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Nucleic Acids Research, 2003, Vol. 31, No. 4 e14
© 2003 Oxford University Press

Three color cDNA microarrays: quantitative assessment through the use of fluorescein-labeled probes

Martin J. Hessner*, Xujing Wang, Katie Hulse, Lisa Meyer, Yan Wu, Steven Nye, Sun-Wei Guo and Soumitra Ghosh

The Max McGee National Research Center for Juvenile Diabetes, The Medical College of Wisconsin and Children’s Hospital of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA

*To whom correspondence should be addressed. Tel: +1 414 456 4496; Fax: +1 414 456 6663; Email: mhessner{at}mcw.edu

Gene expression studies using microarrays have great potential to generate new insights into human disease pathogenesis, but data quality remains a major obstacle. In particular, there does not exist a method to determine prior to hybridization whether an array will yield high quality data, given good study design and target preparation. We have solved this problem through development of a three-color cDNA microarray platform where printed probes are fluorescein labeled, but are spectrally compatible with Cy3 and Cy5 dye-labeled targets when using confocal laser scanners possessing narrow bandwidths. This approach enables prehybridization evaluation of array/spot morphology, DNA deposition and retention and background levels. By using these measurements and the intra-slide coefficient of variation for fluorescence intensity we show that slides in the same batch are not equivalent and measurable prehybridization parameters can be predictive of hybridization performance as determined by replicate consistency. When hybridizing target derived from two cell lines to high and low quality replicate pairs (n = 50 pairs), a direct and significant relationship between prehybridization signal-to-background noise and post-hybridization reproducibility (R2 = 0.80, P < 0.001) was observed. We therefore conclude that slide selection based upon prehybridization quality scores will greatly benefit the ability to generate reliable gene expression data.


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