Clinical and public health research using methylated DNA Immunoprecipitation (MeDIP): A comparison of commercially available kits to examine differential DNA methylation across the genome

The methylated DNA immunoprecipitation method (MeDIP) is a genome-wide, high-resolution approach that detects DNA methylation with oligonucleotide tiling arrays or high throughput sequencing platforms. A simplified high-throughput MeDIP assay will enable translational research studies in clinics and populations, which will greatly enhance our understanding of the human methylome. We compared three commercial kits, MagMeDIP Kit TM (Diagenode), Methylated-DNA IP Kit (Zymo Research) and Methylamp? Methylated DNA Capture Kit (Epigentek), in order to identify which one has better reliability and sensitivity for genomic DNA enrichment. Each kit was used to enrich two samples, one from fresh tissue and one from a cell line, with two different DNA amounts. The enrichment efficiency of each kit was evaluated by agarose gel band intensity after Nco I digestion and by reaction yield of methylated DNA. A successful enrichment is expected to have a 1:4 to 10:1 conversion ratio and a yield of 80% or higher. We also evaluated the hybridization efficiency to genome-wide methylation arrays in a separate cohort of tissue samples. We observed that the MagMeDIP kit had the highest yield for the two DNA amounts and for both the tissue and cell line samples, as well as for the positive control. In addition, the DNA was successfully enriched from a 1:4 to 10:1 ratio. Therefore, the MagMeDIP kit is a useful research tool that will enable clinical and public health genome-wide DNA methylation studies.     

Standardization and quality controls for the methylated DNA immunoprecipitation technique

MeDIP (Methylated DNA Immunoprecipitation) is a relatively recent technique aimed to enrich the methylated fraction of DNA with an antibody directed against 5-methyl-cytosine. MeDIP processed samples are suitable for investigation of the methylation status of specific genomic loci and for performing genome-wide screening when hybridized to DNA methylation microarrays or analyzed by deep sequencing. Here, we describe a standardization protocol and quality controls to assess the specificity, reproducibility and efficiency of the MeDIP procedure. These may have utility when comparing results between samples and experiments within laboratories and between laboratories.     

Methyl-DNA immunoprecipitation (MeDIP): hunting down the DNA methylome

One of the most challenging projects in the field of epigenetics is the generation of detailed functional maps of DNA methylation in different cell and tissue types in normal and disease-associated conditions. This information will help us not only understand the role of DNA methylation but also identify targets for therapeutic treatment. The completion of the various epigenome projects depends on the design of novel strategies to survey and generate detailed cartograms of the DNA methylome. Methyl-DNA immunoprecipitation (MeDIP) assays, in combination with hybridization on high-resolution microarrays or high-throughput sequencing (HTS) techniques, are excellent methods for identifying methylated CpG-rich sequences. We provide a critical overview of different genome-wide techniques for DNA methylation analysis and propose that MeDIP assays may constitute a key method for elucidating the hypermethylome of cancer cells.     

Methylated DNA Immunoprecipitation

The identification of DNA methylation patterns is a common procedure in the study of epigenetics, as methylation is known to have significant effects on gene expression, and is involved with normal development as well as disease ^1-4. Thus, the ability to discriminate between methylated DNA and non-methylated DNA is essential for generating methylation profiles for such studies. Methylated DNA immunoprecipitation (MeDIP) is an efficient technique for the extraction of methylated DNA from a sample of interest ^5-7. A sample of as little as 200 ng of DNA is sufficient for the antibody, or immunoprecipitation (IP), reaction. DNA is sonicated into fragments ranging in size from 300-1000 bp, and is divided into immunoprecipitated (IP) and input (IN) portions. IP DNA is subsequently heat denatured and then incubated with anti-5''mC, allowing the monoclonal antibody to bind methylated DNA. After this, magnetic beads containing a secondary antibody with affinity for the primary antibody are added, and incubated. These bead-linked antibodies will bind the monoclonal antibody used in the first step. DNA bound to the antibody complex (methylated DNA) is separated from the rest of the DNA by using a magnet to pull the complexes out of solution. Several washes using IP buffer are then performed to remove the unbound, non-methylated DNA. The methylated DNA/antibody complexes are then digested with Proteinase K to digest the antibodies leaving only the methylated DNA intact. The enriched DNA is purified by phenol:chloroform extraction to remove the protein matter and then precipitated and resuspended in water for later use. PCR techniques can be used to validate the efficiency of the MeDIP procedure by analyzing the amplification products of IP and IN DNA for regions known to lack and known to contain methylated sequences. The purified methylated DNA can then be used for locus-specific (PCR) or genome-wide (microarray and sequencing) methylation studies, and is particularly useful when applied in conjunction with other research tools such as gene expression profiling and array comparative genome hybridization (CGH) ⁸. Further investigation into DNA methylation will lead to the discovery of new epigenetic targets, which in turn, may be useful in developing new therapeutic or prognostic research tools for diseases such as cancer that are characterized by aberrantly methylated DNA ^{2, 4, 9-11}.     

Exome localization of complex disease association signals

Background

Recent progress in high-throughput technologies has greatly contributed to the development of DNA methylation profiling. Although there are several reports that describe methylome detection of whole genome bisulfite sequencing, the high cost and heavy demand on bioinformatics analysis prevents its extensive application. Thus, current strategies for the study of mammalian DNA methylomes is still based primarily on genome-wide methylated DNA enrichment combined with DNA microarray detection or sequencing. Methylated DNA enrichment is a key step in a microarray based genome-wide methylation profiling study, and even for future high-throughput sequencing based methylome analysis.

Results

In order to evaluate the sensitivity and accuracy of methylated DNA enrichment, we investigated and optimized a number of important parameters to improve the performance of several enrichment assays, including differential methylation hybridization (DMH), microarray-based methylation assessment of single samples (MMASS), and methylated DNA immunoprecipitation (MeDIP). With advantages and disadvantages unique to each approach, we found that assays based on methylation-sensitive enzyme digestion and those based on immunoprecipitation detected different methylated DNA fragments, indicating that they are complementary in their relative ability to detect methylation differences.

Conclusions

Our study provides the first comprehensive evaluation for widely used methodologies for methylated DNA enrichment, and could be helpful for developing a cost effective approach for DNA methylation profiling.     

Genome-scale analysis of DNA methylation in colorectal cancer using Infinium HumanMethylation450 BeadChips

Illumina’s Infinium HumanMethylation450 BeadChip arrays were used to examine genome-wide DNA methylation profiles in 22 sample pairs from colorectal cancer (CRC) and adjacent tissues and 19 colon tissue samples from cancer-free donors. We show that the methylation profiles of tumors and healthy tissue samples can be clearly distinguished from one another and that the main source of methylation variability is associated with disease status. We used different statistical approaches to evaluate the methylation data. In general, at the CpG-site level, we found that common CRC-specific methylation patterns consist of at least 15,667 CpG sites that were significantly different from either adjacent healthy tissue or tissue from cancer-free subjects. Of these sites, 10,342 were hypermethylated in CRC, and 5,325 were hypomethylated. Hypermethylated sites were common in the maximum number of sample pairs and were mostly located in CpG islands, where they were significantly enriched for differentially methylated regions known to be cancer-specific. In contrast, hypomethylated sites were mostly located in CpG shores and were generally sample-specific. Despite the considerable variability in methylation data, we selected a panel of 14 highly robust candidates showing methylation marks in genes SND1, ADHFE1, OPLAH, TLX2, C1orf70, ZFP64, NR5A2, and COL4A. This set was successfully cross-validated using methylation data from 209 CRC samples and 38 healthy tissue samples from The Cancer Genome Atlas consortium (AUC = 0.981 [95% CI: 0.9677–0.9939], sensitivity = 100% and specificity = 82%). In summary, this study reports a large number of loci with novel differential methylation statuses, some of which may serve as candidate markers for diagnostic purposes.     

Predictive properties of DNA methylation patterns in primary tumor samples for osteosarcoma relapse status

Osteosarcoma is the most common primary malignant bone tumor in children. Validated biological markers for disease prognosis available at diagnosis are lacking. No genome-wide DNA methylation studies linked to clinical outcomes have been reported in osteosarcoma to the best of our knowledge. To address this, we tested the methylome at over 1.1 million loci in 15 osteosarcoma biopsy samples obtained prior to the initiation of therapy and correlated these molecular data with disease outcomes. At more than 17% of the tested loci, samples obtained from patients who experienced disease relapse were more methylated than those from patients who did not have recurrence while patients who did not experience disease relapse had more DNA methylation at fewer than 1%. In samples from patients who went on to have recurrent disease, increased DNA methylation was found at gene bodies, intergenic regions and empirically-annotated candidate enhancers, whereas candidate gene promoters were unusual for a more balanced distribution of increased and decreased DNA methylation with 6.6% of gene promoter loci being more methylated and 2% of promoter loci being less methylated in patients with disease relapse. A locus at the TLR4 gene demonstrates one of strongest associations between DNA methylation and 5 y event-free survival (P-value = 1.7 × 10^?6), with empirical annotation of this locus showing promoter characteristics. Our data indicate that DNA methylation information has the potential to be predictive of outcome in pediatric osteosarcoma, and that both promoters and non-promoter loci are potentially informative in DNA methylation studies.     

Genome-wide methylation profiling identifies hypermethylated biomarkers in high-grade cervical intraepithelial neoplasia

Epigenetic modifications, such as aberrant DNA promoter methylation, are frequently observed in cervical cancer. Identification of hypermethylated regions allowing discrimination between normal cervical epithelium and high-grade cervical intraepithelial neoplasia (CIN2/3), or worse, may improve current cervical cancer population-based screening programs. In this study, the DNA methylome of high-grade CIN lesions was studied using genome-wide DNA methylation screening to identify potential biomarkers for early diagnosis of cervical neoplasia. Methylated DNA Immunoprecipitation (MeDIP) combined with DNA microarray was used to compare DNA methylation profiles of epithelial cells derived from high-grade CIN lesions with normal cervical epithelium. Hypermethylated differentially methylated regions (DMRs) were identified. Validation of nine selected DMRs using BSP and MSP in cervical tissue revealed methylation in 63.2–94.7% high-grade CIN and in 59.3–100% cervical carcinomas. QMSP for the two most significant high-grade CIN-specific methylation markers was conducted exploring test performance in a large series of cervical scrapings. Frequency and relative level of methylation were significantly different between normal and cancer samples. Clinical validation of both markers in cervical scrapings from patients with an abnormal cervical smear confirmed that frequency and relative level of methylation were related with increasing severity of the underlying CIN lesion and that ROC analysis was discriminative. These markers represent the COL25A1 and KATNAL2 and their observed increased methylation upon progression could intimate the regulatory role in carcinogenesis. In conclusion, our newly identified hypermethylated DMRs represent specific DNA methylation patterns in high-grade CIN lesions and are candidate biomarkers for early detection.     

Patterns of DNA methylation in the normal colon vary by anatomical location,gender, and age

Alterations in DNA methylation have been proposed to create a field cancerization state in the colon, where molecular alterations that predispose cells to transformation occur in histologically normal tissue. However, our understanding of the role of DNA methylation in field cancerization is limited by an incomplete characterization of the methylation state of the normal colon. In order to determine the colon’s normal methylation state, we extracted DNA from normal colon biopsies from the rectum, sigmoid, transverse, and ascending colon and assessed the methylation status of the DNA by pyrosequencing candidate loci as well as with HumanMethylation450 arrays. We found that methylation levels of repetitive elements LINE-1 and SAT-α showed minimal variability throughout the colon in contrast to other loci. Promoter methylation of EVL was highest in the rectum and progressively lower in the proximal segments, whereas ESR1 methylation was higher in older individuals. Genome-wide methylation analysis of normal DNA revealed 8388, 82, and 93 differentially methylated loci that distinguished right from left colon, males from females, and older vs. younger individuals, respectively. Although variability in methylation between biopsies and among different colon segments was minimal for repetitive elements, analyses of specific cancer-related genes as well as a genome-wide methylation analysis demonstrated differential methylation based on colon location, individual age, and gender. These studies advance our knowledge regarding the variation of DNA methylation in the normal colon, a prerequisite for future studies aimed at understanding methylation differences indicative of a colon field effect.     

Patterns of DNA methylation in the normal colon vary by anatomical location,gender, and age

Alterations in DNA methylation have been proposed to create a field cancerization state in the colon, where molecular alterations that predispose cells to transformation occur in histologically normal tissue. However, our understanding of the role of DNA methylation in field cancerization is limited by an incomplete characterization of the methylation state of the normal colon. In order to determine the colon’s normal methylation state, we extracted DNA from normal colon biopsies from the rectum, sigmoid, transverse, and ascending colon and assessed the methylation status of the DNA by pyrosequencing candidate loci as well as with HumanMethylation450 arrays. We found that methylation levels of repetitive elements LINE-1 and SAT-α showed minimal variability throughout the colon in contrast to other loci. Promoter methylation of EVL was highest in the rectum and progressively lower in the proximal segments, whereas ESR1 methylation was higher in older individuals. Genome-wide methylation analysis of normal DNA revealed 8388, 82, and 93 differentially methylated loci that distinguished right from left colon, males from females, and older vs. younger individuals, respectively. Although variability in methylation between biopsies and among different colon segments was minimal for repetitive elements, analyses of specific cancer-related genes as well as a genome-wide methylation analysis demonstrated differential methylation based on colon location, individual age, and gender. These studies advance our knowledge regarding the variation of DNA methylation in the normal colon, a prerequisite for future studies aimed at understanding methylation differences indicative of a colon field effect.     

Predictive properties of DNA methylation patterns in primary tumor samples for osteosarcoma relapse status

Osteosarcoma is the most common primary malignant bone tumor in children. Validated biological markers for disease prognosis available at diagnosis are lacking. No genome-wide DNA methylation studies linked to clinical outcomes have been reported in osteosarcoma to the best of our knowledge. To address this, we tested the methylome at over 1.1 million loci in 15 osteosarcoma biopsy samples obtained prior to the initiation of therapy and correlated these molecular data with disease outcomes. At more than 17% of the tested loci, samples obtained from patients who experienced disease relapse were more methylated than those from patients who did not have recurrence while patients who did not experience disease relapse had more DNA methylation at fewer than 1%. In samples from patients who went on to have recurrent disease, increased DNA methylation was found at gene bodies, intergenic regions and empirically-annotated candidate enhancers, whereas candidate gene promoters were unusual for a more balanced distribution of increased and decreased DNA methylation with 6.6% of gene promoter loci being more methylated and 2% of promoter loci being less methylated in patients with disease relapse. A locus at the TLR4 gene demonstrates one of strongest associations between DNA methylation and 5 y event-free survival (P-value = 1.7 × 10⁻⁶), with empirical annotation of this locus showing promoter characteristics. Our data indicate that DNA methylation information has the potential to be predictive of outcome in pediatric osteosarcoma, and that both promoters and non-promoter loci are potentially informative in DNA methylation studies.     

Genome-wide methylation profiling identifies hypermethylated biomarkers in high-grade cervical intraepithelial neoplasia

Epigenetic modifications, such as aberrant DNA promoter methylation, are frequently observed in cervical cancer. Identification of hypermethylated regions allowing discrimination between normal cervical epithelium and high-grade cervical intraepithelial neoplasia (CIN2/3), or worse, may improve current cervical cancer population-based screening programs. In this study, the DNA methylome of high-grade CIN lesions was studied using genome-wide DNA methylation screening to identify potential biomarkers for early diagnosis of cervical neoplasia. Methylated DNA Immunoprecipitation (MeDIP) combined with DNA microarray was used to compare DNA methylation profiles of epithelial cells derived from high-grade CIN lesions with normal cervical epithelium. Hypermethylated differentially methylated regions (DMRs) were identified. Validation of nine selected DMRs using BSP and MSP in cervical tissue revealed methylation in 63.2–94.7% high-grade CIN and in 59.3–100% cervical carcinomas. QMSP for the two most significant high-grade CIN-specific methylation markers was conducted exploring test performance in a large series of cervical scrapings. Frequency and relative level of methylation were significantly different between normal and cancer samples. Clinical validation of both markers in cervical scrapings from patients with an abnormal cervical smear confirmed that frequency and relative level of methylation were related with increasing severity of the underlying CIN lesion and that ROC analysis was discriminative. These markers represent the COL25A1 and KATNAL2 and their observed increased methylation upon progression could intimate the regulatory role in carcinogenesis. In conclusion, our newly identified hypermethylated DMRs represent specific DNA methylation patterns in high-grade CIN lesions and are candidate biomarkers for early detection.     

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.     

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.     

Performance Evaluation of Kits for Bisulfite-Conversion of DNA from Tissues,Cell Lines,FFPE Tissues,Aspirates, Lavages,Effusions, Plasma,Serum, and Urine

DNA methylation analyses usually require a preceding bisulfite conversion of the DNA. The choice of an appropriate kit for a specific application should be based on the specific performance requirements with regard to the respective sample material. In this study, the performance of nine kits was evaluated: EpiTect Fast FFPE Bisulfite Kit, EpiTect Bisulfite Kit, EpiTect Fast DNA Bisulfite Kit (Qiagen), EZ DNA Methylation-Gold Kit, EZ DNA Methylation-Direct Kit, EZ DNA Methylation-Lightning Kit (Zymo Research), innuCONVERT Bisulfite All-In-One Kit, innuCONVERT Bisulfite Basic Kit, innuCONVERT Bisulfite Body Fluids Kit (Analytik Jena). The kit performance was compared with regard to DNA yield, DNA degradation, DNA purity, conversion efficiency, stability and handling using qPCR, UV, clone sequencing, HPLC, and agarose gel electrophoresis. All kits yielded highly pure DNA suitable for PCR analyses without PCR inhibition. Significantly higher yields were obtained when using the EZ DNA Methylation-Gold Kit and the innuCONVERT Bisulfite kits. Conversion efficiency ranged from 98.7% (EpiTect Bisulfite Kit) to 99.9% (EZ DNA Methylation-Direct Kit). The inappropriate conversion of methylated cytosines to thymines varied between 0.9% (innuCONVERT Bisulfite kits) and 2.7% (EZ DNA Methylation-Direct Kit). Time-to-result ranged from 131 min (innuCONVERT kits) to 402 min (EpiTect Bisulfite Kit). Hands-on-time was between 66 min (EZ DNA Methylation-Lightning Kit) and 104 min (EpiTect Fast FFPE and Fast DNA Bisulfite kits). Highest yields from formalin-fixed and paraffin-embedded (FFPE) tissue sections without prior extraction were obtained using the innuCONVERT Bisulfite All-In-One Kit while the EZ DNA Methylation-Direct Kit yielded DNA with only low PCR-amplifiability. The innuCONVERT Bisulfite All-In-One Kit exhibited the highest versatility regarding different input sample materials (extracted DNA, tissue, FFPE tissue, cell lines, urine sediment, and cellular fractions of bronchial aspirates, pleural effusions, ascites). The innuCONVERT Bisulfite Body Fluids Kit allowed for the analysis of 3 ml plasma, serum, ascites, pleural effusions and urine.     

A Bayesian deconvolution strategy for immunoprecipitation-based DNA methylome analysis

DNA methylation is an indispensible epigenetic modification required for regulating the expression of mammalian genomes. Immunoprecipitation-based methods for DNA methylome analysis are rapidly shifting the bottleneck in this field from data generation to data analysis, necessitating the development of better analytical tools. In particular, an inability to estimate absolute methylation levels remains a major analytical difficulty associated with immunoprecipitation-based DNA methylation profiling. To address this issue, we developed a cross-platform algorithm-Bayesian tool for methylation analysis (Batman)-for analyzing methylated DNA immunoprecipitation (MeDIP) profiles generated using oligonucleotide arrays (MeDIP-chip) or next-generation sequencing (MeDIP-seq). We developed the latter approach to provide a high-resolution whole-genome DNA methylation profile (DNA methylome) of a mammalian genome. Strong correlation of our data, obtained using mature human spermatozoa, with those obtained using bisulfite sequencing suggest that combining MeDIP-seq or MeDIP-chip with Batman provides a robust, quantitative and cost-effective functional genomic strategy for elucidating the function of DNA methylation.     

Genome-wide high throughput analysis of DNA methylation in eukaryotes

Cytosine methylation is the quintessential epigenetic mark. Two well-established methods, bisulfite sequencing and methyl-DNA immunoprecipitation (MeDIP) lend themselves to the genome-wide analysis of DNA methylation by high throughput sequencing. Here we provide an overview and brief review of these methods. We summarize our experience with MeDIP followed by high throughput Illumina/Solexa sequencing, exemplified by the analysis of the methylated fraction of the Neurospora crassa genome ("methylome"). We provide detailed methods for DNA isolation, processing and the generation of in vitro libraries for Illumina/Solexa sequencing. We discuss potential problems in the generation of sequencing libraries. Finally, we provide an overview of software that is appropriate for the analysis of high throughput sequencing data generated by Illumina/Solexa-type sequencing by synthesis, with a special emphasis on approaches and applications that can generate more accurate depictions of sequence reads that fall in repeated regions of a chosen reference genome.     

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.