893 resultados para cytokine gene expression
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The molecular pathogenesis of myelodysplastic syndromes (MDS) is poorly understood. In order to expand our knowledge of genetic defects in MDS, we determined the overall profile of genes expressed in bone marrow from patients with refractory anemia with excess blasts ( RAEB) by serial analysis of gene expression ( SAGE). The present report describes a partial transcriptome of RAEB bone marrow derived from 56,694 sequenced tags that provides information about expressed gene products. This is the first attempt to determine an overall profile of gene expression specifically in RAEB at diagnosis using SAGE, which should be useful in the understanding of the physiopathology of MDS and in identifying the genes involved.
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Background: Without intensive selection, the majority of bovine oocytes submitted to in vitro embryo production (IVP) fail to develop to the blastocyst stage. This is attributed partly to their maturation status and competences. Using the Affymetrix GeneChip Bovine Genome Array, global mRNA expression analysis of immature (GV) and in vitro matured (IVM) bovine oocytes was carried out to characterize the transcriptome of bovine oocytes and then use a variety of approaches to determine whether the observed transcriptional changes during IVM was real or an artifact of the techniques used during analysis. Results: 8489 transcripts were detected across the two oocyte groups, of which similar to 25.0% (2117 transcripts) were differentially expressed (p < 0.001); corresponding to 589 over-expressed and 1528 under-expressed transcripts in the IVM oocytes compared to their immature counterparts. Over expression of transcripts by IVM oocytes is particularly interesting, therefore, a variety of approaches were employed to determine whether the observed transcriptional changes during IVM were real or an artifact of the techniques used during analysis, including the analysis of transcript abundance in oocytes in vitro matured in the presence of a-amanitin. Subsets of the differentially expressed genes were also validated by quantitative real-time PCR (qPCR) and the gene expression data was classified according to gene ontology and pathway enrichment. Numerous cell cycle linked (CDC2, CDK5, CDK8, HSPA2, MAPK14, TXNL4B), molecular transport (STX5, STX17, SEC22A, SEC22B), and differentiation (NACA) related genes were found to be among the several over-expressed transcripts in GV oocytes compared to the matured counterparts, while ANXA1, PLAU, STC1and LUM were among the over-expressed genes after oocyte maturation. Conclusion: Using sequential experiments, we have shown and confirmed transcriptional changes during oocyte maturation. This dataset provides a unique reference resource for studies concerned with the molecular mechanisms controlling oocyte meiotic maturation in cattle, addresses the existing conflicting issue of transcription during meiotic maturation and contributes to the global goal of improving assisted reproductive technology.
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Cloning by nuclear transfer is often associated with poor results due to abnormal nuclear reprogramming of somatic donor cells and altered gene expression patterns. We investigated the expression patterns of imprinted genes IGF2 and IGF2R in 33- to 36-day bovine embryos and chorio-allantoic membranes derived from in vivo- and in vitro-produced embryos by somatic cell nuclear transfer (SCNT), parthenogenetic activation, and in vitro fertilization (IVF). There was a lower IGF2 expression rate in the SCNT (0.19) and parthenogenetic (0.02) groups when compared to in vivo and IVF embryos (2.01; P < 0.05). In the chorio-allantoic membranes, IGF2 showed a baseline expression pattern (P < 0.05) in parthenotes (0.001) when compared to in vivo, IVF (3.13), and SCNT (0.98) groups. IGF2R was less expressed (P < 0.05) in SCNT chorio-allantoic membranes (0.25) when compared to the in vivo group. The low expression of IGF2 in parthenogenetic embryos and chorio-allantoic membranes confirms its imprinted status in cattle. Alterations in the relative frequency of IGF2 and IGF2R transcripts were observed in SCNT-derived bovine embryos and chorioallantoic membranes, respectively, supporting the hypothesis that abnormalities in the expression of imprinted genes are causes of the low efficiency of SCNT procedures in this species.
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Imprinted inactivation of the paternal X chromosome in marsupials is the primordial mechanism of dosage compensation for X-linked genes between females and males in Therians. In Eutherian mammals, X chromosome inactivation (XCI) evolved into a random process in cells from the embryo proper, where either the maternal or paternal X can be inactivated. However, species like mouse and bovine maintained imprinted XCI exclusively in extraembryonic tissues. The existence of imprinted XCI in humans remains controversial, with studies based on the analyses of only one or two X-linked genes in different extraembryonic tissues. Here we readdress this issue in human term placenta by performing a robust analysis of allele-specific expression of 22 X-linked genes, including XIST, using 27 SNPs in transcribed regions. We show that XCI is random in human placenta, and that this organ is arranged in relatively large patches of cells with either maternal or paternal inactive X. In addition, this analysis indicated heterogeneous maintenance of gene silencing along the inactive X, which combined with the extensive mosaicism found in placenta, can explain the lack of agreement among previous studies. Our results illustrate the differences of XCI mechanism between humans and mice, and highlight the importance of addressing the issue of imprinted XCI in other species in order to understand the evolution of dosage compensation in placental mammals.
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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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Important features of the enteroinvasive Escherichia coli (EIEC) phenotype and gene expression likely to confer EIEC with a lower ability to cause disease than Shigella flexneri were described here for the first time. To confirm the lower pathogenicity of EIEC, we have analyzed the keratoconjunctivitis developed in guinea-pigs with EIEC or S. flexneri. Shigella flexneri induced a more pronounced proinflammatory response, whereas EIEC induced a mild form of the disease. EIEC showed a significantly less efficient cell-to-cell Caco-2 dissemination when compared with S. flexneri. Plaques formed by EIEC during intercellular spreading were four times smaller than those formed by S. flexneri. At the molecular level, the lower expression of virulence genes by EIEC during infection of Caco-2 cells highlighted the importance of effective gene transcription for bacterial pathogenicity.
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Background: The transcription factors SREBP1 and SCAP are involved in intracellular cholesterol homeostasis. Polymorphisms of these genes have been associated with variations on serum lipid levels and response to statins that are potent cholesterol-lowering drugs. We evaluated the effects of atorvastatin on SREBF1a and SCAP mRNA expression in peripheral blood mononuclear cells (PBMC) and a possible association with gene polymorphisms and lowering-cholesterol response. Methods: Fifty-nine hypercholesterolemic patients were treated with atorvastatin (10 mg/day for 4 weeks). Serum lipid profile and mRNA expression in PBMC were assessed before and after the treatment. Gene expression was quantified by real-time PCR using GAPD as endogenous reference and mRNA expression in HepG2 cells as calibrator. SREBF1 -36delG and SCAP A2386G polymorphisms were detected by PCR-RFLP. Results: Our results showed that transcription of SREBF1a and SCAP was coordinately regulated by atorvastatin (r=0.595, p<0.001), and that reduction in SCAP transcription was associated with the 2386AA genotype (p=0.019). Individuals who responded to atorvastatin with a downregulation of SCAP had also a lower triglyceride compared to those who responded to atorvastatin with an upregulation of SCAP. Conclusion: Atorvastatin has differential effects on SREBF1a and SCAP mRNA expression in PBMC that are associated with baseline transcription levels, triglycerides response to atorvastatin and SCAP A2386G polymorphism. (c) 2008 Elsevier B.V. All rights reserved.
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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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Paracoccidioides brasiliensis infectious process relies on the initial expression of virulence faactors that are assumed to be controlled by molecular mechanisms through which the conidia and/or mycelial fragments convert to yeast cells. In order to analyze the profile of the thermally-induced dimorphic gene expression, 48 h C-L transition cultures which had been incubated at 36 degrees C were studied. By this time approximately 50% of the conidial population had already reverted to yeast form cells. At this transition time, an EST-Orestes library was constructed and characterized. As a result, 79 sequences were obtained, of which 39 (49.4%) had not been described previously in other libraries of this fungus and which could represent novel exclusive C-Y transition genes. Two of these sequences are, among others, cholestanol delta-isomerase, and electron transfer flavoprotein-ubiquinoneoxidoreductase (ETF-QO). The other 40 (50.6%) sequences were shared with Mycelia (M), Yeast (Y) or Mycelia to yest transition (M-Y) libraries. An important component of this group of sequences is a putative response regulator receiver SKN7, a protein of high importance in stress adaptation and a regulator of virulence in some bacteria and fungi. This is the first report identifying genes expressed during the C-Y transition process, the initial step required to understand the natural history of P brasiliensis conidia induced infection.
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Crotalus durissus rattlesnakes are responsible for the most lethal cases of snakebites in Brazil. Crotalus durissus collilineatus subspecies is related to a great number of accidents in Southeast and Central West regions, but few studies on its venom composition have been carried out to date. In an attempt to describe the transcriptional profile of the C. durissus collilineatus venom gland, we generated a cDNA library and the sequences obtained could be identified by similarity searches on existing databases. Out of 673 expressed sequence tags (ESTs) 489 produced readable sequences comprising 201 singletons and 47 clusters of two or more ESTs. One hundred and fifty reads (60.5%) produced significant hits to known sequences. The results showed a predominance of toxin-coding ESTs instead of transcripts coding for proteins involved in all cellular functions. The most frequent toxin was crotoxin, comprising 88% of toxin-coding sequences. Crotoxin B, a basic phospholipase A(2) (PLA(2)) subunit of crotoxin, was represented in more variable forms comparing to the non-enzymatic subunit (crotoxin A), and most sequences coding this molecule were identified as CB1 isoform from Crotalus durissus terrificus venom. Four percent of toxin-related sequences in this study were identified as growth factors, comprising five sequences for vascular endothelial growth factor (VEGF) and one for nerve growth factor (NGF) that showed 100% of identity with C. durissus terrificus NGF. We also identified two clusters for metalloprotease from PII class comprising 3% of the toxins, and two for serine proteases, including gyroxin (2.5%). The remaining 2.5% of toxin-coding ESTs represent singletons identified as homologue sequences to cardiotoxin, convulxin, angiotensin-converting enzyme inhibitor and C-type natriuretic peptide, Ohanin, crotamin and PLA(2) inhibitor. These results allowed the identification of the most common classes of toxins in C. durissus collilineatus snake venom, also showing some unknown classes for this subspecies and even for C. durissus species, such as cardiotoxins and VEGF. (C) 2009 Published by Elsevier Masson SAS.
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In the context of cancer diagnosis and treatment, we consider the problem of constructing an accurate prediction rule on the basis of a relatively small number of tumor tissue samples of known type containing the expression data on very many (possibly thousands) genes. Recently, results have been presented in the literature suggesting that it is possible to construct a prediction rule from only a few genes such that it has a negligible prediction error rate. However, in these results the test error or the leave-one-out cross-validated error is calculated without allowance for the selection bias. There is no allowance because the rule is either tested on tissue samples that were used in the first instance to select the genes being used in the rule or because the cross-validation of the rule is not external to the selection process; that is, gene selection is not performed in training the rule at each stage of the cross-validation process. We describe how in practice the selection bias can be assessed and corrected for by either performing a cross-validation or applying the bootstrap external to the selection process. We recommend using 10-fold rather than leave-one-out cross-validation, and concerning the bootstrap, we suggest using the so-called. 632+ bootstrap error estimate designed to handle overfitted prediction rules. Using two published data sets, we demonstrate that when correction is made for the selection bias, the cross-validated error is no longer zero for a subset of only a few genes.
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Four different promoters (35S and enhanced 35S of the cauliflower mosaic virus, polyubiquitin of maize and actin1 of rice) were compared in a transient assay using maize leaves and particle bombardment. A gene encoding the jellyfish green fluorescent protein (GFP) driven by the 358 promoter was used as an internal standard to monitor the effectiveness of each bombardment. Normalisation of the transient expression assay using the GFP reference significantly reduced the variability between separate bombardments and allowed for a rapid and accurate evaluation of different promoters in microprojectile-bombarded leaves.