to the direction of change in DNA methylation (e.g. decreased expression with increased methylation, and vice-versa). Aberrant DNA methylation of two genes, AOX1 and SPON2, were confirmed via bisulfate sequencing, with most of the respective CpG sites showing significant differences between tumor samples and normal tissues. The AOX1 promoter region showed hypermethylation in 92.6% of 54 tested PCa samples in contrast to only three out of 53 tested normal tissues. This study used a new BeadChip combined with gene expression data in PCa to identify novel differentially methylated CpG sites located within genes. The newly identified differentially methylated genes may be used as biomarkers for PCa diagnosis.     

A Bayesian hierarchical model to detect differentially methylated loci from single nucleotide resolution sequencing data

DNA methylation is an important epigenetic modification that has essential roles in cellular processes including gene regulation, development and disease and is widely dysregulated in most types of cancer. Recent advances in sequencing technology have enabled the measurement of DNA methylation at single nucleotide resolution through methods such as whole-genome bisulfite sequencing and reduced representation bisulfite sequencing. In DNA methylation studies, a key task is to identify differences under distinct biological contexts, for example, between tumor and normal tissue. A challenge in sequencing studies is that the number of biological replicates is often limited by the costs of sequencing. The small number of replicates leads to unstable variance estimation, which can reduce accuracy to detect differentially methylated loci (DML). Here we propose a novel statistical method to detect DML when comparing two treatment groups. The sequencing counts are described by a lognormal-beta-binomial hierarchical model, which provides a basis for information sharing across different CpG sites. A Wald test is developed for hypothesis testing at each CpG site. Simulation results show that the proposed method yields improved DML detection compared to existing methods, particularly when the number of replicates is low. The proposed method is implemented in the Bioconductor package DSS.     

High-throughput assessment of CpG site methylation for distinguishing between HCV-cirrhosis and HCV-associated hepatocellular carcinoma

Methylation of promoter CpG islands has been associated with gene silencing and demonstrated to lead to chromosomal instability. Therefore, some postulate that aberrantly methylated CpG regions may be important biomarkers indicative of cancer development. In this study we used the Illumina GoldenGate Methylation BeadArray Cancer Panel I for simultaneously profiling methylation of 1,505 CpG sites in order to identify methylation differences in 76 liver tissues ranging from normal to pre-neoplastic and neoplastic states. CpG sites for ESR1, GSTM2, and MME were significantly differentially methylated when comparing the pre-neoplastic tissues from patients with concomitant hepatocellular carcinoma (HCC) to the pre-neoplastic tissues from patients without HCC. When comparing paired HCC tissues to their corresponding pre-neoplastic non-tumorous tissues, eight CpG sites, including one CpG site that was hypermethylated (APC) and seven (NOTCH4, EMR3, HDAC9, DCL1, HLA-DOA, HLA-DPA1, and ERN1) that were hypomethylated in HCC, were identified. Our study demonstrates that high-throughput methylation technologies may be used to identify differentially methylated CpG sites that may prove to be important molecular events involved in carcinogenesis.     

Identification of a DNA methylome signature of esophageal squamous cell carcinoma and potential epigenetic biomarkers

Esophageal squamous cell carcinoma (ESCC) is believed to arise from esophageal mucosa through accumulation of both genetic and epigenetic changes. DNA methylation is a critical epigenetic mechanism involved in key cellular processes and its deregulation has been linked to many human cancers, including ESCC. The aim of this study is to examine the global deregulation of methylation states in ESCC and identify potential early biomarkers. With this purpose, we performed a bead array analysis of more than 800 cancer-related genes in ten ESCC samples, ten matched surrounding tissues and four esophageal mucosa from healthy individuals. Pyrosequencing was used for validation of DNA methylation changes in up to 106 cases and 27 controls. A total of 37 CpG sites were found to be differentially methylated between tumors and surrounding tissues. These CpG sites were significantly enriched in genes related to several pathways including IL-10 anti-inflammatory signaling pathway and cell communication pathway. In addition, by comparing with healthy esophageal mucosa, we identified TFF1 gene as a potential early marker of ESCC. This is the first study to address methylation changes in ESCC in a large set of genes. Methylome analysis is shown as a sensitive and powerful tool to identify molecular players in ESCC. These data should prove to be the reference for future studies identifying potential biomarkers and molecular targets in ESCC.     

Identification of a DNA methylome signature of esophageal squamous cell carcinoma and potential epigenetic biomarkers

Esophageal squamous cell carcinoma (ESCC) is believed to arise from esophageal mucosa through accumulation of both genetic and epigenetic changes. DNA methylation is a critical epigenetic mechanism involved in key cellular processes and its deregulation has been linked to many human cancers, including ESCC. The aim of this study is to examine the global deregulation of methylation states in ESCC and identify potential early biomarkers. With this purpose, we performed a bead array analysis of more than 800 cancer-related genes in ten ESCC samples, ten matched surrounding tissues and four esophageal mucosa from healthy individuals. Pyrosequencing was used for validation of DNA methylation changes in up to 106 cases and 27 controls. A total of 37 CpG sites were found to be differentially methylated between tumors and surrounding tissues. These CpG sites were significantly enriched in genes related to several pathways including IL-10 anti-inflammatory signaling pathway and cell communication pathway. In addition, by comparing with healthy esophageal mucosa, we identified TFF1 gene as a potential early marker of ESCC. This is the first study to address methylation changes in ESCC in a large set of genes. Methylome analysis is shown as a sensitive and powerful tool to identify molecular players in ESCC. These data should prove to be the reference for future studies identifying potential biomarkers and molecular targets in ESCC.     

Systematic Proteomic Analysis of Protein Methylation in Prokaryotes and Eukaryotes Revealed Distinct Substrate Specificity

The studies of protein methylation mainly focus on lysine and arginine residues due to their diverse roles in essential cellular processes from gene expression to signal transduction. Nevertheless, atypical protein methylation occurring on amino acid residues, such as glutamine and glutamic acid, is largely neglected until recently. In addition, the systematic analysis for the distribution of methylation on different amino acids in various species is still lacking, which hinders our understanding of its functional roles. In this study, we deeply explored the methylated sites in three species Escherichia coli, Saccharomyces cerevisiae, and HeLa cells by employing MS‐based proteomic approach coupled with heavy methyl SILAC method. We identify a total of 234 methylated sites on 187 proteins with high localization confidence, including 94 unreported methylated sites on nine different amino acid residues. KEGG and gene ontology analysis show the pathways enriched with methylated proteins are mainly involved in central metabolism for E. coli and S. cerevisiae, but related to spliceosome for HeLa cells. The analysis of methylation preference on different amino acids is conducted in three species. Protein N‐terminal methylation is dominant in E. coli while methylated lysines and arginines are widely identified in S. cerevisiae and HeLa cells, respectively. To study whether some atypical protein methylation has biological relevance in the pathological process in mammalian cells, we focus on histone methylation in diet‐induced obese (DIO) mouse. Two glutamate methylation sites showed statistical significance in DIO mice compared with chow‐fed mice, suggesting their potential roles in diabetes and obesity. Together, these findings expanded the methylome database from microbes to mammals, which will benefit our further appreciation for the protein methylation as well as its possible functions on disease.     

Detection of differentially methylated regions from whole-genome bisulfite sequencing data without replicates

DNA methylation is an important epigenetic modification involved in many biological processes and diseases. Recent developments in whole genome bisulfite sequencing (WGBS) technology have enabled genome-wide measurements of DNA methylation at single base pair resolution. Many experiments have been conducted to compare DNA methylation profiles under different biological contexts, with the goal of identifying differentially methylated regions (DMRs). Due to the high cost of WGBS experiments, many studies are still conducted without biological replicates. Methods and tools available for analyzing such data are very limited.We develop a statistical method, DSS-single, for detecting DMRs from WGBS data without replicates. We characterize the count data using a rigorous model that accounts for the spatial correlation of methylation levels, sequence depth and biological variation. We demonstrate that using information from neighboring CG sites, biological variation can be estimated accurately even without replicates. DMR detection is then carried out via a Wald test procedure. Simulations demonstrate that DSS-single has greater sensitivity and accuracy than existing methods, and an analysis of H1 versus IMR90 cell lines suggests that it also yields the most biologically meaningful results. DSS-single is implemented in the Bioconductor package DSS.     

A Comparison of the Whole Genome Approach of MeDIP-Seq to the Targeted Approach of the Infinium HumanMethylation450 BeadChip? for Methylome Profiling

DNA methylation is one of the most studied epigenetic marks in the human genome, with the result that the desire to map the human methylome has driven the development of several methods to map DNA methylation on a genomic scale. Our study presents the first comparison of two of these techniques - the targeted approach of the Infinium HumanMethylation450 BeadChip® with the immunoprecipitation and sequencing-based method, MeDIP-seq. Both methods were initially validated with respect to bisulfite sequencing as the gold standard and then assessed in terms of coverage, resolution and accuracy. The regions of the methylome that can be assayed by both methods and those that can only be assayed by one method were determined and the discovery of differentially methylated regions (DMRs) by both techniques was examined. Our results show that the Infinium HumanMethylation450 BeadChip® and MeDIP-seq show a good positive correlation (Spearman correlation of 0.68) on a genome-wide scale and can both be used successfully to determine differentially methylated loci in RefSeq genes, CpG islands, shores and shelves. MeDIP-seq however, allows a wider interrogation of methylated regions of the human genome, including thousands of non-RefSeq genes and repetitive elements, all of which may be of importance in disease. In our study MeDIP-seq allowed the detection of 15,709 differentially methylated regions, nearly twice as many as the array-based method (8070), which may result in a more comprehensive study of the methylome.     

Age-related epigenome-wide DNA methylation and hydroxymethylation in longitudinal mouse blood

DNA methylation at cytosine-phosphate-guanine (CpG) dinucleotides changes as a function of age in humans and animal models, a process that may contribute to chronic disease development. Recent studies have investigated the role of an oxidized form of DNA methylation – 5-hydroxymethylcytosine (5hmC) – in the epigenome, but its contribution to age-related DNA methylation remains unclear. We tested the hypothesis that 5hmC changes with age, but in a direction opposite to 5-methylcytosine (5mC), potentially playing a distinct role in aging. To characterize epigenetic aging, genome-wide 5mC and 5hmC were measured in longitudinal blood samples (2, 4, and 10 months of age) from isogenic mice using two sequencing methods – enhanced reduced representation bisulfite sequencing and hydroxymethylated DNA immunoprecipitation sequencing. Examining the epigenome by age, we identified 28,196 unique differentially methylated CpGs (DMCs) and 8,613 differentially hydroxymethylated regions (DHMRs). Mouse blood showed a general pattern of epigenome-wide hypermethylation and hypo-hydroxymethylation with age. Comparing age-related DMCs and DHMRs, 1,854 annotated genes showed both differential 5mC and 5hmC, including one gene – Nfic – at five CpGs in the same 250 bp chromosomal region. At this region, 5mC and 5hmC levels both decreased with age. Reflecting these age-related epigenetic changes, Nfic RNA expression in blood decreased with age, suggesting that age-related regulation of this gene may be driven by 5hmC, not canonical DNA methylation. Combined, our genome-wide results show age-related differential 5mC and 5hmC, as well as some evidence that changes in 5hmC may drive age-related DNA methylation and gene expression.     

Aberrant signature methylome by DNMT1 hot spot mutation in hereditary sensory and autonomic neuropathy 1E

DNA methyltransferase 1 (DNMT1) is essential for DNA methylation, gene regulation and chromatin stability. We previously discovered DNMT1 mutations cause hereditary sensory and autonomic neuropathy type 1 with dementia and hearing loss (HSAN1E; OMIM 614116). HSAN1E is the first adult-onset neurodegenerative disorder caused by a defect in a methyltransferase gene. HSAN1E patients appear clinically normal until young adulthood, then begin developing the characteristic symptoms involving central and peripheral nervous systems. Some HSAN1E patients also develop narcolepsy and it has recently been suggested that HSAN1E is allelic to autosomal dominant cerebellar ataxia, deafness, with narcolepsy (ADCA-DN; OMIM 604121), which is also caused by mutations in DNMT1. A hotspot mutation Y495C within the targeting sequence domain of DNMT1 has been identified among HSAN1E patients. The mutant DNMT1 protein shows premature degradation and reduced DNA methyltransferase activity. Herein, we investigate genome-wide DNA methylation at single-base resolution through whole-genome bisulfite sequencing of germline DNA in 3 pairs of HSAN1E patients and their gender- and age-matched siblings. Over 1 billion 75-bp single-end reads were generated for each sample. In the 3 affected siblings, overall methylation loss was consistently found in all chromosomes with X and 18 being most affected. Paired sample analysis identified 564,218 differentially methylated CpG sites (DMCs; P < 0.05), of which 300?134 were intergenic and 264?084 genic CpGs. Hypomethylation was predominant in both genic and intergenic regions, including promoters, exons, most CpG islands, L1, L2, Alu, and satellite repeats and simple repeat sequences. In some CpG islands, hypermethylated CpGs outnumbered hypomethylated CpGs. In 201 imprinted genes, there were more DMCs than in non-imprinted genes and most were hypomethylated. Differentially methylated region (DMR) analysis identified 5649 hypomethylated and 1872 hypermethylated regions. Importantly, pathway analysis revealed 1693 genes associated with the identified DMRs were highly associated in diverse neurological disorders and NAD+/NADH metabolism pathways is implicated in the pathogenesis. Our results provide novel insights into the epigenetic mechanism of neurodegeneration arising from a hotspot DNMT1 mutation and reveal pathways potentially important in a broad category of neurological and psychological disorders.     

Identifying and quantifying in vivo methylation sites by heavy methyl SILAC

Protein methylation is a stable post-translational modification (PTM) with important biological functions. It occurs predominantly on arginine and lysine residues with varying numbers of methyl groups, such as mono-, di- or trimethyl lysine. Existing methods for identifying methylation sites are laborious, require large amounts of sample and cannot be applied to complex mixtures. We have previously described stable isotope labeling by amino acids in cell culture (SILAC) for quantitative comparison of proteomes. In heavy methyl SILAC, cells metabolically convert [(13)CD(3)]methionine to the sole biological methyl donor, [(13)CD(3)]S-adenosyl methionine. Heavy methyl groups are fully incorporated into in vivo methylation sites, directly labeling the PTM. This provides markedly increased confidence in identification and relative quantitation of protein methylation by mass spectrometry. Using antibodies targeted to methylated residues and analysis by liquid chromatography-tandem mass spectrometry, we identified 59 methylation sites, including previously unknown sites, considerably extending the number of in vivo methylation sites described in the literature.     

癌症DNA甲基化调控位点的识别

DNA甲基化是一种重要的表观遗传学修饰,在基因的转录调控方面具有重要的作用。异常的DNA甲基化可以导致癌症等复杂疾病发生,癌基因相关的DNA甲基化调控位点的识别对于解析癌症的发生发展机制及识别新的癌症标记具有重要意义。本研究通过整合The Cancer Genome Atlas(TCGA)的泛癌症基因组的高通量甲基化谱和基因表达谱,识别癌基因相关的DNA甲基化调控位点。对于每种癌症分批次计算Cp G位点甲基化与相关基因表达之间的相关性,并筛选调控下游基因的Cp G位点(包括强调控位点、弱调控位点和不调控位点),结果表明仅有一半的Cp G位点对下游基因具有调控作用;对癌症间共享的调控位点的分析发现不同癌症间共享的调控位点不尽相同,表明癌症特异的甲基化调控位点的存在。进一步地,对差异甲基化和差异表达基因的功能富集分析揭示了受甲基化调控的基因确实参与了癌症发生发展相关的功能。本研究的结果是对当前甲基化调控位点集的重要补充,也是识别癌症新型分子标记特征的重要资源。     

Epigenetics: differential DNA methylation in mammalian somatic tissues

Epigenetics refers to heritable phenotypic alterations in the absence of DNA sequence changes, and DNA methylation is one of the extensively studied epigenetic alterations. DNA methylation is an evolutionally conserved mechanism to regulate gene expression in mammals. Because DNA methylation is preserved during DNA replication it can be inherited. Thus, DNA methylation could be a major mechanism by which to produce semi-stable changes in gene expression in somatic tissues. Although it remains controversial whether germ-line DNA methylation in mammalian genomes is stably heritable, frequent tissue-specific and disease-specific de novo methylation events are observed during somatic cell development/differentiation. In this minireview, we discuss the use of restriction landmark genomic scanning, together with in silico analysis, to identify differentially methylated regions in the mammalian genome. We then present a rough overview of quantitative DNA methylation patterns at 4600 NotI sites and more than 150 differentially methylated regions in several C57BL/6J mouse tissues. Comparative analysis between mice and humans suggests that some, but not all, tissue-specific differentially methylated regions are conserved. A deeper understanding of cell-type-specific differences in DNA methylation might lead to a better illustration of the mechanisms behind tissue-specific differentiation in mammals.