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

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

Cell Cycle Control, Checkpoint Mechanisms, and Genotoxic Stress

The ability of cells to maintain genomic integrity is vital for cell survival and proliferation. Lack of fidelity in DNA replication and maintenance can result in deleterious mutations leading to cell death or, in multicellular organisms, cancer. The purpose of this review is to discuss the known signal transduction pathways that regulate cell cycle progression and the mechanisms cells employ to insure DNA stability in the face of genotoxic stress. In particular, we focus on mammalian cell cycle checkpoint functions, their role in maintaining DNA stability during the cell cycle following exposure to genotoxic agents, and the gene products that act in checkpoint function signal transduction cascades. Key transitions in the cell cycle are regulated by the activities of various protein kinase complexes composed of cyclin and cyclin-dependent kinase (Cdk) molecules. Surveillance control mechanisms that check to ensure proper completion of early events and cellular integrity before initiation of subsequent events in cell cycle progression are referred to as cell cycle checkpoints and can generate a transient delay that provides the cell more time to repair damage before progressing to the next phase of the cycle. A variety of cellular responses are elicited that function in checkpoint signaling to inhibit cyclin/Cdk activities. These responses include the p53-dependent and p53-independent induction of Cdk inhibitors and the p53-independent inhibitory phosphorylation of Cdk molecules themselves. Eliciting proper G1, S, and G2 checkpoint responses to double-strand DNA breaks requires the function of the Ataxia telangiectasia mutated gene product. Several human heritable cancer-prone syndromes known to alter DNA stability have been found to have defects in checkpoint surveillance pathways. Exposures to several common sources of genotoxic stress, including oxidative stress, ionizing radiation, UV radiation, and the genotoxic compound benzo[a]pyrene, elicit cell cycle checkpoint responses that show both similarities and differences in their molecular signaling.ImagesFigure

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

Altered DNA methylation in human placenta after (suspected) preterm labor

Aim: The aim of this study was to determine if alterations in DNA methylation in the human placenta would support suspected preterm labor as a pathologic insult associated with diminished placental health. Methods: We evaluated placental DNA methylation at seven loci differentially methylated in placental pathologies using targeted bisulfite sequencing, in placentas associated with preterm labor (term birth after suspected preterm labor [n = 15] and preterm birth [n = 15]), and controls (n = 15). Results: DNA methylation levels at the NCAM1 and PLAGL1 loci in placentas associated with preterm labor did differ significantly (p < 0.05) from controls. Discussion: Specific alterations in methylation patterns indicative of an unfavourable placental environment are associated with preterm labor per se and not restricted to preterm birth

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

SARS-CoV-2 congenital infection and pre-eclampsia-like syndrome in dichorionic twins: A case report and review of the literature

Although the route of transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is mainly respiratory, vertical transmission seems possible.1 We report the case of a woman with a dichorionic diamniotic twin pregnancy admitted to Hospital Clínico Universitario Lozano Blesa at 38+4 weeks of gestation due to severe pre-eclampsia in the context of a SARS-CoV-2 infection (positive nasopharyngeal PCR; Viasure, CerTest Biotec., Zaragoza, Spain) with a probable transplacental transmission of the virus to both twins..

SARS-CoV-2 immunochromatographic IgM/IgG rapid test in pregnancy: A false friend?

Background: An increasing body of evidence has revealed that SARS-CoV-2 infection in pregnant women could increase the risk of adverse maternal and fetal outcomes. Careful monitoring of pregnancies with COVID-19 and measures to prevent neonatal infection are warranted. Therefore, rapid antibody tests have been suggested as an efficient screening tool during pregnancy. Cases: We analysed the clinical performance during pregnancy of a rapid, lateral-flow immunochromatographic assay for qualitative detection of SARS-CoV-2 IgG/IgM antibodies. We performed a universal screening including 169 patients during their last trimester of pregnancy. We present a series of 14 patients with positive SARS-CoV-2 immunochromatographic assay rapid test result. Immunochromatographic assay results were always confirmed by chemiluminescent microparticle immunoassays for quantitative detection of SARS-CoV-2 IgG and IgM+IgA antibodies as the gold standard. We observed a positive predictive value of 50% and a false positive rate of 50% in pregnant women, involving a significantly lower diagnostic performance than reported in non-pregnant patients. Discussion: Our data suggest that although immunochromatographic assay rapid tests may be a fast and profitable screening tool for SARS-CoV-2 infection, they may have a high false positive rate and low positive predictive value in pregnant women. Therefore, immunochromatographic assay for qualitative detection of SARS-CoV-2 IgG/IgM antibodies must be verified by other test in pregnant patients

Bayesian Best-Arm Identification for Selecting Influenza Mitigation Strategies

Pandemic influenza has the epidemic potential to kill millions of people. While various preventive measures exist (i.a., vaccination and school closures), deciding on strategies that lead to their most effective and efficient use remains challenging. To this end, individual-based epidemiological models are essential to assist decision makers in determining the best strategy to curb epidemic spread. However, individual-based models are computationally intensive and it is therefore pivotal to identify the optimal strategy using a minimal amount of model evaluations. Additionally, as epidemiological modeling experiments need to be planned, a computational budget needs to be specified a priori. Consequently, we present a new sampling technique to optimize the evaluation of preventive strategies using fixed budget best-arm identification algorithms. We use epidemiological modeling theory to derive knowledge about the reward distribution which we exploit using Bayesian best-arm identification algorithms (i.e., Top-two Thompson sampling and BayesGap). We evaluate these algorithms in a realistic experimental setting and demonstrate that it is possible to identify the optimal strategy using only a limited number of model evaluations, i.e., 2-to-3 times faster compared to the uniform sampling method, the predominant technique used for epidemiological decision making in the literature. Finally, we contribute and evaluate a statistic for Top-two Thompson sampling to inform the decision makers about the confidence of an arm recommendation