Improving the sensitivity and specificity of gene expression analysis in highly related organisms through the use of electronic masks.

DNA microarrays are powerful tools for comparing gene expression profiles from closely related organisms. However, a single microarray design is frequently used in these studies. Therefore, the levels of certain transcripts can be grossly underestimated due to sequence differences between the transcripts and the arrayed DNA probes. Here, we seek to improve the sensitivity and specificity of oligonucleotide microarray-based gene expression analysis by using genomic sequence information to predict the hybridization efficiency of orthologous transcripts to a given microarray. To test our approach, we examine hybridization patterns from three Escherichia coli strains on E.coli K-12 MG1655 gene expression microarrays. We create electronic mask files to discard data from probes predicted to have poor hybridization sensitivity and specificity to cDNA targets from each strain. We increased the accuracy of gene expression analysis and identified genes that cannot be accurately interrogated in each strain using these microarrays. Overall, these studies provide guidelines for designing effective electronic masks for gene expression analysis in organisms where substantial genome sequence information is available.