140 resultados para CDNA MICROARRAYS
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)
Resumo:
Background -: Sucrose content is a highly desirable trait in sugarcane as the worldwide demand for cost-effective biofuels surges. Sugarcane cultivars differ in their capacity to accumulate sucrose and breeding programs routinely perform crosses to identify genotypes able to produce more sucrose. Sucrose content in the mature internodes reach around 20% of the culms dry weight. Genotypes in the populations reflect their genetic program and may display contrasting growth, development, and physiology, all of which affect carbohydrate metabolism. Few studies have profiled gene expression related to sugarcane's sugar content. The identification of signal transduction components and transcription factors that might regulate sugar accumulation is highly desirable if we are to improve this characteristic of sugarcane plants. Results -: We have evaluated thirty genotypes that have different Brix (sugar) levels and identified genes differentially expressed in internodes using cDNA microarrays. These genes were compared to existing gene expression data for sugarcane plants subjected to diverse stress and hormone treatments. The comparisons revealed a strong overlap between the drought and sucrose-content datasets and a limited overlap with ABA signaling. Genes associated with sucrose content were extensively validated by qRT-PCR, which highlighted several protein kinases and transcription factors that are likely to be regulators of sucrose accumulation. The data also indicate that aquaporins, as well as lignin biosynthesis and cell wall metabolism genes, are strongly related to sucrose accumulation. Moreover, sucrose-associated genes were shown to be directly responsive to short term sucrose stimuli, confirming their role in sugar-related pathways. Conclusion -: Gene expression analysis of sugarcane populations contrasting for sucrose content indicated a possible overlap with drought and cell wall metabolism processes and suggested signaling and transcriptional regulators to be used as molecular markers in breeding programs. Transgenic research is necessary to further clarify the role of the genes and define targets useful for sugarcane improvement programs based on transgenic plants.
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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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Background: The protein kinase YakA is responsible for the growth arrest and induction of developmental processes that occur upon starvation of Dictyostelium cells. yakA-cells are aggregation deficient, have a faster cell cycle and are hypersensitive to oxidative and nitrosoative stress. With the aim of isolating members of the YakA pathway, suppressors of the death induced by nitrosoative stress in the yakA-cells were identified. One of the suppressor mutations occurred in keaA, a gene identical to DG1106 and similar to Keap1 from mice and the Kelch protein from Drosophila, among others that contain Kelch domains. Results: A mutation in keaA suppresses the hypersensitivity to oxidative and nitrosoative stresses but not the faster growth phenotype of yakA-cells. The growth profile of keaA deficient cells indicates that this gene is necessary for growth. keaA deficient cells are more resistant to nitrosoative and oxidative stress and keaA is necessary for the production and detection of cAMP. A morphological analysis of keaA deficient cells during multicellular development indicated that, although the mutant is not absolutely deficient in aggregation, cells do not efficiently participate in the process. Gene expression analysis using cDNA microarrays of wild-type and keaA deficient cells indicated a role for KeaA in the regulation of the cell cycle and pre-starvation responses. Conclusions: KeaA is required for cAMP signaling following stress. Our studies indicate a role for kelch proteins in the signaling that regulates the cell cycle and development in response to changes in the environmental conditions.
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Patients presenting with active Systemic lupus erythematosus (SLE) manifestations may exhibit distinct pathogenetic features in relation to inactive SLE. Also, cDNA microarrays may potentially discriminate the gene expression profile of a disease or disease variant. Therefore, we evaluated the expression profile of 4500 genes in peripheral blood lymphocytes (PBL) of SLE patients. We studied 11 patients with SLE (seven with active SLE and four with inactive SLE) and eight healthy controls. Total RNA was isolated from PBL, reverse transcribed into cDNA, and postlabeled with Cy3 fluorochrome. These probes were then hybridized to a glass slide cDNA microarray containing 4500 human IMAGE cDNA target sequences. An equimolar amount of total RNA from human cell lines served as reference. The microarray images were quantified, normalized, and analyzed using the R environment (ANOVA, significant analysis of microarrays, and cluster-tree view algorithms). Disease activity was assessed by the SLE disease activity index. Compared to the healthy controls, 104 genes in active SLE patients (80 repressed and 24 induced) and 52 genes in nonactive SLE patients (31 induced and 21 repressed) were differentially expressed. The modulation of 12 genes, either induced or repressed, was found in both disease variants; however, each disease variant had differential expression of different genes. Taken together, these results indicate that the two lupus variants studied have common and unique differentially expressed genes. Although the biological significance of the differentially expressed genes discussed above has not been completely understood, they may serve as a platform to further explore the molecular basis of immune deregulation in SLE.
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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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Microarray gene expression profiling is a high-throughput system used to identify differentially expressed genes and regulation patterns, and to discover new tumor markers. As the molecular pathogenesis of meningiomas and schwannomas, characterized by NF2 gene alterations, remains unclear and suitable molecular targets need to be identified, we used low density cDNA microarrays to establish expression patterns of 96 cancer-related genes on 23 schwannomas, 42 meningiomas and 3 normal cerebral meninges. We also performed a mutational analysis of the NF2 gene (PCR, dHPLC, Sequencing and MLPA), a search for 22q LOH and an analysis of gene silencing by promoter hypermethylation (MS-MLPA). Results showed a high frequency of NF2 gene mutations (40%), increased 22q LOH as aggressiveness increased, frequent losses and gains by MLPA in benign meningiomas, and gene expression silencing by hypermethylation. Array analysis showed decreased expression of 7 genes in meningiomas. Unsupervised analyses identified 2 molecular subgroups for both meningiomas and schwannomas showing 38 and 20 differentially expressed genes, respectively, and 19 genes differentially expressed between the two tumor types. These findings provide a molecular subgroup classification for meningiomas and schwannomas with possible implications for clinical practice.
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Urinary bladder cancer is the fourth most common malignancy in the Western world. Transitional cell carcinoma (TCC) is the most common subtype, accounting for about 90% of all bladder cancers. The TP53 gene plays an essential role in the regulation of the cell cycle and apoptosis and therefore contributes to cellular transformation and malignancy; however, little is known about the differential gene expression patterns in human tumors that present with the wild-type or mutated TP53 gene. Therefore, because gene profiling can provide new insights into the molecular biology of bladder cancer, the present study aimed to compare the molecular profiles of bladder cancer cell lines with different TP53 alleles, including the wild type (RT4) and two mutants (5637, with mutations in codons 280 and 72; and T24, a TP53 allele encoding an in-frame deletion of tyrosine 126). Unsupervised hierarchical clustering and gene networks were constructed based on data generated by cDNA microarrays using mRNA from the three cell lines. Differentially expressed genes related to the cell cycle, cell division, cell death, and cell proliferation were observed in the three cell lines. However, the cDNA microarray data did not cluster cell lines based on their TP53 allele. The gene profiles of the RT4 cells were more similar to those of T24 than to those of the 5637 cells. While the deregulation of both the cell cycle and the apoptotic pathways was particularly related to TCC, these alterations were not associated with the TP53 status.
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Gene expression profiling by cDNA microarrays during murine thymus ontogeny has contributed to dissecting the large-scale molecular genetics of T cell maturation. Gene profiling, although useful for characterizing the thymus developmental phases and identifying the differentially expressed genes, does not permit the determination of possible interactions between genes. In order to reconstruct genetic interactions, on RNA level, within thymocyte differentiation, a pair of microarrays containing a total of 1,576 cDNA sequences derived from the IMAGE MTB library was applied on samples of developing thymuses (14-17 days of gestation). The data were analyzed using the GeneNetwork program. Genes that were previously identified as differentially expressed during thymus ontogeny showed their relationships with several other genes. The present method provided the detection of gene nodes coding for proteins implicated in the calcium signaling pathway, such as Prrg2 and Stxbp3, and in protein transport toward the cell membrane, such as Gosr2. The results demonstrate the feasibility of reconstructing networks based on cDNA microarray gene expression determinations, contributing to a clearer understanding of the complex interactions between genes involved in thymus/thymocyte development.
Resumo:
Changes in gene expression have been measured 24 h after injury to mammalian spinal cords that can and cannot regenerate In opossums there is a critical period of development when regeneration stops being possible at 9 days postnatal cervical spinal cords regenerate, at 12 days they do not By the use of marsupial cDNA microarrays we detected 158 genes that respond differentially to injury at the two ages critical for regeneration For selected candidates additional measurements were made by real time PCR and sites of their expression were shown by immunostaining Candidate genes have been classified so as to select those that promote or prevent regeneration Up regulated by injury at 8 days and/or down regulated by injury at 13 days were genes known to promote growth, such as Mitogen activated protein kinase kinase 1 or transcripton factor TCF7L2 By contrast, at 13 days up regulation occurred of Inhibitory molecules including annexins ephrins and genes related to apoptosis and neurodegeneranve diseases Certain genes such as calmodulin 1 and NOGO changed expression similarly in animals that could and could not regenerate without any additional changes in response to injury These findings confirmed and extended changes of gene expression found in earlier screens on 9 and 12 day preparations without lesions and provide a comprehensive list of genes that serve as a basis for testing how identified molecules singly or in combination, promote and prevent central nervous system regeneration (C) 2010 Elsevier B V All rights reserved
Resumo:
Because of the economical relevance of sugarcane and its high potential as a source of biofuel, it is important to understand how this crop will respond to the foreseen increase in atmospheric [CO(2)]. The effects of increased [CO(2)] on photosynthesis, development and carbohydrate metabolism were studied in sugarcane (Saccharum ssp.). Plants were grown at ambient (similar to 370 ppm) and elevated (similar to 720 ppm) [CO(2)] during 50 weeks in open-top chambers. The plants grown under elevated CO(2) showed, at the end of such period, an increase of about 30% in photosynthesis and 17% in height, and accumulated 40% more biomass in comparison with the plants grown at ambient [CO(2)]. These plants also had lower stomatal conductance and transpiration rates (-37 and -32%, respectively), and higher water-use efficiency (c.a. 62%). cDNA microarray analyses revealed a differential expression of 35 genes on the leaves (14 repressed and 22 induced) by elevated CO(2). The latter are mainly related to photosynthesis and development. Industrial productivity analysis showed an increase of about 29% in sucrose content. These data suggest that sugarcane crops increase productivity in higher [CO(2)], and that this might be related, as previously observed for maize and sorghum, to transient drought stress.
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Global gene expression analysis was carried out with Blastocladiella emersonii cells subjected to oxygen deprivation (hypoxia) using cDNA microarrays. In experiments of gradual hypoxia (gradual decrease in dissolved oxygen) and direct hypoxia (direct decrease in dissolved oxygen), about 650 differentially expressed genes were observed. A total of 534 genes were affected directly or indirectly by oxygen availability, as they showed recovery to normal expression levels or a tendency to recover when cells were reoxygenated. In addition to modulating many genes with no putative assigned function, B. emersonii cells respond to hypoxia by readjusting the expression levels of genes responsible for energy production and consumption. At least transcriptionally, this fungus seems to favor anaerobic metabolism through the upregulation of genes encoding glycolytic enzymes and lactate dehydrogenase and the downregulation of most genes coding for tricarboxylic acid (TCA) cycle enzymes. Furthermore, genes involved in energy-costly processes, like protein synthesis, amino acid biosynthesis, protein folding, and transport, had their expression profiles predominantly down-regulated during oxygen deprivation, indicating an energy-saving effort. Data also revealed similarities between the transcriptional profiles of cells under hypoxia and under iron(II) deprivation, suggesting that Fe(2+) ion could have a role in oxygen sensing and/or response to hypoxia in B. emersonii. Additionally, treatment of fungal cells prior to hypoxia with the antibiotic geldanamycin, which negatively affects the stability of mammalian hypoxia transcription factor HIF-1 alpha, caused a significant decrease in the levels of certain upregulated hypoxic genes.
Resumo:
It has been postulated that noncoding RNAs (ncRNAs) are involved in the posttranscriptional control of gene expression, and may have contributed to the emergence of the complex attributes observed in mammalians. We show here that the complement of ncRNAs expressed from intronic regions of the human and mouse genomes comprises at least 78,147 and 39,660 transcriptional units, respectively. To identify conserved intronic sequences expressed in both humans and mice, we used custom-designed human cDNA microarrays to separately interrogate RNA from mouse and human liver, kidney, and prostate tissues. An overlapping tissue expression signature was detected for both species, comprising 198 transcripts; among these, 22 RNAs map to intronic regions with evidence of evolutionary conservation in humans and mice. Transcription of selected human-mouse intronic ncRNAs was confirmed using strand-specific RT-PCR. Altogether, these results support an evolutionarily conserved role of intronic ncRNAs in human and mouse, which are likely to be involved in the fine tuning of gene expression regulation in different mammalian tissues. (C) 2008 Elsevier Inc. All rights reserved.
Resumo:
The molecular pathology of meningiomas and shwannomas involve the inactivation of the NF2 gene to generate grade I tumors. Genomic losses at 1p and 14q are observed in both neoplasms, although more frequently in meningiomas. The inactivation of unidentified genes located in these regions appears associated with tumor progression in meningiomas, but no clues to its molecular/clinical meaning are available in schwannomas. Recent microarray gene expression studies have demonstrated the existence of molecular subgroups in both entities. In the present study, we correlated the presence of genomic deletions at 1p, 14q, and 22q with the expression patterns of 96 tumor-related genes obtained by cDNA low-density microarrays in a series of 65 tumors including 42 meningiomas and 23 schwannomas. Two expression pattern groups were identified by cDNA mycroarray analysis when compared to the expression pattern in normal control RNA in both meningiomas and schwannomas, each one with patterns similar and different from the normal control. Meningioma and schwannoma subgroups differed in the expression of 38 and 16 genes, respectively. Using MLPA and microsatellites, we identified genomic losses at 1p, 14q, and 22q at nonrandom frequencies (12.5-69%) in meningiomas and schwannomas. Losses at 22q were almost equally frequent in both molecular expression subgroups in both neoplasms. However, deletions at 1p and 14q accumulated in meningiomas with a gene expression pattern different from the normal pattern, whereas the inverse situation occurred in schwannomas. Those anomalies characterized the schwannomas with expression pattern similar to the normal control. These findings suggest that deletions at 1p and 14q enhance the development of an abnormal tumor-related gene expression pattern in meningiomas, but this fact is not corroborated in schwannomas. (C) 2010 Elsevier Inc. All rights reserved.
Resumo:
Xylella fastidiosa genome sequencing has generated valuable data by identifying genes acting either on metabolic pathways or in associated pathogenicity and virulence. Based on available information on these genes, new strategies for studying their expression patterns, such as microarray technology, were employed. A total of 2,600 primer pairs were synthesized and then used to generate fragments using the PCR technique. The arrays were hybridized against cDNAs labeled during reverse transcription reactions and which were obtained from bacteria grown under two different conditions (liquid XDM2 and liquid BCYE). All data were statistically analyzed to verify which genes were differentially expressed. In addition to exploring conditions for X. fastidiosa genome-wide transcriptome analysis, the present work observed the differential expression of several classes of genes (energy, protein, amino acid and nucleotide metabolism, transport, degradation of substances, toxins and hypothetical proteins, among others). The understanding of expressed genes in these two different media will be useful in comprehending the metabolic characteristics of X. fastidiosa, and in evaluating how important certain genes are for the functioning and survival of these bacteria in plants.
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Background: Alternative splicing (AS) is a central mechanism in the generation of genomic complexity and is a major contributor to transcriptome and proteome diversity. Alterations of the splicing process can lead to deregulation of crucial cellular processes and have been associated with a large spectrum of human diseases. Cancer-associated transcripts are potential molecular markers and may contribute to the development of more accurate diagnostic and prognostic methods and also serve as therapeutic targets. Alternative splicing-enriched cDNA libraries have been used to explore the variability generated by alternative splicing. In this study, by combining the use of trapping heteroduplexes and RNA amplification, we developed a powerful approach that enables transcriptome-wide exploration of the AS repertoire for identifying AS variants associated with breast tumor cells modulated by ERBB2 (HER-2/neu) oncogene expression. Results: The human breast cell line (C5.2) and a pool of 5 ERBB2 over-expressing breast tumor samples were used independently for the construction of two AS-enriched libraries. In total, 2,048 partial cDNA sequences were obtained, revealing 214 alternative splicing sequence-enriched tags (ASSETs). A subset with 79 multiple exon ASSETs was compared to public databases and reported 138 different AS events. A high success rate of RT-PCR validation (94.5%) was obtained, and 2 novel AS events were identified. The influence of ERBB2-mediated expression on AS regulation was evaluated by capillary electrophoresis and probe-ligation approaches in two mammary cell lines (Hb4a and C5.2) expressing different levels of ERBB2. The relative expression balance between AS variants from 3 genes was differentially modulated by ERBB2 in this model system. Conclusions: In this study, we presented a method for exploring AS from any RNA source in a transcriptome-wide format, which can be directly easily adapted to next generation sequencers. We identified AS transcripts that were differently modulated by ERBB2-mediated expression and that can be tested as molecular markers for breast cancer. Such a methodology will be useful for completely deciphering the cancer cell transcriptome diversity resulting from AS and for finding more precise molecular markers.