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Epigenetic mechanisms are likely to play an important role in the regulation of metabolism and body weight through gene-nutrient interactions. This review focuses on methods for analyzing one of the most important epigenetic mechanisms, DNA methylation, from single nucleotide to global measurement depending on the study goal and scope. In addition, this study highlights the major principles and methods for DNA methylation analysis with emphasis on nutritional applications. Recent developments concerning epigenetic technologies are showing promising results of DNA methylation levels at a single-base resolution and provide the ability to differentiate between 5-methylcytosine and other nucleotide modifications such as 5-hydroxymethylcytosine. A large number of methods can be used for the analysis of DNA methylation such as pyrosequencing TM , primer extension or real-time PCR methods, and genome-wide DNA methylation profile from microarray or sequencing-based methods. Researchers should conduct a preliminary analysis focused on the type of validation and information provided by each technique in order to select the best method fitting for their nutritional research interests.

DNA methylation is a key event regulating gene expression. DNA methylation analysis plays a pivotal role in unlocking association of epigenetic events with cancer. However, simultaneous evaluation of the methylation status of multiple genes is still a technical challenge. Microarray is a promising approach for high-throughput analysis of the methylation status at numerous CpG sites within multiple genes of interest. In this dissertation study, we conducted a systematic study to examine the use of microarray methods for methylation analysis.First, a robust universal microarray was established with more flexible in design and content, and potential cost saving over commercial arrays. In order to produce high quality microarray data, we optimized the attachment chemistry for the modified oligonucleotides, searched for the good combination of fluorescent dyes, and hybridization conditions. To improve the specificity of the microarray, we conducted a study to experimentally search for a set of highly discriminative tag Sequences.Second, SBE-TAGs microarray was successfully adapted from the SNP detection for methylation analysis of multiple genes. SBE-TAGs microarray performed quite well in multiplex methylation analysis of cell lines if a standard calibration curve method was used. 10 CpG sites of 9 tumor suppressor genes (MGMT, GATA4, HLTF, SOCS1, p16, RASSF2, CHFR, TPEF, and Reprimo) were selected for this study.Third, a novel method called CHZMA (Competing-Hybridization- Zipcode-MicroArray) was developed for methylation analysis of tumor tissue samples, which is based on two steps of hybridization to achieve the specific detection of methylation on microarray. On the basis of analysis of seven genes (MGMT, GATA4, HLTF, SOCS1, RASSF2, ER, 3-OST-2), we found that the CHZMA assay can robustly detect methylation of multiple genes in the samples containing as low as 10% of methylated DNA. With the strict control group test and statistical analysis, CHZMA can be a good high-throughput method in place of MSP for methylation analysis of tumor tissue samples.These studies provide reliable and robust tools for methylation analysis, and could be used for cancer prognosis and diagnosis in the future.