Extracting gene expression patterns and identifying co-expressed genes from microarray data reveals biologically responsive processes

Abstract Background A common observation in the analysis of gene expression data is that many genes display similarity in their expression patterns and therefore appear to be co-regulated. However, the variation associated with microarray data and the complexity of the experimental designs make the acquisition of co-expressed genes a challenge. We developed a novel method for Extracting microarray gene expression Patterns and Identifying co-expressed Genes, designated as EPIG. The approach utilizes the underlying structure of gene expression data to extract patterns and identify co-expressed genes that are responsive to experimental conditions. Results Through evaluation of the correlations among profiles, the magnitude of variation in gene expression profiles, and profile signal-to-noise ratio's, EPIG extracts a set of patterns representing co-expressed genes. The method is shown to work well with a simulated data set and microarray data obtained from time-series studies of dauer recovery and L1 starvation in C. elegans and after ultraviolet (UV) or ionizing radiation (IR)-induced DNA damage in diploid human fibroblasts. With the simulated data set, EPIG extracted the appropriate number of patterns which were more stable and homogeneous than the set of patterns that were determined using the CLICK or CAST clustering algorithms. However, CLICK performed better than EPIG and CAST with respect to the average correlation between clusters/patterns of the simulated data. With real biological data, EPIG extracted more dauer-specific patterns than CLICK. Furthermore, analysis of the IR/UV data revealed 18 unique patterns and 2661 genes out of approximately 17,000 that were identified as significantly expressed and categorized to the patterns by EPIG. The time-dependent patterns displayed similar and dissimilar responses between IR and UV treatments. Gene Ontology analysis applied to each pattern-related subset of co-expressed genes revealed underlying biological processes affected by IR- and/or UV- induced DNA damage. Conclusion EPIG competed with CLICK and performed better than CAST in extracting patterns from simulated data. EPIG extracted more biological informative patterns and co-expressed genes from both C. elegans and IR/UV-treated human fibroblasts. Using Gene Ontology analysis of the genes in the patterns extracted by EPIG, several key biological categories related to p53-dependent cell cycle control were revealed from the IR/UV data. Among them were mitotic cell cycle, DNA replication, DNA repair, cell cycle checkpoint, and G0-like status transition. EPIG can be applied to data sets from a variety of experimental designs

A Comparison of the TempO-Seq S1500+ Platform to RNA-Seq and Microarray Using Rat Liver Mode of Action Samples

The TempO-SeqTM platform allows for targeted transcriptomic analysis and is currently used by many groups to perform high-throughput gene expression analysis. Herein we performed a comparison of gene expression characteristics measured using 45 purified RNA samples from the livers of rats exposed to chemicals that fall into one of five modes of action (MOAs). These samples have been previously evaluated using AffymetrixTM rat genome 230 2.0 microarrays and Illumina® whole transcriptome RNA-Seq. Comparison of these data with TempO-Seq analysis using the rat S1500+ beta gene set identified clear differences in the platforms related to signal to noise, root mean squared error, and/or sources of variability. Microarray and TempO-Seq captured the most variability in terms of MOA and chemical treatment whereas RNA-Seq had higher noise and larger differences between samples within a MOA. However, analysis of the data by hierarchical clustering, gene subnetwork connectivity and biological process representation of MOA-varying genes revealed that the samples clearly grouped by treatment as opposed to gene expression platform. Overall these findings demonstrate that the results from the TempO-Seq platform are consistent with findings on other more established approaches for measuring the genome-wide transcriptome

Genes related to apoptosis predict necrosis of the liver as a phenotype observed in rats exposed to a compendium of hepatotoxicants

<p>Abstract</p> <p>Background</p> <p>Some of the biochemical events that lead to necrosis of the liver are well-known. However, the pathogenesis of necrosis of the liver from exposure to hepatotoxicants is a complex biological response to the injury. We hypothesize that gene expression profiles can serve as a signature to predict the level of necrosis elicited by acute exposure of rats to a variety of hepatotoxicants and postulate that the expression profiles of the predictor genes in the signature can provide insight to some of the biological processes and molecular pathways that may be involved in the manifestation of necrosis of the rat liver.</p> <p>Results</p> <p>Rats were treated individually with one of seven known hepatotoxicants and were analyzed for gene expression by microarray. Liver samples were grouped by the level of necrosis exhibited in the tissue. Analysis of significantly differentially expressed genes between adjacent necrosis levels revealed that inflammation follows programmed cell death in response to the agents. Using a Random Forest classifier with feature selection, 21 informative genes were identified which achieved 90%, 80% and 60% prediction accuracies of necrosis against independent test data derived from the livers of rats exposed to acetaminophen, carbon tetrachloride, and allyl alcohol, respectively. Pathway and gene network analyses of the genes in the signature revealed several gene interactions suggestive of apoptosis as a process possibly involved in the manifestation of necrosis of the liver from exposure to the hepatotoxicants. Cytotoxic effects of TNF-α, as well as transcriptional regulation by JUN and TP53, and apoptosis-related genes possibly lead to necrosis.</p> <p>Conclusion</p> <p>The data analysis, gene selection and prediction approaches permitted grouping of the classes of rat liver samples exhibiting necrosis to improve the accuracy of predicting the level of necrosis as a phenotypic end-point observed from the exposure. The strategy, along with pathway analysis and gene network reconstruction, led to the identification of 1) expression profiles of genes as a signature of necrosis and 2) perturbed regulatory processes that exhibited biological relevance to the manifestation of necrosis from exposure of rat livers to the compendium of hepatotoxicants.</p

Identification of Genes Implicated in Methapyrilene-Induced Hepatotoxicity by Comparing Differential Gene Expression in Target and Nontarget Tissue

BACKGROUND: Toxicogenomics experiments often reveal thousands of transcript alterations that are related to multiple processes, making it difficult to identify key gene changes that are related to the toxicity of interest. OBJECTIVES: The objective of this study was to compare gene expression changes in a nontarget tissue to the target tissue for toxicity to help identify toxicity-related genes. METHODS: Male rats were given the hepatotoxicant methapyrilene at two dose levels, with livers and kidneys removed 24 hr after one, three, and seven doses for gene expression analysis. To identify gene changes likely to be related to toxicity, we analyzed genes on the basis of their temporal pattern of change using a program developed at the National Institute of Environmental Health Sciences, termed “EPIG” (extracting gene expression patterns and identifying co-expressed genes). RESULTS: High-dose methapyrilene elicited hepatic damage that increased in severity with the number of doses, whereas no treatment-related lesions were observed in the kidney. High-dose methapyrilene elicited thousands of gene changes in the liver at each time point, whereas many fewer gene changes were observed in the kidney. EPIG analysis identified patterns of gene expression correlated to the observed toxicity, including genes associated with endoplasmic reticulum stress and the unfolded protein response. CONCLUSIONS: By factoring in dose level, number of doses, and tissue into the analysis of gene expression elicited by methapyrilene, we were able to identify genes likely to not be implicated in toxicity, thereby allowing us to focus on a subset of genes to identify toxicity-related processes

DNA damage activates a complex transcriptional response in murine lymphocytes that includes both physiological and cancer-predisposition programs

BACKGROUND: Double strand (ds) DNA breaks are a form of DNA damage that can be generated from both genotoxic exposures and physiologic processes, can disrupt cellular functions and can be lethal if not repaired properly. Physiologic dsDNA breaks are generated in a variety of normal cellular functions, including the RAG endonuclease-mediated rearrangement of antigen receptor genes during the normal development of lymphocytes. We previously showed that physiologic breaks initiate lymphocyte development-specific transcriptional programs. Here we compare transcriptional responses to physiological DNA breaks with responses to genotoxic DNA damage induced by ionizing radiation. RESULTS: We identified a central lymphocyte-specific transcriptional response common to both physiologic and genotoxic breaks, which includes many lymphocyte developmental processes. Genotoxic damage causes robust alterations to pathways associated with B cell activation and increased proliferation, suggesting that genotoxic damage initiates not only the normal B cell maturation processes but also mimics activated B cell response to antigenic agents. Notably, changes including elevated levels of expression of Kras and mmu-miR-155 and the repression of Socs1 were observed following genotoxic damage, reflecting induction of a cancer-prone phenotype. CONCLUSIONS: Comparing these transcriptional responses provides a greater understanding of the mechanisms cells use in the differentiation between types of DNA damage and the potential consequences of different sources of damage. These results suggest genotoxic damage may induce a unique cancer-prone phenotype and processes mimicking activated B cell response to antigenic agents, as well as the normal B cell maturation processes

Patterns of Neoplasia in c-Mos Transgenic Mice and Their Relevance to Multiple Endocrine Neoplasia

We have previously described a neurological phenotype for transgenic mice carrying the c-Mos proto-oncogene. Pheochromocytomas and C-cell thyroid neoplasms occur in these transgenic lines in patterns that are similar to those seen in multiple endocrine neoplasia type 2 (MEN 2). Characterization of the pathological lesions via immunohistochemistry underscores similarities between MEN 2 and these transgenic mice. When transgenic mice that do not display the MEN 2 phenotype are crossed to a different background, the progeny display the MEN 2 phenotype. Thus the interaction of the background with the transgene is such that it can suppress tumor information. This observation bears special relevance to the human syndrome in that this model system may be used to study the question of penetrance of phenotype

ATR Enforces the Topoisomerase II-dependent G 2 Checkpoint through Inhibition of Plk1 Kinase

An ATR-dependent

Human AlkB Homolog ABH8 Is a tRNA Methyltransferase Required for Wobble Uridine Modification and DNA Damage Survival

tRNA nucleosides are extensively modified to ensure their proper function in translation. However, many of the enzymes responsible for tRNA modifications in mammals await identification. Here, we show that human AlkB homolog 8 (ABH8) catalyzes tRNA methylation to generate 5-methylcarboxymethyl uridine (mcm[superscript 5]U) at the wobble position of certain tRNAs, a critical anticodon loop modification linked to DNA damage survival. We find that ABH8 interacts specifically with tRNAs containing mcm5U and that purified ABH8 complexes methylate RNA in vitro. Significantly, ABH8 depletion in human cells reduces endogenous levels of mcm[superscript 5]U in RNA and increases cellular sensitivity to DNA-damaging agents. Moreover, DNA-damaging agents induce ABH8 expression in an ATM-dependent manner. These results expand the role of mammalian AlkB proteins beyond that of direct DNA repair and support a regulatory mechanism in the DNA damage response pathway involving modulation of tRNA modification.United States. National Institutes of Health (grant CA055042)United States. National Institutes of Health (grant ES002109)United States. National Institutes of Health (grant ES01701)National Institutes of Health (U.S.). Intramural Research ProgramWestaway Research FundNational Center for Research Resources (U.S.) (grant S10-RR023783

Moving Forward in Human Cancer Risk Assessment

The goal of human risk assessment is to decide whether a given exposure level to a particular chemical or substance is acceptable to human health, and to provide risk management measures based on an evaluation and prediction of the effects of that exposure on human health. Within this framework, the current safety paradigm for assessing possible carcinogenic properties of drugs, cosmetics, industrial chemicals and environmental exposures relies mainly on in vitro genotoxicity testing followed by 2-year bioassays in mice and rats. This testing paradigm was developed 40 to 50 years ago with the initial premise that ¿mutagens are also carcinogens¿ and that the carcinogenic risk to humans can be extrapolated from the tumor incidence after lifetime exposure to maximally tolerated doses of chemicals in rodents. Genotoxicity testing is used as a surrogate for carcinogenicity testing and is required for initiation of clinical trials (Jacobs and Jacobson-Kram 2004) and for most industrial chemicals safety assessment. Although the carcinogenicity-testing paradigm has effectively protected patients and consumers from introduction of harmful carcinogens as drugs and other products, the testing paradigm is clearly not sustainable in the future. The causal link between genetic damage and carcinogenicity is well documented; however, the limitations of genotoxicity/carcinogenicity testing assays, the presence of additional non-genotoxic mechanisms, issues of species-specific effects, and the lack of mechanistic insights provide an enormous scientific challenge. The 2-year rodent carcinogenicity bioassays are associated with technical complexity, high costs, high animal burden as well as the uncertainty associated with extrapolating from rodents to humans. Additional frustrations exist because of the limited predictability of the 2-year bioassay and, in particular, with regard to the problem of the prediction of false positives. For instance, in the Carcinogenic Potency Project DataBase (CPDB) which includes results from chronic, long-term animal cancer tests with mice, rats, hamsters amounting to a total of 6540 individual experiments with 1547 chemicals, 751 of those chemicals or 51% have positive findings in rodent studies. Similarly, when one considers all chronically used human pharmaceuticals, some 50% induce tumors in rodents. Yet only 20 human pharmaceutical compounds have been identified as carcinogens in epidemiological studies, despite the fact that quite a large number of epidemiological studies have been carried out on these compounds, e.g. NSAID¿s, benzodiazepines, phenobarbital. This high incidence of tumors in bioassays has lead to questions concerning the human relevance of tumors induced in rodents (Knight et al. 2006; Ward 2008). In summary, dependency on the rodent model as a golden standard of cancer risk assessment is neglecting the high number of false positives and clearly has serious limitations. Consequently, there is a growing appeal for a paradigm change after "50 years of rats and mice". For instance, the current demands for volume of carcinogenic testing together with limitations of animal usage as initially stipulated by REACH (Combes et al. 2006) will require revolutionary change in the testing paradigm. For the purpose of developing a road map for this needed paradigm change in carcinogenicity testing, a workshop was held in August 2009 in Venice, Italy entitled ¿Genomics in Cancer Risk Assessment.¿ This workshop brought together toxicologists from academia and industry with governmental regulators and risk assessors from the US and the EU, for discussing the state-of-the-art in developing alternative testing strategies for genotoxicity and carcinogenicity, thereby focusing on the contribution from the ¿omics technologies. What follows is a highlight of the major conclusions and suggestions from this workshop as a path forward.JRC.DG.I.3-In-vitro method