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Improvement in the Reproducibility and Accuracy of DNA Microarray Quantification by Optimizing Hybridization Conditions

Authors :
P. Scott Pine
Karol L. Thompson
Leming Shi
Tao Han
James C. Fuscoe
William S. Branham
Carrie L. Moland
Cathy D. Melvin
Source :
BMC Bioinformatics, Vol 7, Iss Suppl 2, p S17 (2006), BMC Bioinformatics
Publication Year :
2006
Publisher :
Springer Science and Business Media LLC, 2006.

Abstract

Background DNA microarrays, which have been increasingly used to monitor mRNA transcripts at a global level, can provide detailed insight into cellular processes involved in response to drugs and toxins. This is leading to new understandings of signaling networks that operate in the cell, and the molecular basis of diseases. Custom printed oligonucleotide arrays have proven to be an effective way to facilitate the applications of DNA microarray technology. A successful microarray experiment, however, involves many steps: well-designed oligonucleotide probes, printing, RNA extraction and labeling, hybridization, and imaging. Optimization is essential to generate reliable microarray data. Results Hybridization and washing steps are crucial for a successful microarray experiment. By following the hybridization and washing conditions recommended by an oligonucleotide provider, it was found that the expression ratios were compressed greater than expected and data analysis revealed a high degree of non-specific binding. A series of experiments was conducted using rat mixed tissue RNA reference material (MTRRM) and other RNA samples to optimize the hybridization and washing conditions. The optimized hybridization and washing conditions greatly reduced the non-specific binding and improved the accuracy of spot intensity measurements. Conclusion The results from the optimized hybridization and washing conditions greatly improved the reproducibility and accuracy of expression ratios. These experiments also suggested the importance of probe designs using better bioinformatics approaches and the need for common reference RNA samples for platform performance evaluation in order to fulfill the potential of DNA microarray technology.

Details

ISSN :
14712105
Volume :
7
Database :
OpenAIRE
Journal :
BMC Bioinformatics
Accession number :
edsair.doi.dedup.....1e8397b76e8ef70ee69895e263c752a6