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Open Access Technical Note

A refined, rapid and reproducible high resolution melt (HRM)-based method suitable for quantification of global LINE-1 repetitive element methylation

M Yat Tse1*, Janet E Ashbury2, Nora Zwingerman2, Will D King2, Sherry AM Taylor3 and Stephen C Pang1*

Author Affiliations

1 Department of Anatomy and Cell Biology, Queen's University, Kingston, ON, Canada

2 Department of Community Health and Epidemiology, Queen's University, Kingston, ON, Canada

3 Department of Laboratory Medicine, Saint John Regional Hospital, Horizon Health Network and Department of Pathology, Dalhousie University, Halifax, NS, Canada

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BMC Research Notes 2011, 4:565  doi:10.1186/1756-0500-4-565

Published: 28 December 2011

Abstract

Background

The methylation of DNA is recognized as a key mechanism in the regulation of genomic stability and evidence for its role in the development of cancer is accumulating. LINE-1 methylation status represents a surrogate measure of genome-wide methylation.

Findings

Using high resolution melt (HRM) curve analysis technology, we have established an in-tube assay that is linear (r > 0.9986) with a high amplification efficiency (90-105%), capable of discriminating between partcipant samples with small differences in methylation, and suitable for quantifying a wide range of LINE-1 methylation levels (0-100%)--including the biologically relevant range of 50-90% expected in human DNA. We have optimized this procedure to perform using 2 μg of starting DNA and 2 ng of bisulfite-converted DNA for each PCR reaction. Intra- and inter-assay coefficients of variation were 1.44% and 0.49%, respectively, supporting the high reproducibility and precision of this approach.

Conclusions

In summary, this is a completely linear, quantitative HRM PCR method developed for the measurement of LINE-1 methylation. This cost-efficient, refined and reproducible assay can be performed using minimal amounts of starting DNA. These features make our assay suitable for high throughput analysis of multiple samples from large population-based studies.