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Results for “Oligonucleotide Array Sequence Analysis”

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At least 649 records · Page 36Linked to original sources
PubMed2003

Graphical exploration of gene expression data: a comparative study of three multivariate methods.

This article describes three multivariate projection methods and compares them for their ability to identify clusters of biological samples and genes using real-life data on gene expression levels of leukemia patients. It is shown that principal component analysis (PCA) has the disadvantage that the resulting principal factors are not very informative, while correspondence factor analysis (CFA) has difficulties interpreting distances between objects. Spectral map analysis (SMA) is introduced as an alternative approach to the analysis of microarray data. Weighted SMA outperforms PCA, and is at least as powerful as CFA, in finding clusters in the samples, as well as identifying genes related to these clusters. SMA addresses the problem of data analysis in microarray experiments in a more appropriate manner than CFA, and allows more flexible weighting to the genes and samples. Proper weighting is important, since it enables less reliable data to be down-weighted and more reliable information to be emphasized.

Biometry↗
PubMed2006

The role of microarray technologies in the study of soft tissue tumours.

Array technologies (gene array, tissue microarray and others) are being used in a growing number of research projects involving soft tissue tumours. Gene array techniques allow for measurements of RNA expression levels or gene copy number changes for a large number of genes in a single specimen. A complementary technique, tissue microarrays, allows for the measurement of expression of a single gene in a large number of specimens. These techniques and similar ones have created a fundamentally new approach to the investigation of soft tissue tumours. This review addresses some of the advantages, problems, and solutions to those problems that come with these technologies.

Cluster Analysis↗
PubMed2006

A simple and reliable assay for detecting specific nucleotide sequences in plants using optical thin-film biosensor chips.

Here we report the adaptation and optimization of an efficient, accurate and inexpensive assay that employs custom-designed silicon-based optical thin-film biosensor chips to detect unique transgenes in genetically modified (GM) crops and SNP markers in model plant genomes. Briefly, aldehyde-attached sequence-specific single-stranded oligonucleotide probes are arrayed and covalently attached to a hydrazine-derivatized biosensor chip surface. Unique DNA sequences (or genes) are detected by hybridizing biotinylated PCR amplicons of the DNA sequences to probes on the chip surface. In the SNP assay, target sequences (PCR amplicons) are hybridized in the presence of a mixture of biotinylated detector probes and a thermostable DNA ligase. Only perfect matches between the probe and target sequences, but not those with even a single nucleotide mismatch, can be covalently fixed on the chip surface. In both cases, the presence of specific target sequences is signified by a color change on the chip surface (gold to blue/purple) after brief incubation with an anti-biotin IgG horseradish peroxidase (HRP) to generate a precipitable product from an HRP substrate. Highly sensitive and accurate identification of PCR targets can be completed within 30 min. This assay is extremely robust, exhibits high sensitivity and specificity, and is flexible from low to high throughput and very economical. This technology can be customized for any nucleotide sequence-based identification assay and widely applied in crop breeding, trait mapping, and other work requiring positive detection of specific nucleotide sequences.

Alleles↗
PubMed2005

Oligonucleotide microarray for HLA-DRB1 genotyping: preparation and clinical evaluation.

In this study, HLA-DRB1 gene was genotyped by using the microarray technique. Oligonucleotide probes were designed based on partial sequences of various genotypes of HLA-DRB1, and were fixed on a silylated slide to form a microarray. The second exon of HLA-DRB1 gene in the extracted genomic DNA samples was amplified and labelled by means of polymerase chain reaction (PCR); then it was hybridized to the microarray. The microarray was scanned, and the result was analysed in order to determine the genotypes of HLA-DRB1 of the tested sample. A total of 1574 of 1592 clinical samples had accordant results of genotypes in either microarray assay or PCR-SSP assay; 8 of 10 samples that had inconsistent results of genotypes were proved to be microarray-assay reliable by confirmation of DNA sequencing. It is concluded that microarray is an alternative reliable method for HLA-DRB1 genotyping.

China↗
PubMed2006

Growth phase-dependent expression of the Pseudomonas putida KT2440 transcriptional machinery analysed with a genome-wide DNA microarray.

Bacterial transcriptional networks are built on a hierarchy of regulators, on top of which lie the components of the RNA polymerase (in particular the sigma factors) and the global control elements, which play a pivotal role. We have designed a genome-wide oligonucleotide-based DNA microarray for Pseudomonas putida KT2440. In combination with real-time reverse transcription polymerase chain reaction (RT-PCR), we have used it to analyse the expression pattern of the genes encoding the RNA polymerase subunits (the core enzyme and the 24 sigma factors), and various proteins involved in global regulation (Crc, Lrp, Fur, Anr, Fis, CsrA, IHF, HupA, HupB, HupN, BipA and several MvaT-like proteins), during the shift from exponential growth in rich medium into starvation and stress brought about by the entry into stationary phase. Expression of the genes encoding the RNA polymerase core and the vegetative sigma factor decreased in stationary phase, while that of sigma(S) increased. Data obtained for sigma(N), sigma(H), FliA and for the 19 extracytoplasmic function (ECF)-like sigma factors suggested that their mRNA levels change little upon entry into stationary phase. Expression of Crc, BipA, Fis, HupB, HupN and the MvaT-like protein PP3693 decreased in stationary phase, while that of HupA and the MvaT-like protein PP3765 increased significantly. Expression of IHF was indicative of post-transcriptional control. These results provide the first global study of the expression of the transcriptional machinery through the exponential stationary-phase shift in P. putida.

DNA-Directed RNA Polymerases↗
PubMed2005

Imputation and variable selection in linear regression models with missing covariates.

Across multiply imputed data sets, variable selection methods such as stepwise regression and other criterion-based strategies that include or exclude particular variables typically result in models with different selected predictors, thus presenting a problem for combining the results from separate complete-data analyses. Here, drawing on a Bayesian framework, we propose two alternative strategies to address the problem of choosing among linear regression models when there are missing covariates. One approach, which we call "impute, then select" (ITS) involves initially performing multiple imputation and then applying Bayesian variable selection to the multiply imputed data sets. A second strategy is to conduct Bayesian variable selection and missing data imputation simultaneously within one Gibbs sampling process, which we call "simultaneously impute and select" (SIAS). The methods are implemented and evaluated using the Bayesian procedure known as stochastic search variable selection for multivariate normal data sets, but both strategies offer general frameworks within which different Bayesian variable selection algorithms could be used for other types of data sets. A study of mental health services utilization among children in foster care programs is used to illustrate the techniques. Simulation studies show that both ITS and SIAS outperform complete-case analysis with stepwise variable selection and that SIAS slightly outperforms ITS.

Algorithms↗
PubMed2005

Use of principal component analysis and the GE-biplot for the graphical exploration of gene expression data.

This note is in response to Wouters et al. (2003, Biometrics 59, 1131-1139) who compared three methods for exploring gene expression data. Contrary to their summary that principal component analysis is not very informative, we show that it is possible to determine principal component analyses that are useful for exploratory analysis of microarray data. We also present another biplot representation, the GE-biplot (Gene Expression biplot), that is a useful method for exploring gene expression data with the major advantage of being able to aid interpretation of both the samples and the genes relative to each other.

Algorithms↗
PubMed2006

Detecting single nucleotide polymorphisms using DNA arrays for plant pathogen diagnosis.

The lack of a rapid and reliable means for routine pathogen identification has been one of the main limitations in plant disease management, and has pushed the development of culture-independent, molecular approaches. Currently, DNA array technology is the most suitable technique for high-throughput detection and identification, as well as quantification, of multiple pathogens in a single assay. Closely related pathogens that may have completely different host ranges or pathogenicity often differ in only a single to a few base pairs in genes that may be targeted for identification. Therefore, the ability to discriminate single nucleotide polymorphisms (SNPs) should be pursued in any diagnostic assay. In this paper, we demonstrate the utility of DNA array technology to detect SNPs while accounting for specific criteria such as the position of the mismatch, the sequence of the oligonucleotide, and the length and amount of labeled amplicons that are hybridized. When disregarding mismatches at the extreme ends of the oligonucleotides, cross hybridization to single mismatch oligonucleotides is rare when processing environmental samples that contain genetic material from unknown sources. In addition to plant pathology, this study is relevant for any field of research where DNA arrays are used to detect mutations or polymorphisms, ranging from human diagnostics to environmental microbiology and microbial ecology.

DNA, Fungal↗
PubMedDate not supplied

Screening for the breast cancer gene (BRCA1) using a biochip system and molecular beacon probes immobilized on solid surfaces.

We describe the use of a biochip based on complementary metal oxide semiconductor (CMOS) technology for detection of specific genetic sequences using molecular beacons (MB) immobilized on solid surfaces as probes. The applicability of this miniature detection system for screening for the BRCA1 gene is evaluated using MB probes, designed especially for the BRCA1 gene. MB probes are immobilized on a zeta-probe membrane by biotin-streptavidin immobilization. Two immobilization strategies are investigated to obtain optimal assay sensitivity. The MB is immobilized by manual spotting on zeta-probe membrane surfaces with the use of a custom-made stamping system. The detection of the BRCA1 gene using an MB probe is successfully demonstrated and expands the use of the CMOS biochip for medical applications.

Adsorption↗
PubMedDate not supplied

Noise factor analysis for cDNA microarrays.

A microarray-image model is used that takes into account many factors, including spot morphology, signal strength, background fluorescent noise, and shape and surface degradation. The model yields synthetic images whose appearance and quality reflect that of real microarray images. The model is used to link noise factors to the fidelity of signal extraction with respect to a standard image-extraction algorithm. Of particular interest is the identification of the noise factors and their interactions that significantly degrade the ability to accurately detect the true gene-expression signal. This study uses statistical criteria in conjunction with the simulation of various noise conditions to better understand the noise influence on signal extraction for cDNA microarray images. It proposes a paradigm that is implemented in software. It specifically considers certain kinds of noise in the noise model and sets these at certain levels; however, one can choose other types of noise or use different noise levels. In sum, it develops a statistical package that can work in conjunction with the existing image simulation toolbox.

Algorithms↗
PubMed2002

Array-based electrical detection of DNA with nanoparticle probes.

A DNA array detection method is reported in which the binding of oligonucleotides functionalized with gold nanoparticles leads to conductivity changes associated with target-probe binding events. The binding events localize gold nanoparticles in an electrode gap; silver deposition facilitated by these nanoparticles bridges the gap and leads to readily measurable conductivity changes. An unusual salt concentration-dependent hybridization behavior associated with these nanoparticle probes was exploited to achieve selectivity without a thermal-stringency wash. Using this method, we have detected target DNA at concentrations as low as 500 femtomolar with a point mutation selectivity factor of approximately 100,000:1.

Antigens, Bacterial↗
PubMed2002

Large-scale transcriptional activity in chromosomes 21 and 22.

The sequences of the human chromosomes 21 and 22 indicate that there are approximately 770 well-characterized and predicted genes. In this study, empirically derived maps identifying active areas of RNA transcription on these chromosomes have been constructed with the use of cytosolic polyadenylated RNA obtained from 11 human cell lines. Oligonucleotide arrays containing probes spaced on average every 35 base pairs along these chromosomes were used. When compared with the sequence annotations available for these chromosomes, it is noted that as much as an order of magnitude more of the genomic sequence is transcribed than accounted for by the predicted and characterized exons.

Cell Line↗
PubMed2004

A gene expression map for the euchromatic genome of Drosophila melanogaster.

We used a maskless photolithography method to produce DNA oligonucleotide microarrays with unique probe sequences tiled throughout the genome of Drosophila melanogaster and across predicted splice junctions. RNA expression of protein coding and nonprotein coding sequences was determined for each major stage of the life cycle, including adult males and females. We detected transcriptional activity for 93% of annotated genes and RNA expression for 41% of the probes in intronic and intergenic sequences. Comparison to genome-wide RNA interference data and to gene annotations revealed distinguishable levels of expression for different classes of genes and higher levels of expression for genes with essential cellular functions. Differential splicing was observed in about 40% of predicted genes, and 5440 previously unknown splice forms were detected. Genes within conserved regions of synteny with D. pseudoobscura had highly correlated expression; these regions ranged in length from 10 to 900 kilobase pairs. The expressed intergenic and intronic sequences are more likely to be evolutionarily conserved than nonexpressed ones, and about 15% of them appear to be developmentally regulated. Our results provide a draft expression map for the entire nonrepetitive genome, which reveals a much more extensive and diverse set of expressed sequences than was previously predicted.

Algorithms↗
PubMed2004

Global identification of human transcribed sequences with genome tiling arrays.

Elucidating the transcribed regions of the genome constitutes a fundamental aspect of human biology, yet this remains an outstanding problem. To comprehensively identify coding sequences, we constructed a series of high-density oligonucleotide tiling arrays representing sense and antisense strands of the entire nonrepetitive sequence of the human genome. Transcribed sequences were located across the genome via hybridization to complementary DNA samples, reverse-transcribed from polyadenylated RNA obtained from human liver tissue. In addition to identifying many known and predicted genes, we found 10,595 transcribed sequences not detected by other methods. A large fraction of these are located in intergenic regions distal from previously annotated genes and exhibit significant homology to other mammalian proteins.

Animals↗
PubMed2005

MicroRNA expression in zebrafish embryonic development.

MicroRNAs (miRNAs) are small noncoding RNAs, about 21 nucleotides in length, that can regulate gene expression by base-pairing to partially complementary mRNAs. Regulation by miRNAs can play essential roles in embryonic development. We determined the temporal and spatial expression patterns of 115 conserved vertebrate miRNAs in zebrafish embryos by microarrays and by in situ hybridizations, using locked-nucleic acid-modified oligonucleotide probes. Most miRNAs were expressed in a highly tissue-specific manner during segmentation and later stages, but not early in development, which suggests that their role is not in tissue fate establishment but in differentiation or maintenance of tissue identity.

Animals↗
PubMed2000

Scanometric DNA array detection with nanoparticle probes.

A method for analyzing combinatorial DNA arrays using oligonucleotide-modified gold nanoparticle probes and a conventional flatbed scanner is described here. Labeling oligonucleotide targets with nanoparticle rather than fluorophore probes substantially alters the melting profiles of the targets from an array substrate. This difference permits the discrimination of an oligonucleotide sequence from targets with single nucleotide mismatches with a selectivity that is over three times that observed for fluorophore-labeled targets. In addition, when coupled with a signal amplification method based on nanoparticle-promoted reduction of silver(I), the sensitivity of this scanometric array detection system exceeds that of the analogous fluorophore system by two orders of magnitude.

Base Pair Mismatch↗
PubMed2002

Nanoparticles with Raman spectroscopic fingerprints for DNA and RNA detection.

Multiplexed detection of oligonucleotide targets has been performed with gold nanoparticle probes labeled with oligonucleotides and Raman-active dyes. The gold nanoparticles facilitate the formation of a silver coating that acts as a surface-enhanced Raman scattering promoter for the dye-labeled particles that have been captured by target molecules and an underlying chip in microarray format. The strategy provides the high-sensitivity and high-selectivity attributes of gray-scale scanometric detection but adds multiplexing and ratioing capabilities because a very large number of probes can be designed based on the concept of using a Raman tag as a narrow-band spectroscopic fingerprint. Six dissimilar DNA targets with six Raman-labeled nanoparticle probes were distinguished, as well as two RNA targets with single nucleotide polymorphisms. The current unoptimized detection limit of this method is 20 femtomolar.

Coloring Agents↗