Tissue-specific gene expression in soybean (Glycine max) detected by cDNA microarray analysis

We have constructed cDNA microarrays for soybean (Glycine max L. Merrill), containing approximately 4,100 Unigene ESTs derived from axenic roots, to evaluate their application and utility for functional genomics of organ differentiation in legumes. We assessed microarray technology by conducting studies to evaluate the accuracy of microarray data and have found them to be both reliable and reproducible in repeat hybridisations. Several ESTs showed high levels (>50 fold) of differential expression in either root or shoot tissue of soybean. A small number of physiologically interesting, and differentially expressed sequences found by microarray analysis were verified by both quantitative real-time RT-PCR and Northern blot analysis. There was a linear correlation (r(2) = 0.99, over 5 orders of magnitude) between microarray and quantitative real-time RT-PCR data. Microarray analysis of soybean has enormous potential not only for the discovery of new genes involved in tissue differentiation and function, but also to study the expression of previously characterised genes, gene networks and gene interactions in wild-type, mutant or transgenic; plants.

The full Bayesian significance test for mixture models: results in gene expression clustering

Gene clustering is a useful exploratory technique to group together genes with similar expression levels under distinct cell cycle phases or distinct conditions. It helps the biologist to identify potentially meaningful relationships between genes. In this study, we propose a clustering method based on multivariate normal mixture models, where the number of clusters is predicted via sequential hypothesis tests: at each step, the method considers a mixture model of m components (m = 2 in the first step) and tests if in fact it should be m - 1. If the hypothesis is rejected, m is increased and a new test is carried out. The method continues (increasing m) until the hypothesis is accepted. The theoretical core of the method is the full Bayesian significance test, an intuitive Bayesian approach, which needs no model complexity penalization nor positive probabilities for sharp hypotheses. Numerical experiments were based on a cDNA microarray dataset consisting of expression levels of 205 genes belonging to four functional categories, for 10 distinct strains of Saccharomyces cerevisiae. To analyze the method's sensitivity to data dimension, we performed principal components analysis on the original dataset and predicted the number of classes using 2 to 10 principal components. Compared to Mclust (model-based clustering), our method shows more consistent results.

Gene expression profile of the plant pathogen Fusarium graminearum under the antagonistic effect of Pantoea agglomerans

The pathogenic fungus Fusarium graminearum is an ongoing threat to agriculture, causing losses in grain yield and quality in diverse crops. Substantial progress has been made in the identification of genes involved in the suppression of phytopathogens by antagonistic microorganisms; however, limited information regarding responses of plant pathogens to these biocontrol agents is available. Gene expression analysis was used to identify differentially expressed transcripts of the fungal plant pathogen F. graminearum under antagonistic effect of the bacterium Pantoea agglomerans. A macroarray was constructed, using 1014 transcripts from an F. graminearum cDNA library. Probes consisted of the cDNA of F. graminearum grown in the presence and in the absence of P. agglomerans. Twenty-nine genes were either up (19) or down (10) regulated during interaction with the antagonist bacterium. Genes encoding proteins associated with fungal defense and/or virulence or with nutritional and oxidative stress responses were induced. The repressed genes coded for a zinc finger protein associated with cell division, proteins containing cellular signaling domains, respiratory chain proteins, and chaperone-type proteins. These data give molecular and biochemical evidence of response of F. graminearum to an antagonist and could help develop effective biocontrol procedures for pathogenic plant fungi.

Global gene expression under nitrogen starvation in Xylella fastidiosa: contribution of the sigma(54) regulon

Background: Xylella fastidiosa, a Gram-negative fastidious bacterium, grows in the xylem of several plants causing diseases such as citrus variegated chlorosis. As the xylem sap contains low concentrations of amino acids and other compounds, X. fastidiosa needs to cope with nitrogen limitation in its natural habitat. Results: In this work, we performed a whole-genome microarray analysis of the X. fastidiosa nitrogen starvation response. A time course experiment (2, 8 and 12 hours) of cultures grown in defined medium under nitrogen starvation revealed many differentially expressed genes, such as those related to transport, nitrogen assimilation, amino acid biosynthesis, transcriptional regulation, and many genes encoding hypothetical proteins. In addition, a decrease in the expression levels of many genes involved in carbon metabolism and energy generation pathways was also observed. Comparison of gene expression profiles between the wild type strain and the rpoN null mutant allowed the identification of genes directly or indirectly induced by nitrogen starvation in a sigma(54)-dependent manner. A more complete picture of the sigma(54) regulon was achieved by combining the transcriptome data with an in silico search for potential sigma(54)-dependent promoters, using a position weight matrix approach. One of these sigma(54)-predicted binding sites, located upstream of the glnA gene (encoding glutamine synthetase), was validated by primer extension assays, confirming that this gene has a sigma(54)-dependent promoter. Conclusions: Together, these results show that nitrogen starvation causes intense changes in the X. fastidiosa transcriptome and some of these differentially expressed genes belong to the sigma(54) regulon.

Differential gene expression between the biotrophic-like and saprotrophic mycelia of the witches` broom pathogen Moniliophthora perniciosa

Moniliophthora perniciosa is a hemibiotrophic fungus that causes witches` broom disease (WBD) in cacao. Marked dimorphism characterizes this fungus, showing a monokaryotic or biotrophic phase that causes disease symptoms and a later dikaryotic or saprotrophic phase. A combined strategy of DNA microarray, expressed sequence tag, and real-time reverse-transcriptase polymerase chain reaction analyses was employed to analyze differences between these two fungal stages in vitro. In all, 1,131 putative genes were hybridized with cDNA from different phases, resulting in 189 differentially expressed genes, and 4,595 reads were clusterized, producing 1,534 unigenes. The analysis of these genes, which represent approximately 21% of the total genes, indicates that the biotrophic-like phase undergoes carbon and nitrogen catabollite repression that correlates to the expression of phytopathogenicity genes. Moreover, downregulation of mitochondrial oxidative phosphorylation and the presence of a putative ngr1 of Saccharomyces cerevisiae could help explain its lower growth rate. In contrast, the saprotrophic mycelium expresses genes related to the metabolism of hexoses, ammonia, and oxidative phosphorylation, which could explain its faster growth. Antifungal toxins were upregulated and could prevent the colonization by competing fungi. This work significantly contributes to our understanding of the molecular mechanisms of WBD and, to our knowledge, is the first to analyze differential gene expression of the different phases of a hemibiotrophic fungus.

Using biplots to interpret gene expression patterns in plants

Sum: Plant biologists in fields of ecology, evolution, genetics and breeding frequently use multivariate methods. This paper illustrates Principal Component Analysis (PCA) and Gabriel's biplot as applied to microarray expression data from plant pathology experiments. Availability: An example program in the publicly distributed statistical language R is available from the web site (www.tpp.uq.edu.au) and by e-mail from the contact. Contact: scott.chapman@csiro.au.

Reciprocal changes in gene expression profiles of cocultured breast epithelial cells and primary fibroblasts

The importance of epithelial-stroma interaction in normal breast development and tumor progression has been recognized. To identify genes that were regulated by these reciprocal interactions, we cocultured a nonmalignant (MCF10A) and a breast cancer derived (MDA-MB231) basal cell lines, with fibroblasts isolated from breast benign-disease adjacent tissues (NAF) or with carcinoma-associated fibroblasts (CAF), in a transwell system. Gene expression profiles of each coculture pair were compared with the correspondent monocultures, using a customized microarray. Contrariwise to large alterations in epithelial cells genomic profiles, fibroblasts were less affected. In MDA-MB231 highly represented genes downregulated by CAF derived factors coded for proteins important for the specificity of vectorial transport between ER and golgi, possibly affecting cell polarity whereas the response of MCF10A comprised an induction of genes coding for stress responsive proteins, representing a prosurvival effect. While NAF downregulated genes encoding proteins associated to glycolipid and fatty acid biosynthesis in MDA-MB231, potentially affecting membrane biogenesis, in MCF10A, genes critical for growth control and adhesion were altered. NAFs responded to coculture with MDA-MB231 by a decrease in the expression of genes induced by TGF beta 1 and associated to motility. However, there was little change in NAFs gene expression profile influenced by MCF10A. CAFs responded to the presence of both epithelial cells inducing genes implicated in cell proliferation. Our data indicate that interactions between breast fibroblasts and basal epithelial cells resulted in alterations in the genomic profiles of both cell types which may help to clarify some aspects of this heterotypic signaling. (C) 2009 UICC

Insights on PRAME and osteosarcoma by means of gene expression profiling

Osteosarcoma (OS) is the most frequent bone tumor in children and adolescents. Tumor antigens are encoded by genes that are expressed in many types of solid tumors but are silent in normal tissues, with the exception of placenta and male germ-line cells. It has been proposed that antigen tumors are potential tumor markers. The premise of this study is that the identification of novel OS-associated transcripts will lead to a better understanding of the events involved in OS pathogenesis and biology. We analyzed the expression of a panel of seven tumor antigens in OS samples to identify possible tumor markers. After selecting the tumor antigen expressed in most samples of the panel, gene expression profiling was used to identify osteosarcoma-associated molecular alterations. A microarray was employed because of its ability to accurately produce comprehensive expression profiles. PRAME was identified as the tumor antigen expressed in most OS samples; it was detected in 68% of the cases. Microarray results showed differences in expression for genes functioning in cell signaling and adhesion as well as extracellular matrix-related genes, implying that such tumors could indeed differ in regard to distinct patterns of tumorigenesis. The hypothesis inferred in this study was gathered mostly from available data concerning other kinds of tumors. There is circumstantial evidence that PRAME expression might be related to distinct patterns of tumorigenesis. Further investigation is needed to validate the differential expression of genes belonging to tumorigenesis-related pathways in PRAME-positive and PRAME-negative tumors.

Alterations in myocardial gene expression associated with experimental Trypanosoma cruzi infection

Chagas disease, characterized by acute myocarditis and chronic cardiomyopathy, is caused by infection with the protozoan parasite Trypanosoma cruzi. We sought to identify genes altered during the development of parasite-induced cardiomyopathy. Microarrays containing 27,400 sequence-verified mouse cDNAs were used to analyze global gene expression changes in the myocardium of a murine model of chagasic cardiomyopathy. Changes in gene expression were determined as the acute stage of infection developed into the chronic stage. This analysis was performed on the hearts of male CD-1 mice infected with trypomastigotes of T. cruzi (Brazil strain). At each interval we compared infected and uninfected mice and confirmed the microarray data with dye reversal. We identified eight distinct categories of mRNAs that were differentially regulated during infection and identified dysregulation of several key genes. These data may provide insight into the pathogenesis of chagasic cardiomyopathy and provide new targets for intervention. (c) 2008 Elsevier Inc. All rights reserved.

Gene expression profile analysis of primary glioblastomas and non-neoplastic brain tissue: identification of potential target genes by oligonucleotide microarray and real-time quantitative PCR

The prognosis of glioblastomas is still extremely poor and the discovery of novel molecular therapeutic targets can be important to optimize treatment strategies. Gene expression analyses comparing normal and neoplastic tissues have been used to identify genes associated with tumorigenesis and potential therapeutic targets. We have used this approach to identify differentially expressed genes between primary glioblastomas and non-neoplastic brain tissues. We selected 20 overexpressed genes related to cell cycle, cellular movement and growth, proliferation and cell-to-cell signaling and analyzed their expression levels by real time quantitative PCR in cDNA obtained from microdissected fresh tumor tissue from 20 patients with primary glioblastomas and from 10 samples of non-neoplastic white matter tissue. The gene expression levels were significantly higher in glioblastomas than in non-neoplastic white matter in 18 out of 20 genes analyzed: P < 0.00001 for CDKN2C, CKS2, EEF1A1, EMP3, PDPN, BNIP2, CA12, CD34, CDC42EP4, PPIE, SNAI2, GDF15 and MMP23b; and NFIA (P: 0.0001), GPS1 (P: 0.0003), LAMA1 (P: 0.002), STIM1 (P: 0.006), and TASP1 (P: 0.01). Five of these genes are located in contiguous loci at 1p31-36 and 2 at 17q24-25 and 8 of them encode surface membrane proteins. PDPN and CD34 protein expression were evaluated by immunohistochemistry and they showed concordance with the PCR results. The present results indicate the presence of 18 overexpressed genes in human primary glioblastomas that may play a significant role in the pathogenesis of these tumors and that deserve further functional investigation as attractive candidates for new therapeutic targets.

Evidence for a network transcriptional control of promiscuous gene expression in medullary thymic epithelial cells

The expression of peripheral tissue antigens (PTAs) in the thymus by medullary thymic epithelial cells (mTECs) is essential for the central self-tolerance in the generation of the T cell repertoire. Due to heterogeneity of autoantigen representation, this phenomenon has been termed promiscuous gene expression (PGE), in which the autoimmune regulator (Aire) gene plays a key role as a transcription factor in part of these genes. Here we used a microarray strategy to access PGE in cultured murine CD80(+) 3.10 mTEC line. Hierarchical clustering of the data allowed observation that PTA genes were differentially expressed being possible to found their respective induced or repressed mRNAs. To further investigate the control of PGE, we tested the hypothesis that genes involved in this phenomenon might also be modulated by transcriptional network. We then reconstructed such network based on the microarray expression data, featuring the guanylate cyclase 2d (Gucy2d) gene as a main node. In such condition, we established 167 positive and negative interactions with downstream PTA genes. Silencing Aire by RNA interference, Gucy2d while down regulated established a larger number (355) of interactions with PTA genes. T- and G-boxes corresponding to AIRE protein binding sites located upstream to ATG codon of Gucy2d supports this effect. These findings provide evidence that Aire plays a role in association with Gucy2d, which is connected to Several PTA genes and establishes a cascade-like transcriptional control of promiscuous gene expression in mTEC cells. (C) 2009 Elsevier Ltd. All rights reserved.

Differential gene expression of peripheral blood mononuclear cells from rheumatoid arthritis patients may discriminate immunogenetic, pathogenic and treatment features

This study aimed to evaluate the association between the differential gene expression profiling of peripheral blood mononuclear cells of rheumatoid arthritis patients with their immunogenetic (human leucocyte antigen shared-epitope, HLA-SE), autoimmune response [anti-cyclic citrullinated peptide (CCP) antibodies], disease activity score (DAS-28) and treatment (disease-modifying antirheumatic drugs and tumour necrosis factor blocker) features. Total RNA samples were copied into Cy3-labelled complementary DNA probes, hybridized onto a glass slide microarray containing 4500 human IMAGE complementary DNA target sequences. The Cy3-monocolour microarray images from patients were quantified and normalized. Analysis of the data using the significance analysis of microarrays algorithm together with a Venn diagram allowed the identification of shared and of exclusively modulated genes, according to patient features. Thirteen genes were exclusively associated with the presence of HLA-SE alleles, whose major biological function was related to signal transduction, phosphorylation and apoptosis. Ninety-one genes were associated with disease activity, being involved in signal transduction, apoptosis, response to stress and DNA damage. One hundred and one genes were associated with the presence of anti-CCP antibodies, being involved in signal transduction, cell proliferation and apoptosis. Twenty-eight genes were associated with tumour necrosis factor blocker treatment, being involved in intracellular signalling cascade, phosphorylation and protein transport. Some of these genes had been previously associated with rheumatoid arthritis pathogenesis, whereas others were unveiled for future research.

Affected and non-affected skin fibroblasts from systemic sclerosis patients share a gene expression profile deviated from the one observed in healthy individuals

Objectives To evaluate the gene expression profile of fibroblasts from affected and non-affected skin of systemic sclerosis (SSc) patients and from controls. Materials and methods Labeled cDNA from fibroblast cultures from forearm (affected) and axillary (non-affected) skin from six diffuse SSc patients, from three normal controls, and from MOLT-4/HEp-2/normal fibroblasts (reference pool) was probed in microarrays generated with 4193 human cDNAs from the IMAGE Consortium. Microarray images were converted into numerical data and gene expression was calculated as the ratio between fibroblast cDNA (Cy5) and reference pool cDNA (Cy3) data and analyzed by R environment/Aroma, Cluster, Tree View, and SAM softwares. Differential expression was confirmed by real time PCR for a set of selected genes. Results Eighty-eight genes were up- and 241 genes down-regulated in SSc fibroblasts. Gene expression correlation was strong between affected and non-affected fibroblast samples from the same patient (r>0.8), moderate among fibroblasts from all patients (r=0.72) and among fibroblasts from all controls (r=0.70), and modest among fibroblasts from patients and controls (r=0.55). The differential expression was confirmed by real time PCR for all selected genes. Conclusions Fibroblasts from affected and non-affected skin of SSc patients shared a similar abnormal gene expression profile, suggesting that the widespread molecular disturbance in SSc fibroblasts is more sensitive than histological and clinical alterations. Novel molecular elements potentially involved in SSc pathogenesis were identified.

Development of computational tools for the integrated analysis of DNA microarray data with applications in cancer research

The MAP-i Doctoral Program of the Universities of Minho, Aveiro and Porto

Integrating data from heterogeneous DNA microarray platforms

DNA microarrays are one of the most used technologies for gene expression measurement. However, there are several distinct microarray platforms, from different manufacturers, each with its own measurement protocol, resulting in data that can hardly be compared or directly integrated. Data integration from multiple sources aims to improve the assertiveness of statistical tests, reducing the data dimensionality problem. The integration of heterogeneous DNA microarray platforms comprehends a set of tasks that range from the re-annotation of the features used on gene expression, to data normalization and batch effect elimination. In this work, a complete methodology for gene expression data integration and application is proposed, which comprehends a transcript-based re-annotation process and several methods for batch effect attenuation. The integrated data will be used to select the best feature set and learning algorithm for a brain tumor classification case study. The integration will consider data from heterogeneous Agilent and Affymetrix platforms, collected from public gene expression databases, such as The Cancer Genome Atlas and Gene Expression Omnibus.