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Evaluation of Quality-Control Criteria for Microarray Gene Expression Analysis

Departments of¹ Pathology,² Biostatistics, and³ Surgery, Virginia Commonwealth University, Richmond, VA.

^aAddress correspondence to this author at: Molecular Diagnostics Division, Department of Pathology, Virginia Commonwealth University, Clinical Support Center Building, Room 247, 403 North 13th St., PO Box 980248, Richmond, VA 23298-0248. Fax 804-225-4738; e-mail agonzalez{at}hsc.vcu.edu.

Background: Development of quality-control criteria to ensure reproducibility of microarray results for potential clinical application is still in its infancy.

Methods: In the present studies we developed quality-control criteria and evaluated their effect in microarray data analysis using total RNA from cell lines, frozen tumors, and a commercially available reference RNA. Quality-control criteria such as A₂₆₀/A₂₈₀ ratios, percentage of rRNA, and median size of cDNA and cRNA synthesis products were evaluated for robustness in microarray analysis. Furthermore, precision studies using a reference material were performed on the Affymetrix® HG-U133A high-density oligonucleotide microarrays. The same reference RNA sample was examined in 16 different chips run on 2 different days in the four different modules of the Affymetrix fluidics workstation. Fresh and frozen fragmented cRNAs were also compared. An ANOVA model was fit to identify the main sources of variation.

Results: Good-quality samples showed >30% rRNA in the electropherograms and cDNA and cRNA synthesis products with median sizes of 2.0 and 3.0 kb, respectively. Precision studies showed that the main source of variation was the day-to-day variability, minimally affecting hybridization exogenous control genes. Altogether, the results showed that the Affymetrix Genechip® system is highly reproducible when RNA that meet the quality-control criteria are used (overall P >0.01).

Conclusions: These results confirm the need to establish defined quality-control criteria for sample quality to distinguish between analytical and biological variability.

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