Nucleic Acids Research Advance Access originally published online on July 2, 2008
Nucleic Acids Research 2008 36(13):4417-4423; doi:10.1093/nar/gkn409
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Nucleic Acids Research, 2008, Vol. 36, No. 13 4417-4423
© 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.
Genomics |
Effect of polymorphisms within probe–target sequences on olignonucleotide microarray experiments
1Department of Human Genetics, McGill University, Montreal, QC, Canada and 2McGill University and Genome Quebec Innovation Center, Montreal, QC, Canada
*To whom correspondence should be addressed. Tel: 514 398 3311 X00292; Fax: 514 389 1790; Email: davidbenovoy{at}gmail.com
Received April 17, 2008. Revised June 9, 2008. Accepted June 10, 2008.
Hybridization-based technologies, such as microarrays, rely on precise probe-target interactions to ensure specific and accurate measurement of RNA expression. Polymorphisms present in the probe–target sequences have been shown to alter probe- hybridization affinities, leading to reduced signal intensity measurements and resulting in false-positive results. Here, we characterize this effect on exon and gene expression estimates derived from the Affymetrix Exon Array. We conducted an association analysis between expression levels of probes, exons and transcripts and the genotypes of neighboring SNPs in 57 CEU HapMap individuals. We quantified the dependence of the effect of genotype on signal intensity with respect to the number of polymorphisms within target sequences, number of affected probes and position of the polymorphism within each probe. The effect of SNPs is quite severe and leads to considerable false-positive rates, particularly when the analysis is performed at the exon level and aimed at detecting alternative splicing events. Finally, we propose simple solutions, based on ‘masking’ probes, which are putatively affected by polymorphisms and show that such strategy results in a large decrease in false-positive rates, with a very modest reduction in coverage of the transcriptome.