Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Oligonucleotide Array Sequence Analysis”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 739 records · Page 41Linked to original sources

The construction and use of bacterial DNA microarrays based on an optimized two-stage PCR strategy.

BACKGROUND: DNA microarrays are a powerful tool with important applications such as global gene expression profiling. Construction of bacterial DNA microarrays from genomic sequence data using a two-stage PCR amplification approach for the production of arrayed DNA is attractive because it allows, in principal, the continued re-amplification of DNA fragments and facilitates further utilization of the DNA fragments for additional uses (e.g. over-expression of protein). We describe the successful construction and use of DNA microarrays by the two-stage amplification approach and discuss the technical challenges that were met and resolved during the project. RESULTS: Chimeric primers that contained both gene-specific and shared, universal sequence allowed the two-stage amplification of the 3,168 genes identified on the genome of Synechocystis sp. PCC6803, an important prokaryotic model organism for the study of oxygenic photosynthesis. The gene-specific component of the primer was of variable length to maintain uniform annealing temperatures during the 1st round of PCR synthesis, and situated to preserve full-length ORFs. Genes were truncated at 2 kb for efficient amplification, so that about 92% of the PCR fragments were full-length genes. The two-stage amplification had the additional advantage of normalizing the yield of PCR products and this improved the uniformity of DNA features robotically deposited onto the microarray surface. We also describe the techniques utilized to optimize hybridization conditions and signal-to-noise ratio of the transcription profile. The inter-lab transportability was demonstrated by the virtual error-free amplification of the entire genome complement of 3,168 genes using the universal primers in partner labs. The printed slides have been successfully used to identify differentially expressed genes in response to a number of environmental conditions, including salt stress. CONCLUSIONS: The technique detailed here minimizes the cost and effort to replicate a PCR-generated DNA gene fragment library and facilitates several downstream processes (e.g. directional cloning of fragments and gene expression as affinity-tagged fusion proteins) beyond the primary objective of producing DNA microarrays for global gene expression profiling.

Cyanobacteria↗

Application of four dyes in gene expression analyses by microarrays.

BACKGROUND: DNA microarrays are widely used in gene expression analyses. To increase throughput and minimize costs without reducing gene expression data obtained, we investigated whether four mRNA samples can be analyzed simultaneously by applying four different fluorescent dyes. RESULTS: Following tests for cross-talk of fluorescence signals, Alexa 488, Alexa 594, Cyanine 3 and Cyanine 5 were selected for hybridizations. For self-hybridizations, a single RNA sample was labelled with all dyes and hybridized on commercial cDNA arrays or on in-house spotted oligonucleotide arrays. Correlation coefficients for all combinations of dyes were above 0.9 on the cDNA array. On the oligonucleotide array they were above 0.8, except combinations with Alexa 488, which were approximately 0.5. Standard deviation of expression differences for replicate spots were similar on the cDNA array for all dye combinations, but on the oligonucleotide array combinations with Alexa 488 showed a higher variation. CONCLUSION: In conclusion, the four dyes can be used simultaneously for gene expression experiments on the tested cDNA array, but only three dyes can be used on the tested oligonucleotide array. This was confirmed by hybridizations of control with test samples, as all combinations returned similar numbers of differentially expressed genes with comparable effects on gene expression.

Benzo(a)pyrene↗

Leveraging human genomic information to identify nonhuman primate sequences for expression array development.

BACKGROUND: Nonhuman primates (NHPs) are essential for biomedical research due to their similarities to humans. The utility of NHPs will be greatly increased by the application of genomics-based approaches such as gene expression profiling. Sequence information from the 3' end of genes is the key resource needed to create oligonucleotide expression arrays. RESULTS: We have developed the algorithms and procedures necessary to quickly acquire sequence information from the 3' end of nonhuman primate orthologs of human genes. To accomplish this, we identified terminal exons of over 15,000 human genes by aligning mRNA sequences with genomic sequence. We found the mean length of complete last exons to be approximately 1,400 bp, significantly longer than previous estimates. We designed primers to amplify genomic DNA, which included at least 300 bp of the terminal exon. We cloned and sequenced the PCR products representing over 5,500 Macaca mulatta (rhesus monkey) orthologs of human genes. This sequence information has been used to select probes for rhesus gene expression profiling. We have also tested 10 sets of primers with genomic DNA from Macaca fascicularis (Cynomolgus monkey), Papio hamadryas (Baboon), and Chlorocebus aethiops (African green monkey, vervet). The results indicate that the primers developed for this study will be useful for acquiring sequence from the 3' end of genes for other nonhuman primate species. CONCLUSION: This study demonstrates that human genomic DNA sequence can be leveraged to obtain sequence from the 3' end of NHP orthologs and that this sequence can then be used to generate NHP oligonucleotide microarrays. Affymetrix and Agilent used sequences obtained with this approach in the design of their rhesus macaque oligonucleotide microarrays.

Algorithms↗

Hyperspectral microarray scanning: impact on the accuracy and reliability of gene expression data.

BACKGROUND: Commercial microarray scanners and software cannot distinguish between spectrally overlapping emission sources, and hence cannot accurately identify or correct for emissions not originating from the labeled cDNA. We employed our hyperspectral microarray scanner coupled with multivariate data analysis algorithms that independently identify and quantitate emissions from all sources to investigate three artifacts that reduce the accuracy and reliability of microarray data: skew toward the green channel, dye separation, and variable background emissions. RESULTS: Here we demonstrate that several common microarray artifacts resulted from the presence of emission sources other than the labeled cDNA that can dramatically alter the accuracy and reliability of the array data. The microarrays utilized in this study were representative of a wide cross-section of the microarrays currently employed in genomic research. These findings reinforce the need for careful attention to detail to recognize and subsequently eliminate or quantify the presence of extraneous emissions in microarray images. CONCLUSION: Hyperspectral scanning together with multivariate analysis offers a unique and detailed understanding of the sources of microarray emissions after hybridization. This opportunity to simultaneously identify and quantitate contaminant and background emissions in microarrays markedly improves the reliability and accuracy of the data and permits a level of quality control of microarray emissions previously unachievable. Using these tools, we can not only quantify the extent and contribution of extraneous emission sources to the signal, but also determine the consequences of failing to account for them and gain the insight necessary to adjust preparation protocols to prevent such problems from occurring.

Algorithms↗

Discovery and validation of breast cancer subtypes.

BACKGROUND: Previous studies demonstrated breast cancer tumor tissue samples could be classified into different subtypes based upon DNA microarray profiles. The most recent study presented evidence for the existence of five different subtypes: normal breast-like, basal, luminal A, luminal B, and ERBB2+. RESULTS: Based upon the analysis of 599 microarrays (five separate cDNA microarray datasets) using a novel approach, we present evidence in support of the most consistently identifiable subtypes of breast cancer tumor tissue microarrays being: ESR1+/ERBB2-, ESR1-/ERBB2-, and ERBB2+ (collectively called the ESR1/ERBB2 subtypes). We validate all three subtypes statistically and show the subtype to which a sample belongs is a significant predictor of overall survival and distant-metastasis free probability. CONCLUSION: As a consequence of the statistical validation procedure we have a set of centroids which can be applied to any microarray (indexed by UniGene Cluster ID) to classify it to one of the ESR1/ERBB2 subtypes. Moreover, the method used to define the ESR1/ERBB2 subtypes is not specific to the disease. The method can be used to identify subtypes in any disease for which there are at least two independent microarray datasets of disease samples.

Algorithms↗

Overexpression of cathepsin F, matrix metalloproteinases 11 and 12 in cervical cancer.

BACKGROUND: Cervical carcinoma (CC) is one of the most common cancers among women worldwide and the first cause of death among the Mexican female population. CC progression shows a continuum of neoplastic transitions until invasion. Matrix metalloproteinases (MMPs) and cathepsins play a central role on the enhancement of tumor-induced angiogenesis, cell migration, proliferation, apoptosis and connective tissue degradation. MMPs -2 and -9 expression has been widely studied in cervical cancer. Nevertheless, no other metalloproteinases or cathepsins have been yet related with the progression and/or invasion of this type of cancer. METHODS: Three HPV18 CC cell lines, two HPV16 CC cell lines and three HPV16 tumor CC tissues were compared with three morphologically normal, HPV negative, cervical specimens by cDNA arrays. Overexpression of selected genes was confirmed by end point semiquantitative reverse transcription-PCR with densitometry. In situ hybridization and protein expression of selected genes was further studied by means of two tissue microarrays, one consisting of 10 HSIL and 15 CC and the other one of 15 normal cervical and 10 LSIL tissues. RESULTS: TIMP1, Integrins alpha 1 and 4, cadherin 2 and 11, Cathepsins F, B L2, MMP 9, 10 11 and 12 were upregulated and Cathepsin S, L, H and C, Cadherins 3 and 4, TIMP3, MMP 13, Elastase 2 and Integrin beta 8 were found to be downregulated by cDNA arrays. Endpoint RT-PCR with densitometry gave consistent results with the cDNA array findings for all three genes selected for study (CTSF, MMP11 and MMP12). In situ hybridization of all three genes confirmed overexpression in all the HSIL and CC. Two of the selected proteins were detected in LSIL, HSIL and CC by immunohistochemistry. CONCLUSION: Novel undetected CC promoting genes have been identified. Increased transcription of these genes may result in overexpression of proteins, such as CTSF, MMP11 and MMP12 which could contribute to the pathogenesis of CC.

Carcinoma↗

Oligodeoxyribonucleotide probe accessibility on a three-dimensional DNA microarray surface and the effect of hybridization time on the accuracy of expression ratios.

BACKGROUND: DNA microarrays are now routinely used to monitor the transcript levels of thousands of genes simultaneously. However, the array fabrication method, hybridization conditions, and oligodeoxyribonucleotide probe length can impact the performance of a DNA microarray platform. RESULTS: We demonstrate solution-phase hybridization behavior of probe:target interactions by showing a strong correlation between the effect of mismatches in probes attached to a three dimensional matrix of a microarray and solution-based, thermodynamic duplex melting studies. The effects of mismatches in the probes attached to the microarray also demonstrate that most, if not all, of the oligodeoxyribonucleotide is available for hybridization. Kinetic parameters were also investigated. As anticipated, hybridization signals increased in a transcript concentration-dependent manner, and mismatch specificity increased with hybridization time. Unexpectedly, hybridization time increased the accuracy of fold changes by relieving the compression observed in expression ratios, and this effect may be more dramatic for larger fold changes. CONCLUSIONS: Taken together, these studies demonstrate that a three-dimensional surface may enable use of shorter oligodeoxyribonucleotide probes and that hybridization time may be critical in improving the accuracy of microarray data.

DNA, Complementary↗

Permutation-validated principal components analysis of microarray data.

BACKGROUND: In microarray data analysis, the comparison of gene-expression profiles with respect to different conditions and the selection of biologically interesting genes are crucial tasks. Multivariate statistical methods have been applied to analyze these large datasets. Less work has been published concerning the assessment of the reliability of gene-selection procedures. Here we describe a method to assess reliability in multivariate microarray data analysis using permutation-validated principal components analysis (PCA). The approach is designed for microarray data with a group structure. RESULTS: We used PCA to detect the major sources of variance underlying the hybridization conditions followed by gene selection based on PCA-derived and permutation-based test statistics. We validated our method by applying it to well characterized yeast cell-cycle data and to two datasets from our laboratory. We could describe the major sources of variance, select informative genes and visualize the relationship of genes and arrays. We observed differences in the level of the explained variance and the interpretability of the selected genes. CONCLUSIONS: Combining data visualization and permutation-based gene selection, permutation-validated PCA enables one to illustrate gene-expression variance between several conditions and to select genes by taking into account the relationship of between-group to within-group variance of genes. The method can be used to extract the leading sources of variance from microarray data, to visualize relationships between genes and hybridizations and to select informative genes in a statistically reliable manner. This selection accounts for the level of reproducibility of replicates or group structure as well as gene-specific scatter. Visualization of the data can support a straightforward biological interpretation.

Animals↗

Assessing unmodified 70-mer oligonucleotide probe performance on glass-slide microarrays.

BACKGROUND: Long oligonucleotide microarrays are potentially more cost- and management-efficient than cDNA microarrays, but there is little information on the relative performance of these two probe types. The feasibility of using unmodified oligonucleotides to accurately measure changes in gene expression is also unclear. RESULTS: Unmodified sense and antisense 70-mer oligonucleotides representing 75 known rat genes and 10 Arabidopsis control genes were synthesized, printed and UV cross-linked onto glass slides. Printed alongside were PCR-amplified cDNA clones corresponding to the same genes, enabling us to compare the two probe types simultaneously. Our study was designed to evaluate the mRNA profiles of heart and brain, along with Arabidopsis cRNA spiked into the labeling reaction at different relative copy number. Hybridization signal intensity did not correlate with probe type but depended on the extent of UV irradiation. To determine the effect of oligonucleotide concentration on hybridization signal, 70-mers were serially diluted. No significant change in gene-expression ratio or loss in hybridization signal was detected, even at the lowest concentration tested (6.25 microm). In many instances, signal intensity actually increased with decreasing concentration. The correlation coefficient between oligonucleotide and cDNA probes for identifying differentially expressed genes was 0.80, with an average coefficient of variation of 13.4%. Approximately 8% of the genes showed discordant results with the two probe types, and in each case the cDNA results were more accurate, as determined by real-time PCR. CONCLUSIONS: Microarrays of UV cross-linked unmodified oligonucleotides provided sensitive and specific measurements for most of the genes studied.

Arabidopsis↗

Statistical tests for differential expression in cDNA microarray experiments.

Extracting biological information from microarray data requires appropriate statistical methods. The simplest statistical method for detecting differential expression is the t test, which can be used to compare two conditions when there is replication of samples. With more than two conditions, analysis of variance (ANOVA) can be used, and the mixed ANOVA model is a general and powerful approach for microarray experiments with multiple factors and/or several sources of variation.

Analysis of Variance↗

POSaM: a fast, flexible, open-source, inkjet oligonucleotide synthesizer and microarrayer.

DNA arrays are valuable tools in molecular biology laboratories. Their rapid acceptance was aided by the release of plans for a pin-spotting microarrayer by researchers at Stanford. Inkjet microarraying is a flexible, complementary technique that allows the synthesis of arrays of any oligonucleotide sequences de novo. We describe here an open-source inkjet arrayer capable of rapidly producing sets of unique 9,800-feature arrays.

DNA, Fungal↗

Transcript copy number estimation using a mouse whole-genome oligonucleotide microarray.

The ability to quantitatively measure the expression of all genes in a given tissue or cell with a single assay is an exciting promise of gene-expression profiling technology. An in situ-synthesized 60-mer oligonucleotide microarray designed to detect transcripts from all mouse genes was validated, as well as a set of exogenous RNA controls derived from the yeast genome (made freely available without restriction), which allow quantitative estimation of absolute endogenous transcript abundance.

Animals↗

Tumor reversion: protein kinase A isozyme switching.

The regulatory subunit of cAMP-dependent protein kinase (PKA) exists in the isoforms RI and RII, which distinguish PKA isozymes type I (PKA-I) and type II (PKA-II). Evidence obtained from different experimental approaches-such as site-selective cAMP analogs, antisense oligonucleotides, transcription factor decoys, cDNA microarrays, and gene transfer-has shown that PKA-I and -II are expressed in a balance of cell growth and differentiation. Loss of this balance may underlie cancer genesis and progression. DNA microarrays demonstrate that antisense suppression of the RIalpha, which upregulates RIIbeta, downregulates a wide range of genes involved in cell proliferation and transformation while upregulating cell differentiation and reverse transformation genes in PC3M prostate tumors that undergo regression. Conversely, the vector-mediated overexpression of RIIbeta, as opposed to those of RIalpha and Calpha, exhibits induction of differentiation genes along with suppression of cell proliferation and transformation genes leading to reversion of tumor phenotype. Thus, switching of PKA isozyme can cause tumor cells to undergo phenotypic reversion of the malignancy.

8-Bromo Cyclic Adenosine Monophosphate↗

Combining gene expression profiles and clinical parameters for risk stratification in medulloblastomas.

PURPOSE: Stratification of risk in patients with medulloblastoma remains a challenge. As clinical parameters have been proven insufficient for accurately defining disease risk, molecular markers have become the focus of interest. Outcome predictions on the basis of microarray gene expression profiles have been the most accurate to date. We ask in a multivariate model whether clinical parameters enhance survival predictions of gene expression profiles. PATIENTS AND METHODS: In a cohort of 55 young patients (whose medulloblastoma samples have been analyzed previously for gene expression profile), associations between clinical and gene expression variables and survival were assessed using Cox proportional hazards models. Available clinical variables included age, stage (ie, the presence of disseminated disease at diagnosis), sex, histologic subtype, treatment, and status. RESULTS: Univariate analysis demonstrated expression profiles to be the only significant clinical prognostic factor (P=.03). In multivariate analysis, gene expression profiles predicted outcome independent of other criteria. Clinical criteria did not significantly contribute additional information for outcome predictions, although an exploratory analysis noted a trend for decreased survival of patients with metastases at diagnosis but favorable gene expression profile. CONCLUSION: Gene expression profiling predicts medulloblastoma outcome independent of clinical variables. These results need to be validated in a larger prospective study.

Adolescent↗

Pharmacogenomic responses of rat liver to methylprednisolone: an approach to mining a rich microarray time series.

A data set was generated to examine global changes in gene expression in rat liver over time in response to a single bolus dose of methylprednisolone. Four control animals and 43 drug-treated animals were humanely killed at 16 different time points following drug administration. Total RNA preparations from the livers of these animals were hybridized to 47 individual Affymetrix RU34A gene chips, generating data for 8799 different probe sets for each chip. Data mining techniques that are applicable to gene array time series data sets in order to identify drug-regulated changes in gene expression were applied to this data set. A series of 4 sequentially applied filters were developed that were designed to eliminate probe sets that were not expressed in the tissue, were not regulated by the drug treatment, or did not meet defined quality control standards. These filters eliminated 7287 probe sets of the 8799 total (82%) from further consideration. Application of judiciously chosen filters is an effective tool for data mining of time series data sets. The remaining data can then be further analyzed by clustering and mathematical modeling techniques.

Adrenalectomy↗

Gene expression profile of adipocyte differentiation and its regulation by peroxisome proliferator-activated receptor-gamma agonists.

PPAR gamma is an adipocyte-specific nuclear hormone receptor. Agonists of PPAR gamma, such as thiazolidinediones (TZDs), promote adipocyte differentiation and have insulin-sensitizing effects in animals and diabetic patients. Affymetrix oligonucleotide arrays representing 6347 genes were employed to profile the gene expression responses of mature 3T3-L1 adipocytes and differentiating preadipocytes to a TZD PPAR gamma agonist in vitro. The expression of 579 genes was significantly up- or down-regulated by more than 1.5-fold during differentiation and/or by treatment with TZD, and these genes were organized into 32 clusters that demonstrated concerted changes in expression of genes controlling cell growth or lipid metabolism. Quantitative PCR was employed to further characterize gene expression and led to the identification of beta-catenin as a new PPAR gamma target gene. Both mRNA and protein levels for beta-catenin were down-regulated in 3T3-L1 adipocytes compared with fibroblasts and were further decreased by treatment of adipocytes with PPAR gamma agonists. Treatment of db/db mice with a PPAR gamma agonist also resulted in reduction of beta-catenin mRNA levels in adipose tissue. These results suggest that beta-catenin plays an important role in the regulation of adipogenesis. Thus, the transcriptional patterns revealed in this study further the understanding of adipogenesis process and the function of PPAR gamma activation.

3T3 Cells↗

Gene expression profiles of mouse submandibular gland development: FGFR1 regulates branching morphogenesis in vitro through BMP- and FGF-dependent mechanisms.

Analyses of gene expression profiles at five different stages of mouse submandibular salivary gland development provide insight into gland organogenesis and identify genes that may be critical at different stages. Genes with similar expression profiles were clustered, and RT-PCR was used to confirm the developmental changes. We focused on fibroblast growth factor receptor 1 (FGFR1), as its expression is highest early in gland development. We extended our array results and analyzed the developmental expression patterns of other FGFR and FGF isoforms. The functional significance of FGFR1 was confirmed by submandibular gland organ culture. Antisense oligonucleotides decreased expression of FGFR1 and reduced branching morphogenesis of the glands. Inhibiting FGFR1 signaling with SU5402, a FGFR1 tyrosine kinase inhibitor, reduced branching morphogenesis. SU5402 treatment decreased cell proliferation but did not increase apoptosis. Fgfr, Fgf and Bmp gene expression was localized to either the mesenchyme or the epithelium by PCR, and then measured over time by real time PCR after SU5402 treatment. FGFR1 signaling regulates Fgfr1, Fgf1, Fgf3 and Bmp7 expression and indirectly regulates Fgf7, Fgf10 and Bmp4. Exogenous FGFs and BMPs added to glands in culture reveal distinct effects on gland morphology. Glands cultured with SU5402 were then rescued with exogenous BMP7, FGF7 or FGF10. Taken together, our results suggest specific FGFs and BMPs play reciprocal roles in regulating branching morphogenesis and FGFR1 signaling plays a central role by regulating both FGF and BMP expression.

Animals↗

Wnt/beta-catenin regulation of the Sp1-related transcription factor sp5l promotes tail development in zebrafish.

Tail formation in vertebrates involves the specification of a population of multipotent precursors, the tailbud, which will give rise to all of the posterior structures of the embryo. Wnts are signaling proteins that are candidates for promoting tail outgrowth in zebrafish, although which Wnts are involved, what genes they regulate, and whether Wnts are required for initiation or maintenance steps in tail formation has not been resolved. We show here that both wnt3a and wnt8 are expressed in the zebrafish tailbud and that simultaneous inhibition of both wnt3a and wnt8 using morpholino oligonucleotides can completely block tail formation. In embryos injected with wnt3a and wnt8 morpholinos, expression of genes in undifferentiated presomitic mesoderm is initiated, but not maintained. To identify genes that might function downstream of Wnts in tail formation, a DNA microarray screen was conducted, revealing that sp5l, a member of the Sp1 family of zinc-finger transcription factors, is activated by Wnt signaling. Moreover, we show that sp5l expression in the developing tail is dependent on both wnt3a and wnt8 function. Supporting a role for sp5l in tail formation, we find that inhibition of sp5l strongly enhances the effects of wnt3a inhibition, and overexpression of sp5l RNA is able to completely restore normal tail development in wnt3a morphants. These data place sp5l downstream of wnt3a and wnt8 in a Wnt/beta-catenin signaling pathway that controls tail development in zebrafish.

Animals↗