542 resultados para Microarrays


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Microarrays can measure the expression of thousands of genes to identify changes in expression between different biological states. Methods are needed to determine the significance of these changes while accounting for the enormous number of genes. We describe a method, Significance Analysis of Microarrays (SAM), that assigns a score to each gene on the basis of change in gene expression relative to the standard deviation of repeated measurements. For genes with scores greater than an adjustable threshold, SAM uses permutations of the repeated measurements to estimate the percentage of genes identified by chance, the false discovery rate (FDR). When the transcriptional response of human cells to ionizing radiation was measured by microarrays, SAM identified 34 genes that changed at least 1.5-fold with an estimated FDR of 12%, compared with FDRs of 60 and 84% by using conventional methods of analysis. Of the 34 genes, 19 were involved in cell cycle regulation and 3 in apoptosis. Surprisingly, four nucleotide excision repair genes were induced, suggesting that this repair pathway for UV-damaged DNA might play a previously unrecognized role in repairing DNA damaged by ionizing radiation.

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A key step in the regulation of networks that control gene expression is the sequence-specific binding of transcription factors to their DNA recognition sites. A more complete understanding of these DNA–protein interactions will permit a more comprehensive and quantitative mapping of the regulatory pathways within cells, as well as a deeper understanding of the potential functions of individual genes regulated by newly identified DNA-binding sites. Here we describe a DNA microarray-based method to characterize sequence-specific DNA recognition by zinc-finger proteins. A phage display library, prepared by randomizing critical amino acid residues in the second of three fingers of the mouse Zif268 domain, provided a rich source of zinc-finger proteins with variant DNA-binding specificities. Microarrays containing all possible 3-bp binding sites for the variable zinc fingers permitted the quantitation of the binding site preferences of the entire library, pools of zinc fingers corresponding to different rounds of selection from this library, as well as individual Zif268 variants that were isolated from the library by using specific DNA sequences. The results demonstrate the feasibility of using DNA microarrays for genome-wide identification of putative transcription factor-binding sites.

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We describe a method to screen pools of DNA from multiple transposon lines for insertions in many genes simultaneously. We use thermal asymmetric interlaced–PCR, a hemispecific PCR amplification protocol that combines nested, insertion-specific primers with degenerate primers, to amplify DNA flanking the transposons. In reconstruction experiments with previously characterized Arabidopsis lines carrying insertions of the maize Dissociation (Ds) transposon, we show that fluorescently labeled, transposon-flanking fragments overlapping ORFs hybridize to cognate expressed sequence tags (ESTs) on a DNA microarray. We further show that insertions can be detected in DNA pools from as many as 100 plants representing different transposon lines and that all of the tested, transposon-disrupted genes whose flanking fragments can be amplified individually also can be detected when amplified from the pool. The ability of a transposon-flanking fragment to hybridize declines rapidly with decreasing homology to the spotted DNA fragment, so that only ESTs with >90% homology to the transposon-disrupted gene exhibit significant cross-hybridization. Because thermal asymmetric interlaced–PCR fragments tend to be short, use of the present method favors recovery of insertions in and near genes. We apply the technique to screening pools of new Ds lines using cDNA microarrays containing ESTs for ≈1,000 stress-induced and -repressed Arabidopsis genes.

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Xylella fastidiosa (Xf) é o agente etiológico causador de doenças em uma grande variedade de cultivos de grande importância econômica, causando a c1orose variegada dos citros, uma das doenças mais danosas à indústria de citros no Brasil. Os genomas de algumas cepas deste fitopatógeno foram completamente seqüenciados promovendo assim estudos funcionais do genoma em larga escala. Neste trabalho nós nos propusemos a investigar o perfil de transcrição de Xf através da técnica microarranjos (no título da dissertação microarrays, mas a partir de agora usaremos microaarranjos) de DNA usando todo o genoma do fitopatógeno e cultivando-a sob meio definido variando a concentração de glicose. O objetivo inicial deste trabalho era observar se Xf comportava-se da mesma forma que Xac, que tem a expressão de goma aumentada devido ao aumento da concentração de glicose do meio. Nossas análises revelaram que enquanto os transcritos relacionados à goma não se mostraram afetados com a concentração de glicose, genes que codificam para análogos a Colicina-V e precursores de fimbria foram induzidos em alta concentração de glicose. Baseados nestes resultados, nós propusemos um modelo de mecanismo de produção e defesa contra a Colicina em Xf.

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The shrimp aquaculture industry is a relatively new livestock industry, having developed over the past 30 years. Thus, it is poised to take advantage of new technologies from the outset of selective breeding programs. This contrasts with long established livestock industries, where there are already highly specialised breeds. This review focuses specifically on the potential application of microarrays to shrimp breeding. Potential applications of microarrays in selective breeding programs are summarised. Microarrays can be used as a rapid means to generate molecular markers for genetic linkage mapping, and genetic maps have been constructed for yeast, Arabidopsis and barley using microarray technology. Microarrays can also be used in the hunt for candidate genes affecting particular traits, leading to development of perfect markers for these traits (i.e. causative mutations). However, this requires that microarray analysis be combined with genetic linkage mapping, and that substantial genomic information is available for the species in question. A novel application of microarrays is to treat gene expression as a quantitative trait in itself and to combine this with linkage mapping to identify quantitative trait loci controlling the levels of gene expression; this approach may identify higher level regulatory genes in specific pathways. Finally, patterns of gene expression observed using microarrays may themselves be treated as phenotypic traits in selection programs (e.g. a particular pattern of gene expression might be indicative of a disease tolerant individual). Microarrays are now being developed for a number of shrimp species in laboratories around the world, primarily with a focus on identifying genes involved in the immune response. However, at present, there is no central repository of shrimp genomic information, which limits the rate at which shrimp genomic research can be progressed. The application of microarrays to shrimp breeding will be extremely limited until there is a shared repository of genomic information for shrimp, and the collective will and resources to develop comprehensive genomic tools for shrimp.

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Motivation: An important problem in microarray experiments is the detection of genes that are differentially expressed in a given number of classes. We provide a straightforward and easily implemented method for estimating the posterior probability that an individual gene is null. The problem can be expressed in a two-component mixture framework, using an empirical Bayes approach. Current methods of implementing this approach either have some limitations due to the minimal assumptions made or with more specific assumptions are computationally intensive. Results: By converting to a z-score the value of the test statistic used to test the significance of each gene, we propose a simple two-component normal mixture that models adequately the distribution of this score. The usefulness of our approach is demonstrated on three real datasets.

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An important and common problem in microarray experiments is the detection of genes that are differentially expressed in a given number of classes. As this problem concerns the selection of significant genes from a large pool of candidate genes, it needs to be carried out within the framework of multiple hypothesis testing. In this paper, we focus on the use of mixture models to handle the multiplicity issue. With this approach, a measure of the local FDR (false discovery rate) is provided for each gene. An attractive feature of the mixture model approach is that it provides a framework for the estimation of the prior probability that a gene is not differentially expressed, and this probability can subsequently be used in forming a decision rule. The rule can also be formed to take the false negative rate into account. We apply this approach to a well-known publicly available data set on breast cancer, and discuss our findings with reference to other approaches.

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We demonstrate a single-step method for the generation of collagen and poly-l-Lysine (PLL) micropatterns on a poly(ethylene glycol) (PEG) functionalized glass surface for cell based assays. The method involves establishing a reliable silanization method to create an effective non-adhesive PEG layer on glass that inhibits cell attachment, followed by the spotting of collagen or PLL solutions using non-contact piezoelectric printing. We show for the first time that the spotted protein micropatterns remain stable on the PEG surface even after extensive washing, thus significantly simplifying protein pattern formation. We found that adherence and spreading of NIH-3T3 fibroblasts was confined to PLL and collagen areas of the micropatterns. In contrast, primary rat hepatocytes adhered and spread only on collagen micropatterns, where they formed uniform, well defined functionally active cell arrays. The differing affinity of hepatocytes and NIH-3T3 fibroblasts for collagen and PLL patterns was used to develop a simple technique for creating a co-culture of the two cell types. This has the potential to form structured arrays that mimic the in vivo hepatic environment and is easily integrated within a miniaturized analytical platform for developing high throughput toxicity analysis in vitro.

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A protein microarray hybridisation system has been implemented by employing patterned hydrophobic thin films on hydrophilic substrates as a means of confinement for aqueous samples. This approach has the ability to handle, and keep separate, small sample volumes of just a few microlitres. In addition, the system is more straightforward to use than the existing multi-well gasket solution. The paper describes the fabrication method and the system is demonstrated for a model protein microarray assay. © 2011 American Institute of Physics.

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Abstract Molecular probe-based methods (Fluorescent in-situ hybridisation or FISH, Next Generation Sequencing or NGS) have proved successful in improving both the efficiency and accuracy of the identification of microorganisms, especially those that lack distinct morphological features, such as picoplankton. However, FISH methods have the major drawback that they can only identify one or just a few species at a time because of the reduced number of available fluorochromes that can be added to the probe. Although the length of sequence that can be obtained is continually improving, NGS still requires a great deal of handling time, its analysis time is still months and with a PCR step it will always be sensitive to natural enzyme inhibitors. With the use of DNA microarrays, it is possible to identify large numbers of taxa on a single-glass slide, the so-called phylochip, which can be semi-quantitative. This review details the major steps in probe design, design and production of a phylochip and validation of the array. Finally, major microarray studies in the phytoplankton community are reviewed to demonstrate the scope of the method.