Global DNA methylation measurement by HPLC using low amounts of DNA

Epigenetic changes in chromatin structure can influence gene expression without affecting the DNA sequence. The most commonly studied epigenetic modification, DNA methylation, has been implicated in normal tissue development and disease progression, and can be influenced by diet and other environmental factors. Current HPLC methods of determining DNA methylation may require relatively large amounts of DNA (50 μg); as many tissues have low DNA yields, this can be hard to achieve. We isolated DNA from mouse colon and liver in a study investigating post-natal supplementation with selenium and folic acid. After optimizing the methods to account for lower initial DNA amounts, we digested 3 μg of DNA to deoxynucleotide monophosphates, then purified and quantified it. Samples were analyzed by reversed-phase HPLC to determine global DNA methylation levels using commercial nucleotide standards. The HPLC column was cooled to 6(C (reducing run time), and detection was at 280 nm (UV). We showed that methylated cytosine can be accurately and reproducibly measured in as little as 3 μg of DNA using this HPLC analysis method (within-assay CV <2%). We also used this method to detect reduced DNA methylation in liver (P = 0.009) in response to post-natal supplementation with selenium and folate.     

A simple method for estimating global DNA methylation using bisulfite PCR of repetitive DNA elements

We report a method for studying global DNA methylation based on using bisulfite treatment of DNA and simultaneous PCR of multiple DNA repetitive elements, such as Alu elements and long interspersed nucleotide elements (LINE). The PCR product, which represents a pool of approximately 15000 genomic loci, could be used for direct sequencing, selective restriction digestion or pyrosequencing, in order to quantitate DNA methylation. By restriction digestion or pyrosequencing, the assay was reproducible with a standard deviation of only 2% between assays. Using this method we found that almost two-thirds of the CpG methylation sites in Alu elements are mutated, but of the remaining methylation target sites, 87% were methylated. Due to the heavy methylation of repetitive elements, this assay was especially useful in detecting decreases in DNA methylation, and this assay was validated by examining cell lines treated with the methylation inhibitor 5-aza-2′deoxycytidine (DAC), where we found a 1–16% decrease in Alu element and 18–60% LINE methylation within 3 days of treatment. This method can be used as a surrogate marker of genome-wide methylation changes. In addition, it is less labor intensive and requires less DNA than previous methods of assessing global DNA methylation.     

Utility of the methylation-sensitive amplified polymorphism (MSAP) marker for detection of DNA methylation polymorphism and epigenetic population structure in a wild barley species (<Emphasis Type="Italic">Hordeum brevisubulatum</Emphasis>)

We report here that by using a modified scoring criterion, the methylation-sensitive amplified polymorphism or MSAP marker can be used effectively to detect polymorphism in DNA methylation patterns within and among populations of a perennial wild barley species, Hordeum brevisubulatum. Twenty-four selected individual genotypes representing four natural populations of H. brevisubulatum distributed in the Songnen Prairie in northeastern China were studied. The utility of MSAP was evidenced by its detection of high levels of polymorphism in DNA methylation patterns between individuals within a given population, and the clear inter-population differentiation in methylation patterns (methylation-based epigenetic population structure) revealed among the four populations. The resolving power of MSAP to detect DNA methylation polymorphism was found to be comparable with that of a retrotransposon-based sequence-specific amplified polymorphism marker, or SSAP, to detect genetic polymorphism in the same set of plants, suggesting that MSAP with a modified scoring criterion can be used efficiently to detect DNA methylation polymorphism and assess epigenetic population structure in natural plant populations. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Direct and continuous fluorescence-based measurements of Pyrococcus horikoshii DNA N-6 adenine methyltransferase activity

N-6 methylation of adenine destabilises duplex DNA and this can increase the proportion of DNA that dissociates into single strands. We have investigated utilising this property to measure the DNA adenine methyltransferase-catalyzed conversion of hemimethylated to fully methylated DNA through a simple, direct, fluorescence-based assay. The effects of methylation on the kinetics and thermodynamics of hybridisation were measured by comparing a fully methylated oligonucleotide product and a hemimethylated oligonucleotide substrate using a 13-bp duplex labeled on adjacent strands with a fluorophore (fluorescein) and quencher (dabcyl). Enzymatic methylation of the hemimethylated GATC site resulted in destabilisation of the duplex, increasing the proportion of dissociated DNA, and producing an observable increase in fluorescence. The assay provides a direct measurement of methylation rate in real time and is highly reproducible, with a coefficient of variance over 48 independent measurements of 3.6%. DNA methylation rates can be measured as low as 3.55 ± 1.84 fmol s⁻¹ in a 96-well plate format, and the assay has been used to kinetically characterise the Pyrococcus horikoshii DNA adenine methyltransferase.     

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.     

Adjustment of Cell-Type Composition Minimizes Systematic Bias in Blood DNA Methylation Profiles Derived by DNA Collection Protocols

Differences in DNA collection protocols may be a potential confounder in epigenome-wide association studies (EWAS) using a large number of blood specimens from multiple biobanks and/or cohorts. Here we show that pre-analytical procedures involved in DNA collection can induce systematic bias in the DNA methylation profiles of blood cells that can be adjusted by cell-type composition variables. In Experiment 1, whole blood from 16 volunteers was collected to examine the effect of a 24 h storage period at 4°C on DNA methylation profiles as measured using the Infinium HumanMethylation450 BeadChip array. Our statistical analysis showed that the P-value distribution of more than 450,000 CpG sites was similar to the theoretical distribution (in quantile-quantile plot, λ = 1.03) when comparing two control replicates, which was remarkably deviated from the theoretical distribution (λ = 1.50) when comparing control and storage conditions. We then considered cell-type composition as a possible cause of the observed bias in DNA methylation profiles and found that the bias associated with the cold storage condition was largely decreased (λ_adjusted = 1.14) by taking into account a cell-type composition variable. As such, we compared four respective sample collection protocols used in large-scale Japanese biobanks or cohorts as well as two control replicates. Systematic biases in DNA methylation profiles were observed between control and three of four protocols without adjustment of cell-type composition (λ = 1.12–1.45) and no remarkable biases were seen after adjusting for cell-type composition in all four protocols (λ_adjusted = 1.00–1.17). These results revealed important implications for comparing DNA methylation profiles between blood specimens from different sources and may lead to discovery of disease-associated DNA methylation markers and the development of DNA methylation profile-based predictive risk models.     

Different measures of “genome-wide” DNA methylation exhibit unique properties in placental and somatic tissues

DNA methylation of CpGs located in two types of repetitive elements—LINE1 (L1) and Alu—is used to assess “global” changes in DNA methylation in studies of human disease and environmental exposure. L1 and Alu contribute close to 30% of all base pairs in the human genome and transposition of repetitive elements is repressed through DNA methylation. Few studies have investigated whether repetitive element DNA methylation is associated with DNA methylation at other genomic regions, or the biological and technical factors that influence potential associations. Here, we assess L1 and Alu DNA methylation by Pyrosequencing of consensus sequences and using subsets of probes included in the Illumina Infinium HumanMethylation27 BeadChip array. We show that evolutionary age and assay method affect the assessment of repetitive element DNA methylation. Additionally, we compare Pyrosequencing results for repetitive elements to average DNA methylation of CpG islands, as assessed by array probes classified into strong, weak and non-islands. We demonstrate that each of these dispersed sequences exhibits different patterns of tissue-specific DNA methylation. Correlation of DNA methylation suggests an association between L1 and weak CpG island DNA methylation in some of the tissues examined. We caution, however, that L1, Alu and CpG island DNA methylation are distinct measures of dispersed DNA methylation and one should not be used in lieu of another. Analysis of DNA methylation data is complex and assays may be influenced by environment and pathology in different or complementary ways.     

iDNA-Methyl: Identifying DNA methylation sites via pseudo trinucleotide composition

Predominantly occurring on cytosine, DNA methylation is a process by which cells can modify their DNAs to change the expression of gene products. It plays very important roles in life development but also in forming nearly all types of cancer. Therefore, knowledge of DNA methylation sites is significant for both basic research and drug development. Given an uncharacterized DNA sequence containing many cytosine residues, which one can be methylated and which one cannot? With the avalanche of DNA sequences generated during the postgenomic age, it is highly desired to develop computational methods for accurately identifying the methylation sites in DNA. Using the trinucleotide composition, pseudo amino acid components, and a dataset-optimizing technique, we have developed a new predictor called “iDNA-Methyl” that has achieved remarkably higher success rates in identifying the DNA methylation sites than the existing predictors. A user-friendly web-server for the new predictor has been established at http://www.jci-bioinfo.cn/iDNA-Methyl, where users can easily get their desired results. We anticipate that the web-server predictor will become a very useful high-throughput tool for basic research and drug development and that the novel approach and technique can also be used to investigate many other DNA-related problems and genome analysis.     

Sensitive quantitative analysis of murine LINE1 DNA methylation using high resolution melt analysis

We present here the first high resolution melt (HRM) assay to quantitatively analyze differences in murine DNA methylation levels utilizing CpG methylation of Long Interspersed Elements-1 (LINE1 or L1). By calculating the integral difference in melt temperature between samples and a methylated control, and biasing PCR primers for unmethylated CpGs, the assay demonstrates enhanced sensitivity to detect changes in methylation in a cell line treated with low doses of 5-aza-2’-deoxycytidine (5-aza). The L1 assay was confirmed to be a good marker of changes in DNA methylation of L1 elements at multiple regions across the genome when compared with total 5-methyl-cytosine content, measured by Liquid Chromatography-Mass Spectrometry (LC-MS). The assay design was also used to detect changes in methylation at other murine repeat elements (B1 and Intracisternal-A-particle Long-terminal Repeat elements). Pyrosequencing analysis revealed that L1 methylation changes were non-uniform across the CpGs within the L1-HRM target region, demonstrating that the L1 assay can detect small changes in CpG methylation among a large pool of heterogeneously methylated DNA templates. Application of the assay to various tissues from Balb/c and CBA mice, including previously unreported peripheral blood (PB), revealed a tissue hierarchy (from hypermethylated to hypomethylated) of PB > kidney > liver > prostate > spleen. CBA mice demonstrated overall greater methylation than Balb/c mice, and male mice demonstrated higher tissue methylation compared with female mice in both strains. Changes in DNA methylation have been reported to be an early and fundamental event in the pathogenesis of many human diseases, including cancer. Mouse studies designed to identify modulators of DNA methylation, the critical doses, relevant time points and the tissues affected are limited by the low throughput nature and exorbitant cost of many DNA methylation assays. The L1 assay provides a high throughput, inexpensive and sensitive screening tool for identifying and characterizing DNA methylation changes to L1 elements at multiple regions across the genome.     

Integrative analysis identifies potential DNA methylation biomarkers for pan-cancer diagnosis and prognosis

DNA methylation status is closely associated with diverse diseases, and is generally more stable than gene expression, thus abnormal DNA methylation could be important biomarkers for tumor diagnosis, treatment and prognosis. However, the signatures regarding DNA methylation changes for pan-cancer diagnosis and prognosis are less explored. Here we systematically analyzed the genome-wide DNA methylation patterns in diverse TCGA cancers with machine learning. We identified seven CpG sites that could effectively discriminate tumor samples from adjacent normal tissue samples for 12 main cancers of TCGA (1216 samples, AUC > 0.99). Those seven potential diagnostic biomarkers were further validated in the other 9 different TCGA cancers and 4 independent datasets (AUC > 0.92). Three out of the seven CpG sites were correlated with cell division, DNA replication and cell cycle. We also identified 12 CpG sites that can effectively distinguish 26 different cancers (7605 samples), and the result was repeatable in independent datasets as well as two disparate tumors with metastases (micro-average AUC > 0.89). Furthermore, a series of potential signatures that could significantly predict the prognosis of tumor patients for 7 different cancer were identified via survival analysis (p-value < 1e-4). Collectively, DNA methylation patterns vary greatly between tumor and adjacent normal tissues, as well as among different types of cancers. Our identified signatures may aid the decision of clinical diagnosis and prognosis for pan-cancer and the potential cancer-specific biomarkers could be used to predict the primary site of metastatic breast and prostate cancers.