950 resultados para Microarray-based genomic hybridization


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We have used microarray gene expression pro. ling and machine learning to predict the presence of BRAF mutations in a panel of 61 melanoma cell lines. The BRAF gene was found to be mutated in 42 samples (69%) and intragenic mutations of the NRAS gene were detected in seven samples (11%). No cell line carried mutations of both genes. Using support vector machines, we have built a classifier that differentiates between melanoma cell lines based on BRAF mutation status. As few as 83 genes are able to discriminate between BRAF mutant and BRAF wild-type samples with clear separation observed using hierarchical clustering. Multidimensional scaling was used to visualize the relationship between a BRAF mutation signature and that of a generalized mitogen-activated protein kinase ( MAPK) activation ( either BRAF or NRAS mutation) in the context of the discriminating gene list. We observed that samples carrying NRAS mutations lie somewhere between those with or without BRAF mutations. These observations suggest that there are gene-specific mutation signals in addition to a common MAPK activation that result from the pleiotropic effects of either BRAF or NRAS on other signaling pathways, leading to measurably different transcriptional changes.

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Medical microbiology and virology laboratories use nucleic acid tests (NAT) to detect genomic material of infectious organisms in clinical samples. Laboratories choose to perform assembled (or in-house) NAT if commercial assays are not available or if assembled NAT are more economical or accurate. One reason commercial assays are more expensive is because extensive validation is necessary before the kit is marketed, as manufacturers must accept liability for the performance of their assays, assuming their instructions are followed. On the other hand, it is a particular laboratory's responsibility to validate an assembled NAT prior to using it for testing and reporting results on human samples. There are few published guidelines for the validation of assembled NAT. One procedure that laboratories can use to establish a validation process for an assay is detailed in this document. Before validating a method, laboratories must optimise it and then document the protocol. All instruments must be calibrated and maintained throughout the testing process. The validation process involves a series of steps including: (i) testing of dilution series of positive samples to determine the limits of detection of the assay and their linearity over concentrations to be measured in quantitative NAT; (ii) establishing the day-to-day variation of the assay's performance; (iii) evaluating the sensitivity and specificity of the assay as far as practicable, along with the extent of cross-reactivity with other genomic material; and (iv) assuring the quality of assembled assays using quality control procedures that monitor the performance of reagent batches before introducing new lots of reagent for testing.

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Recent molecular analyses indicate that many reef coral species belong to hybridizing species complexes or "syngameons." Such complexes consist of numerous genetically distinct-species or lineages, which periodically split and/or fuse as they extend through time. During splitting and fusion, morphologic intermediates form and species overlap. Here we focus on processes associated with lineage fusion, specifically introgressive hybridization, and the recognition of such hybridization in the fossil record. Our approach involves comparing patterns of ecologic and morphologic overlap in genetically characterized modern species with fossil representatives of the same or closely related species. We similarly consider the long-term consequences of past hybridization on the structure of modern-day species boundaries. Our study involves the species complex Montastraea annularis s.l. and is based in the Bahamas, where, unlike other Caribbean locations, two of the three members of the complex today are not genetically distinct. We measured and collected colonies along linear transects across Pleistocene reef terraces of last interglacial age (approximately 125 Ka) on the islands of San Salvador, Andros, and Great Inagua. We performed quantitative ecologic and morphologic analyses of the fossil data, and compared patterns of overlap among species with data from modern localities where species are and are not genetically distinct. Ecologic and morphologic analyses reveal "moderate" overlap (>10%, but statistically significant differences) and sometimes "high" overlap (no statistically significant differences) among Pleistocene growth forms (= "species"). Ecologic analyses show that three species (massive, column, organ-pipe) co-occurred. Although organ-pipes had higher abundances in patch reef environments, columnar and massive species exhibited broad, completely overlapping distributions and had abundances that were not related to reef environment. For morphometric analyses, we used multivariate discriminant analysis on landmark data and linear measurements. The results show that columnar species overlap "moderately" with organ-pipe and massive species. Comparisons with genetically characterized colonies from Panama show that the Pleistocene Bahamas species have intermediate morphologies, and that the observed "moderate" overlap differs from the morphologic separation among the three modern species. In contrast, massive and columnar species from the Pleistocene of the Dominican Republic comprise distinct morphologic clusters, similar to the modern species; organ-pipe species exhibit "low" overlap (

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Detection of point mutations or single nucleotide polymorphisms (SNPs) is important in relation to disease susceptibility or detection in pathogens of mutations determining drug resistance or host range. There is an emergent need for rapid detection methods amenable to point-of-care applications. The purpose of this study was to reduce to practice a novel method for SNP detection and to demonstrate that this technology can be used downstream of nucleic acid amplification. The authors used a model system to develop an oligonucleotide-based SNP detection system on nitrocellulose lateral flow strips. To optimize the assay they used cloned sequences of the herpes simplex virus-1 (HSV-1) DNA polymerase gene into which they introduced a point mutation. The assay system uses chimeric polymerase chain reaction (PCR) primers that incorporate hexameric repeat tags ("hexapet tags"). The chimeric sequences allow capture of amplified products to predefined positions on a lateral flow strip. These "hexapet" sequences have minimal cross-reactivity and allow specific hybridization-based capture of the PCR products at room temperature onto lateral flow strips that have been striped with complementary hexapet tags. The allele-specific amplification was carried out with both mutant and wild-type primer sets present in the PCR mix ("competitive" format). The resulting PCR products carried a hexapet tag that corresponded with either a wild-type or mutant sequence. The lateral flow strips are dropped into the PCR reaction tube, and mutant sequence and wild-type sequences diffuse along the strip and are captured at the corresponding position on the strip. A red line indicative of a positive reaction is visible after 1 minute. Unlike other systems that require separate reactions and strips for each target sequence, this system allows multiplex PCR reactions and multiplex detection on a single strip or other suitable substrates. Unambiguous visual discrimination of a point mutation under room temperature hybridization conditions was achieved with this model system in 10 minutes after PCR. The authors have developed a capture-based hybridization method for the detection and discrimination of HSV-1 DNA polymerase genes that contain a single nucleotide change. It has been demonstrated that the hexapet oligonucleotides can be adapted for hybridization on the lateral flow strip platform for discrimination of SNPs. This is the first step in demonstrating SNP detection on lateral flow using the hexapet oligonucleotide capture system. It is anticipated that this novel system can be widely used in point-of-care settings.

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We describe the creation process of the Minimum Information Specification for In Situ Hybridization and Immunohistochemistry Experiments (MISFISHIE). Modeled after the existing minimum information specification for microarray data, we created a new specification for gene expression localization experiments, initially to facilitate data sharing within a consortium. After successful use within the consortium, the specification was circulated to members of the wider biomedical research community for comment and refinement. After a period of acquiring many new suggested requirements, it was necessary to enter a final phase of excluding those requirements that were deemed inappropriate as a minimum requirement for all experiments. The full specification will soon be published as a version 1.0 proposal to the community, upon which a more full discussion must take place so that the final specification may be achieved with the involvement of the whole community. This paper is part of the special issue of OMICS on data standards.

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Cdca4 (Hepp) was originally identified as a gene expressed specifically in hematopoietic progenitor cells as opposed to hematopoietic stem cells. More recently, it has been shown to stimulate p53 activity and also lead to p53-independent growth inhibition when overexpressed. We independently isolated the murine Cdca4 gene in a genomic expression-based screen for genes involved in mammalian craniofacial development, and show that Cdca4 is expressed in a spatio-temporally restricted pattern during mouse embryogenesis. In addition to expression in the facial primordia including the pharyngeal arches, Cdca4 is expressed in the developing limb buds, brain, spinal cord, dorsal root ganglia, teeth, eye and hair follicles. Along with a small number of proteins from a range of species, the predicted CDCA4 protein contains a novel SERTA motif in addition to cyclin A-binding and PHD bromodomain-binding regions of homology. While the function of the SERTA domain is unknown, proteins containing this domain have previously been linked to cell cycle progression and chromatin remodelling. Using in silico database mining we have extended the number of evolutionarily conserved orthologues of known SERTA domain proteins and identified an uncharacterised member of the SERTA domain family, SERTAD4, with orthologues to date in human, mouse, rat, dog, cow, Tetraodon and chicken. Immunolocalisation of transiently and stably transfected epitope-tagged CDCA4 protein in mammalian cells suggests that it resides predominantly in the nucleus throughout all stages of the cell cycle. (c) 2006 Elsevier B.V. All rights reserved.

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Deterioration of enhanced biological phosphorus removal (EBPR) has been linked to the proliferation of glycogen-accumulating organisms (GAOs), but few organisms possessing the GAO metabolic phenotype have been identified. An unidentified GAO was highly enriched in a laboratory-scale bioreactor and attempts to identify this organism using conventional 16S rRNA gene cloning had failed. Therefore, rRNA-based stable isotope probing followed by full-cycle rRNA analysis was used to specifically identify the putative GAOs based on their characteristic metabolic phenotype. The study obtained sequences from a group of Alphaproteobacteria not previously shown to possess the GAO phenotype, but 90% identical by 16S rRNA gene analysis to a phylogenetic clade containing cloned sequences from putative GAOs and the isolate Defluvicoccus vanus. Fluorescence in situ hybridization (FISH) probes (DF988 and DF1020) were designed to target the new group and post-FISH chemical staining demonstrated anaerobic-aerobic cycling of polyhydroxyalkanoates, as per the GAO phenotype. The successful use of probes DF988 and DF1020 required the use of unlabelled helper probes which increased probe signal intensity up to 6.6-fold, thus highlighting the utility of helper probes in FISH. The new group constituted 33% of all Bacteria in the lab-scale bioreactor from which they were identified and were also abundant (51 and 55% of Bacteria) in two other similar bioreactors in which phosphorus removal had deteriorated. Unlike the previously identified Defluvicoccus-related organisms, the group identified in this study were also found in two full-scale treatment plants performing EBPR, suggesting that this group may be industrially relevant.

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Novel, low-abundance microbial species can be easily overlooked in standard polymerase chain reaction (PCR)-based surveys. We used community genomic data obtained without PCR or cultivation to reconstruct DNA fragments bearing unusual 16S ribosomal RNA ( rRNA) and protein-coding genes from organisms belonging to novel archaeal lineages. The organisms are minor components of all biofilms growing in pH 0.5 to 1.5 solutions within the Richmond Mine, California. Probes specific for 16S rRNA showed that the fraction less than 0.45 micrometers in diameter is dominated by these organisms. Transmission electron microscope images revealed that the cells are pleomorphic with unusual folded membrane protrusions and have apparent volumes of < 0.006 cubic micrometer.

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Enterovirus 71 (EV71) is one of the main causative agents of hand, foot and mouth disease (HFMD) in young children. Infections caused by EV71 could lead to many complications, ranging from brainstem encephalitis to pulmonary oedema, resulting in high mortality. Thus, rapid detection of the virus is required to enable measures to be implemented in preventing widespread transmission. Based on primers and probes targeting at the VP1 region, a real-time reverse-transcriptase polymerase chain reaction (RT-PCR) hybridization probe assay was developed for specific detection of EV71 from clinical specimens. Quantitative analysis showed that the assay was able to detect as low as 5 EV71 viral copies and EV71 was detected from 46 of the 55 clinical specimens obtained from pediatric patients suffering from HFMD during the period from 2000 to 2003 in Singapore. This study showed that the single tube real-time RT-PCR assay developed in this study can be applied as a rapid and sensitive method for specific detection of EV71 directly from clinical specimens. (c) 2005 Elsevier Ltd. All rights reserved.

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This paper considers a model-based approach to the clustering of tissue samples of a very large number of genes from microarray experiments. It is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. Frequently in practice, there are also clinical data available on those cases on which the tissue samples have been obtained. Here we investigate how to use the clinical data in conjunction with the microarray gene expression data to cluster the tissue samples. We propose two mixture model-based approaches in which the number of components in the mixture model corresponds to the number of clusters to be imposed on the tissue samples. One approach specifies the components of the mixture model to be the conditional distributions of the microarray data given the clinical data with the mixing proportions also conditioned on the latter data. Another takes the components of the mixture model to represent the joint distributions of the clinical and microarray data. The approaches are demonstrated on some breast cancer data, as studied recently in van't Veer et al. (2002).

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Alcoholism results in changes in the human brain which reinforce the cycle of craving and dependency, and these changes are manifest in the pattern of expression of mRNA and proteins in key cells and brain areas. Long-term alcohol abuse also results in damage to selected regions of the cortex. We have used cDNA microarrays to show that less than 1% of mRNA transcripts differ signifi cantly between cases and controls in the susceptible area and that the expression profi le of a subset of these transcripts is suffi cient to distinguish alcohol abusers from controls. In addition, we have utilized a 2D gel proteomics based approach to determine the identity of proteins in the superior frontal cortex (SFC) of the human brain that show differential expression in controls and long term alcohol abusers. Overall, 182 proteins differed by the criterion of > 2-fold between case and control samples. Of these, 139 showed signifi cantly lower expression in alcoholics, 35 showed signifi cantly higher expression, and 8 were new or had disappeared. To date 63 proteins have been identifi ed. The expression of one family of proteins, the synucleins, has been further characterized using Real Time PCR and Western Blotting. The expression of alpha-synuclein mRNA was signifi cantly lower in the SFC of alcoholics compared with the same area in controls (P = 0.01) whereas no such difference in expression was found in the motor cortex. The expression of beta- and gamma- synuclein were not signifi cantly different between alcoholics and controls. In contrast, the pattern of alphasynuclein protein expression differs from that of the corresponding RNA transcript. Because of the key role of synaptic proteins in the pathogenesis of alcoholism, we are developing 2-D DIGE based techniques to quantify expression changes in synaptosomes prepared from the SFC of controls and alcoholics.

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In recent years, strategies for gene identification based on differential gene expression have become increasingly popular, due in part to the development of microarray technology. These strategies are particularly well suited to the identification of genes involved in sex determination and gonadal development, which unlike the development of other organ systems, proceeds along two very different alternative courses, depending on the sex of the embryo. We have used a high-throughput, array-based expression screen to identify several genes expressed sex-specifically in developing mouse gonads. One of these, vanin 1, appears to play a role in mediating migration of mesonephric cells into the male genital ridge. Progress in characterizing other genes arising from the screen is discussed.

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Objective: Recently, much research has been proposed using nature inspired algorithms to perform complex machine learning tasks. Ant colony optimization (ACO) is one such algorithm based on swarm intelligence and is derived from a model inspired by the collective foraging behavior of ants. Taking advantage of the ACO in traits such as self-organization and robustness, this paper investigates ant-based algorithms for gene expression data clustering and associative classification. Methods and material: An ant-based clustering (Ant-C) and an ant-based association rule mining (Ant-ARM) algorithms are proposed for gene expression data analysis. The proposed algorithms make use of the natural behavior of ants such as cooperation and adaptation to allow for a flexible robust search for a good candidate solution. Results: Ant-C has been tested on the three datasets selected from the Stanford Genomic Resource Database and achieved relatively high accuracy compared to other classical clustering methods. Ant-ARM has been tested on the acute lymphoblastic leukemia (ALL)/acute myeloid leukemia (AML) dataset and generated about 30 classification rules with high accuracy. Conclusions: Ant-C can generate optimal number of clusters without incorporating any other algorithms such as K-means or agglomerative hierarchical clustering. For associative classification, while a few of the well-known algorithms such as Apriori, FP-growth and Magnum Opus are unable to mine any association rules from the ALL/AML dataset within a reasonable period of time, Ant-ARM is able to extract associative classification rules.

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To capture the genomic profiles for histone modification, chromatin immunoprecipitation (ChIP) is combined with next generation sequencing, which is called ChIP-seq. However, enriched regions generated from the ChIP-seq data are only evaluated on the limited knowledge acquired from manually examining the relevant biological literature. This paper proposes a novel framework, which integrates multiple knowledge sources such as biological literature, Gene Ontology, and microarray data. In order to precisely analyze ChIP-seq data for histone modification, knowledge integration is based on a unified probabilistic model. The model is employed to re-rank the enriched regions generated from peak finding algorithms. Through filtering the reranked enriched regions using some predefined threshold, more reliable and precise results could be generated. The combination of the multiple knowledge sources with the peaking finding algorithm produces a new paradigm for ChIP-seq data analysis. © (2012) Trans Tech Publications, Switzerland.

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The breadth and depth of available clinico-genomic information, present an enormous opportunity for improving our ability to study disease mechanisms and meet the individualised medicine needs. A difficulty occurs when the results are to be transferred 'from bench to bedside'. Diversity of methods is one of the causes, but the most critical one relates to our inability to share and jointly exploit data and tools. This paper presents a perspective on current state-of-the-art in the analysis of clinico-genomic data and its relevance to medical decision support. It is an attempt to investigate the issues related to data and knowledge integration. Copyright © 2010 Inderscience Enterprises Ltd.