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Although microarray technology has emerged as a powerful tool to explore expression levels of thousands of genes or even complete genomes after exposure to toxicants, the functional interpretation of microarray data sets still represents a time-consuming and challenging task. Gene ontology (GO) and pathway mapping have both been shown to be powerful approaches to generate a global view of biological processes and cellular components impacted by toxicants. However, current methods only allow for comparisons across two experimental settings at one particular time point. In addition, the resulting annotations are presented in extensive gene lists with minimal or limited quantitative information, data that are crucial in the application of toxicogenomic data for risk assessment. To facilitate quantitative interpretation of dose- or time-dependent genomic data, we propose to use combined average raw gene expression values (e.g., intensity or ratio) of genes associated with specific functional categories derived from the GO database. We developed an extended program (GO-Quant) to extract quantitative gene expression values and to calculate the average intensity or ratio for those significantly altered by functional gene category based on MAPPFinder results. To demonstrate its application, we applied this approach to a previously published dose- and time-dependent toxicogenomic data set (J. F. Dillman et al., 2005, Chem. Res. Toxicol. 18, 28-34). Our results indicate that the above systems approach can describe quantitatively the degree to which functional gene systems change across dose or time. Additionally, this approach provides a robust measurement to illustrate results compared to single-gene assessments and enables the user to calculate the corresponding ED(50) for each specific functional GO term, important for risk assessment.

Gene expression profiling is an important tool in the development of medical countermeasures against chemical warfare agents (CWAs). Non-human primates (NHPs), specifically the rhesus macaque (Macaca mulatta), the cynomologus macaque (Macaca fascicularis), and the African green monkey (Chlorocebus aethiops), are vital models in the development of CWA prophylactics, therapeutics, and diagnostics. However, gene expression profiling of these NHPs is complicated by the fact their genomes are not completely sequenced, and that no commercially available oligonucleotide microarrays (genechips) exist. We, therefore, sought to determine whether gene expression profiling of NHPs could be performed using human genechips. Whole blood RNA was isolated from each species and used to generate genechip probes. Hybridization of the NHP samples to human genechips (Affymetrix Human U133 Plus 2.0) resulted in comparable numbers of transcripts detected compared with human samples. Statistical analysis revealed intraspecies reproducibility of genechip quality control metrics; interspecies comparison between NHPs and humans showed little significant difference in the quality and reproducibility of data generated using human genechips. Expression profiles of each species were compared using principal component analysis (PCA) and hierarchical clustering to determine the similarity of the expression profiles within and across the species. The cynomologus group showed the least intraspecies variability, and the human group showed the greatest intraspecies variability. Intraspecies comparison of the expression profiles identified probe sets that were reproducibly detected within each species. Each NHP species was found to be dissimilar to humans; the cynomologus group was the most dissimilar. Interspecies comparison of the expression profiles revealed probe sets that were reproducibly detected in all species examined. These results show that human genechips can be used for expression profiling of NHP samples and provide a foundation for the development of tools for comparing human and NHP gene expression profiles.