Abstract: Careful analysis of microarray probe design should be an obligatory
component of MicroArray Quality Control (MACQ) project [Patterson et al.,
2006; Shi et al., 2006] initiated by the FDA (USA) in order to provide
quality control tools to researchers of gene expression profiles and to
translate the microarray technology from bench to bedside. The identification
and filtering of unreliable probesets are important preprocessing steps before
analysis of microarray data. These steps may result in an essential improvement
in the selection of differentially expressed genes, gene clustering and
construction of co-regulatory expression networks. We revised genome
localization of the Affymetrix U133A&B GeneChip initial (target) probe
sequences, and evaluated the impact of erroneous and poorly annotated target
sequences on the quality of gene expression data. We found about 25% of
Affymetrix target sequences overlapping with interspersed repeats that could
cause cross-hybridization effects. In total, discrepancies in target sequence
annotation account for up to ∼30% of 44692 Affymetrix
probesets. We introduce a novel quality control algorithm based on target
sequence mapping onto genome and GeneChip expression data analysis. To validate
the quality of probesets we used expression data from large, clinically and
genetically distinct groups of breast cancers (249 samples). For the first
time, we quantitatively evaluated the effect of repeats and other sources of
inadequate probe design on the specificity, reliability and discrimination
ability of Affymetrix probesets. We propose that only functionally reliable
Affymetrix probesets that passed our quality control algorithm (∼
86%) for gene expression analysis should be utilized. The target
sequence annotation and filtering is available upon request.
Keywords: U133 microarray, target sequences, noise signals, cross-hybridization, human genome, gene expression, sense-antisense gene pairs, interspersed repeats, breast cancer
