A statistical framework for the design of microarray experiments and effective detection of differential gene expression

Four reasons why you might wish to read this paper: 1. We have devised a new statistical T test to determine differentially expressed genes (DEG) in the context of microarray experiments. This statistical test adds a new member to the traditional T-test family. 2. An exact formula for calculating the detection power of this T test is presented, which can also be fairly easily modified to cover the traditional T tests. 3. We have presented an accurate yet computationally very simple method to estimate the fraction of non-DEGs in a set of genes being tested. This method is superior to an existing one which is computationally much involved. 4. We approach the multiple testing problem from a fresh angle, and discuss its relation to the classical Bonferroni procedure and to the FDR (false discovery rate) approach. This is most useful in the analysis of microarray data, where typically several thousands of genes are being tested simultaneously.Comment: 9 pages, 1 table; to appear in Bioinformatic

Inflammatory Genomics

Inflammatory genomic

sscMap: An extensible Java application for connecting small-molecule drugs using gene-expression signatures

Background: Connectivity mapping is a process to recognize novel pharmacological and toxicological properties in small molecules by comparing their gene expression signatures with others in a database. A simple and robust method for connectivity mapping with increased specificity and sensitivity was recently developed, and its utility demonstrated using experimentally derived gene signatures. Results: This paper introduces sscMap (statistically significant connections' map), a Java application designed to undertake connectivity mapping tasks using the recently published method. The software is bundled with a default collection of reference gene-expression profiles based on the publicly available dataset from the Broad Institute Connectivity Map 02, which includes data from over 7000 Affymetrix microarrays, for over 1000 small-molecule compounds, and 6100 treatment instances in 5 human cell lines. In addition, the application allows users to add their custom collections of reference profiles and is applicable to a wide range of other 'omics technologies. Conclusions: The utility of sscMap is two fold. First, it serves to make statistically significant connections between a user-supplied gene signature and the 6100 core reference profiles based on the Broad Institute expanded dataset. Second, it allows users to apply the same improved method to custom-built reference profiles which can be added to the database for future referencing. The software can be freely downloaded from http://purl.oclc.org/NET/sscMapComment: 3 pages, 1 table, 1 eps figur

A novel method for poly(A) fractionation reveals a large population of mRNAs with a short poly(A) tail in mammalian cells.

The length of the poly(A) tail of an mRNA plays an important role in translational efficiency, mRNA stability and mRNA degradation. Regulated polyadenylation and deadenylation of specific mRNAs is involved in oogenesis, embryonic development, spermatogenesis, cell cycle progression and synaptic plasticity. Here we report a new technique to analyse the length of poly(A) tails and to separate a mixed population of mRNAs into fractions dependent on the length of their poly(A) tails. The method can be performed on crude lysate or total RNA, is fast, highly reproducible and minor changes in poly(A) tail length distribution are easily detected. We validated the method by analysing mRNAs known to undergo cytoplasmic polyadenylation during Xenopus laevis oocyte maturation. We then separated RNA from NIH3T3 cells into two fractions with short and long poly(A) tails and compared them by microarray analysis. In combination with the validation experiments, the results indicate that approximately 25% of the expressed genes have a poly(A) tail of less than 30 residues in a significant percentage of their transcripts

Association of gene expression with sequential proliferation, differentiation and tumor formation in murine skin.

Differential gene expression in two established initiation and promotion skin carcinogenesis models during promo-tion and tumor formation was determined by microarray technology with the purpose of distinguishing the genes more associated with neoplastic transformation from those linked with proliferation and differentiation. The first model utilized dimethylbenz[a]anthracene initiation and 12-O-tetradecanoylphorbol 13-acetate (TPA) promotion in the FVB/N mouse, and the second TPA promotion of the Tg.Ac mouse, which is endogenously initiated by virtue of an activated Ha-ras transgene. Comparison of gene expression profiles across the two models identified genes whose altered expression was associated with papilloma formation rather than TPA-induced proliferation and differentiation. DMBA suppressed TPA-induced dif-ferentiation which allowed identification of those genes associated more specifically with differentiation rather than proliferation. EASE (Expression Analysis Systemic Explorer) indicated a correlation between muscle-associated genes and skin differentiation, whereas genes involved with protein biosynthesis were strongly correlated with proliferation. For verification the altered expression of selected genes were confirmed by RT–PCR; Carbonic anhydrase 2, Thioredoxin 1 and Glutathione S-transferase omega 1 associated with papilloma formation and Enolase 3, Cystatin b and Filaggrin associated with TPA-induced proliferation and differentiation. In situ analysis located the papillomas Glutathione S-transferase omega 1 expres-sion to the proliferating areas of the papillomas. Thus we have identified profiles of differential gene expression associated with the tumorigenesis and promotion stages for skin carcinogenesis in the mouse

A simple and robust method for connecting small-molecule drugs using gene-expression signatures

Interaction of a drug or chemical with a biological system can result in a gene-expression profile or signature characteristic of the event. Using a suitably robust algorithm these signatures can potentially be used to connect molecules with similar pharmacological or toxicological properties. The Connectivity Map was a novel concept and innovative tool first introduced by Lamb et al to connect small molecules, genes, and diseases using genomic signatures [Lamb et al (2006), Science 313, 1929-1935]. However, the Connectivity Map had some limitations, particularly there was no effective safeguard against false connections if the observed connections were considered on an individual-by-individual basis. Further when several connections to the same small-molecule compound were viewed as a set, the implicit null hypothesis tested was not the most relevant one for the discovery of real connections. Here we propose a simple and robust method for constructing the reference gene-expression profiles and a new connection scoring scheme, which importantly allows the valuation of statistical significance of all the connections observed. We tested the new method with the two example gene-signatures (HDAC inhibitors and Estrogens) used by Lamb et al and also a new gene signature of immunosuppressive drugs. Our testing with this new method shows that it achieves a higher level of specificity and sensitivity than the original method. For example, our method successfully identified raloxifene and tamoxifen as having significant anti-estrogen effects, while Lamb et al's Connectivity Map failed to identify these. With these properties our new method has potential use in drug development for the recognition of pharmacological and toxicological properties in new drug candidates.Comment: 8 pages, 2 figures, and 2 tables; supplementary data supplied as a ZIP fil

Doxorubicin In Vivo Rapidly Alters Expression and Translation of Myocardial Electron Transport Chain Genes, Leads to ATP Loss and Caspase 3 Activation

BackgroundDoxorubicin is one of the most effective anti-cancer drugs but its use is limited by cumulative cardiotoxicity that restricts lifetime dose. Redox damage is one of the most accepted mechanisms of toxicity, but not fully substantiated. Moreover doxorubicin is not an efficient redox cycling compound due to its low redox potential. Here we used genomic and chemical systems approaches in vivo to investigate the mechanisms of doxorubicin cardiotoxicity, and specifically test the hypothesis of redox cycling mediated cardiotoxicity.Methodology/principal findingsMice were treated with an acute dose of either doxorubicin (DOX) (15 mg/kg) or 2,3-dimethoxy-1,4-naphthoquinone (DMNQ) (25 mg/kg). DMNQ is a more efficient redox cycling agent than DOX but unlike DOX has limited ability to inhibit gene transcription and DNA replication. This allowed specific testing of the redox hypothesis for cardiotoxicity. An acute dose was used to avoid pathophysiological effects in the genomic analysis. However similar data were obtained with a chronic model, but are not specifically presented. All data are deposited in the Gene Expression Omnibus (GEO). Pathway and biochemical analysis of cardiac global gene transcription and mRNA translation data derived at time points from 5 min after an acute exposure in vivo showed a pronounced effect on electron transport chain activity. This led to loss of ATP, increased AMPK expression, mitochondrial genome amplification and activation of caspase 3. No data gathered with either compound indicated general redox damage, though site specific redox damage in mitochondria cannot be entirely discounted.Conclusions/significanceThese data indicate the major mechanism of doxorubicin cardiotoxicity is via damage or inhibition of the electron transport chain and not general redox stress. There is a rapid response at transcriptional and translational level of many of the genes coding for proteins of the electron transport chain complexes. Still though ATP loss occurs with activation caspase 3 and these events probably account for the heart damage

Circadian Cycling of the Mouse Liver Transcriptome, as Revealed by cDNA Microarray, Is Driven by the Suprachiasmatic Nucleus

AbstractBackground: Genes encoding the circadian pacemaker in the hypothalamic suprachiasmatic nuclei (SCN) of mammals have recently been identified, but the molecular basis of circadian timing in peripheral tissue is not well understood. We used a custom-made cDNA microarray to identify mouse liver transcripts that show circadian cycles of abundance under constant conditions.Results: Using two independent tissue sampling and hybridization regimes, we show that ∼9% of the 2122 genes studied show robust circadian cycling in the liver. These transcripts were categorized by their phase of abundance, defining clusters of day- and night-related genes, and also by the function of their products. Circadian regulation of genes was tissue specific, insofar as novel rhythmic liver genes were not necessarily rhythmic in the brain, even when expressed in the SCN. The rhythmic transcriptome in the periphery is, nevertheless, dependent on the SCN because surgical ablation of the SCN severely dampened or destroyed completely the cyclical expression of both canonical circadian genes and novel genes identified by microarray analysis.Conclusions: Temporally complex, circadian programming of the transcriptome in a peripheral organ is imposed across a wide range of core cellular functions and is dependent on an interaction between intrinsic, tissue-specific factors and extrinsic regulation by the SCN central pacemaker

Grouping of UVCB substances with dose-response transcriptomics data from human cell-based assays

The application of in vitro biological assays as new approach methodologies (NAMs) to support grouping of UVCB (unknown or variable composition, complex reaction products, and biological materials) substances has recently been demonstrated. In addition to cell-based phenotyping as NAMs, in vitro transcriptomic profiling is used to gain deeper mechanistic understanding of biological responses to chemicals and to support grouping and read-across. However, the value of gene expression profiling for characterizing complex substances like UVCBs has not been explored. Using 141 petroleum substance extracts, we performed dose-response transcriptomic profiling in human induced pluripotent stem cell (iPSC)-derived hepatocytes, cardiomyocytes, neurons, and endothelial cells, as well as cell lines MCF7 and A375. The goal was to determine whether transcriptomic data can be used to group these UVCBs and to further characterize the molecular basis for in vitro biological responses. We found distinct transcriptional responses for petroleum substances by manufacturing class. Pathway enrichment informed interpretation of effects of substances and UVCB petroleum-class. Transcriptional activity was strongly correlated with concentration of polycyclic aromatic compounds (PAC), especially in iPSC-derived hepatocytes. Supervised analysis using transcriptomics, alone or in combination with bioactivity data collected on these same substances/cells, suggest that transcriptomics data provide useful mechanistic information, but only modest additional value for grouping. Overall, these results further demonstrate the value of NAMs for grouping of UVCBs, identify informative cell lines, and provide data that could be used for justifying selection of substances for further testing that may be required for registration