Pooling samples within microarray studies: a comparative analysis of rat liver transcription response to prototypical toxicants.

Combining or pooling individual samples when carrying out transcript profiling using microarrays is a fairly common means to reduce both the cost and complexity of data analysis. However, pooling does not allow for statistical comparison of changes between samples and can result in a loss of information. Because a rigorous comparison of the identified expression changes from the two approaches has not been reported, we compared the results for hepatic transcript profiles from pooled vs. individual samples. Hepatic transcript profiles from a single-dose time-course rat study in response to the prototypical toxicants clofibrate, diethylhexylphthalate, and valproic acid were evaluated. Approximately 50% more transcript expression changes were observed in the individual (statistical) analysis compared with the pooled analysis. While the majority of these changes were less than twofold in magnitude ( approximately 80%), a substantial number were greater than twofold (approximately 20%). Transcript changes unique to the individual analysis were confirmed by quantitative RT-PCR, while all the changes unique to the pooled analysis did not confirm. The individual analysis identified more hits per biological pathway than the pooled approach. Many of the transcripts identified by the individual analysis were novel findings and may contribute to a better understanding of molecular mechanisms of these compounds. Furthermore, having individual animal data provided the opportunity to correlate changes in transcript expression to phenotypes (i.e., histology) observed in toxicology studies. The two approaches were similar when clustering methods were used despite the large difference in the absolute number of transcripts changed. In summary, pooling reduced resource requirements substantially, but the individual approach enabled statistical analysis that identified more gene expression changes to evaluate mechanisms of toxicity. An individual animal approach becomes more valuable when the overall expression response is subtle and/or when associating expression data to variable phenotypic responses.

[1]  R A Irizarry,et al.  On the utility of pooling biological samples in microarray experiments. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[2]  J. Waring,et al.  Clofibrate-induced gene expression changes in rat liver: a cross-laboratory analysis using membrane cDNA arrays. , 2004, Environmental health perspectives.

[3]  J. Waring,et al.  Microvesicular Steatosis Induced by a Short Chain Fatty Acid: Effects on Mitochondrial Function and Correlation with Gene Expression , 2004, Toxicologic pathology.

[4]  K. Mitsumori,et al.  Possible Mechanisms Underlying the Testicular Toxicity of Oxfendazole in Rats , 2004, Toxicologic pathology.

[5]  W. H. Jordan,et al.  Adipsin, a Biomarker of Gastrointestinal Toxicity Mediated by a Functional γ-Secretase Inhibitor* , 2003, Journal of Biological Chemistry.

[6]  J. Reddy,et al.  Peroxisome proliferator-activated receptors, fatty acid oxidation, steatohepatitis and hepatocarcinogenesis. , 2003, Current molecular medicine.

[7]  Michael I. Jordan,et al.  Toward a protein profile of Escherichia coli: Comparison to its transcription profile , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[8]  D. Stone,et al.  Prediction of clinical drug efficacy by classification of drug-induced genomic expression profiles in vitro , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[9]  Mengsu Yang,et al.  Inhibitory actions of genistein in human breast cancer (MCF-7) cells. , 2003, Biochimica et biophysica acta.

[10]  C. Kendziorski,et al.  The efficiency of pooling mRNA in microarray experiments. , 2003, Biostatistics.

[11]  Arnold J. Stromberg,et al.  Statistical implications of pooling RNA samples for microarray experiments , 2003, BMC Bioinform..

[12]  Siew Hong Leong,et al.  A combined comparative genomic hybridization and expression microarray analysis of gastric cancer reveals novel molecular subtypes. , 2003, Cancer research.

[13]  Thomas K. H. Chang,et al.  The effect of valproic acid on hepatic and plasma levels of 15-F2t-isoprostane in rats. , 2003, Free radical biology & medicine.

[14]  Yaning Yang,et al.  Microarray expression profiling: analysis and applications. , 2003, Current opinion in drug discovery & development.

[15]  Henrik Antti,et al.  Contemporary issues in toxicology the role of metabonomics in toxicology and its evaluation by the COMET project. , 2003, Toxicology and applied pharmacology.

[16]  E. Winzeler,et al.  Protein pathway and complex clustering of correlated mRNA and protein expression analyses in Saccharomyces cerevisiae , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[17]  P. Macgregor.  Gene expression in cancer: the application of microarrays , 2003, Expert review of molecular diagnostics.

[18]  J. Fisher.  PBPK modeling advances understanding of D4 pharmacokinetics. , 2003, Toxicological sciences : an official journal of the Society of Toxicology.

[19]  Roger E Bumgarner,et al.  Identification of novel tumor markers in hepatitis C virus-associated hepatocellular carcinoma. , 2003, Cancer research.

[20]  Steven C. Lawlor,et al.  MAPPFinder: using Gene Ontology and GenMAPP to create a global gene-expression profile from microarray data , 2003, Genome Biology.

[21]  J. Waring,et al.  Identifying toxic mechanisms using DNA microarrays: evidence that an experimental inhibitor of cell adhesion molecule expression signals through the aryl hydrocarbon nuclear receptor. , 2002, Toxicology.

[22]  S. Gill,et al.  Gene expression changes induced in mouse liver by di(2-ethylhexyl) phthalate. , 2002, Toxicology and applied pharmacology.

[23]  G. Duyk,et al.  Sharper tools and simpler methods , 2002, Nature Genetics.

[24]  Joseph Geradts,et al.  Differential gene expression patterns in HER2/neu-positive and -negative breast cancer cell lines and tissues. , 2002, The American journal of pathology.

[25]  K. Kolaja,et al.  Toxicogenomics: an opportunity to optimise drug development and safety evaluation , 2002, Expert opinion on drug safety.

[26]  T. Speed,et al.  Design issues for cDNA microarray experiments , 2002, Nature Reviews Genetics.

[27]  G. Orphanides,et al.  Downregulation of Lactoferrin by PPARα Ligands: Role in Perturbation of Hepatocyte Proliferation and Apoptosis , 2002 .

[28]  J. Waring,et al.  The promise of toxicogenomics. , 2002, Current opinion in molecular therapeutics.

[29]  Steven C. Lawlor,et al.  GenMAPP, a new tool for viewing and analyzing microarray data on biological pathways , 2002, Nature Genetics.

[30]  Geoffrey J McLachlan,et al.  Selection bias in gene extraction on the basis of microarray gene-expression data , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[31]  David E. Misek,et al.  Discordant Protein and mRNA Expression in Lung Adenocarcinomas * , 2002, Molecular & Cellular Proteomics.

[32]  L. Hood,et al.  Complementary Profiling of Gene Expression at the Transcriptome and Proteome Levels in Saccharomyces cerevisiae*S , 2002, Molecular & Cellular Proteomics.

[33]  R. Wooster,et al.  Gene expression microarray analysis in cancer biology, pharmacology, and drug development: progress and potential. , 2001, Biochemical pharmacology.

[34]  R. Spang,et al.  Predicting the clinical status of human breast cancer by using gene expression profiles , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[35]  Ka Yee Yeung,et al.  Principal component analysis for clustering gene expression data , 2001, Bioinform..

[36]  R G Ulrich,et al.  Clustering of hepatotoxins based on mechanism of toxicity using gene expression profiles. , 2001, Toxicology and applied pharmacology.

[37]  M. Marton,et al.  Transcriptional Profiling Shows that Gcn4p Is a Master Regulator of Gene Expression during Amino Acid Starvation in Yeast , 2001, Molecular and Cellular Biology.

[38]  D. Botstein,et al.  Genomic expression programs in the response of yeast cells to environmental changes. , 2000, Molecular biology of the cell.

[39]  S. Wang,et al.  Identification and characterization of differentially expressed genes in the early response phase during liver regeneration. , 2000, Biochemical and biophysical research communications.

[40]  G. A. Whitmore,et al.  Importance of replication in microarray gene expression studies: statistical methods and evidence from repetitive cDNA hybridizations. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[41]  Andrea Califano,et al.  Analysis of Gene Expression Microarrays for Phenotype Classification , 2000, ISMB.

[42]  S. Gygi,et al.  Correlation between Protein and mRNA Abundance in Yeast , 1999, Molecular and Cellular Biology.

[43]  M. Nagao,et al.  Influence of valproic acid on the expression of various acyl‐CoA dehydrogenases in rats , 1999, Pediatrics international : official journal of the Japan Pediatric Society.

[44]  J. Peters,et al.  Mechanism of Action of the Nongenotoxic Peroxisome Proliferators: Role of the Peroxisome Proliferator-Activated Receptor α , 1998 .

[45]  M. Sobaniec-Łotowska.  Effects of long-term administration of the antiepileptic drug--sodium valproate upon the ultrastructure of hepatocytes in rats. , 1997, Experimental and toxicologic pathology : official journal of the Gesellschaft fur Toxikologische Pathologie.

[46]  H. Yokoo,et al.  Up‐Regulation of Sodium Channel Subunit mRNAs and Their Cell Surface Expression by Antiepileptic Valproic Acid: Activation of Calcium Channel and Catecholamine Secretion in Adrenal Chromaffin Cells , 1997, Journal of neurochemistry.

[47]  M. Kilberg,et al.  Nuclear retention of the induced mRNA following amino acid-dependent transcriptional regulation of mammalian ribosomal proteins L17 and S25. , 1994, The Journal of biological chemistry.

[48]  F. Van hoof,et al.  Influence of chronic administration of valproate on ultrastructure and enzyme content of peroxisomes in rat liver and kidney. Oxidation of valproate by liver peroxisomes. , 1991, Biochemical pharmacology.

[49]  B. Stiemer.  Morphological evaluation of steatosis in monolayer cultures (MDCK cells) after treatment with gentamicin and valproic acid. , 1989, Histology and histopathology.

[50]  P. Alberti,et al.  Heat shock, protein synthesis and ribosomal protein S6 phosphorylation in vitro in Yoshida AH 130 ascites hepatoma cells. , 1988, Cell biology international reports.

[51]  P. Alberti,et al.  Activation of a ribosomal protein S6 kinase during the 4-dimethylaminoazobenzene-induced rat hepatocarcinogenesis. , 1988, Cancer Letters.

[52]  M. Radmacher,et al.  Pitfalls in the use of DNA microarray data for diagnostic and prognostic classification. , 2003, Journal of the National Cancer Institute.

[53]  G. Orphanides,et al.  Downregulation of lactoferrin by PPARalpha ligands: role in perturbation of hepatocyte proliferation and apoptosis. , 2002, Toxicological Sciences.

[54]  J. Peters,et al.  Mechanism of action of the nongenotoxic peroxisome proliferators: role of the peroxisome proliferator-activator receptor alpha. , 1998, Journal of the National Cancer Institute.

[55]  M. Sobaniec-Lotowska.  Effects of long-term administration of the antiepileptic drug--sodium valproate upon the ultrastructure of hepatocytes in rats. , 1997, Experimental and Toxicological Pathology.

[56]  A. Caro-Patón,et al.  Histological, ultrastructural and mitochondrial oxidative phosphorylation studies in liver of rats chronically treated with oral valproic acid. , 1985, Journal of hepatology.