890 resultados para Gene-expression Data


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Background: High-throughput molecular approaches for gene expression profiling, such as Serial Analysis of Gene Expression (SAGE), Massively Parallel Signature Sequencing (MPSS) or Sequencing-by-Synthesis (SBS) represent powerful techniques that provide global transcription profiles of different cell types through sequencing of short fragments of transcripts, denominated sequence tags. These techniques have improved our understanding about the relationships between these expression profiles and cellular phenotypes. Despite this, more reliable datasets are still necessary. In this work, we present a web-based tool named S3T: Score System for Sequence Tags, to index sequenced tags in accordance with their reliability. This is made through a series of evaluations based on a defined rule set. S3T allows the identification/selection of tags, considered more reliable for further gene expression analysis. Results: This methodology was applied to a public SAGE dataset. In order to compare data before and after filtering, a hierarchical clustering analysis was performed in samples from the same type of tissue, in distinct biological conditions, using these two datasets. Our results provide evidences suggesting that it is possible to find more congruous clusters after using S3T scoring system. Conclusion: These results substantiate the proposed application to generate more reliable data. This is a significant contribution for determination of global gene expression profiles. The library analysis with S3T is freely available at http://gdm.fmrp.usp.br/s3t/.S3T source code and datasets can also be downloaded from the aforementioned website.

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Positional information in developing embryos is specified by spatial gradients of transcriptional regulators. One of the classic systems for studying this is the activation of the hunchback (hb) gene in early fruit fly (Drosophila) segmentation by the maternally-derived gradient of the Bicoid (Bcd) protein. Gene regulation is subject to intrinsic noise which can produce variable expression. This variability must be constrained in the highly reproducible and coordinated events of development. We identify means by which noise is controlled during gene expression by characterizing the dependence of hb mRNA and protein output noise on hb promoter structure and transcriptional dynamics. We use a stochastic model of the hb promoter in which the number and strength of Bcd and Hb (self-regulatory) binding sites can be varied. Model parameters are fit to data from WT embryos, the self-regulation mutant hb(14F), and lacZ reporter constructs using different portions of the hb promoter. We have corroborated model noise predictions experimentally. The results indicate that WT (self-regulatory) Hb output noise is predominantly dependent on the transcription and translation dynamics of its own expression, rather than on Bcd fluctuations. The constructs and mutant, which lack self-regulation, indicate that the multiple Bcd binding sites in the hb promoter (and their strengths) also play a role in buffering noise. The model is robust to the variation in Bcd binding site number across a number of fly species. This study identifies particular ways in which promoter structure and regulatory dynamics reduce hb output noise. Insofar as many of these are common features of genes (e. g. multiple regulatory sites, cooperativity, self-feedback), the current results contribute to the general understanding of the reproducibility and determinacy of spatial patterning in early development.

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Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

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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.

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Ethylene signal transduction initiates with ethylene binding at receptor proteins and terminates in a transcription cascade involving the EIN3/EIL transcription factors. Here, we have isolated four cDNAs homologs of the Arabidopsis EIN3/EIN3-like gene, MA-EILs (Musa acuminata ethylene insensitive 3-like) from banana fruit. Sequence comparison with other banana EIL gene already registered in the database led us to conclude that, at this day, at least five different genes namely MA-EIL1, MA-EIL2/AB266318, MA-EIL3/AB266319, MA-EIL4/AB266320 and AB266321 exist in banana. Phylogenetic analyses included all banana EIL genes within a same cluster consisting of rice OsEILs, a monocotyledonous plant as banana. However, MA-EIL1, MA-EIL2/AB266318, MA-EIL4/AB266320 and AB266321 on one side, and MA-EIL3/AB266319 on the other side, belong to two distant subclusters. MA-EIL mRNAs were detected in all examined banana tissues but at lower level in peel than in pulp. According to tissues, MA-EIL genes were differentially regulated by ripening and ethylene in mature green fruit and wounding in old and young leaves. MA-EIL2/AB266318 was the unique ripening- and ethylene-induced gene; MA-EIL1, MA-EIL4/Ab266320 and AB266321 genes were downregulated, while MA-EIL3/AB266319 presented an unusual pattern of expression. Interestingly, a marked change was observed mainly in MA-EIL1 and MA-EIL3/Ab266319 mRNA accumulation concomitantly with changes in ethylene responsiveness of fruit. Upon wounding, the main effect was observed in MA-EIL4/AB266320 and AB266321 mRNA levels, which presented a markedly increase in both young and old leaves, respectively. Data presented in this study suggest the importance of a transcriptionally step control in the regulation of EIL genes during banana fruit ripening.

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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.

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Statement of the study: Based on data from ecological and analytic epidemiological studies, we have proposed that low prenatal vitamin D is a candidate risk-modifying factor for schizophrenia. Previously, we demonstrated that low prenatal vitamin D adversely affected brain development in neonatal rats (Eyles et al, 2003). Here we examine the impact of both prenatal and early life hypovitaminosis D on various outcomes in the adult rat brain. Methods: Female Sprague-Dawley rats were made vitamin D deficient via the use of a special diet (Dyets CA) and lighting conditions that excluded UVB radiation. Animals were kept under these conditions for 6 weeks then mated with males kept under normal conditions. Vitamin deplete dams were kept under these conditions during pregnancy. Offspring from two test groups were examined. Offspring were either reared with dams repleted with vitamin D at birth or remained under deplete conditions till weaning. Both test groups were weaned under normal vitamin D conditions and remained so till testing at adulthood. We compared the brains of adult offspring kept under both test conditions with animals from control environments. Summary of results: We found a significant persistent dose-related increase in lateral ventricle volume and alterations in anterior cingulate and prefrontal cortical cell densities (consistent with the known prodifferentiation properties of this steroid). In both test groups we observed a reduced expression of NGF as well as a down-regulation of transcripts coding for GABAA alpha 4 receptor and two neuronal structural elements; MAP2 and Neurofilament L. Conclusion: These findings provide further evidence that vitamin D is involved in brain development. An increase in prefrontal cortical cell density, a reduction neuronal structural elements and persistent ventriculomegaly are all common anatomical findings in the brains of patients with schizophrenia. The specific reduction in transcripts for neuronal structural proteins but not GFAP is also in accordance with the proposal that frontal cortical architecture in schizophrenia reflects a reduction in connectivity rather than a reduction in glial processes(Goldman-Rakic and Selemon, 1997). These findings confirm the biological plausibility of early life hypovitaminosis D as a risk factor for schizophrenia.

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Purpose: To identify papillary thyroid carcinoma (PTC)-associated transcripts, we compared the gene expression profiles of three Serial Analysis of Gene Expression libraries generated from thyroid tumors and a normal thyroid tissue. Experimental Design: Selected transcripts were validated in a panel of 57 thyroid tumors using quantitative PCR (qPCR). An independent set of 71 paraffin-embedded sections was used for validation using immunohistochemical analysis. To determine if PTC-associated gene expression could predict lymph node involvement, a separate cohort of 130 primary PTC (54 metastatic and 76 nonmetastatic) was investigated. The BRAF(V600E) mutational status was compared with qPCR data to identify genes that might be regulated by abnormal BRAF/MEK/extracellular signal-regulated kinase signaling. Results: We identified and validated new PTC-associated transcripts. Three genes (CST6, CXCL14, and DHRS3) are strongly associated with PTC. Immunohistochemical analysis of CXCL14 confirmed the qPCR data and showed protein expression in PTC epithelial cells. We also observed that CST6, CXCL14, DHRS3, and SPP1 were associated with PTC lymph node metastasis, with CST6, CXCL14, and SPP1 being positively correlated with metastasis and DHRS3 being negatively correlated. Finally, we found a strong correlation between CST6 and CXCL14 expression and BRAF(V600E) mutational status, suggesting that these genes may be induced subsequently to BRAF activation and therefore may be downstream in the BRAF/MEK/extracellular signal-regulated kinase signaling pathway. Conclusion: CST6, CXCL14, DHRS3, and SPP1 may play a role in PTC pathogenesis and progression and are possible molecular targets for FTC therapy.

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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

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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.

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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.

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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.

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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.

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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.

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The MHC region (6p21) aggregates the major genes that contribute to susceptibility to type 1 diabetes (T1D). Three additional relevant susceptibility regions mapped on chromosomes 1p13 (PTPN22), 2q33 (CTLA-4), and 11p15 (insulin) have also been described by linkage studies. To evaluate the contribution of these susceptibility regions and the chromosomes that house these regions, we performed a large-scale differential gene expression on lymphomononuclear cells of recently diagnosed T1D patients, pinpointing relevant modulated genes clustered in these regions and their respective chromosomes. A total of 4608 cDNAs from the IMAGE library were spotted onto glass slides using robotic technology. Statistical analysis was carried out using the SAM program, and data regarding gene location and biological function were obtained at the SOURCE, NCBI, and FATIGO programs. Three induced genes were observed spanning around the MHC region (6p21-6p23), and seven modulated genes (5 repressed and 2 repressed) were seen spanning around the 6q21-24 region. Additional modulated genes were observed in and around the 1p13, 2q33, and 11p15 regions. Overall, modulated genes in these regions were primarily associated with cellular metabolism, transcription factors and signaling transduction. The differential gene expression characterization may identify new genes potentially involved with diabetes pathogenesis.