37 resultados para gene identification

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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BACKGROUND: Porphyria cutanea tarda is the most common form of porphyria, characterized by the decreased activity of the uroporphyrinogen decarboxylase enzyme. Several reports associated HFE gene mutations of hereditary hemochromatosis with porphyria cutanea tarda worldwide, although up to date only one study has been conducted in Brazil. OBJECTIVES: Investigation of porphyria cutanea tarda association with C282Y and H63D mutations in the HFE gene. Identification of precipitating factors (hepatitis C, HIV, alcoholism and estrogen) and their link with HFE mutations. METHODS: An ambispective study of 60 patients with PCT was conducted during the period from 2003 to 2012. Serological tests for hepatitis C and HIV were performed and histories of alcohol abuse and estrogen intake were investigated. HFE mutations were identified with real-time PCR. RESULTS: Porphyria cutanea tarda predominated in males and alcohol abuse was the main precipitating factor. Estrogen intake was the sole precipitating factor present in 25% of female patients. Hepatitis C was present in 41.7%. All HIV-positive patients (15.3%) had a history of alcohol abuse. Allele frequency for HFE mutations, i.e., C282Y (p = 0.0001) and H63D (p = 0.0004), were significantly higher in porphyria cutanea tarda patients, compared to control group. HFE mutations had no association with the other precipitating factors. CONCLUSIONS: Alcohol abuse, hepatitis C and estrogen intake are prevalent precipitating factors in our porphyria cutanea tarda population; however, hemochromatosis in itself can also contribute to the outbreak of porphyria cutanea tarda, which makes the research for HFE mutations necessary in these patients

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Background: Common bean (Phaseolus vulgaris L.) is the most important grain legume for human diet worldwide and the angular leaf spot (ALS) is one of the most devastating diseases of this crop, leading to yield losses as high as 80%. In an attempt to breed resistant cultivars, it is important to first understand the inheritance mode of resistance and to develop tools that could be used in assisted breeding. Therefore, the aim of this study was to identify quantitative trait loci (QTL) controlling resistance to ALS under natural infection conditions in the field and under inoculated conditions in the greenhouse. Results: QTL analyses were made using phenotypic data from 346 recombinant inbreed lines from the IAC-UNA x CAL 143 cross, gathered in three experiments, two of which were conducted in the field in different seasons and one in the greenhouse. Joint composite interval mapping analysis of QTL x environment interaction was performed. In all, seven QTLs were mapped on five linkage groups. Most of them, with the exception of two, were significant in all experiments. Among these, ALS10.1(DG,UC) presented major effects (R-2 between 16% - 22%). This QTL was found linked to the GATS11b marker of linkage group B10, which was consistently amplified across a set of common bean lines and was associated with the resistance. Four new QTLs were identified. Between them the ALS5.2 showed an important effect (9.4%) under inoculated conditions in the greenhouse. ALS4.2 was another major QTL, under natural infection in the field, explaining 10.8% of the variability for resistance reaction. The other QTLs showed minor effects on resistance. Conclusions: The results indicated a quantitative inheritance pattern of ALS resistance in the common bean line CAL 143. QTL x environment interactions were observed. Moreover, the major QTL identified on linkage group B10 could be important for bean breeding, as it was stable in all the environments. Thereby, the GATS11b marker is a potential tool for marker assisted selection for ALS resistance.

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Xanthomonas axonopodis pv. citri, the bacterium responsible for citrus canker, uses effector proteins secreted by a type III protein secretion system to colonize its hosts. Among the putative effector proteins identified for this bacterium, we focused on the analysis of the roles of AvrXacE1, AvrXacE2 and Xac3090 in pathogenicity and their interactions with host plant proteins. Bacterial deletion mutants in avrXacE1, avrXacE2 and xac3090 were constructed and evaluated in pathogenicity assays. The avrXacE1 and avrXacE2 mutants presented lesions with larger necrotic areas relative to the wild-type strain when infiltrated in citrus leaves. Yeast two-hybrid studies were used to identify several plant proteins likely to interact with AvrXacE1, AvrXacE2 and Xac3090. We also assessed the localization of these effector proteins fused to green fluorescent protein in the plant cell, and observed that they co-localized to the subcellular spaces in which the plant proteins with which they interacted were predicted to be confined. Our results suggest that, although AvrXacE1 localizes to the plant cell nucleus, where it interacts with transcription factors and DNA-binding proteins, AvrXacE2 appears to be involved in lesion-stimulating disease 1-mediated cell death, and Xac3090 is directed to the chloroplast where its function remains to be clarified.

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Translocation (8;21)(q22;q22)/RUNX1-RUNX1T1 is a molecular marker that is usually associated with a favorable outcome in both pediatric and adult patients with acute myeloid leukemia (AML). The present report describes the results of hematologic, cytogenetic, and fluorescence in situ hybridization analysis of a case of AML with maturation in a 23-year-old woman. Cytogenetic analysis revealed a balanced translocation involving chromosomal band 21q22, which disrupts the RUNX1 gene, and 10q22, with the following karyotype: 45,X,-X,t(10;21)(q24;q22)[cp16]/46,XX [4]. Interphase FISH showed, in 67% of the 300 interphase nuclei analyzed, three signals for RUNX1 and two RUNX1T1, but no signals corresponding to RUNX1-RUNX1T1 fusion gene. These results were corroborated by RT-PCR, which revealed negative results for the amplification of RUNX1-RUNX1T1 fusion gene. The patient was refractory to conventional and salvage chemotherapy regimens and early relapsed after unrelated donor bone marrow transplantation (BMT), dying of pneumonia, acute respiratory failure, and sepsis on day +80 after BMT, 1 year after diagnosis.

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The objective of this work was to identify genes that could be used as suitable markers for molecular recognition of phenological stages during coffee (Coffea arabica) fruit development. Four cultivars were evaluated as to their differential expression of genes associated to fruit development and maturation processes. Gene expression was characterized by both semi-quantitative and quantitative RT-PCR, in fruit harvested at seven different developmental stages, during three different seasons. No size polymorphisms or differential expression were observed among the cultivars for the evaluated genes; however, distinct expression profiles along fruit development were determined for each gene. Four out of the 28 evaluated genes exhibited a regular expression profile in all cultivars and harvest seasons, and, therefore, they were validated as candidate phenological markers of coffee fruit. The gene a-galactosidase can be used as a marker of green stage, caffeine synthase as a marker of transition to green and yellowish-green stages, and isocitrate lyase and ethylene receptor 3 as markers of late maturation.

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Abstract Background The sequencing of the D.melanogaster genome revealed an unexpected small number of genes (~ 14,000) indicating that mechanisms acting on generation of transcript diversity must have played a major role in the evolution of complex metazoans. Among the most extensively used mechanisms that accounts for this diversity is alternative splicing. It is estimated that over 40% of Drosophila protein-coding genes contain one or more alternative exons. A recent transcription map of the Drosophila embryogenesis indicates that 30% of the transcribed regions are unannotated, and that 1/3 of this is estimated as missed or alternative exons of previously characterized protein-coding genes. Therefore, the identification of the variety of expressed transcripts depends on experimental data for its final validation and is continuously being performed using different approaches. We applied the Open Reading Frame Expressed Sequence Tags (ORESTES) methodology, which is capable of generating cDNA data from the central portion of rare transcripts, in order to investigate the presence of hitherto unnanotated regions of Drosophila transcriptome. Results Bioinformatic analysis of 1,303 Drosophila ORESTES clusters identified 68 sequences derived from unannotated regions in the current Drosophila genome version (4.3). Of these, a set of 38 was analysed by polyA+ northern blot hybridization, validating 17 (50%) new exons of low abundance transcripts. For one of these ESTs, we obtained the cDNA encompassing the complete coding sequence of a new serine protease, named SP212. The SP212 gene is part of a serine protease gene cluster located in the chromosome region 88A12-B1. This cluster includes the predicted genes CG9631, CG9649 and CG31326, which were previously identified as up-regulated after immune challenges in genomic-scale microarray analysis. In agreement with the proposal that this locus is co-regulated in response to microorganisms infection, we show here that SP212 is also up-regulated upon injury. Conclusion Using the ORESTES methodology we identified 17 novel exons from low abundance Drosophila transcripts, and through a PCR approach the complete CDS of one of these transcripts was defined. Our results show that the computational identification and manual inspection are not sufficient to annotate a genome in the absence of experimentally derived data.

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Background The genetic mechanisms underlying interindividual blood pressure variation reflect the complex interplay of both genetic and environmental variables. The current standard statistical methods for detecting genes involved in the regulation mechanisms of complex traits are based on univariate analysis. Few studies have focused on the search for and understanding of quantitative trait loci responsible for gene × environmental interactions or multiple trait analysis. Composite interval mapping has been extended to multiple traits and may be an interesting approach to such a problem. Methods We used multiple-trait analysis for quantitative trait locus mapping of loci having different effects on systolic blood pressure with NaCl exposure. Animals studied were 188 rats, the progenies of an F2 rat intercross between the hypertensive and normotensive strain, genotyped in 179 polymorphic markers across the rat genome. To accommodate the correlational structure from measurements taken in the same animals, we applied univariate and multivariate strategies for analyzing the data. Results We detected a new quantitative train locus on a region close to marker R589 in chromosome 5 of the rat genome, not previously identified through serial analysis of individual traits. In addition, we were able to justify analytically the parametric restrictions in terms of regression coefficients responsible for the gain in precision with the adopted analytical approach. Conclusion Future work should focus on fine mapping and the identification of the causative variant responsible for this quantitative trait locus signal. The multivariable strategy might be valuable in the study of genetic determinants of interindividual variation of antihypertensive drug effectiveness.

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Background: A current challenge in gene annotation is to define the gene function in the context of the network of relationships instead of using single genes. The inference of gene networks (GNs) has emerged as an approach to better understand the biology of the system and to study how several components of this network interact with each other and keep their functions stable. However, in general there is no sufficient data to accurately recover the GNs from their expression levels leading to the curse of dimensionality, in which the number of variables is higher than samples. One way to mitigate this problem is to integrate biological data instead of using only the expression profiles in the inference process. Nowadays, the use of several biological information in inference methods had a significant increase in order to better recover the connections between genes and reduce the false positives. What makes this strategy so interesting is the possibility of confirming the known connections through the included biological data, and the possibility of discovering new relationships between genes when observed the expression data. Although several works in data integration have increased the performance of the network inference methods, the real contribution of adding each type of biological information in the obtained improvement is not clear. Methods: We propose a methodology to include biological information into an inference algorithm in order to assess its prediction gain by using biological information and expression profile together. We also evaluated and compared the gain of adding four types of biological information: (a) protein-protein interaction, (b) Rosetta stone fusion proteins, (c) KEGG and (d) KEGG+GO. Results and conclusions: This work presents a first comparison of the gain in the use of prior biological information in the inference of GNs by considering the eukaryote (P. falciparum) organism. Our results indicates that information based on direct interaction can produce a higher improvement in the gain than data about a less specific relationship as GO or KEGG. Also, as expected, the results show that the use of biological information is a very important approach for the improvement of the inference. We also compared the gain in the inference of the global network and only the hubs. The results indicates that the use of biological information can improve the identification of the most connected proteins.

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Sugarcane is an important sugar and energy crop that can be used efficiently for biofuels production. The development of sugarcane cultivars tolerant to drought could allow for the expansion of plantations to sub-prime regions. Knowledge on the mechanisms underlying drought responses and its relationship with carbon partition would greatly help to define routes to increase yield. In this work we studied sugarcane responses to drought using a custom designed oligonucleotide array with 21,901 different probes. The oligoarrays were designed to contain probes that detect transcription in both sense and antisense orientation. We validated the results obtained using quantitative real-time PCR (qPCR). A total of 987 genes were differentially expressed in at least one sample of sugarcane plants submitted to drought for 24, 72 and 120 h. Among them, 928 were sense transcripts and 59 were antisense transcripts. Genes related to Carbohydrate Metabolism, RNA Metabolism and Signal Transduction were selected for gene expression validation by qPCR that indicated a validation percentage of 90 %. From the probes presented on the array, 75 % of the sense probes and 11.9 % of the antisense probes have signal above background and can be classified as expressed sequences. Our custom sugarcane oligonucleotide array provides sensitivity and good coverage of sugarcane transcripts for the identification of a representative proportion of natural antisense transcripts (NATs) and sense-antisense transcript pairs (SATs). The antisense transcriptome showed, in most cases, co-expression with respective sense transcripts.

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Background: CAH patients have an increased risk of cardiovascular disease, and it remains unknown if lifelong glucocorticoid (GC) treatment is a contributing factor. In the general population, glucocorticoid receptor gene (NR3C1) polymorphisms are associated with an adverse metabolic profile. Our aim was to analyze the association between the NR3C1 polymorphisms and the metabolic profile of CAH patients. Methodology: Sixty-eight adult patients (34SV/34SW) with a mean age of 28.4 +/- 9 years received dexamethasone (mean 0.27 +/- 0.11 mg/day) to obtain normal androgen levels. SW patients also received fludrocortisone (50 mu g/day). Metabolic syndrome (MetS) was defined by the NCEP ATPIII criteria and obesity by BMI >= 30 kg/m(2). NR3C1 alleles were genotyped, and association analyses with phenotype were carried out with Chi-square, t-test and regression analysis. Results: Obesity and MetS were observed in 23.5% and 7.3% of patients, respectively, and were not correlated with GC doses and treatment duration. BMI was positively correlated with blood pressure (BP), triglycerides (TG), LDL-c levels and HOMA-IR and inversely correlated with HDL-c levels. BclI and A3669G variants were found in 26.4% and 9.6% of alleles, respectively. Heterozygotes for the BclI polymorphism presented with higher BMI (29 kg/m(2) +/- 5.3 vs. 26 kg/m(2) +/- 5.3, respectively) and waist circumference (89 cm +/- 12.7 vs. 81 cm +/- 13, respectively) compared to wild-type subjects. Hypertension was found in 12% of patients and heterozygotes for the BclI polymorphism presented higher systolic BP than wild type subjects. Low HDL-c and high TG levels were identified in 30% and 10% of patients, respectively, and were not associated with the NR3C1 polymorphisms. A3669G carriers and non-carriers did not differ. Conclusion: In addition to GC therapy, the BclI GR variant might play an important role in obesity susceptibility in CAH patients. Genotyping of GR polymorphisms could result in the identification of a subgroup at risk patients, allowing for the establishment of personalized treatment and the avoidance of long-term adverse consequences.

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In silico analyses of Leishmania spp. genome data are a powerful resource to improve the understanding of these pathogens' biology. Trypanosomatids such as Leishmania spp. have their protein-coding genes grouped in long polycistronic units of functionally unrelated genes. The control of gene expression happens by a variety of posttranscriptional mechanisms. The high degree of synteny among Leishmania species is accompanied by highly conserved coding sequences (CDS) and poorly conserved intercoding untranslated sequences. To identify the elements involved in the control of gene expression, we conducted an in silico investigation to find conserved intercoding sequences (CICS) in the genomes of L major, L infantum, and L braziliensis. We used a combination of computational tools, such as Linux-Shell, PERL and R languages, BLAST, MSPcrunch, SSAKE, and Pred-A-Term algorithms to construct a pipeline which was able to: (i) search for conservation in target-regions, (ii) eliminate CICS redundancy and mask repeat elements, (iii) predict the mRNA's extremities, (iv) analyze the distribution of orthologous genes within the generated LeishCICS-clusters, (v) assign GO terms to the LeishCICS-clusters. and (vi) provide statistical support for the gene-enrichment annotation. We associated the LeishCICS-cluster data, generated at the end of the pipeline, with the expression profile oft. donovani genes during promastigote-amastigote differentiation, as previously evaluated by others (GEO accession: GSE21936). A Pearson's correlation coefficient greater than 0.5 was observed for 730 LeishCICS-clusters containing from 2 to 17 genes. The designed computational pipeline is a useful tool and its application identified potential regulatory cis elements and putative regulons in Leishmania. (C) 2012 Elsevier B.V. All rights reserved.

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The plant pathogen Fusarium solani causes a disease root rot of common bean (Phaseolus vulgaris) resulting in great losses of yield in irrigated areas of the Southeast and Midwest regions of Brazil. Species of the genus Trichoderma have been used in the biological control of this pathogen as an alternative to chemical control. To gain new insights into the biocontrol mechanism used by Trichoderma harzianum against the phytopathogenic fungus, Fusarium solani, we performed a transcriptome analysis using expressed sequence tags (ESTs) and quantitative real-time PCR (RT-qPCR) approaches. A cDNA library from T. harzianum mycelium (isolate ALL42) grown on cell walls of F. solani (CWFS) was constructed and analyzed. A total of 2927 high quality sequences were selected from 3845 and 37.7% were identified as unique genes. The Gene Ontology analysis revealed that the majority of the annotated genes are involved in metabolic processes (80.9%), followed by cellular process (73.7%). We tested twenty genes that encode proteins with potential role in biological control. RT-qPCR analysis showed that none of these genes were expressed when T. harzianum was challenged with itself. These genes showed different patterns of expression during in vitro interaction between T. harzianum and F. solani. (C) 2012 Elsevier Inc. All rights reserved.

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The search for molecular markers to improve diagnosis, individualize treatment and predict behavior of tumors has been the focus of several studies. This study aimed to analyze homeobox gene expression profile in oral squamous cell carcinoma (OSCC) as well as to investigate whether some of these genes are relevant molecular markers of prognosis and/or tumor aggressiveness. Homeobox gene expression levels were assessed by microarrays and qRT-PCR in OSCC tissues and adjacent non-cancerous matched tissues (margin), as well as in OSCC cell lines. Analysis of microarray data revealed the expression of 147 homeobox genes, including one set of six at least 2-fold up-regulated, and another set of 34 at least 2-fold down-regulated homeobox genes in OSCC. After qRT-PCR assays, the three most up-regulated homeobox genes (HOXA5, HOXD10 and HOXD11) revealed higher and statistically significant expression levels in OSCC samples when compared to margins. Patients presenting lower expression of HOXA5 had poorer prognosis compared to those with higher expression (P=0.03). Additionally, the status of HOXA5, HOXD10 and HOXD11 expression levels in OSCC cell lines also showed a significant up-regulation when compared to normal oral keratinocytes. Results confirm the presence of three significantly upregulated (>4-fold) homeobox genes (HOXA5, HOXD10 and HOXD11) in OSCC that may play a significant role in the pathogenesis of these tumors. Moreover, since lower levels of HOXA5 predict poor prognosis, this gene may be a novel candidate for development of therapeutic strategies in OSCC.

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As the available public cerebral gene expression image data increasingly grows, the demand for automated methods to analyze such large amount of data also increases. An important study that can be carried out on these data is related to the spatial relationship between gene expressions. Similar spatial density distribution of expression between genes may indicate they are functionally correlated, thus the identification of these similarities is useful in suggesting directions of investigation to discover gene interactions and their correlated functions. In this paper, we describe the use of a high-throughput methodology based on Voronoi diagrams to automatically analyze and search for possible local spatial density relationships between gene expression images. We tested this method using mouse brain section images from the Allen Mouse Brain Atlas public database. This methodology provided measurements able to characterize the similarity of the density distribution between gene expressions and allowed the visualization of the results through networks and Principal Component Analysis (PCA). These visualizations are useful to analyze the similarity level between gene expression patterns, as well as to compare connection patterns between region networks. Some genes were found to have the same type of function and to be near each other in the PCA visualizations. These results suggest cerebral density correlations between gene expressions that could be further explored. (C) 2011 Elsevier B.V. All rights reserved.

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Bovine coronavirus has been associated with diarrhoea in newborn calves, winter dysentery in adult cattle and respiratory tract infections in calves and feedlot cattle. In Cuba, the presence of BCoV was first reported in 2006. Since then, sporadic outbreaks have continued to occur. This study was aimed at deepening the knowledge of the evolution, molecular markers of virulence and epidemiology of BCoV in Cuba. A total of 30 samples collected between 2009 and 2011 were used for PCR amplification and direct sequencing of partial or full S gene. Sequence comparison and phylogenetic studies were conducted using partial or complete S gene sequences as phylogenetic markers. All Cuban bovine coronavirus sequences were located in a single cluster supported by 100% bootstrap and 1.00 posterior probability values. The Cuban bovine coronavirus sequences were also clustered with the USA BCoV strains corresponding to the GenBank accession numbers EF424621 and EF424623, suggesting a common origin for these viruses. This phylogenetic cluster was also the only group of sequences in which no recombination events were detected. Of the 45 amino acid changes found in the Cuban strains, four were unique. (C) 2012 Elsevier B.V. All rights reserved.