title: Cubic regression-based degree of correction predicts the performance of whole bisulfitome amplified DNA methylation analysis.
abstract: Epigenetic mechanisms, including DNA methylation, are important determinants in development and disease. There is a need for technologies capable of detecting small variations in methylation levels in an accurate and reproducible manner, even if only limited amounts of DNA are available (which is the case in many studies in humans). Quantitative methylation analysis of minute DNA amounts after whole bisulfitome amplification (qMAMBA) has been proposed as an alternative, but this technique has not been adequately standardized and no comparative study against conventional methods has been performed, that includes a wide range of methylation percentages and different target assays. We designed an experiment to compare the performance of qMAMBA and bisulfite-treated genomic (non-amplified) DNA pyrosequencing. Reactions were performed in duplicate for each technique in eight different target genes, using nine artificially constructed DNA samples with methylation levels ranging between 0% and 100% with intervals of 12.5%. Cubic polynomial curves were plotted from the experimental results and the real methylation values and the resulting equation was used to estimate new corrected data points. The use of the cubic regression-based correction benefits the accuracy and the power of discrimination in methylation studies. Additionally, dispersion of the new estimated data around a y = x line (R ( 2) ) served to fix a cutoff that can discriminate, with a single 9-point curve experiment, whether whole bisulfitome amplification and subsequent qMAMBA can produce accurate methylation results. Finally, even with an optimized reagent kit, DNA samples subjected to whole bisulfitome amplification enhance the preferential amplification of unmethylated alleles, and subtle changes in methylation levels cannot be detected confidently.
authors.affiliation: Immunogenetics Research Laboratory, Department of Genetics, Physical Anthropology and Animal Physiology, BioCruces Health Research Institute, University of the Basque Country UPV/EHU, Leioa, Basque Country, Spain.
authors.forename: Nora
authors.initials: N
authors.lastname: Fernandez-Jimenez
authors.forename: Leticia
authors.initials: L
authors.lastname: Plaza-Izurieta
authors.forename: Tamara
authors.initials: T
authors.lastname: Lopez-Euba
authors.forename: Amaia
authors.initials: A
authors.lastname: Jauregi-Miguel
authors.forename: Jose
authors.initials: J
authors.lastname: Ramon Bilbao
mesh_terms: D000483:Alleles; D018899:CpG Islands; D019175:DNA Methylation; D006801:Humans; D012044:Regression Analysis; D017422:Sequence Analysis, DNA / Q000379:methods*; D013447:Sulfites / Q000737:chemistry*
chemical_list: D013447:Sulfites; C042345:hydrogen sulfite