Comparative genome-wide DNA methylation analysis of colorectal tumor and matched normal tissues

Aberrant DNA methylation often occurs in colorectal cancer (CRC). In our study we applied a genome-wide DNA methylation analysis approach, MethylCap-seq, to map the differentially methylated regions (DMRs) in 24 tumors and matched normal colon samples. In total, 2687 frequently hypermethylated and 468 frequently hypomethylated regions were identified, which include potential biomarkers for CRC diagnosis. Hypermethylation in the tumor samples was enriched at CpG islands and gene promoters, while hypomethylation was distributed throughout the genome. Using epigenetic data from human embryonic stem cells, we show that frequently hypermethylated regions coincide with bivalent loci in human embryonic stem cells. DNA methylation is commonly thought to lead to gene silencing; however, integration of publically available gene expression data indicates that 75% of the frequently hypermethylated genes were most likely already lowly or not expressed in normal tissue. Collectively, our study provides genome-wide DNA methylation maps of CRC, comprehensive lists of DMRs, and gives insights into the role of aberrant DNA methylation in CRC formation.     

Comparative genome-wide DNA methylation analysis of colorectal tumor and matched normal tissues

Aberrant DNA methylation often occurs in colorectal cancer (CRC). In our study we applied a genome-wide DNA methylation analysis approach, MethylCap-seq, to map the differentially methylated regions (DMRs) in 24 tumors and matched normal colon samples. In total, 2687 frequently hypermethylated and 468 frequently hypomethylated regions were identified, which include potential biomarkers for CRC diagnosis. Hypermethylation in the tumor samples was enriched at CpG islands and gene promoters, while hypomethylation was distributed throughout the genome. Using epigenetic data from human embryonic stem cells, we show that frequently hypermethylated regions coincide with bivalent loci in human embryonic stem cells. DNA methylation is commonly thought to lead to gene silencing; however, integration of publically available gene expression data indicates that 75% of the frequently hypermethylated genes were most likely already lowly or not expressed in normal tissue. Collectively, our study provides genome-wide DNA methylation maps of CRC, comprehensive lists of DMRs, and gives insights into the role of aberrant DNA methylation in CRC formation.     

PMeS: prediction of methylation sites based on enhanced feature encoding scheme

Protein methylation is predominantly found on lysine and arginine residues, and carries many important biological functions, including gene regulation and signal transduction. Given their important involvement in gene expression, protein methylation and their regulatory enzymes are implicated in a variety of human disease states such as cancer, coronary heart disease and neurodegenerative disorders. Thus, identification of methylation sites can be very helpful for the drug designs of various related diseases. In this study, we developed a method called PMeS to improve the prediction of protein methylation sites based on an enhanced feature encoding scheme and support vector machine. The enhanced feature encoding scheme was composed of the sparse property coding, normalized van der Waals volume, position weight amino acid composition and accessible surface area. The PMeS achieved a promising performance with a sensitivity of 92.45%, a specificity of 93.18%, an accuracy of 92.82% and a Matthew's correlation coefficient of 85.69% for arginine as well as a sensitivity of 84.38%, a specificity of 93.94%, an accuracy of 89.16% and a Matthew's correlation coefficient of 78.68% for lysine in 10-fold cross validation. Compared with other existing methods, the PMeS provides better predictive performance and greater robustness. It can be anticipated that the PMeS might be useful to guide future experiments needed to identify potential methylation sites in proteins of interest. The online service is available at http://bioinfo.ncu.edu.cn/inquiries_PMeS.aspx.     

Age-related DNA methylation in normal breast tissue and its relationship with invasive breast tumor methylation

Age is a key risk factor for breast cancer and epigenetic alterations may contribute to age-related increases in breast cancer risk, though the relation of age-related methylation in normal breast tissues with altered methylation in breast tumors is unclear. We investigated the relation of age with DNA methylation in normal breast tissues genome-wide using two data sets from the Gene Expression Omnibus (GEO) database ({"type":"entrez-geo","attrs":{"text":"GSE32393","term_id":"32393"}}GSE32393 and {"type":"entrez-geo","attrs":{"text":"GSE31979","term_id":"31979"}}GSE31979). We validated our observations in an independent set of normal breast tissues, examined age-related methylation in normal breast for enrichment of genomic features, and compared age-related methylation in normal tissue with methylation alterations in breast tumors. Between the two array-based methylation data sets, there were 204 CpG loci with significant (P < 0.05) and consistent age-related methylation, 97% of which were increases in methylation. Our validation sets confirmed the direction of age-related DNA methylation changes in all measured regions. Among the 204 age-related CpG loci, we observed a significant enrichment for CpG islands (P = 8.7E-6) and polycomb group protein target genes (P = 0.03). In addition, 24 of the 204 CpGs with age-related methylation in normal breast were significantly differentially methylated between normal and breast tumor tissues. We identified consistent age-related methylation changes in normal breast tissue that are further altered in breast tumors and may represent early events contributing to breast carcinogenesis. This work identifies age-related methylation in normal breast tissue and begins to deconstruct the contribution of aging to epigenetic alterations present in breast tumors.     

Age-related DNA methylation in normal breast tissue and its relationship with invasive breast tumor methylation

Age is a key risk factor for breast cancer and epigenetic alterations may contribute to age-related increases in breast cancer risk, though the relation of age-related methylation in normal breast tissues with altered methylation in breast tumors is unclear. We investigated the relation of age with DNA methylation in normal breast tissues genome-wide using two data sets from the Gene Expression Omnibus (GEO) database (GSE32393 and GSE31979). We validated our observations in an independent set of normal breast tissues, examined age-related methylation in normal breast for enrichment of genomic features, and compared age-related methylation in normal tissue with methylation alterations in breast tumors. Between the two array-based methylation data sets, there were 204 CpG loci with significant (P < 0.05) and consistent age-related methylation, 97% of which were increases in methylation. Our validation sets confirmed the direction of age-related DNA methylation changes in all measured regions. Among the 204 age-related CpG loci, we observed a significant enrichment for CpG islands (P = 8.7E-6) and polycomb group protein target genes (P = 0.03). In addition, 24 of the 204 CpGs with age-related methylation in normal breast were significantly differentially methylated between normal and breast tumor tissues. We identified consistent age-related methylation changes in normal breast tissue that are further altered in breast tumors and may represent early events contributing to breast carcinogenesis. This work identifies age-related methylation in normal breast tissue and begins to deconstruct the contribution of aging to epigenetic alterations present in breast tumors.     

Robust prediction of gene regulation in colorectal cancer tissues from DNA methylation profiles

DNA methylation is recognized as one of several epigenetic regulators of gene expression and as potential driver of carcinogenesis through gene-silencing of tumor suppressors and activation of oncogenes. However, abnormal methylation, even of promoter regions, does not necessarily alter gene expression levels, especially if the gene is already silenced, leaving the exact mechanisms of methylation unanswered. Using a large cohort of matching DNA methylation and gene expression samples of colorectal cancer (CRC; n = 77) and normal adjacent mucosa tissues (n = 108), we investigated the regulatory role of methylation on gene expression. We show that on a subset of genes enriched in common cancer pathways, methylation is significantly associated with gene regulation through gene-specific mechanisms. We built two classification models to infer gene regulation in CRC from methylation differences of tumor and normal tissues, taking into account both gene-silencing and gene-activation effects through hyper- and hypo-methylation of CpGs. The classification models result in high prediction performances in both training and independent CRC testing cohorts (0.92<AUC<0.97) as well as in individual patient data (average AUC = 0.82), suggesting a robust interplay between methylation and gene regulation. Validation analysis in other cancerous tissues resulted in lower prediction performances (0.69<AUC<0.90); however, it identified genes that share robust dependencies across cancerous tissues. In conclusion, we present a robust classification approach that predicts the gene-specific regulation through DNA methylation in CRC tissues with possible transition to different cancer entities. Furthermore, we present HMGA1 as consistently associated with methylation across cancers, suggesting a potential candidate for DNA methylation targeting cancer therapy.     

Comparative DNA methylation analysis in normal and tumour tissues and in cancer cell lines using differential methylation hybridisation

Immortalized human cancer cell lines are widely used as tools and model systems in cancer research but their authenticity with regard to primary tissues remains a matter of debate. We have used differential methylation hybridisation to obtain comparative methylation profiles from normal and tumour tissues of lung and colon, and permanent cancer cell lines originally derived from these tissues. Average methylation differences only larger than 25% between sample groups were considered for the profiles and with this criterion approximately 1000 probesets, around 2% of the sites represented on the array, indicated differential methylation between normal lung and primary lung cancer tissue, and approximately 700 probesets between normal colon and primary colon cancer tissue. Both hyper- and hypomethylation was found to differentiate normal tissue from cancer tissue. The profiles obtained from these tissue comparisons were found to correspond largely to those from the corresponding cancer cell lines, indicating that the cell lines represent the methylation pattern of the primary tissue rather well. Moreover, the cancer specific profiles were found to be very similar for the two tumour types studied. Tissue specific differential methylation between lung and colon tissues, in contrast, was found to be preserved to a larger extent only in the malignant tissue, but was not preserved well in the cancer cell lines studied. Overall, our data therefore provide further evidence that permanent cell lines are good model systems for cancer specific methylation patterns, but deviate with regard to tissue-specific methylation.     

DNA methylation in the promoter regions of the laminin family genes in normal and breast carcinoma tissues

Molecular Biology - Extracellular glycoproteins of the laminin family are essential components of basement membranes involved in a number of biological processes, including tissue differentiation,...     

Characterization of age signatures of DNA methylation in normal and cancer tissues from multiple studies

Background

DNA methylation (DNAm) levels can be used to predict the chronological age of tissues; however, the characteristics of DNAm age signatures in normal and cancer tissues are not well studied using multiple studies.

Results

We studied approximately 4000 normal and cancer samples with multiple tissue types from diverse studies, and using linear and nonlinear regression models identified reliable tissue type-invariant DNAm age signatures. A normal signature comprising 127 CpG loci was highly enriched on the X chromosome. Age-hypermethylated loci were enriched for guanine–and-cytosine-rich regions in CpG islands (CGIs), whereas age-hypomethylated loci were enriched for adenine–and-thymine-rich regions in non-CGIs. However, the cancer signature comprised only 26 age-hypomethylated loci, none on the X chromosome, and with no overlap with the normal signature. Genes related to the normal signature were enriched for aging-related gene ontology terms including metabolic processes, immune system processes, and cell proliferation. The related gene products of the normal signature had more than the average number of interacting partners in a protein interaction network and had a tendency not to interact directly with each other. The genomic sequences of the normal signature were well conserved and the age-associated DNAm levels could satisfactorily predict the chronological ages of tissues regardless of tissue type. Interestingly, the age-associated DNAm increases or decreases of the normal signature were aberrantly accelerated in cancer samples.

Conclusion

These tissue type-invariant DNAm age signatures in normal and cancer can be used to address important questions in developmental biology and cancer research.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-997) contains supplementary material, which is available to authorized users.     

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。     

Tissue specific DNA methylation of CpG islands in normal human adult somatic tissues distinguishes neural from non-neural tissues

Although most CpG islands are generally thought to remain unmethylated in all adult somatic tissues, recent genome-wide approaches have found that some CpG islands have distinct methylation patterns in various tissues, with most differences being seen between germ cells and somatic tissues. Few studies have addressed this among human somatic tissues and fewer still have studied the same sets of tissues from multiple individuals. In the current study, we used Restriction Landmark Genomic Scanning to study tissue specific methylation patterns in a set of twelve human tissues collected from multiple individuals. We identified 34 differentially methylated CpG islands among these tissues, many of which showed consistent patterns in multiple individuals. Of particular interest were striking differences in CpG island methylation, not only among brain regions, but also between white and grey matter of the same region. These findings were confirmed for selected loci by quantitative bisulfite sequencing. Cluster analysis of the RLGS data indicated that several tissues clustered together, but the strongest clustering was in brain. Tissues from different brain regions clustered together, and, as a group, brain tissues were distinct from either mesoderm or endoderm derived tissues which demonstrated limited clustering. These data demonstrate consistent tissue specific methylation for certain CpG islands, with clear differences between white and grey matter of the brain. Furthermore, there was an overall pattern of tissue specifically methylated CpG islands that distinguished neural tissues from non-neural.     

Tissue specific DNA methylation of CpG islands in normal human adult somatic tissues distinguishes neural from non-neural tissues

Although most CpG islands are generally thought to remain unmethylated in all adult somatic tissues, recent genome-wide approaches have found that some CpG islands have distinct methylation patterns in various tissues, with most differences being seen between germ cells and somatic tissues. Few studies have addressed this among human somatic tissues and fewer still have studied the same sets of tissues from multiple individuals. In the current study, we used Restriction Landmark Genomic Scanning to study tissue specific methylation patterns in a set of 12 human tissues collected from multiple individuals. We identified 34 differentially methylated CpG islands among these tissues, many of which showed consistent patterns in multiple individuals. Of particular interest were striking differences in CpG island methylation, not only among brain regions, but also between white and grey matter of the same region. These findings were confirmed for selected loci by quantitative bisulfite sequencing. Cluster analysis of the RLGS data indicated that several tissues clustered together, but the strongest clustering was in brain. Tissues from different brain regions clustered together, and, as a group, brain tissues were distinct from either mesoderm or endoderm derived tissues which demonstrated limited clustering. These data demonstrate consistent tissue specific methylation for certain CpG islands, with clear differences between white and grey matter of the brain. Furthermore, there was an overall pattern of tissue specifically methylated CpG islands that distinguished neural tissues from non-neural.Key words: Tissue specific methylation, CpG island methylation, neural, brain tissue, grey matter, white matter     

The effect of morphine upon DNA methylation in ten regions of the rat brain

Morphine is one of the most effective analgesics in medicine. However, its use is associated with the development of tolerance and dependence. Recent studies demonstrating epigenetic changes in the brain after exposure to opiates have provided insight into mechanisms possibly underlying addiction. In this study, we sought to identify epigenetic changes in ten regions of the rat brain following acute and chronic morphine exposure. We analyzed DNA methylation of six nuclear-encoded genes implicated in brain function (Bdnf, Comt, Il1b, Il6, Nr3c1, and Tnf) and three mitochondrially-encoded genes (Mtco1, Mtco2, and Mtco3), and measured global 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5?hmC) levels. We observed differential methylation of Bdnf and Il6 in the pons, Nr3c1 in the cerebellum, and Il1b in the hippocampus in response to acute morphine exposure (all P value < 0.05). Chronic exposure was associated with differential methylation of Bdnf and Comt in the pons, Nr3c1 in the hippocampus and Il1b in the medulla oblongata (all P value < 0.05). Global 5mC levels significantly decreased in the superior colliculus following both acute and chronic morphine exposure, and increased in the hypothalamus following chronic exposure. Chronic exposure was also associated with significantly increased global 5hmC levels in the cerebral cortex, hippocampus, and hypothalamus, but significantly decreased in the midbrain. Our results demonstrate, for the first time, highly localized epigenetic changes in the rat brain following acute and chronic morphine exposure. Further work is required to elucidate the potential role of these changes in the formation of tolerance and dependence.     

Protein bound to mitochondrial DNA from tumor and normal tissues of humans and animals

Stable mitochondrial (mt) DNA-protein complexes have been reported repeatedly in the last decade. We have found that the amount of proteins bound to mt DNA was increased in human HL-60 promyelocytic and chronic myelocytic leukemia cells. Mt of human tumor cells and bovine and rate liver cells were isolated by differential centrifugation. The DNA was purified by SDS-NaCl precipitation of protein, alcohol precipitation, and sucrose density gradient centrifugation. Mt DNA-bound protein obtained by enzymatic digestion of the DNA and purified by gel exclusion and reverse-phase HPLC chomatographies and SDS-polyacrylamide gel electrophoresis, showed a major protein band at 70 kD and a minor band at 35 kD. Hydrolysis of the mtDNA-protein complex in formic acid yielded DNA bases and peptides by HPLC on a C18 reverse-phase column. Tumor cell mtDNA contained 5-10 times more bound protein than mtDNA from normal tissue.     

DNA methylation age of human tissues and cell types

Background

It is not yet known whether DNA methylation levels can be used to accurately predict age across a broad spectrum of human tissues and cell types, nor whether the resulting age prediction is a biologically meaningful measure.

Results

I developed a multi-tissue predictor of age that allows one to estimate the DNA methylation age of most tissues and cell types. The predictor, which is freely available, was developed using 8,000 samples from 82 Illumina DNA methylation array datasets, encompassing 51 healthy tissues and cell types. I found that DNA methylation age has the following properties: first, it is close to zero for embryonic and induced pluripotent stem cells; second, it correlates with cell passage number; third, it gives rise to a highly heritable measure of age acceleration; and, fourth, it is applicable to chimpanzee tissues. Analysis of 6,000 cancer samples from 32 datasets showed that all of the considered 20 cancer types exhibit significant age acceleration, with an average of 36 years. Low age-acceleration of cancer tissue is associated with a high number of somatic mutations and TP53 mutations, while mutations in steroid receptors greatly accelerate DNA methylation age in breast cancer. Finally, I characterize the 353 CpG sites that together form an aging clock in terms of chromatin states and tissue variance.

Conclusions

I propose that DNA methylation age measures the cumulative effect of an epigenetic maintenance system. This novel epigenetic clock can be used to address a host of questions in developmental biology, cancer and aging research.     

Analysis of DNA methylation in various swine tissues

DNA methylation is known to play an important role in regulating gene expression during biological development and tissue differentiation in eukaryotes. In this study, we used the fluorescence-labeled methylation-sensitive amplified polymorphism (F-MSAP) method to assess the extent and pattern of cytosine methylation in muscle, heart, liver, spleen, lung, kidney and stomach from the swine strain Laiwu, and we also examined specific methylation patterns in the seven tissues. In total, 96,371 fragments, each representing a recognition site cleaved by either or both EcoRI + HpaII and EcoRI + MspI, the HpaII and MspI are isoschizomeric enzymes, were amplified using 16 pairs of selective primers. A total of 50,094 sites were found to be methylated at cytosines in seven tissues. The incidence of DNA methylation was approximately 53.99% in muscle, 51.24% in the heart, 50.18% in the liver, 53.31% in the spleen, 51.97% in the lung, 51.15% in the kidney and 53.39% in the stomach, as revealed by the incidence of differential digestion. Additionally, differences in DNA methylation levels imply that such variations may be related to specific gene expression during tissue differentiation, growth and development. Three types of bands were generated in the F-MSAP profile, the total numbers of these three types of bands in the seven tissues were 46,277, 24,801 and 25,293, respectively.In addition, different methylation patterns were observed in seven tissues from pig, and almost all of the methylation patterns detected by F-MSAP could be confirmed by Southern analysis using the isolated amplified fragments as probes. The results clearly demonstrated that the F-MSAP technique can be adapted for use in large-scale DNA methylation detection in the pig genome.