Nucleic Acids Research Advance Access originally published online on June 17, 2008
Nucleic Acids Research 2008 36(13):e80; doi:10.1093/nar/gkn378
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Nucleic Acids Research, 2008, Vol. 36, No. 13 e80
© 2008 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 |
Impact of whole genome amplification on analysis of copy number variants
1Genome Sciences Centre and 2Department of Pathology, BC Cancer Agency, Vancouver, BC, Canada
*To whom correspondence should be addressed. Tel: +1 604 877 6082; Fax: +1 604 876 3561; Email: mmarra{at}bcgsc.ca
Received November 28, 2007. Revised May 27, 2008. Accepted May 28, 2008.
Large-scale copy number variants (CNVs) have recently been recognized to play a role in human genome variation and disease. Approaches for analysis of CNVs in small samples such as microdissected tissues can be confounded by limited amounts of material. To facilitate analyses of such samples, whole genome amplification (WGA) techniques were developed. In this study, we explored the impact of Phi29 multiple-strand displacement amplification on detection of CNVs using oligonucleotide arrays. We extracted DNA from fresh frozen lymph node samples and used this for amplification and analysis on the Affymetrix Mapping 500k SNP array platform. We demonstrated that the WGA procedure introduces hundreds of potentially confounding CNV artifacts that can obscure detection of bona fide variants. Our analysis indicates that many artifacts are reproducible, and may correlate with proximity to chromosome ends and GC content. Pair-wise comparison of amplified products considerably reduced the number of apparent artifacts and partially restored the ability to detect real CNVs. Our results suggest WGA material may be appropriate for copy number analysis when amplified samples are compared to similarly amplified samples and that only the CNVs with the greatest significance values detected by such comparisons are likely to be representative of the unamplified samples.