Three-color cDNA microarrays with prehybridization quality control yield gene expression data comparable to that of commercial platforms

Abstract

Despite their lower cost and high content flexibility, a limitation of in-house-prepared arrays has been their susceptibility to quality control (QC) issues and lack of QC standards across laboratories. Therefore, we developed a novel three-color array system that allows prehybridization QC as well as the Matarray software to facilitate acquisition of accurate gene expression data. In this study, we compared performance of our rat cDNA array to the Affymetrix RG-U34A and Agilent G4130A arrays using 2,824 UniGenes represented on all three arrays. Before data filtering, poor interplatform agreement was observed; however, after data filtering, differentially expressed UniGenes exhibited correlation coefficients of 0.91, 0.88, and 0.92 between the Affymetrix vs. Agilent, Affymetrix vs. cDNA, and Agilent vs. cDNA arrays, respectively. The Affymetrix, Agilent, and cDNA arrays agreed well with quantitative RT-PCR conducted on 42 UniGenes, yielding correlation coefficients of 0.90, 0.90, and 0.96, respectively. Each platform underestimated ratios relative to quantitative RT-PCR, possessing respective slopes of 0.86 ( R2 = 0.81), 0.65 ( R2 = 0.81), and 0.70 ( R2 = 0.92). Overall, these data show that the combination of our novel technical and analytic approaches yield an accurate platform for functional genomics that is concordant with commercial discovery arrays in terms of identifying regulated genes and pathways.

Correlation of mRNA and protein levels: Cell type-specific gene expression of cluster designation antigens in the prostate

“…These previous studies have discovered several factors that effect data comparison across different microarray platforms. In addition to our findings, updated annotation through RefSeq or UniGene databases has repeatedly been shown to increase cross-platform content and consistency [ 27 - 31 ]. Biological variability, and inter-laboratory variation have also been previously implicated as sources of cross-platform data discrepancies [ 32 - 34 ].…”

Nanog regulates molecules involved in stemness and cell cycle‐signaling pathway for maintenance of pluripotency of P19 embryonal carcinoma stem cells

“…Previous publications have suggested that some of the variability in cross‐platform studies could be due to annotation problems that make it difficult to reconcile the genes measured by specific probes (Mecham et al, 2004; Irizarry et al, 2005; Shi et al, 2006a). For example, a 3.1% (5/160) error rate in clone annotation were found by analyzing 160 randomly selected clones obtained from 30 different source plate (Hessner et al, 2006). Microarray platforms that use different probe sequences for detection of target gene could also have introduced a bias between different array platforms.…”

Two-Laser, Large-Field Hyperspectral Microarray Scanner for the Analysis of Multicolor Microarrays

“…The necessity of quality control spotting on microarrays fabricated in-house is well recognized, and similar approaches, i.e., using one spectral channel for quality control, were developed for two-color gene expression arrays. It was demonstrated that spotting quality control can provide increased performance of arrays spotted in-house when compared to commercial ones . At present, four-color genotyping arrays are exclusively produced by spotting, especially APEX arrays that need free 3′-ends of immobilized oligonucleotides. , Because the hyperspectral scanner we describe is able to discriminate five overlapping spectra (Figure ), it opens the way for the further development of four-color genotyping microarrays containing internal spotting quality controls in the form of spotted prelabeled oligonucleotides or labeled oligonucleotides added to the hybridization mixtures subsequently. , More than 10 years ago, Schena and colleagues introduced cyanine dyes for the analysis of differential gene expression by using spotted cDNA microarrays on microscope slides .…”