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Optimizing methodologies for PCR-based DNA methylation analysis
 
Hernán G. Hernández1,2, 3, M. Yat Tse4, Stephen C. Pang4, Humberto Arboleda2, and Diego A. Forero1
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The quantitative aspect of MethyLight has been explored since its inception. Analyses using different ratios of methylated to unmethylated DNA have been employed to verify the linearity of this quantitative assay, with a high linear correlation found between the dilution ratios and the MethyLight MP measurements (55,57). MethyLight has shown higher levels of accuracy and lower rates of false negatives when compared with previously described techniques (45,55). For this reason, MethyLight is frequently used to validate other techniques for DNA methylation studies (36). However, unlike MS-HRM (36), the most commonly used MethyLight technique cannot detect heterogeneous methylation in a sample because the MethyLight primers and probes are designed to measure a specific methylation pattern (fully methylated).

Primers and probe design considerations: In a MethyLight assay, it is necessary to normalize each qPCR reaction using sets of primers and probes that bind a converted DNA region independent of its methylation status (Figure 3A, top). Therefore, each MethyLight assay should include both an ROI amplification reaction and an MIP reaction for the control region. Currently, commercially available Beacon Designer software (Primer Biosoft, Palo Alto, CA) is the method of choice for MethyLight primer design. This program is able to design MethyLight assays, but in practice it is restricted to CpG islands, possibly because CpG density in the island shores and in some promoters lacking islands is low.

Data analysis: Depending on the MethyLight design, relative fluorescence units (RFUs) should be used to calculate the methylation percentage. For the common MethyLight design described in this section, the broadly accepted determination formula for DNA methylation percentage is shown in Equation 1 (55).

In order to evaluate the methylation status of an ROI using MethyLight, it is best to select a previously validated primer/probe set for that ROI if a similar research question is to be addressed. Houshdaran et al. (58) have performed ∼300 MethyLight assays and have made the primer and probe sequences available.

Example of MethyLight selection: MethyLight is the technique of choice when a study requires accurate quantitative assessment of DNA methylation. It has been used in a number of cancer associated DNA methylation studies, including the development of an assay to measure the presence of methylated alleles in three genes associated with colorectal cancer (59). Here, the assay was focused on clinical applications of cancer detection. It should be noted that the cost of using TaqMan probes can be higher than other real-time PCR methods that utilize cheaper intercalating dyes (46). This is of particular importance if the sample size of the proposed study is large, or if a significant number of ROIs is to be assessed.

Methylation-sensitive high resolution melting

In the DNA double helix, a cytosine and a guanine of complementary strands are linked by a triple hydrogen bond while a thymine and an adenine are joined by a double hydrogen bond (36). Therefore, base composition can directly influence the thermodynamic behavior of DNA in a melting analysis. Tm is defined as the temperature at which the PCR product dissociates into two single strands and a sharp drop in fluorescence of a DNA intercalating dye is observed (37). This basic principle can be used to discriminate between methylated and unmethylated alleles following bisulfite conversion. Distinction between alleles is achieved through Tm analysis of the MIP-PCR products in the ROI, in which the methylated allele usually has a higher Tm than the unmethylated allele (60) (Figure 3D).





Initially, Worm et al. (61) described an in-tube melting protocol for analyzing DNA methylation prior to the development of high resolution melting (HRM) technology. After technical improvements in melting assays, Wojdacz et al. developed a DNA methylation assay implementing HRM technology: the methylation-sensitive high-resolution melting (MS-HRM) techniques (36). The MS-HRM methodology consists of real-time PCR using bisulfite-converted DNA (regardless of the methylation status) and melting analysis of PCR products (HRM) to discriminate the ROI methylation status reflected in the thermodynamic behavior of the MS-HRM amplicon.

The MS-HRM method enables assessment of the percentage of the methylated allele present for a particular sample in an ROI. This is possible through comparison with melting standard curves created by different dilution ratios of methylated and unmethylated DNA controls (37). Since the technique analyzes the melting properties of the final PCR products, MS-HRM not only evaluates fully methylated alleles in proportion to fully unmethylated ones, but is also able to detect heterogeneously methylated samples (62).

PCR bias: As for other MIP based amplifications, potential PCR bias for MS-HRM was evaluated during development of the technique (21). MS-HRM showed a strong amplification bias toward unmethylated sequences when the classic recommendations for primer design stated by Clark et al. were followed (25). In contrast, using the recommendations of Wojdacz et al. for primer design (21), variations of the annealing temperature in the PCR cycling step allowed for control of PCR bias (21). Monitoring of real-time PCR amplification establishes an additional quality control step for MS-HRM experiments (13). Similar to digital-BSP, digital MS-HRM is also useful for reducing PCR bias (62). Considering the possibility of PCR bias, it is important to highlight that quantitative methylation analysis with MS-HRM is based on the assumption that methylation levels of CpG sites between the primers is the same as methylation levels of CpG sites covered by the primers.

Primer design considerations: MS-HRM primer design follows the same general principles of classic MIP design as previously detailed by Clark et al. (25). However, in order to compensate for PCR bias, there are new recommendations for MS-HRM primer design that advise inclusion of one or two CpG annealing sites (located as far as possible from the 3′end of the primers to avoid methylation specific amplification) (Figure 3C) (60). Currently, there are no programs for MS-HRM primer design that incorporate the new recommendations to compensate for PCR bias. Finally, several programs such as OligoCalc, Poland, and MELT (Table 4) can predict the melting curves of the PCR products.

Data Analysis: Wojdacz et al. (36,37) proposed a method for estimating methylation levels by comparing the melting patterns of standard templates with known proportions of methylated and unmethylated DNA controls to the melting patterns found in a sample. The semiquantitative estimate is based on similarities in HRM patterns without a mathematical approach for calculating the DNA methylation percentage. More recently, Tse et al. (2011) implemented an MS-HRM approach to quantify the methylation status of each sample with high reproducibility. Peak-height and area under-the-curve from the normalized, temperature-shifted difference curves were used to generate linear standard curves (13) (Figure 3D). Quantitative data were obtained by interpolation of the first derivative of the normalized melt curves, generated by the linear regression analysis of the standard curve (13). When heterogeneous DNA methylation patterns are present in a sample, HRM analysis will identify such heterogeneity by the complex shape of the melting curves; however, in such cases quantitative HRM measurement is not possible (62). The presence of SNPs in the amplicon region could generate additional variations in the melting profiles (37).

Examples of MS-HRM selection: MSP-based assays only evaluate DNA methylation for CpG sites present in the primer binding region (usually <25 bp per primer). In contrast, MS-HRM evaluates all of the CpGs banked by the primers (usually >80 bp), regardless of the methylation status of CpGs within the primer binding site (36). Therefore, MS-HRM provides the ability to evaluate a larger genomic region when compared with MSP-related techniques (Figure 4) (11). MS-HRM is a good choice for quantitative determination of DNA methylation levels, when sequence level detail is not required (63). A good example of the usage of MS-HRM is a colorectal cancer study where the authors distinguished different stages of the disease and their correlations with the quantity of DNA methylation (64).





Proper controls for PCR-based DNA methylation analysis

In addition to the controls used in conventional PCR assays, other steps should be taken to verify the accuracy of DNA methylation data generated in PCR-based assays. Unconverted genomic DNA is an essential control that should be included in all optimization processes for PCR-based DNA methylation assays; it provides information on the amplification of non-converted DNA with primers that are specific for the converted DNA. For specific assays, amplification from bisulfite-treated DNA should show a clear difference from any possible result using non-converted DNA.

In one of the pioneering MSP studies, Herman et al. verified primer specificity for the bisulfite modified p16 sequence using untreated DNA in reactions with either methylated-specific or unmethylated-specific primers (11). As expected, no amplification was found when non-converted DNA was used as a template. Nonetheless, several reports of MSP standardization did not include or report this kind of control (65,66).

Similarly, the use of non-converted DNA is also recommended when using the MS-HRM technique during assay optimization (37). This type of control is the easiest to include but, paradoxically, is the controal most commonly omitted or not reported (63). It allows experimental verification of the specificity of the assay for converted DNA. In most cases, there should be no amplification products; however, in some instances products will be amplified that can be easily identified when compared with the converted DNA (37).

Use of fully methylated and unmethylated DNA is a critical experimental control as well. It should be noted that DNA considered to be fully unmethylated comes from a variety of different sources. The practice of using DNA obtained from peripheral blood mononuclear cells (PBMC) as a fully unmethylated DNA control is valid in cases where the samples are indeed completely unmethylated at the loci of interest. Several reports have focused on detecting DNA methylation status in peripheral blood, showing biologically important methylation levels for multiple genes (52,67). For example, low level methylation of many cancer-relevant genes may be found in the PBMCs from normal individuals. Therefore, the indiscriminate use of DNA from PBMCs as a negative control in sensitive assays for DNA methylation detection may be particularly problematic (52).

Manufacturers of commercially available DNA controls have different strategies for providing fully methylated and unmethylated DNA. For example, fully non-methylated kits from Zymo and Millipore use DNA from cells that contain genetic knockouts of 2 key DNA methyltransferases, thus reducing methylation levels by more than 95% (68).

Fully methylated DNA can be obtained from M.SssI-methylated DNA from, among many sources, double knockout cells for DNMT1 and DNMT3b (Table 2). Another alternative is to use the product from whole genome amplification (WGA) with kits such as REPLI-g (Qiagen), which does not reproduce the DNA methylation pattern and has a theoretical methylation level of less than 10−6. However, this amplification approach may carry the risk of reduced representation of the loci of interest (69). Therefore, the use of identical amounts of methylated and unmethylated controls derived from the same class of template (genomic DNA or WGA-products) could guarantee that equivalent amounts of effective templates are included.

Discussion

Studying DNA methylation for a candidate ROI using PCR-based methods is a topic of present and future importance. There are many advantages of genome-wide platforms; however, PCR-based techniques permit detailed analysis of specific regions of the genome, including CpG island shores. In addition, the associated costs of implementing and executing PCR-based techniques are lower, allowing the initial study of several candidate ROIs. PCR-based approaches also offer the advantage of a lower burden of false discoveries and the ability to confirm a large number of ROIs identified in genome-wide screening of a few samples (70).

DNA methylation analysis using pyrosequencing is a quantitative approach that does not require a cloning step, but presents the risk of PCR bias, similar to BSP. More importantly, pyrosequencing instrumentation is not commonly available in a general laboratory. For interested readers, comparisons and discussions of pyrosequencing techniques are available elsewhere (71).

This article highlights several considerations for PCR-based DNA methylation studies. The approaches reviewed here have different advantages and disadvantages that should be evaluated before starting any DNA methylation study. Similarly, it is clear that the different PCR-based techniques discussed here have differences in CpG coverage and possibility for quantitation (Figure 4). A comparison of all PCR-based DNA methylation techniques is presented in Table 5.

Table 5. 





Several considerations concerning PCR-based methods for DNA methylation analysis will be crucial for the consolidation of the field of molecular epigenetics. Current needs in this field include (i) detailed experimental comparisons of results obtained with different PCR-based techniques (72), (ii) the availability of a large number of predesigned PCR-based DNA methylation assays to facilitate broad use, (iii) the implementation of minimum reporting guidelines for manuscripts describing results of PCR-based analyses of DNA methylation, including details of experimental conditions such as controls, primer sequences, and programs used for primer design (73), (iv) the further development of additional PCR-based techniques that allow DNA methylation measurements in a more quantitative and reproducible way (5), and (v) the implementation of automatic and multiplexed protocols for DNA methylation using currently available techniques to improve efficiency and reduce costs (59). For readers interested in genome-wide DNA methylation analysis, we recommend two available review articles (74,75). Finally, it is critical to keep in mind that the results of PCR-based DNA methylation methodologies are reliable only in an experimental setting with adequate methodological controls.

Acknowledgments

This work was supported by grants from Colciencias (Contract # 401-2011), UAN-VCTI, and UNAL-DIB. HGH is a recipient of a PhD fellowship from Colciencias. The authors would like to thank the anonymous reviewers for their important comments and suggestions.

Competing interests

The authors declare no competing interests.

Correspondence
Address correspondence to Diego A. Forero, Laboratory of NeuroPsychiatric Genetics, Biomedical Sciences Research Group, School of Medicine, Universidad Antonio Nariño, Bogotá, Colombia. E-mail: [email protected]">[email protected]

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