Versatile gene-specific sequence tags for Arabidopsis functional genomics: transcript profiling and reverse genetics applications.

Microarray transcript profiling and RNA interference are two new technologies crucial for large-scale gene function studies in multicellular eukaryotes. Both rely on sequence-specific hybridization between complementary nucleic acid strands, inciting us to create a collection of gene-specific sequence tags (GSTs) representing at least 21,500 Arabidopsis genes and which are compatible with both approaches. The GSTs were carefully selected to ensure that each of them shared no significant similarity with any other region in the Arabidopsis genome. They were synthesized by PCR amplification from genomic DNA. Spotted microarrays fabricated from the GSTs show good dynamic range, specificity, and sensitivity in transcript profiling experiments. The GSTs have also been transferred to bacterial plasmid vectors via recombinational cloning protocols. These cloned GSTs constitute the ideal starting point for a variety of functional approaches, including reverse genetics. We have subcloned GSTs on a large scale into vectors designed for gene silencing in plant cells. We show that in planta expression of GST hairpin RNA results in the expected phenotypes in silenced Arabidopsis lines. These versatile GST resources provide novel and powerful tools for functional genomics.

EuroDia: a beta-cell gene expression resource.

Type 2 diabetes mellitus (T2DM) is a major disease affecting nearly 280 million people worldwide. Whilst the pathophysiological mechanisms leading to disease are poorly understood, dysfunction of the insulin-producing pancreatic beta-cells is key event for disease development. Monitoring the gene expression profiles of pancreatic beta-cells under several genetic or chemical perturbations has shed light on genes and pathways involved in T2DM. The EuroDia database has been established to build a unique collection of gene expression measurements performed on beta-cells of three organisms, namely human, mouse and rat. The Gene Expression Data Analysis Interface (GEDAI) has been developed to support this database. The quality of each dataset is assessed by a series of quality control procedures to detect putative hybridization outliers. The system integrates a web interface to several standard analysis functions from R/Bioconductor to identify differentially expressed genes and pathways. It also allows the combination of multiple experiments performed on different array platforms of the same technology. The design of this system enables each user to rapidly design a custom analysis pipeline and thus produce their own list of genes and pathways. Raw and normalized data can be downloaded for each experiment. The flexible engine of this database (GEDAI) is currently used to handle gene expression data from several laboratory-run projects dealing with different organisms and platforms. Database URL: http://eurodia.vital-it.ch.

Predator-prey chemical warfare determines the expression of biocontrol genes by rhizosphere-associated Pseudomonas fluorescens.

Soil bacteria are heavily consumed by protozoan predators, and many bacteria have evolved defense strategies such as the production of toxic exometabolites. However, the production of toxins is energetically costly and therefore is likely to be adjusted according to the predation risk to balance the costs and benefits of predator defense. We investigated the response of the biocontrol bacterium Pseudomonas fluorescens CHA0 to a common predator, the free-living amoeba Acanthamoeba castellanii. We monitored the effect of the exposure to predator cues or direct contact with the predators on the expression of the phlA, prnA, hcnA, and pltA genes, which are involved in the synthesis of the toxins, 2,4-diacetylphloroglucinol (DAPG), pyrrolnitrin, hydrogen cyanide, and pyoluteorin, respectively. Predator chemical cues led to 2.2-, 2.0-, and 1.2-fold increases in prnA, phlA, and hcnA expression, respectively, and to a 25% increase in bacterial toxicity. The upregulation of the tested genes was related to the antiprotozoan toxicity of the corresponding toxins. Pyrrolnitrin and DAPG had the highest toxicity, suggesting that bacteria secrete a predator-specific toxin cocktail. The response of the bacteria was elicited by supernatants of amoeba cultures, indicating that water-soluble chemical compounds were responsible for induction of the bacterial defense response. In contrast, direct contact of bacteria with living amoebae reduced the expression of the four bacterial toxin genes by up to 50%, suggesting that protozoa can repress bacterial toxicity. The results indicate that predator-prey interactions are a determinant of toxin production by rhizosphere P. fluorescens and may have an impact on its biocontrol potential.

Low-grade and high-grade mammary carcinomas in WAP-T transgenic mice are independent entities distinguished by Met expression.

Mammary carcinomas developing in SV40 transgenic WAP-T mice arise in two distinct histological phenotypes: as differentiated low-grade and undifferentiated high-grade tumors. We integrated different types of information such as histological grading, analysis of aCGH-based gene copy number and gene expression profiling to provide a comprehensive molecular description of mammary tumors in WAP-T mice. Applying a novel procedure for the correlation of gene copy number with gene expression on a global scale, we observed in tumor samples a global coherence between genotype and transcription. This coherence can be interpreted as a matched transcriptional regulation inherited from the cells of tumor origin and determined by the activity of cancer driver genes. Despite common recurrent genomic aberrations, e.g. gain of chr. 15 in most WAP-T tumors, loss of chr. 19 frequently occurs only in low-grade tumors. These tumors show features of "basal-like" epithelial differentiation, particularly expression of keratin 14. The high-grade tumors are clearly separated from the low-grade tumors by strong expression of the Met gene and by coexpression of epithelial (e.g. keratin 18) and mesenchymal (e.g. vimentin) markers. In high-grade tumors, the expression of the nonmutated Met protein is associated with Met-locus amplification and Met activity. The role of Met as a cancer driver gene is supported by the contribution of active Met signaling to motility and growth of mammary tumor-derived cells. Finally, we discuss the independent origin of low- and high-grade tumors from distinct cells of tumor origin, possibly luminal progenitors, distinguished by Met gene expression and Met signaling.

Cooperative expression of junctional adhesion molecule-C and -B supports growth and invasion of glioma.

Brain invasion is a biological hallmark of glioma that contributes to its aggressiveness and limits the potential of surgery and irradiation. Deregulated expression of adhesion molecules on glioma cells is thought to contribute to this process. Junctional adhesion molecules (JAMs) include several IgSF members involved in leukocyte trafficking, angiogenesis, and cell polarity. They are expressed mainly by endothelial cells, white blood cells, and platelets. Here, we report JAM-C expression by human gliomas, but not by their normal cellular counterpart. This expression correlates with the expression of genes involved in cytoskeleton remodeling and cell migration. These genes, identified by a transcriptomic approach, include poliovirus receptor and cystein-rich 61, both known to promote glioma invasion, as well as actin filament associated protein, a c-Src binding partner. Gliomas also aberrantly express JAM-B, a high affinity JAM-C ligand. Their interaction activates the c-Src proto-oncogene, a central upstream molecule in the pathways regulating cell migration and invasion. In the tumor microenvironment, this co-expression may thus promote glioma invasion through paracrine stimuli from both tumor cells and endothelial cells. Accordingly, JAM-C/B blocking antibodies impair in vivo glioma growth and invasion, highlighting the potential of JAM-C and JAM-B as new targets for the treatment of human gliomas.

A modular approach for integrative analysis of large-scale gene-expression and drug-response data

High-throughput technologies are now used to generate more than one type of data from the same biological samples. To properly integrate such data, we propose using co-modules, which describe coherent patterns across paired data sets, and conceive several modular methods for their identification. We first test these methods using in silico data, demonstrating that the integrative scheme of our Ping-Pong Algorithm uncovers drug-gene associations more accurately when considering noisy or complex data. Second, we provide an extensive comparative study using the gene-expression and drug-response data from the NCI-60 cell lines. Using information from the DrugBank and the Connectivity Map databases we show that the Ping-Pong Algorithm predicts drug-gene associations significantly better than other methods. Co-modules provide insights into possible mechanisms of action for a wide range of drugs and suggest new targets for therapy

Gene expression databases and data mining.

The DNA microarray technology has arguably caught the attention of the worldwide life science community and is now systematically supporting major discoveries in many fields of study. The majority of the initial technical challenges of conducting experiments are being resolved, only to be replaced with new informatics hurdles, including statistical analysis, data visualization, interpretation, and storage. Two systems of databases, one containing expression data and one containing annotation data are quickly becoming essential knowledge repositories of the research community. This present paper surveys several databases, which are considered "pillars" of research and important nodes in the network. This paper focuses on a generalized workflow scheme typical for microarray experiments using two examples related to cancer research. The workflow is used to reference appropriate databases and tools for each step in the process of array experimentation. Additionally, benefits and drawbacks of current array databases are addressed, and suggestions are made for their improvement.

Classification of human astrocytic gliomas on the basis of gene expression: a correlated group of genes with angiogenic activity emerges as a strong predictor of subtypes.

The development of targeted treatment strategies adapted to individual patients requires identification of the different tumor classes according to their biology and prognosis. We focus here on the molecular aspects underlying these differences, in terms of sets of genes that control pathogenesis of the different subtypes of astrocytic glioma. By performing cDNA-array analysis of 53 patient biopsies, comprising low-grade astrocytoma, secondary glioblastoma (respective recurrent high-grade tumors), and newly diagnosed primary glioblastoma, we demonstrate that human gliomas can be differentiated according to their gene expression. We found that low-grade astrocytoma have the most specific and similar expression profiles, whereas primary glioblastoma exhibit much larger variation between tumors. Secondary glioblastoma display features of both other groups. We identified several sets of genes with relatively highly correlated expression within groups that: (a). can be associated with specific biological functions; and (b). effectively differentiate tumor class. One prominent gene cluster discriminating primary versus nonprimary glioblastoma comprises mostly genes involved in angiogenesis, including VEGF fms-related tyrosine kinase 1 but also IGFBP2, that has not yet been directly linked to angiogenesis. In situ hybridization demonstrating coexpression of IGFBP2 and VEGF in pseudopalisading cells surrounding tumor necrosis provided further evidence for a possible involvement of IGFBP2 in angiogenesis. The separating groups of genes were found by the unsupervised coupled two-way clustering method, and their classification power was validated by a supervised construction of a nearly perfect glioma classifier.

Gene expression variation and expression quantitative trait mapping of human chromosome 21 genes.

Inter-individual differences in gene expression are likely to account for an important fraction of phenotypic differences, including susceptibility to common disorders. Recent studies have shown extensive variation in gene expression levels in humans and other organisms, and that a fraction of this variation is under genetic control. We investigated the patterns of gene expression variation in a 25 Mb region of human chromosome 21, which has been associated with many Down syndrome (DS) phenotypes. Taqman real-time PCR was used to measure expression variation of 41 genes in lymphoblastoid cells of 40 unrelated individuals. For 25 genes found to be differentially expressed, additional analysis was performed in 10 CEPH families to determine heritabilities and map loci harboring regulatory variation. Seventy-six percent of the differentially expressed genes had significant heritabilities, and genomewide linkage analysis led to the identification of significant eQTLs for nine genes. Most eQTLs were in trans, with the best result (P=7.46 x 10(-8)) obtained for TMEM1 on chromosome 12q24.33. A cis-eQTL identified for CCT8 was validated by performing an association study in 60 individuals from the HapMap project. SNP rs965951 located within CCT8 was found to be significantly associated with its expression levels (P=2.5 x 10(-5)) confirming cis-regulatory variation. The results of our study provide a representative view of expression variation of chromosome 21 genes, identify loci involved in their regulation and suggest that genes, for which expression differences are significantly larger than 1.5-fold in control samples, are unlikely to be involved in DS-phenotypes present in all affected individuals.

The fou2 gain-of-function allele and the wild-type allele of Two Pore Channel 1 contribute to different extents or by different mechanisms to defense gene expression in Arabidopsis.

The fatty acid oxygenation up-regulated 2 (fou2) mutant in Arabidopsis thaliana creates a gain-of-function allele in a non-selective cation channel encoded by the Two Pore Channel 1 (TPC1) gene. This mutant genetically implicates cation fluxes in the control of the positive feedback loop whereby jasmonic acid (JA) stimulates its own synthesis. In this study we observed extensive transcriptome reprogramming in healthy fou2 leaves closely resembling that induced by treatment with methyl jasmonate, biotic stresses and the potassium starvation response. Proteomic analysis of fou2 leaves identified increased levels of seven biotic stress- and JA-inducible proteins. In agreement with these analyses, epistasis studies performed by crossing fou2 with aos indicated that elevated levels of JA in fou2 are the major determinant of the mutant phenotype. In addition, generation of fou2 aba1-5, fou2 etr1-1 and fou2 npr1-1 double mutants showed that the fou2 phenotype was only weakly affected by ABA levels and unaffected by mutations in NPR1 and ETR1. The results now suggest possible mechanisms whereby fou2 could induce JA synthesis/signaling early in the wound response. In contrast to fou2, transcriptome analysis of a loss-of-function allele of TPC1, tpc1-2, revealed no differential expression of JA biosynthesis genes in resting leaves. However, the analysis disclosed reduced mRNA levels of the pathogenesis-related genes PDF1.2a and THI2.1 in healthy and diseased tpc1-2 leaves. The results suggest that wild-type TPC1 contributes to their expression by mechanisms somewhat different from those affecting their expression in fou2.

Identification of corticosteroid-regulated genes in cardiomyocytes by serial analysis of gene expression.

Corticosteroids (aldosterone, cortisol/corticosterone) exert direct functional effects on cardiomyocytes. However, gene networks activated by corticosteroids in cardiomyocytes, as well as the involvement of the mineralocorticoid receptor (MR) vs the glucocorticoid receptor (GR) in these effects, remain largely unknown. Here we characterized the corticosteroid-dependent transcriptome in primary culture of neonatal mouse cardiomyocytes treated with 10(-6) M aldosterone, a concentration predicted to occupy both MR and GR. Serial analysis of gene expression revealed 101 aldosterone-regulated genes. The MR/GR specificity was characterized for one regulated transcript, namely ecto-ADP-ribosyltransferase-3 (Art3). Using cardiomyocytes from GR(null/null) or MR(null/null) mice we demonstrate that in GR(null/null) cardiomyocytes the response is abrogated, but it is fully maintained in MR(null/null) cardiomyocytes. We conclude that Art3 expression is regulated exclusively via the GR. Our study identifies a new set of corticosteroid-regulated genes in cardiomyocytes and demonstrates a new approach to studying the selectivity of MR- vs GR-dependent effects.

Steady-state expression of self-regulated genes.

MOTIVATION: Regulatory gene networks contain generic modules such as feedback loops that are essential for the regulation of many biological functions. The study of the stochastic mechanisms of gene regulation is instrumental for the understanding of how cells maintain their expression at levels commensurate with their biological role, as well as to engineer gene expression switches of appropriate behavior. The lack of precise knowledge on the steady-state distribution of gene expression requires the use of Gillespie algorithms and Monte-Carlo approximations. METHODOLOGY: In this study, we provide new exact formulas and efficient numerical algorithms for computing/modeling the steady-state of a class of self-regulated genes, and we use it to model/compute the stochastic expression of a gene of interest in an engineered network introduced in mammalian cells. The behavior of the genetic network is then analyzed experimentally in living cells. RESULTS: Stochastic models often reveal counter-intuitive experimental behaviors, and we find that this genetic architecture displays a unimodal behavior in mammalian cells, which was unexpected given its known bimodal response in unicellular organisms. We provide a molecular rationale for this behavior, and we implement it in the mathematical picture to explain the experimental results obtained from this network.

Analysis of HIV-1 expression level and sense of transcription by high-throughput sequencing of the infected cell.

Next-generation sequencing offers an unprecedented opportunity to jointly analyze cellular and viral transcriptional activity without prerequisite knowledge of the nature of the transcripts. SupT1 cells were infected with a vesicular stomatitis virus G envelope protein (VSV-G)-pseudotyped HIV vector. At 24 h postinfection, both cellular and viral transcriptomes were analyzed by serial analysis of gene expression followed by high-throughput sequencing (SAGE-Seq). Read mapping resulted in 33 to 44 million tags aligning with the human transcriptome and 0.23 to 0.25 million tags aligning with the genome of the HIV-1 vector. Thus, at peak infection, 1 transcript in 143 is of viral origin (0.7%), including a small component of antisense viral transcription. Of the detected cellular transcripts, 826 (2.3%) were differentially expressed between mock- and HIV-infected samples. The approach also assessed whether HIV-1 infection modulates the expression of repetitive elements or endogenous retroviruses. We observed very active transcription of these elements, with 1 transcript in 237 being of such origin, corresponding on average to 123,123 reads in mock-infected samples (0.40%) and 129,149 reads in HIV-1-infected samples (0.45%) mapping to the genomic Repbase repository. This analysis highlights key details in the generation and interpretation of high-throughput data in the setting of HIV-1 cellular infection.

The effect of translocation-induced nuclear reorganization on gene expression.

Translocations are known to affect the expression of genes at the breakpoints and, in the case of unbalanced translocations, alter the gene copy number. However, a comprehensive understanding of the functional impact of this class of variation is lacking. Here, we have studied the effect of balanced chromosomal rearrangements on gene expression by comparing the transcriptomes of cell lines from controls and individuals with the t(11;22)(q23;q11) translocation. The number of differentially expressed transcripts between translocation-carrying and control cohorts is significantly higher than that observed between control samples alone, suggesting that balanced rearrangements have a greater effect on gene expression than normal variation. Many of the affected genes are located along the length of the derived chromosome 11. We show that this chromosome is concomitantly altered in its spatial organization, occupying a more central position in the nucleus than its nonrearranged counterpart. Derivative 22-mapping chromosome 22 genes, on the other hand, remain in their usual environment. Our results are consistent with recent studies that experimentally altered nuclear organization, and indicated that nuclear position plays a functional role in regulating the expression of some genes in mammalian cells. Our study suggests that chromosomal translocations can result in hitherto unforeseen, large-scale changes in gene expression that are the consequence of alterations in normal chromosome territory positioning. This has consequences for the patterns of gene expression change seen during tumorigenesis-associated genome instability and during the karyotype changes that lead to speciation.

Angiogenesis-related gene expression profile with independent prognostic value in advanced ovarian carcinoma.

BACKGROUND Ovarian carcinoma is the most important cause of gynecological cancer-related mortality in Western societies. Despite the improved median overall survival in patients receiving chemotherapy regimens such as paclitaxel and carboplatin combination, relapse still occurs in most advanced diseased patients. Increased angiogenesis is associated with rapid recurrence and decreased survival in ovarian cancer. This study was planned to identify an angiogenesis-related gene expression profile with prognostic value in advanced ovarian carcinoma patients. METHODOLOGY/PRINCIPAL FINDINGS RNAs were collected from formalin-fixed paraffin-embedded samples of 61 patients with III/IV FIGO stage ovarian cancer who underwent surgical cytoreduction and received a carboplatin plus paclitaxel regimen. Expression levels of 82 angiogenesis related genes were measured by quantitative real-time polymerase chain reaction using TaqMan low-density arrays. A 34-gene-profile which was able to predict the overall survival of ovarian carcinoma patients was identified. After a leave-one-out cross validation, the profile distinguished two groups of patients with different outcomes. Median overall survival and progression-free survival for the high risk group was 28.3 and 15.0 months, respectively, and was not reached by patients in the low risk group at the end of follow-up. Moreover, the profile maintained an independent prognostic value in the multivariate analysis. The hazard ratio for death was 2.3 (95% CI, 1.5 to 3.2; p<0.001). CONCLUSIONS/SIGNIFICANCE It is possible to generate a prognostic model for advanced ovarian carcinoma based on angiogenesis-related genes using formalin-fixed paraffin-embedded samples. The present results are consistent with the increasing weight of angiogenesis genes in the prognosis of ovarian carcinoma.