Nucleic Acids Research Advance Access originally published online on May 27, 2009
Nucleic Acids Research 2009 37(12):e89; doi:10.1093/nar/gkp413
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Nucleic Acids Research, 2009, Vol. 37, No. 12 e89
© 2009 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Methods Online |
Methylation detection oligonucleotide microarray analysis: a high-resolution method for detection of CpG island methylation
1Philips Research North America, Briarcliff Manor, NY 10510, USA, 2Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, 3Department of Genetics, Institute for Cancer Research, 4Department of Oncology, Norwegian Radium Hospital, Rikshospitalet University Hospital and 5Faculty Division, The Norwegian Radium Hospital Faculty of Medicine, University of Oslo, Oslo, Norway
*To whom correspondence should be addressed. Tel: +1 516 422 4138; Fax: +1 516 422 4109; Email: lucito{at}cshl.edu
Received October 9, 2008. Revised April 29, 2009. Accepted May 2, 2009.
Methylation of CpG islands associated with genes can affect the expression of the proximal gene, and methylation of non-associated CpG islands correlates to genomic instability. This epigenetic modification has been shown to be important in many pathologies, from development and disease to cancer. We report the development of a novel high-resolution microarray that detects the methylation status of over 25 000 CpG islands in the human genome. Experiments were performed to demonstrate low system noise in the methodology and that the array probes have a high signal to noise ratio. Methylation measurements between different cell lines were validated demonstrating the accuracy of measurement. We then identified alterations in CpG islands, both those associated with gene promoters, as well as non-promoter-associated islands in a set of breast and ovarian tumors. We demonstrate that this methodology accurately identifies methylation profiles in cancer and in principle it can differentiate any CpG methylation alterations and can be adapted to analyze other species.