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Methylation-sensitive high resolution melting (MS-HRM): a new approach for sensitive and high-throughput assessment of methylation

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Wojdacz, T. K., Dobrovic, A.·2007·Nucleic Acids Research

Abstract

In this article, we show that high resolution melting analysis (HRM) is a sensitive and specific method for the detection of methylation. Methylated DNA and unmethylated DNA acquire different sequences after bisulphite treatment resulting in PCR products with markedly different melting profiles. We used PCR to amplify both methylated and unmethylated sequences and assessed HRM for the determination of the methylation status of the MGMT promoter region. Reconstruction experiments showed that MGMT methylation could be detected at levels as low as 0.1%. Moreover, MS-HRM allows for estimation of the methylation level by comparing the melting profiles of unknown PCR products to the melting profiles of PCR products derived from standards with a known unmethylated to methylated template ratio. We used MS-HRM for the analysis of eight cell lines of known methylation status and a panel of colorectal cancer specimens. The simplicity and high reproducibility of the MS-HRM protocol makes MS-HRM the method of choice for methylation assessment in many diagnostic and research applications.

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Metadata

Authors
Wojdacz, T. K., & Dobrovic, A.
Venue
Nucleic Acids Research
Published
2007-03-01
Volume
35
Issue
6
Pages
e41-e41
ISSN
  • 0305-1048 (ISSN-L)
  • 1362-4962
OpenAlex
W2098442878
Cited by
551
References
0
FWCI
8.62
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Methylation-sensitive high resolution melting (MS-HRM): a new approach for sensitive and high-throughput assessment of methylation. https://app.cochat.ai/papers/10.1093/nar/gkm013
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Wojdacz, T. K., & Dobrovic, A. (2007). Methylation-sensitive high resolution melting (MS-HRM): a new approach for sensitive and high-throughput assessment of methylation. Nucleic Acids Research. https://doi.org/10.1093/nar/gkm013

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.