Dataset Information

Analysis of factorial time-course microarrays with application to a clinical study of burn injury.

ABSTRACT: Time-course microarray experiments are capable of capturing dynamic gene expression profiles. It is important to study how these dynamic profiles depend on the multiple factors that characterize the experimental condition under which the time course is observed. Analytic methods are needed to simultaneously handle the time course and factorial structure in the data. We developed a method to evaluate factor effects by pooling information across the time course while accounting for multiple testing and nonnormality of the microarray data. The method effectively extracts gene-specific response features and models their dependency on the experimental factors. Both longitudinal and cross-sectional time-course data can be handled by our approach. The method was used to analyze the impact of age on the temporal gene response to burn injury in a large-scale clinical study. Our analysis reveals that 21% of the genes responsive to burn are age-specific, among which expressions of mitochondria and immunoglobulin genes are differentially perturbed in pediatric and adult patients by burn injury. These new findings in the body's response to burn injury between children and adults support further investigations of therapeutic options targeting specific age groups. The methodology proposed here has been implemented in R package "TANOVA" and submitted to the Comprehensive R Archive Network at http://www.r-project.org/. It is also available for download at http://gluegrant1.stanford.edu/TANOVA/.

SUBMITTER: Zhou B

PROVIDER: S-EPMC2890487 | biostudies-literature | 2010 Jun

REPOSITORIES: biostudies-literature

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Analysis of factorial time-course microarrays with application to a clinical study of burn injury.

Zhou Baiyu B Xu Weihong W Herndon David D Tompkins Ronald R Davis Ronald R Xiao Wenzhong W Wong Wing Hung WH Toner Mehmet M Warren H Shaw HS Schoenfeld David A DA Rahme Laurence L McDonald-Smith Grace P GP Hayden Douglas D Mason Philip P Fagan Shawn S Yu Yong-Ming YM Cobb J Perren JP Remick Daniel G DG Mannick John A JA Lederer James A JA Gamelli Richard L RL Silver Geoffrey M GM West Michael A MA Shapiro Michael B MB Smith Richard R Camp David G DG Qian Weijun W Storey John J Mindrinos Michael M Tibshirani Rob R Lowry Stephen S Calvano Steven S Chaudry Irshad I West Michael A MA Cohen Mitchell M Moore Ernest E EE Johnson Jeffrey J Moldawer Lyle L LL Baker Henry V HV Efron Philip A PA Balis Ulysses G J UG Billiar Timothy R TR Ochoa Juan B JB Sperry Jason L JL Miller-Graziano Carol L CL De Asit K AK Bankey Paul E PE Finnerty Celeste C CC Jeschke Marc G MG Minei Joseph P JP Arnoldo Brett D BD Hunt John L JL Horton Jureta J Cobb J Perren JP Brownstein Bernard B Freeman Bradley B Maier Ronald V RV Nathens Avery B AB Cuschieri Joseph J Gibran Nicole N Klein Matthew M O'Keefe Grant G

Proceedings of the National Academy of Sciences of the United States of America 20100517 22

Time-course microarray experiments are capable of capturing dynamic gene expression profiles. It is important to study how these dynamic profiles depend on the multiple factors that characterize the experimental condition under which the time course is observed. Analytic methods are needed to simultaneously handle the time course and factorial structure in the data. We developed a method to evaluate factor effects by pooling information across the time course while accounting for multiple testin ...[more]

PMID: 20479259

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Project description:TNF time course series of HelA tet off cells cultured in presence or absence of Dox TNF is a pro-inflammatory cytokine that controls expression of inflammatory genetic networks. Although the Nuclear Factor-kB (NF-kB) pathway is crucial for mediating cellular TNF responses, the complete spectrum of NF-kB dependent genes is unknown. In this study, we used a tetracycline-regulated cell line expressing an NF-kB inhibitor to systematically identify NF-kB dependent genes. A microarray data set generated from a time course of TNF stimulation in the presence or absence of NF-kB signaling was analyzed. Methods: Cell culture, treatment and transfection-The human cervical epithelioid carcinoma cell line HeLa expressing tTA (HeLa Tet-Off) pBI-EGFP- IkBa Mut was constructed earlier (23). HeLa Tet-Off were grown in medium containing 90 % Dulbecco’s Modified Eagle’s Medium (DMEM), 10 % heat-inactivated fetal bovine serum (FBS), 4mM L-glutamine, 0.1 mM non-essential amino acids, 1 mM sodium pyruvate, 100 mg/ml G418, 100 units /ml penicillin G sodium, and 100 mg/ml streptomycin sulfate in a humidified atmosphere of 5 % CO2. For TNF stimulation, freshly isolated cells were split into two cultures, one group maintained in Dox, the other without for 7 d, a time at which IkBa Mut expression was maximal. Thereafter, recombinant human (rh) TNFa (25 ng/ml, final concentration) was added directly to the culture medium for indicated times prior to harvest. Oligonucleotide probe based microarray-Hu95Av2 GeneChip (Affymetrix Inc, Santa Clara, CA) containing 12,626 sequenced human genes were hybridized according to the manufacturer’s recommendations and washed using both non-stringent (1 M NaCl, 25 °C) and stringent (1 M NaCl, 50 °C) conditions prior to staining with phycoerythrin streptavidin (10 mg/ml final). Arrays were scanned using a Gene Array Scanner (Hewlett Packard) and analyzed using the Gene Chip Analysis Suite 5 software (Affymetrix Inc). For each gene, 16-20 probe pairs are immobilized as ~25-mer oligonucleotides that hybridize throughout the mRNA; each probe pair is represented as a perfect match (PM) oligonucleotide and a mismatch (MM) oligonucleotide as hybridization control. The the Absolute Call [e.g., the gene is detected (“present”) or not (“absent”)] and the Signal Intensity (measure of mRNA abundance) is determined. Four independent experiments were performed identically including control (0 h ), 1, 3 and 6 h TNF stimulation (25 ng/ml) in the presence or absence of Doxycyline (2 mg/ml) in growth medium. These are indicated as 180, 181, 220 and 266 series, and are considered replicates of each other. Keywords: time-course

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Analysis of factorial time-course microarrays with application to a clinical study of burn injury.

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Analysis of factorial time-course microarrays with application to a clinical study of burn injury.

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