[Bioinformatics for drug discovery].
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Cluster Analysis↗
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Results for “Oligonucleotide Array Sequence Analysis”
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Microarrays for bacterial detection and microbial community analysis.
Several types of microarrays have recently been developed and evaluated for bacterial detection and microbial community analysis. These studies demonstrated that specific, sensitive and quantitative detection could be obtained with both functional gene arrays and community genome arrays. Although single-base mismatch can be differentiated with phylogenetic oligonucleotide arrays, reliable specific detection at the single-base level is still problematic. Microarray-based hybridization approaches are also useful for defining genome diversity and bacterial relatedness. However, more rigorous and systematic assessment and development are needed to realize the full potential of microarrays for microbial detection and community analysis.
Bacteria↗
An oligonucleotide microarray for high-throughput sequencing of the mitochondrial genome.
Previously we developed an oligonucleotide sequencing microarray (MitoChip) as an array-based sequencing platform for rapid and high-throughput analysis of mitochondrial DNA. The first generation MitoChip, however, was not tiled with probes for the noncoding D-loop region, a site frequently mutated in human cancers. Here we report the development of a second-generation MitoChip (v2.0) with oligonucleotide probes to sequence the entire mitochondrial genome. In addition, the MitoChip v2.0 contains redundant tiling of sequences for 500 of the most common haplotypes including single-nucleotide changes, insertions, and deletions. Sequencing results from 14 primary head and neck tumor tissues demonstrated that the v2.0 MitoChips detected a larger number of variants than the original version. Multiple coding region variants detected only in the second generation MitoChips, but not the earlier chip version, were further confirmed with conventional sequencing. Moreover, 31 variations in noncoding region were identified using MitoChips v2.0. Replicate experiments demonstrated >99.99% reproducibility in the second generation MitoChip. In seven head and neck cancer samples with matched lymphocyte DNA, the MitoChip v2.0 detected at least one cancer-associated mitochondrial mutation in four (57%) samples. These results indicate that the second generation MitoChip is a high-throughput platform for identification of mitochondrial DNA mutations in primary tumors.
Base Sequence↗
Deoxynucleotides can replace dideoxynucleotides in minisequencing by arrayed primer extension.
Scientific literature describing arrayed primer extension and other array-based minisequencing technologies consistently cite the requirement for four fluorescent dideoxynucleotides (with concomitant absence/inactivation of deoxynucleotides) to ensure single-base extension and thus sequence-specific intensity data that can be interpreted as a base call or genotype. We present compelling evidence that fluorescent deoxynucleotides can reliably be used in microarray minisequencing experiments, generating fluorescent sequence extension intensity profiles that are homologous to the single-base extensions obtained with terminator dideoxynucleotides. Due to the almost 10-fold higher costs (and limited fluorophore choice) of many commercially available fluorescent dideoxynucleotides, compared to fluorescent deoxynucleotides, as well as other potentially constraining intellectual property and licensing issues, this hitherto dismissed microarray chemistry represents an important reevaluation in the field of array-based genotyping and related enzymology.
Chromosome Mapping↗
Factor analysis of cluster-specific gene expression levels from cDNA microarrays.
The ever-increasing use of cDNA microarrays in medical research will require the development of new algorithms designed specifically for desktop analysis of potentially large genetic data sets. This paper describes the CLUSFAVOR algorithm (CLUSter and Factor Analysis Using Varimax Orthogonal Rotation) for performing cluster and factor analysis of gene expression data obtained from cDNA microarrays. A unique feature of the CLUSFAVOR algorithm is that a user can perform cluster analysis, view dendograms, and run factor analysis on cluster-specific genes selected interactively within a single executable program. CLUSFAVOR also performs a varimax orthogonal rotation on the extracted factors to increase parsimony in the loadings, revealing unique expression profiles for genes and expressed sequence tags (ESTs) for which pathway and function information is unknown. Microarray data used by the program must be stored and input from a disk file. Optional output contains matrices for the input data, standardized data, distance matrices, factor loadings, eigenvalues, eigenvectors, and percentage of total variation for genes within a cluster. Color cluster image displays containing gene expression levels, dendograms for arrays and genes, and factor loadings are displayed for the entire group of genes and arrays analyzed as well as selected genes within a cluster. Cluster images are also exported to JPG and linked to HTML files for viewing.
Algorithms↗
New approach to gene expression analysis.
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Gene Expression Profiling↗
Gene expression analysis enriched.
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Gene Expression Profiling↗
DNA microarray analysis for the detection of mutations in hemophilia A.
BACKGROUND: Congenital deficiency of factor (F) VIII results in the inherited X-linked bleeding disorder hemophilia A. More than 900 different mutations are reported in the hemophilia A mutation database with the largest number of mutations being single nucleotide substitutions distributed throughout the gene. Complicating the molecular characterization of this disease is the complexity of the F8 gene, the mutational heterogeneity, and technical limitations of the current mutation detection techniques. OBJECTIVE: Development of a DNA oligonucleotide microarray-based technique for F8 gene analysis to detect hemophilia A mutations. METHODS: To construct the oligonucleotide DNA microarray system: a total of 720, one base pair overlapping, 25-mer perfect match probes were designed from six exons of the F8 gene. Twenty-two different F8 gene mutations previously identified by CSGE and DNA sequence analysis were tested by using a loss-of-signal analysis approach. Differentially labeled wild type and hemophilic samples were co-hybridized to the array. Sequence alterations were detected by quantifying relative losses of test sample hybridization signals to the perfectly matched probes. RESULTS: A total of 22 different F8 mutations were tested. To test the sensitivity of the system, a blinded study was performed on 16 of the samples. F8 gene mutations can be detected with 96% efficiency with this microarray system. CONCLUSION: This proof-of-principle study has demonstrated that a F8 DNA microarray platform is an alternative gene mutation analysis approach that has a high sensitivity, and reproducibility. The methodology is, however, expensive and time consuming, and with the reduction in sequencing costs, direct sequencing is now the most cost and time efficient strategy for hemophilia A mutation analysis.
DNA Mutational Analysis↗
Design of a DNA chip for detection of unknown genetically modified organisms (GMOs).
MOTIVATION: Unknown genetically modified organisms (GMOs) have not undergone a risk evaluation, and hence might pose a danger to health and environment. There are, today, no methods for detecting unknown GMOs. In this paper we propose a novel method intended as a first step in an approach for detecting unknown genetically modified (GM) material in a single plant. RESULTS: A model is designed where biological and combinatorial reduction rules are applied to a set of DNA chip probes containing all possible sequences of uniform length n, creating probes capable of detecting unknown GMOs. The model is theoretically tested for Arabidopsis thaliana Columbia, and the probabilities for detecting inserts and receiving false positives are assessed for various parameters for this organism. From a theoretical standpoint, the model looks very promising but should be tested further in the laboratory. AVAILABILITY: The model and algorithms will be available upon request to the corresponding author.
Algorithms↗
cis-Regulatory sequences of the genes involved in apoptosis, cell growth, and proliferation may provide a target for some of the effects of acute ethanol exposure.
The physiological effects of alcohol are known to include drunkenness, toxicity, and addiction leading to alcohol-related health and societal problems. Some of these effects are mediated by regulation of expression of many genes involved in alcohol response pathways. Analysis of the regulatory elements and biological interaction of the genes that show coexpression in response to alcohol may give an insight into how they are regulated. Fifty-two ethanol-responsive (ER) genes displaying differential expression in mouse brain in response to acute ethanol exposure were subjected to bioinformatics analysis to identify known or putative transcription factor binding sites and cis-regulatory modules in the promoter regions that may be involved in their responsiveness to alcohol. Functional interactions of these genes were also examined to assess their cumulative contribution to metabolomic pathways. Clustering and promoter sequence analysis of the ER genes revealed the DNA binding site for nuclear transcription factor Y (NFY) as the most significant. NFY also take part in the proposed biological association network of a number of ER genes, where these genes interact with themselves and other cellular components, and may generate a major cumulative effect on apoptosis, cell survival, and proliferation in response to alcohol. NFY has the potential to play a critical role in mediating the expression of a set of ER genes whose interactions contribute to apoptosis, cell survival, and proliferation, which in turn may affect alcohol-related behaviors.
Animals↗
Mass distributed clustering: a new algorithm for repeated measurements in gene expression data.
The availability of whole-genome sequence data and high-throughput techniques such as DNA microarray enable researchers to monitor the alteration of gene expression by a certain organ or tissue in a comprehensive manner. The quantity of gene expression data can be greater than 30,000 genes per one measurement, making data clustering methods for analysis essential. Biologists usually design experimental protocols so that statistical significance can be evaluated; often, they conduct experiments in triplicate to generate a mean and standard deviation. Existing clustering methods usually use these mean or median values, rather than the original data, and take significance into account by omitting data showing large standard deviations, which eliminates potentially useful information. We propose a clustering method that uses each of the triplicate data sets as a probability distribution function instead of pooling data points into a median or mean. This method permits truly unsupervised clustering of the data from DNA microarrays.
Algorithms↗
Polymorphism analysis within the HLA-A locus by universal oligonucleotide array.
Human leukocyte antigen (HLA) class I genes present some of the most complex single nucleotide polymorphism (SNP) patterns in the human genome. HLA typing is therefore extremely challenging. In this article, we use the ligation detection reaction (LDR) combined with a universal array (UA) as a robust and efficient method to analyze SNPs within the HLA-A region that includes HLA-A alleles of interest for immunotherapy in tumor diseases. The LDR, combined with a UA platform, has been optimized for the detection of 27 alleles distributed within exons 2 and 3 of HLA-A. The assay involves the amplification by PCR of the HLA-A genomic region (1,900 bp), the cycled ligation reaction, followed by the capture of ligated products through hybridization onto a UA. Each slide was designed to allow the detection of up to eight samples in parallel. The PCR/LDR/UA HLA-A assay was evaluated by analyzing 62 individuals (31 homozygous and 31 heterozygous) previously typed by direct sequencing. We demonstrate that the microarray genotyping procedure described here is a robust and efficient method for unambiguous detection of HLA alleles. HLA genotyping by PCR/LDR/UA is in perfect agreement with typing obtained by direct sequencing. Our results clearly demonstrate that the combination of enzymatic processing (LDR) and a demultiplexing hybridization onto a UA is a robust tool for SNP discrimination within the highly polymorphic HLA region. We demonstrate the specificity and efficiency of such an approach, suggesting the feasibility of a PCR/LDR/UA low resolution HLA typing procedure.
Alleles↗
Integration of multiple PCR amplifications and DNA mutation analyses by using oligonucleotide microchip.
We have developed a method for parallel independent on-chip amplification and the following sequence variation analysis of multiple DNA regions directly using microchip with an array of nanoliter gel pads containing specific sets of tethered primers. The method has three key features. First, DNA to be amplified is enriched at gel pads by its hybridization with immobilized primers. Second, different sets of specific primers are immobilized within various gel pads, and primers are detached within gel pads just before polymerase chain reaction to enhance the amplification. A gel pad may contain an additional permanently immobilized dormant primer that is activated to carry out the allele-specific primer extension reaction to detect mutations. Third, multiple polymerase chain reactions are confined within nanoliter gel pads covered and separated from each other with mineral oil. The method was applied to simultaneously identify several abundant drug-resistant mutations in three genes of Mycobacterium tuberculosis.
Antibiotics, Antitubercular↗
Fundamentals of DNA hybridization arrays for gene expression analysis.
DNA hybridization arrays [also known as macroarrays, microarrays and/or high-density oligonucleotide arrays (Gene Chips)] bring gene expression analysis to a genomic scale by permitting investigators to simultaneously examine changes in the expression of literally thousands of genes. For hybridization arrays, the general approach is to immobilize gene-specific sequences (probes) on a solid state matrix (nylon membranes, glass microscope slides, silicon/ceramic chips). These sequences are then queried with labeled copies of nucleic acids from biological samples (targets). The underlying theory is that the greater the expression of a gene, the greater the amount of labeled target, and hence, the greater output signal. In spite of the simplicity of the experimental design, there are at least four different platforms and several different approaches to processing and labeling the biological samples. Moreover, investigators must also determine whether they will utilize commercially available arrays or generate their own. This review will cover the status of the hybridization array field with an eye toward underlying principles and available technologies. Future developments and technological trends will also be evaluated.
Cluster Analysis↗
Evaluating the comparability of gene expression in blood and brain.
The availability of an accessible tissue whose gene expression profile is similar to more inaccessible CNS tissues has the potential to advance research in neuropsychiatric disorders. We conducted secondary data analysis of transcriptional profiling of 79 human tissues for 33,698 genes using the Affymetrix U133A microarray augmented with a custom microarray (Affymetrix GNF1H), which were produced by the Genomics Institute of the Novartis Research Foundation (http://symatlas.gnf.org). Our analyses suggested that: (a) on a transcriptome level, whole blood shares significant gene expression similarities with multiple CNS tissues; (b) the median non-parametric correlation between transcripts present in both whole blood and CNS was around 0.5; (c) this correlation of 0.5 was intermediate relative to all tissues in the Novartis data set--less than for the maximum achievable value of 0.85, less than a set of immune tissues (0.64), comparable to a heterogeneous set of somatic tissues (0.57) but greater than muscle (0.48) and peripheral nervous system tissues (0.36); (d) about half of a set of candidate genes relevant to schizophrenia were expressed in both whole blood and prefrontal cortex; and (e) the expression levels of many classes of biologically relevant processes were not significantly different between whole blood and prefrontal cortex. These analyses suggest that gene expression in whole blood is neither perfectly correlated and useful nor perfectly uncorrelated and useless with gene expression in multiple brain tissues. This suggests that the cautious and thoughtful use of peripheral gene expression may be a useful surrogate for gene expression in the CNS when it has been determined that the relevant gene is expressed in both.
Brain↗
DNA chip analysis of comprehensive food function: inhibition of angiogenesis and telomerase activity with unsaturated vitamin E, tocotrienol.
Inhibition of angiogenesis and telomerase activity with vitamin E compounds, especially for tocotrienol (T3), has been investigated. Nutrigenomic tools have been used for elucidating the bioactive mechanisms of T3. In the cell culture experiments, T3 reduced the vascular endothelial growth factor (VEGF)-stimulated tube formation by human umbilical vein endothelial cells (HUVEC). Among T3 isomers, delta-T3 appeared the highest activity. The T3 inhibited the new blood vessels formation on the growing chick embryo chorioallantoic membrane (CAM assay for an in vivo model of angiogenesis). In contrast, tocopherol did not. The findings suggested that the T3 has potential use for reducing angiogenic disorder. DNA chip analysis revealed that T3 specifically down-regulates the expression of VEGF receptor (VEGFR) in endothelial cells. It is well-known that VEGF regulates angiogenesis by binding to VEGFR. Therefore, T3 could block the intracellular signaling of VEGF via down-regulation of VEGFR, which resulted in the inhibition of angiogenesis. On the other hand, DNA chip analysis also revealed that T3 down-regulates the expression of protein kinase C (PKC) in the cultured HUVEC. Since PKC is involved with the control of telomerase activity, T3 has potential to act as anti-telomerase inhibitor via PKC inhibition. In this manner, DNA chip technology provides efficient access to genetic information regarding food function and its mechanism.
Allantois↗
An improved gel-based DNA microarray method for detecting single nucleotide mismatch.
3-D polyacrylamide gel-based DNA microarray platforms provide a high capacity for nucleic acids immobilization and a solution-mimicking environment for hybridization. However, several technological bottlenecks still remain in these platforms, such as difficult microarray preparation and high fluorescent background, which limit their application. In this study, two new approaches have been developed to improve the convenience in microarray preparation and to reduce the background after hybridization. To control the polymerization process, solutions containing acrylamide-modified oligonucleotide, acrylamide, glycerol and ammonium persulfate are spotted onto a functionalized glass slide, and then the slide is transferred to a vacuum chamber with TEMED, so that TEMED is vaporized and diffused into the spots to induce polymerization. By applying an electric field across a hybridized microarray to remove the nonspecifically bound labeled targets, this approach can solve the problem of high fluorescent background of the gel-based microarray after hybridization. Experimental results show that our immobilization method can be used to construct high quality microarrays and exhibits good reproducibility. Moreover, the polymerization is not affected by PCR medium, so that PCR products can be used for microarray construction without being treated by commercial purification cartridges. Electrophoresis can improve the signal-to-noise significantly and has the ability to differentiate single nucleotide variation between two homozygotes and a heterozygote. Our results demonstrated that this is a reliable novel method for high-throughput mutation analysis and disease diagnosis.
Base Pair Mismatch↗
Testing and improving experimental parameters for the use of low molecular weight targets in array-CGH experiments.
Array-comparative genomic hybridization (CGH) has evolved as a useful technique for the detection and characterization of deletions, and, to a lesser extent, of duplications. The resolution of the technique is dictated by the genomic distance between targets spotted on the microarray, and by the targets' sizes. The use of region-specific, high-resolution microarrays is a specific goal when studying regions that are prone to rearrangements, such as those involved in deletion syndromes. The aim of the present study was to evaluate the best experimental conditions to be used for array-CGH analysis using low molecular weight (LMW) targets. The parameters tested were: the target concentration, the way LMW targets are prepared (either as linearized plasmids or as purified PCR products), and the way the targets are attached to the array-CGH slide (in a random fashion on amino-silane coated slides, or by one amino-modified end on epoxysilane-coated slides). As a test case, we constructed a microarray harboring LMW targets located in the CREBBP gene, mutations of which cause the Rubinstein-Taybi syndrome (RTS). From 10 to 15% of RTS patients have a CREBBP deletion. We showed that aminosilane- and epoxysilane-coated slides were equally efficient with targets above 1,000 bp in size. On the other hand, with the smallest targets, especially those below 500 bp, epoxysilane-coated slides were superior to aminosilane-coated slides, which did not allow deletion detection. Use of the high resolution array allowed us to map intragenic breakpoints with precision and to identify a very small deletion and a duplication that were not detected by the currently available techniques for finding CREBBP deletions.
Biomarkers↗