Performance of Different Analytical Software Packages in Quantification of DNA Methylation by Pyrosequencing

Pyrosequencing has emerged as an alternative method of nucleic acid sequencing, well suited for many applications which aim to characterize single nucleotide polymorphisms, mutations, microbial types and CpG methylation in the target DNA. The commercially available pyrosequencing systems can harbor two different types of software which allow analysis in AQ or CpG mode, respectively, both widely employed for DNA methylation analysis.

Aim of the study was to assess the performance for DNA methylation analysis at CpG sites of the two pyrosequencing software which allow analysis in AQ or CpG mode, respectively. Despite CpG mode having been specifically generated for CpG methylation quantification, many investigations on this topic have been carried out with AQ mode. As proof of equivalent performance of the two software for this type of analysis is not available, the focus of this paper was to evaluate if the two modes currently used for CpG methylation assessment by pyrosequencing may give overlapping results.

We compared the performance of the two software in quantifying DNA methylation in the promoter of selected genes (GSTP1, MGMT, LINE-1) by testing two case series which include DNA from paraffin embedded prostate cancer tissues (PC study, N = 36) and DNA from blood fractions of healthy people (DD study, N = 28), respectively.

We found discrepancy in the two pyrosequencing software-based quality assignment of DNA methylation assays. Compared to the software for analysis in the AQ mode, less permissive criteria are supported by the Pyro Q-CpG software, which enables analysis in CpG mode. CpG mode warns the operators about potential unsatisfactory performance of the assay and ensures a more accurate quantitative evaluation of DNA methylation at CpG sites.

The implementation of CpG mode is strongly advisable in order to improve the reliability of the methylation analysis results achievable by pyrosequencing.

PloS one. 2016 Mar 02*** epublish ***

Chiara Grasso, Morena Trevisan, Valentina Fiano, Valentina Tarallo, Laura De Marco, Carlotta Sacerdote, Lorenzo Richiardi, Franco Merletti, Anna Gillio-Tos

Cancer Epidemiology Unit - C.E.R.M.S, Department of Medical Sciences, University of Turin, Turin, Italy., Cancer Epidemiology Unit - C.E.R.M.S, Department of Medical Sciences, University of Turin, Turin, Italy., Cancer Epidemiology Unit - C.E.R.M.S, Department of Medical Sciences, University of Turin, Turin, Italy., Cancer Epidemiology Unit - C.E.R.M.S, Department of Medical Sciences, University of Turin, Turin, Italy., Cancer Epidemiology Unit - C.E.R.M.S, Department of Medical Sciences, University of Turin, Turin, Italy., Cancer Epidemiology Unit, Department of Medical Sciences, City of Health and Science Hospital, Turin, Italy., Cancer Epidemiology Unit - C.E.R.M.S, Department of Medical Sciences, University of Turin, Turin, Italy., Cancer Epidemiology Unit - C.E.R.M.S, Department of Medical Sciences, University of Turin, Turin, Italy., Cancer Epidemiology Unit - C.E.R.M.S, Department of Medical Sciences, University of Turin, Turin, Italy.