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Experimental factors affecting the robustness of DNA methylation analysis

View Article: PubMed Central - PubMed

ABSTRACT

Diverging methylation frequencies are often reported for the same locus in the same disease, underscoring the need for limiting technical variability in DNA methylation analyses. We have investigated seven likely sources of variability at different steps of bisulfite PCR-based DNA methylation analyses using a fully automated quantitative methylation-specific PCR setup of six gene promoters across 20 colon cancer cell lines. Based on >15,000 individual PCRs, all tested parameters affected the normalized percent of methylated reference (PMR) differences, with a fourfold varying magnitude. Additionally, large variations were observed across the six genes analyzed. The highest variation was seen using single-copy genes as reference for normalization, followed by different amounts of template in the PCR, different amounts of DNA in the bisulfite reaction, and storage of bisulfite converted samples. Finally, when a highly standardized pipeline was repeated, the difference in PMR value for the same assay in the same cell line was on average limited to five (on a 0–100 scale). In conclusion, a standardized pipeline is essential for consistent methylation results, where parameters are kept constant for all samples. Nevertheless, a certain level of variation in methylation values must be expected, underscoring the need for careful interpretation of data.

No MeSH data available.


Normalized PMR differences for individual assays and cell lines, per tested parameter.Each cell line is represented by an individual dot. Each plot represents a comparison between the default and an alternative parameter. The roman numerals correspond to the pipeline in Fig. 1. Each plot for the storage experiments (V), represents an average of four rounds of analysis; two repeated rounds with both bisulfite kits (results for individual rounds are shown in Supplementary Fig. S6). Cases with a PMRalternative = 0 and PMRdefault ≠ 0 contributes with a normalized PMR difference of 1.0, and are indicated with an unfilled dot. Abbreviations: Norm. PMR diff., normalized PMR difference.
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f2: Normalized PMR differences for individual assays and cell lines, per tested parameter.Each cell line is represented by an individual dot. Each plot represents a comparison between the default and an alternative parameter. The roman numerals correspond to the pipeline in Fig. 1. Each plot for the storage experiments (V), represents an average of four rounds of analysis; two repeated rounds with both bisulfite kits (results for individual rounds are shown in Supplementary Fig. S6). Cases with a PMRalternative = 0 and PMRdefault ≠ 0 contributes with a normalized PMR difference of 1.0, and are indicated with an unfilled dot. Abbreviations: Norm. PMR diff., normalized PMR difference.

Mentions: Over 15,000 individual PCRs were performed in the present study (see Supplementary Information) involving evaluation of various pipeline parameters across six different gene promoters and 20 colon cancer cell lines (Fig. 1). The normalized PMR differences per locus and cell line for the tested parameters are summarized in Fig. 2. The reference for normalization (VII in Figs 1 and 2) and the template amount in the PCR (VI) caused the largest normalized PMR differences. Storage (V), DNA input in the bisulfite conversion (III), and type of bisulfite kit (IV) caused intermediate levels of difference. Different investigators (I) and different time points of analysis (II) resulted in the smallest differences across the tested parameters.


Experimental factors affecting the robustness of DNA methylation analysis
Normalized PMR differences for individual assays and cell lines, per tested parameter.Each cell line is represented by an individual dot. Each plot represents a comparison between the default and an alternative parameter. The roman numerals correspond to the pipeline in Fig. 1. Each plot for the storage experiments (V), represents an average of four rounds of analysis; two repeated rounds with both bisulfite kits (results for individual rounds are shown in Supplementary Fig. S6). Cases with a PMRalternative = 0 and PMRdefault ≠ 0 contributes with a normalized PMR difference of 1.0, and are indicated with an unfilled dot. Abbreviations: Norm. PMR diff., normalized PMR difference.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5037394&req=5

f2: Normalized PMR differences for individual assays and cell lines, per tested parameter.Each cell line is represented by an individual dot. Each plot represents a comparison between the default and an alternative parameter. The roman numerals correspond to the pipeline in Fig. 1. Each plot for the storage experiments (V), represents an average of four rounds of analysis; two repeated rounds with both bisulfite kits (results for individual rounds are shown in Supplementary Fig. S6). Cases with a PMRalternative = 0 and PMRdefault ≠ 0 contributes with a normalized PMR difference of 1.0, and are indicated with an unfilled dot. Abbreviations: Norm. PMR diff., normalized PMR difference.
Mentions: Over 15,000 individual PCRs were performed in the present study (see Supplementary Information) involving evaluation of various pipeline parameters across six different gene promoters and 20 colon cancer cell lines (Fig. 1). The normalized PMR differences per locus and cell line for the tested parameters are summarized in Fig. 2. The reference for normalization (VII in Figs 1 and 2) and the template amount in the PCR (VI) caused the largest normalized PMR differences. Storage (V), DNA input in the bisulfite conversion (III), and type of bisulfite kit (IV) caused intermediate levels of difference. Different investigators (I) and different time points of analysis (II) resulted in the smallest differences across the tested parameters.

View Article: PubMed Central - PubMed

ABSTRACT

Diverging methylation frequencies are often reported for the same locus in the same disease, underscoring the need for limiting technical variability in DNA methylation analyses. We have investigated seven likely sources of variability at different steps of bisulfite PCR-based DNA methylation analyses using a fully automated quantitative methylation-specific PCR setup of six gene promoters across 20 colon cancer cell lines. Based on >15,000 individual PCRs, all tested parameters affected the normalized percent of methylated reference (PMR) differences, with a fourfold varying magnitude. Additionally, large variations were observed across the six genes analyzed. The highest variation was seen using single-copy genes as reference for normalization, followed by different amounts of template in the PCR, different amounts of DNA in the bisulfite reaction, and storage of bisulfite converted samples. Finally, when a highly standardized pipeline was repeated, the difference in PMR value for the same assay in the same cell line was on average limited to five (on a 0–100 scale). In conclusion, a standardized pipeline is essential for consistent methylation results, where parameters are kept constant for all samples. Nevertheless, a certain level of variation in methylation values must be expected, underscoring the need for careful interpretation of data.

No MeSH data available.