The impact of quantitative optimization of hybridization conditions on gene expression analysis

Background: With the growing availability of entire genome sequences, an increasing number of scientists can exploit oligonucleotide microarrays for genome-scale expression studies. While probe-design is a major research area, relatively little work has been reported on the optimization of microarray protocols. Results: As shown in this study, suboptimal conditions can have considerable impact on biologically relevant observations. For example, deviation from the optimal temperature by one degree Celsius lead to a loss of up to 44% of differentially expressed genes identified. While genes from thousands of Gene Ontology categories were affected, transcription factors and other low-copy-number regulators were disproportionately lost. Calibrated protocols are thus required in order to take full advantage of the large dynamic range of microarrays. For an objective optimization of protocols we introduce an approach that maximizes the amount of information obtained per experiment. A compar...

• Type: Journal
• Year: 2011
• Where: BMCBI
• Authors: Peter Sykacek, David P. Kreil, Lisa A. Meadows, Richard P. Auburn, Bettina Fischer, Steven Russell, Gos Micklem
• Keywords: Artificial Intelligence, BMCBI 2011, Entire Genome Sequences, Genome-scale Expression Studies, Transcription Factor