Comparison of Smoking-Induced Gene Expression on Affymetrix Exon and 3'-Based Expression Arrays

Xiaoling Zhang[1] (zhangxl@bu.edu)
Gang Liu[2] (gliu@lung.bumc.bu.edu)
Marc E Lenburg[3] (mlenburg@bu.edu)
Avrum Spira[2] (aspira@bu.edu)

[1]Bioinformatics Program, Boston University, 24 Cummington Street, Boston, Massachusetts 02215, USA
[2]The Pulmonary Center, Boston University Medical Center, 715 Albany Street, Boston, Massachusetts 02118, USA
[3]Department of Genetics and Genomics, Boston University, 715 Albany Street, Boston, Massachusetts 02118, USA


Abstract

Cigarette smoke is the major cause of lung cancer and chronic obstructive pulmonary disease in the United States. We have previously defined the impact of tobacco smoke on intrathoracic airway gene expression among healthy nonsmokers and smokers using standard 3f-based expression U133A arrays [12]. In this report, we compared the performance of the Affymetrix GeneChip Human Exon 1.0 ST array with the HG-U133A array for detecting smoking-related gene expression changes in large airway epithelium obtained at bronchoscopy. RNA obtained from the same bronchial airway epithelial cell samples of four current smokers and three never smokers was hybridized to both arrays. Out of 22,215 probe sets on HG-U133A, 14,741 RefSeq transcripts were mapped to 17,800 core transcripts on the Exon array and the 2 platforms were compared for this overlapping transcript set. While the reproducibility of both platforms was high, the Exon array had a slightly stronger correlation for technical replicates. A majority of the genes with the largest smoking-related fold changes were tightly correlated between platforms, but there were a number of smoking-related changes in gene expression that were detected only on the Exon arrays. Furthermore, while the HGU133A study did not have enough power to detect any differentially expressed genes between the 4 current vs. 3 never smokers at a False Discovery Rate (FDR) < 0.05, seventy differential expressed genes were detected at FDR < 0.05 in the same set of samples using the Exon platform. These findings suggest that the all-Exon array is a more robust platform for measuring airway epithelial gene expression and can serve as an effective tool for exploring host response to and damage from cigarette smoke.

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Japanese Society for Bioinformatics