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Sample records for oligonucleotide microarray analysis

  1. Design and analysis of mismatch probes for long oligonucleotide microarrays

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    Deng, Ye; He, Zhili; Van Nostrand, Joy D.; Zhou, Jizhong

    2008-08-15

    Nonspecific hybridization is currently a major concern with microarray technology. One of most effective approaches to estimating nonspecific hybridizations in oligonucleotide microarrays is the utilization of mismatch probes; however, this approach has not been used for longer oligonucleotide probes. Here, an oligonucleotide microarray was constructed to evaluate and optimize parameters for 50-mer mismatch probe design. A perfect match (PM) and 28 mismatch (MM) probes were designed for each of ten target genes selected from three microorganisms. The microarrays were hybridized with synthesized complementary oligonucleotide targets at different temperatures (e.g., 42, 45 and 50 C). In general, the probes with evenly distributed mismatches were more distinguishable than those with randomly distributed mismatches. MM probes with 3, 4 and 5 mismatched nucleotides were differentiated for 50-mer oligonucleotide probes hybridized at 50, 45 and 42 C, respectively. Based on the experimental data generated from this study, a modified positional dependent nearest neighbor (MPDNN) model was constructed to adjust the thermodynamic parameters of matched and mismatched dimer nucleotides in the microarray environment. The MM probes with four flexible positional mismatches were designed using the newly established MPDNN model and the experimental results demonstrated that the redesigned MM probes could yield more consistent hybridizations. Conclusions: This study provides guidance on the design of MM probes for long oligonucleotides (e.g., 50 mers). The novel MPDNN model has improved the consistency for long MM probes, and this modeling method can potentially be used for the prediction of oligonucleotide microarray hybridizations.

  2. Design and analysis of mismatch probes for long oligonucleotide microarrays

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    Deng, Ye; He, Zhili; Van Nostrand, Joy D.; Zhou, Jizhong

    2008-08-15

    Nonspecific hybridization is currently a major concern with microarray technology. One of most effective approaches to estimating nonspecific hybridizations in oligonucleotide microarrays is the utilization of mismatch probes; however, this approach has not been used for longer oligonucleotide probes. Here, an oligonucleotide microarray was constructed to evaluate and optimize parameters for 50-mer mismatch probe design. A perfect match (PM) and 28 mismatch (MM) probes were designed for each of ten target genes selected from three microorganisms. The microarrays were hybridized with synthesized complementary oligonucleotide targets at different temperatures (e.g., 42, 45 and 50 C). In general, the probes with evenly distributed mismatches were more distinguishable than those with randomly distributed mismatches. MM probes with 3, 4 and 5 mismatched nucleotides were differentiated for 50-mer oligonucleotide probes hybridized at 50, 45 and 42 C, respectively. Based on the experimental data generated from this study, a modified positional dependent nearest neighbor (MPDNN) model was constructed to adjust the thermodynamic parameters of matched and mismatched dimer nucleotides in the microarray environment. The MM probes with four flexible positional mismatches were designed using the newly established MPDNN model and the experimental results demonstrated that the redesigned MM probes could yield more consistent hybridizations. Conclusions: This study provides guidance on the design of MM probes for long oligonucleotides (e.g., 50 mers). The novel MPDNN model has improved the consistency for long MM probes, and this modeling method can potentially be used for the prediction of oligonucleotide microarray hybridizations.

  3. Experimental analysis of oligonucleotide microarray design criteria to detect deletions by comparative genomic hybridization

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    Moerman Donald G

    2008-10-01

    quality when varying the oligonucleotide length between 50 and 70, and even when using an isothermal design strategy. Conclusion We have determined experimentally the effects of varying several key oligonucleotide microarray design criteria for detection of deletions in C. elegans and humans with NimbleGen's CGH technology. Our oligonucleotide design recommendations should be applicable for CGH analysis in most species.

  4. An imputation approach for oligonucleotide microarrays.

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    Ming Li

    Full Text Available Oligonucleotide microarrays are commonly adopted for detecting and qualifying the abundance of molecules in biological samples. Analysis of microarray data starts with recording and interpreting hybridization signals from CEL images. However, many CEL images may be blemished by noises from various sources, observed as "bright spots", "dark clouds", and "shadowy circles", etc. It is crucial that these image defects are correctly identified and properly processed. Existing approaches mainly focus on detecting defect areas and removing affected intensities. In this article, we propose to use a mixed effect model for imputing the affected intensities. The proposed imputation procedure is a single-array-based approach which does not require any biological replicate or between-array normalization. We further examine its performance by using Affymetrix high-density SNP arrays. The results show that this imputation procedure significantly reduces genotyping error rates. We also discuss the necessary adjustments for its potential extension to other oligonucleotide microarrays, such as gene expression profiling. The R source code for the implementation of approach is freely available upon request.

  5. Analysis of gene expression profiles in human systemic lupus erythematosus using oligonucleotide microarray.

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    Han, G-M; Chen, S-L; Shen, N; Ye, S; Bao, C-D; Gu, Y-Y

    2003-04-01

    Epidemiologic studies suggest a strong genetic component for susceptibility to systemic lupus erythematosus (SLE). To investigate the genetic mechanism of pathogenesis of SLE, we studied the difference in gene expression of peripheral blood cells between 10 SLE patients and 18 healthy controls using oligonucleotide microarray. When gene expression for patients was compared to the mean of normal controls, among the 3002 target genes, 61 genes were identified with greater than a two-fold change difference in expression level. Of these genes, 24 were upregulated and 37 downregulated in at least half of the patients. By the Welch's ANOVA/Welch's t-test, all these 61 genes were significantly different (PTSA-1/Sca-2) may play an important role in the mechanism of SLE pathogenesis. TSA-1 antigens may represent an important alternative pathway for T-cell activation that may be involved in IFN-mediated immunomodulation. Hierarchical clustering showed that patient samples were clearly separated from controls based on their gene expression profile. These results demonstrate that high-density oligonucleotide microarray has the potential to explore the mechanism of pathogenesis of systemic lupus erythematosus.

  6. Hybridization kinetics analysis of an oligonucleotide microarray for microRNA detection

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    Botao Zhao; Shuo Ding; Wei Li; Youxin Jin

    2011-01-01

    MicroRNA (miRNA) microarrays have been successfully used for profiling miRNA expression in many physiological processes such as development, differentiation, oncogenesis,and other disease processes. Detecting miRNA by miRNA microarray is actually based on nucleic acid hybridization between target molecules and their corresponding complementary probes. Due to the small size and high degree of similarity among miRNA sequences, the hybridization condition must be carefully optimized to get specific and reliable signals. Previously, we reported a microarray platform to detect miRNA expression. In this study, we evaluated the sensitivity and specificity of our microarray platform. After systematic analysis, we determined an optimized hybridization condition with high sensitivity and specificity for miRNA detection. Our results would be helpful for other hybridization-based miRNA detection methods, such as northern blot and nuclease protection assay.

  7. Optimization of RNA Isolation from the Archaebacterium Methanosarcina Barkeri and Validation for Oligonucleotide Microarray Analysis

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    Culley, David E.; Kovacik, William P.; Brockman, Fred J.; Zhang, Weiwen

    2006-10-01

    ABSTRACT-The recent completion of a draft genome sequence for Methanosarcina barkeri has allowed the application of various high throughput post-genomics technologies, such as nucleic acid microarrays and mass spectrometry of proteins to detect global changes in transcription and translation that occur in response to experimental treatments...

  8. [mRNA expression analysis and classification of colonic biopsy samples using oligonucleotide and cDNA microarray techniques].

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    Galamb, Orsolya

    2008-07-20

    Despite tremendous progress in the past few decades, certain important aspects regarding the diagnosis, therapy, and follow-up of colorectal cancer still remain unsolved. In our work we searched for biomarkers of the development of colorectal carcinoma, and performed gene expression analysis for colorectal disease classification. We have established that the oligonucleotide microarray analyses of biopsy samples wholly fulfil the Affymetrix quality requirements, are highly standard and reproducible and the Taqman microfluidic card system is suitable for high-throughput, quick and cost efficient real-time-PCR validation of gene expression changes. We have shown that the sequential overexpression of osteopontin and osteonectin mRNAs and proteins significantly correlates with the progression of the colorectal adenoma-dysplasia-carcinoma sequence. We have identified and validated ten novel markers with continuously increasing mRNA expression in line with the adenoma-dysplasia-carcinoma transition. We have identified the top 27, 13 and 10 genes associated with adenoma, colorectal cancer, and inflammatory bowel diseases.

  9. Comparative genomic analysis of Acidithiobacillus ferrooxidans strains using the A. ferrooxidans ATCC 23270 whole-genome oligonucleotide microarray.

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    Luo, Hailang; Shen, Li; Yin, Huaqun; Li, Qian; Chen, Qijiong; Luo, Yanjie; Liao, Liqin; Qiu, Guanzhou; Liu, Xueduan

    2009-05-01

    Acidithiobacillus ferrooxidans is an important microorganism used in biomining operations for metal recovery. Whole-genomic diversity analysis based on the oligonucleotide microarray was used to analyze the gene content of 12 strains of A. ferrooxidans purified from various mining areas in China. Among the 3100 open reading frames (ORFs) on the slides, 1235 ORFs were absent in at least 1 strain of bacteria and 1385 ORFs were conserved in all strains. The hybridization results showed that these strains were highly diverse from a genomic perspective. The hybridization results of 4 major functional gene categories, namely electron transport, carbon metabolism, extracellular polysaccharides, and detoxification, were analyzed. Based on the hybridization signals obtained, a phylogenetic tree was built to analyze the evolution of the 12 tested strains, which indicated that the geographic distribution was the main factor influencing the strain diversity of these strains. Based on the hybridization signals of genes associated with bioleaching, another phylogenetic tree showed an evolutionary relationship from which the co-relation between the clustering of specific genes and geochemistry could be observed. The results revealed that the main factor was geochemistry, among which the following 6 factors were the most important: pH, Mg, Cu, S, Fe, and Al.

  10. Sex determination of bovine preimplantation embryos by oligonucleotide microarray.

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    Yang, Hua; Zhong, Fagang; Yang, Yonglin; Wang, Xinhua; Liu, Shouren; Zhu, Bin

    2013-06-01

    The aim has been to set up a rapid and accurate microarray assay using sandwich mode for sex determination of bovine preimplantation embryos. Twelve sequence-specific oligonucleotide capture probes used to discriminate 12 samples were spotted onto the aldehyde-modified glass slides by Arrayer. The 2 recognition probes used to identify coding regions of the sex-determining region of the Y chromosome gene (SRY) and β-casein (CSN2) reference gene were coupled with biotin. The assay was optimized by using genomic DNA extracted from blood samples of known sex individuals. Polymerase chain reaction (PCR) was used to amplify the fragments in the HMG box region of SRY gene and CSN2 gene with sequence-specific primers. The sex of samples was identified by detecting both the SRY and CSN2 genes simultaneously in 2 reaction cells of microarrays, with the male having SRY and CSN2 signals and the female only CSN2. The sex of 20 bovine preimplantation embryos was determined by oligonucleotide microarray. The protocol was run with a blind test that showed a 100% (82/82) specificity and accuracy in sexing of leukocytes. The bovine embryos were transferred into 20 bovine recipients, with a pregnant rate of 40% (8/20). Three calves were born at term, and 5 fetuses were miscarried. Their sexes were fully in accordance with the embryonic sex predetermination predicted by oligonucleotide microarray. This suggests that the oligonucleotide microarray method of SRY gene analysis can be used in early sex prediction of bovine embryos in breeding programs.

  11. Analysis of baseline and cisplatin-inducible gene expression in Fanconi anemia cells using oligonucleotide-based microarrays

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    Liu Johnson M

    2002-11-01

    Full Text Available Abstract Background Patients with Fanconi anemia (FA suffer from multiple defects, most notably of the hematological compartment (bone marrow failure, and susceptibility to cancer. Cells from FA patients show increased spontaneous chromosomal damage, which is aggravated by exposure to low concentrations of DNA cross-linking agents such as mitomycin C or cisplatin. Five of the identified FA proteins form a nuclear core complex. However, the molecular function of these proteins remains obscure. Methods Oligonucleotide microarrays were used to compare the expression of approximately 12,000 genes from FA cells with matched controls. Expression profiles were studied in lymphoblastoid cell lines derived from three different FA patients, one from the FA-A and two from the FA-C complementation groups. The isogenic control cell lines were obtained by either transfecting the cells with vectors expressing the complementing cDNAs or by using a spontaneous revertant cell line derived from the same patient. In addition, we analyzed expression profiles from two cell line couples at several time points after a 1-hour pulse treatment with a discriminating dose of cisplatin. Results Analysis of the expression profiles showed differences in expression of a number of genes, many of which have unknown function or are difficult to relate to the FA defect. However, from a selected number of proteins involved in cell cycle regulation, DNA repair and chromatin structure, Western blot analysis showed that p21waf1/Cip1 was significantly upregulated after low dose cisplatin treatment in FA cells specifically (as well as being expressed at elevated levels in untreated FA cells. Conclusions The observed increase in expression of p21waf1/Cip1 after treatment of FA cells with crosslinkers suggests that the sustained elevated levels of p21waf1/Cip1 in untreated FA cells detected by Western blot analysis likely reflect increased spontaneous damage in these cells.

  12. Oligonucleotide microarray analysis of dietary-induced hyperlipidemia gene expression profiles in miniature pigs.

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    Junko Takahashi

    Full Text Available BACKGROUND: Hyperlipidemia animal models have been established, but complete gene expression profiles of the transition from normal lipid levels have not been obtained. Miniature pigs are useful model animals for gene expression studies on dietary-induced hyperlipidemia because they have a similar anatomy and digestive physiology to humans, and blood samples can be obtained from them repeatedly. METHODOLOGY: Two typical dietary treatments were used for dietary-induced hyperlipidemia models, by using specific pathogen-free (SPF Clawn miniature pigs. One was a high-fat and high-cholesterol diet (HFCD and the other was a high-fat, high-cholesterol, and high-sucrose diet (HFCSD. Microarray analyses were conducted from whole blood samples during the dietary period and from white blood cells at the end of the dietary period to evaluate the transition of expression profiles of the two dietary models. PRINCIPAL FINDINGS: Variations in whole blood gene expression intensity within the HFCD or the HFCSD group were in the same range as the controls provide with normal diet at all periods. This indicates uniformity of dietary-induced hyperlipidemia for our dietary protocols. Gene ontology- (GO based functional analyses revealed that characteristics of the common changes between HFCD and HFCSD were involved in inflammatory responses and reproduction. The correlation coefficient between whole blood and white blood cell expression profiles at 27 weeks with the HFCSD diet was significantly lower than that of the control and HFCD diet groups. This may be due to the effects of RNA originating from the tissues and/or organs. CONCLUSIONS: No statistically significant differences in fasting plasma lipids and glucose levels between the HFCD and HFCSD groups were observed. However, blood RNA analyses revealed different characteristics corresponding to the dietary protocols. In this study, whole blood RNA analyses proved to be a useful tool to evaluate transitions in

  13. Cassava (Manihot esculenta) transcriptome analysis in response to infection by the fungus Colletotrichum gloeosporioides using an oligonucleotide-DNA microarray.

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    Utsumi, Yoshinori; Tanaka, Maho; Kurotani, Atsushi; Yoshida, Takuhiro; Mochida, Keiichi; Matsui, Akihiro; Ishitani, Manabu; Sraphet, Supajit; Whankaew, Sukhuman; Asvarak, Thipa; Narangajavana, Jarunya; Triwitayakorn, Kanokporn; Sakurai, Tetsuya; Seki, Motoaki

    2016-07-01

    Cassava anthracnose disease (CAD), caused by the fungus Colletotrichum gloeosporioides f. sp. Manihotis, is a serious disease of cassava (Manihot esculenta) worldwide. In this study, we established a cassava oligonucleotide-DNA microarray representing 59,079 probes corresponding to approximately 30,000 genes based on original expressed sequence tags and RNA-seq information from cassava, and applied it to investigate the molecular mechanisms of resistance to fungal infection using two cassava cultivars, Huay Bong 60 (HB60, resistant to CAD) and Hanatee (HN, sensitive to CAD). Based on quantitative real-time reverse transcription PCR and expression profiling by the microarray, we showed that the expressions of various plant defense-related genes, such as pathogenesis-related (PR) genes, cell wall-related genes, detoxification enzyme, genes related to the response to bacterium, mitogen-activated protein kinase (MAPK), genes related to salicylic acid, jasmonic acid and ethylene pathways were higher in HB60 compared with HN. Our results indicated that the induction of PR genes in HB60 by fungal infection and the higher expressions of defense response-related genes in HB60 compared with HN are likely responsible for the fungal resistance in HB60. We also showed that the use of our cassava oligo microarray could improve our understanding of cassava molecular mechanisms related to environmental responses and development, and advance the molecular breeding of useful cassava plants.

  14. Oligonucleotide microarray analysis reveals dysregulation of energy-related metabolism in insulin-sensitive tissues of type 2 diabetes patients.

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    Wang, M; Wang, X C; Zhao, L; Zhang, Y; Yao, L L; Lin, Y; Peng, Y D; Hu, R M

    2014-06-17

    Impaired insulin action within skeletal muscle, adipose tissue, and the liver is an important characteristic of type 2 diabetes (T2D). In order to identify common underlying defects in insulin-sensitive tissues that may be involved in the pathogenesis of T2D, the gene expression profiles of skeletal muscle, visceral adipose tissue, and liver from autopsy donors with or without T2D were examined using oligonucleotide microarrays and quantitative reverse transcriptase-PCR. Compared with controls, 691 genes were commonly dysregulated in these three insulin-sensitive tissues of humans with T2D. These co-expressed genes were enriched within the mitochondrion, with suggested involvement in energy metabolic processes such as glycolysis and gluconeogenesis, fatty acid beta oxidative, tricarboxylic acid cycle, and electron transport. Genes related to energy metabolism were mostly downregulated in diabetic skeletal muscle and visceral adipose tissue, while they were upregulated in the diabetic liver. This observed dysregulation in energy-related metabolism may be the underlying factor leading to the molecular mechanisms responsible for the insulin resistance of patients with T2D.

  15. Particle-Based Microarrays of Oligonucleotides and Oligopeptides.

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    Nesterov-Mueller, Alexander; Maerkle, Frieder; Hahn, Lothar; Foertsch, Tobias; Schillo, Sebastian; Bykovskaya, Valentina; Sedlmayr, Martyna; Weber, Laura K; Ridder, Barbara; Soehindrijo, Miriam; Muenster, Bastian; Striffler, Jakob; Bischoff, F Ralf; Breitling, Frank; Loeffler, Felix F

    2014-10-28

    In this review, we describe different methods of microarray fabrication based on the use of micro-particles/-beads and point out future tendencies in the development of particle-based arrays. First, we consider oligonucleotide bead arrays, where each bead is a carrier of one specific sequence of oligonucleotides. This bead-based array approach, appearing in the late 1990s, enabled high-throughput oligonucleotide analysis and had a large impact on genome research. Furthermore, we consider particle-based peptide array fabrication using combinatorial chemistry. In this approach, particles can directly participate in both the synthesis and the transfer of synthesized combinatorial molecules to a substrate. Subsequently, we describe in more detail the synthesis of peptide arrays with amino acid polymer particles, which imbed the amino acids inside their polymer matrix. By heating these particles, the polymer matrix is transformed into a highly viscous gel, and thereby, imbedded monomers are allowed to participate in the coupling reaction. Finally, we focus on combinatorial laser fusing of particles for the synthesis of high-density peptide arrays. This method combines the advantages of particles and combinatorial lithographic approaches.

  16. Particle-Based Microarrays of Oligonucleotides and Oligopeptides

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    Alexander Nesterov-Mueller

    2014-10-01

    Full Text Available In this review, we describe different methods of microarray fabrication based on the use of micro-particles/-beads and point out future tendencies in the development of particle-based arrays. First, we consider oligonucleotide bead arrays, where each bead is a carrier of one specific sequence of oligonucleotides. This bead-based array approach, appearing in the late 1990s, enabled high-throughput oligonucleotide analysis and had a large impact on genome research. Furthermore, we consider particle-based peptide array fabrication using combinatorial chemistry. In this approach, particles can directly participate in both the synthesis and the transfer of synthesized combinatorial molecules to a substrate. Subsequently, we describe in more detail the synthesis of peptide arrays with amino acid polymer particles, which imbed the amino acids inside their polymer matrix. By heating these particles, the polymer matrix is transformed into a highly viscous gel, and thereby, imbedded monomers are allowed to participate in the coupling reaction. Finally, we focus on combinatorial laser fusing of particles for the synthesis of high-density peptide arrays. This method combines the advantages of particles and combinatorial lithographic approaches.

  17. A review of statistical methods for preprocessing oligonucleotide microarrays.

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    Wu, Zhijin

    2009-12-01

    Microarrays have become an indispensable tool in biomedical research. This powerful technology not only makes it possible to quantify a large number of nucleic acid molecules simultaneously, but also produces data with many sources of noise. A number of preprocessing steps are therefore necessary to convert the raw data, usually in the form of hybridisation images, to measures of biological meaning that can be used in further statistical analysis. Preprocessing of oligonucleotide arrays includes image processing, background adjustment, data normalisation/transformation and sometimes summarisation when multiple probes are used to target one genomic unit. In this article, we review the issues encountered in each preprocessing step and introduce the statistical models and methods in preprocessing.

  18. Design of oligonucleotides for microarrays and perspectives for design of multi-transcriptome arrays

    DEFF Research Database (Denmark)

    Nielsen, Henrik Bjørn; Wernersson, Rasmus; Knudsen, Steen

    2003-01-01

    Optimal design of oligonucleotides for microarrays involves tedious and laborious work evaluating potential oligonucleotides relative to a series of parameters. The currently available tools for this purpose are limited in their flexibility and do not present the oligonucleotide designer with an ......Optimal design of oligonucleotides for microarrays involves tedious and laborious work evaluating potential oligonucleotides relative to a series of parameters. The currently available tools for this purpose are limited in their flexibility and do not present the oligonucleotide designer...

  19. Development, characterization and experimental validation of a cultivated sunflower (Helianthus annuus L. gene expression oligonucleotide microarray.

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    Paula Fernandez

    Full Text Available Oligonucleotide-based microarrays with accurate gene coverage represent a key strategy for transcriptional studies in orphan species such as sunflower, H. annuus L., which lacks full genome sequences. The goal of this study was the development and functional annotation of a comprehensive sunflower unigene collection and the design and validation of a custom sunflower oligonucleotide-based microarray. A large scale EST (>130,000 ESTs curation, assembly and sequence annotation was performed using Blast2GO (www.blast2go.de. The EST assembly comprises 41,013 putative transcripts (12,924 contigs and 28,089 singletons. The resulting Sunflower Unigen Resource (SUR version 1.0 was used to design an oligonucleotide-based Agilent microarray for cultivated sunflower. This microarray includes a total of 42,326 features: 1,417 Agilent controls, 74 control probes for sunflower replicated 10 times (740 controls and 40,169 different non-control probes. Microarray performance was validated using a model experiment examining the induction of senescence by water deficit. Pre-processing and differential expression analysis of Agilent microarrays was performed using the Bioconductor limma package. The analyses based on p-values calculated by eBayes (p<0.01 allowed the detection of 558 differentially expressed genes between water stress and control conditions; from these, ten genes were further validated by qPCR. Over-represented ontologies were identified using FatiScan in the Babelomics suite. This work generated a curated and trustable sunflower unigene collection, and a custom, validated sunflower oligonucleotide-based microarray using Agilent technology. Both the curated unigene collection and the validated oligonucleotide microarray provide key resources for sunflower genome analysis, transcriptional studies, and molecular breeding for crop improvement.

  20. Development, characterization and experimental validation of a cultivated sunflower (Helianthus annuus L.) gene expression oligonucleotide microarray.

    Science.gov (United States)

    Fernandez, Paula; Soria, Marcelo; Blesa, David; DiRienzo, Julio; Moschen, Sebastian; Rivarola, Maximo; Clavijo, Bernardo Jose; Gonzalez, Sergio; Peluffo, Lucila; Príncipi, Dario; Dosio, Guillermo; Aguirrezabal, Luis; García-García, Francisco; Conesa, Ana; Hopp, Esteban; Dopazo, Joaquín; Heinz, Ruth Amelia; Paniego, Norma

    2012-01-01

    Oligonucleotide-based microarrays with accurate gene coverage represent a key strategy for transcriptional studies in orphan species such as sunflower, H. annuus L., which lacks full genome sequences. The goal of this study was the development and functional annotation of a comprehensive sunflower unigene collection and the design and validation of a custom sunflower oligonucleotide-based microarray. A large scale EST (>130,000 ESTs) curation, assembly and sequence annotation was performed using Blast2GO (www.blast2go.de). The EST assembly comprises 41,013 putative transcripts (12,924 contigs and 28,089 singletons). The resulting Sunflower Unigen Resource (SUR version 1.0) was used to design an oligonucleotide-based Agilent microarray for cultivated sunflower. This microarray includes a total of 42,326 features: 1,417 Agilent controls, 74 control probes for sunflower replicated 10 times (740 controls) and 40,169 different non-control probes. Microarray performance was validated using a model experiment examining the induction of senescence by water deficit. Pre-processing and differential expression analysis of Agilent microarrays was performed using the Bioconductor limma package. The analyses based on p-values calculated by eBayes (p<0.01) allowed the detection of 558 differentially expressed genes between water stress and control conditions; from these, ten genes were further validated by qPCR. Over-represented ontologies were identified using FatiScan in the Babelomics suite. This work generated a curated and trustable sunflower unigene collection, and a custom, validated sunflower oligonucleotide-based microarray using Agilent technology. Both the curated unigene collection and the validated oligonucleotide microarray provide key resources for sunflower genome analysis, transcriptional studies, and molecular breeding for crop improvement.

  1. Expression profiling of gastric cancer samples by oligonucleotide microarray analysis reveals low degree of intra-tumor variability

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    Karolin Trautmann; Christine Steudel; Dana Grossmann; Daniela Aust; Gerhard Ehninger; Stephan Miehlke; Christian Thiede

    2005-01-01

    AIM: Gene expression profiling provides an unique opportunity to gain insight into the development of different types of gastric cancer. Tumor sample heterogeneity is thought to decrease the sensitivity and tumor specificity of microarray analysis. Thus, microdissection and preamplification of RNA is frequently performed. However, this technique may also induce considerable changes to the expression profile. To assess the effect of gastric tumor heterogeneity on expression profiling results, we measured the variation in gene expression within the same gastric cancer sample by performing a gene chip analysis with two RNA preparations extracted from the same tumor specimen.METHODS: Tumor samples from six intestinal T2 gastric tumors were dissected under liquid nitrogen and RNA was prepared from two separate tumor fragments. Each extraction was individually processed and hybridized to an Affymetrix U133A gene chip covering approximately 18 000 human gene transcripts. Expression profiles were analyzed using Microarray Suite 5.0 (Affymetrix) and GeneSpring 6.0 (Silicon Genetics).RESULTS: All gastric cancers showed little variance in expression profiles between different regions of the same tumor sample. In this case, gene chips displayed mean pair wise correlation coefficients of 0.94±0.02 (mean±SD),compared to values of 0.61±0.1 for different tumor samples. Expression of the variance between the two expression profiles as a percentage of "total change"(Affymetrix) revealed a remarkably low average value of 1.18±0.78 for comparing fragments of the same tumor sample.In contrast, comparison of fragments from different tumors revealed a percentage of 24.4±4.5.CONCLUSION: Our study indicates a low degree of expression profile variability within gastric tumor samples isolated from one patient. These data suggest that tumor tissue heterogeneity is not a dominant source of error for microarray analysis of larger tumor samples, making total RNA extraction an appropriate

  2. Empirical evaluation of oligonucleotide probe selection for DNA microarrays.

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    Jennifer G Mulle

    Full Text Available DNA-based microarrays are increasingly central to biomedical research. Selecting oligonucleotide sequences that will behave consistently across experiments is essential to the design, production and performance of DNA microarrays. Here our aim was to improve on probe design parameters by empirically and systematically evaluating probe performance in a multivariate context. We used experimental data from 19 array CGH hybridizations to assess the probe performance of 385,474 probes tiled in the Duchenne muscular dystrophy (DMD region of the X chromosome. Our results demonstrate that probe melting temperature, single nucleotide polymorphisms (SNPs, and homocytosine motifs all have a strong effect on probe behavior. These findings, when incorporated into future microarray probe selection algorithms, may improve microarray performance for a wide variety of applications.

  3. Empirical evaluation of oligonucleotide probe selection for DNA microarrays.

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    Mulle, Jennifer G; Patel, Viren C; Warren, Stephen T; Hegde, Madhuri R; Cutler, David J; Zwick, Michael E

    2010-03-29

    DNA-based microarrays are increasingly central to biomedical research. Selecting oligonucleotide sequences that will behave consistently across experiments is essential to the design, production and performance of DNA microarrays. Here our aim was to improve on probe design parameters by empirically and systematically evaluating probe performance in a multivariate context. We used experimental data from 19 array CGH hybridizations to assess the probe performance of 385,474 probes tiled in the Duchenne muscular dystrophy (DMD) region of the X chromosome. Our results demonstrate that probe melting temperature, single nucleotide polymorphisms (SNPs), and homocytosine motifs all have a strong effect on probe behavior. These findings, when incorporated into future microarray probe selection algorithms, may improve microarray performance for a wide variety of applications.

  4. Application of Oligonucleotide Microarrays for Bacterial Source Tracking of Environmental Enterococcus sp. Isolates

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    John S. Furey

    2005-04-01

    Full Text Available In an effort towards adapting new and defensible methods for assessing and managing the risk posed by microbial pollution, we evaluated the utility of oligonucleotide microarrays for bacterial source tracking (BST of environmental Enterococcus sp. isolates derived from various host sources. Current bacterial source tracking approaches rely on various phenotypic and genotypic methods to identify sources of bacterial contamination resulting from point or non-point pollution. For this study Enterococcus sp. isolates originating from deer, bovine, gull, and human sources were examined using microarrays. Isolates were subjected to Box PCR amplification and the resulting amplification products labeled with Cy5. Fluorescent-labeled templates were hybridized to in-house constructed nonamer oligonucleotide microarrays consisting of 198 probes. Microarray hybridization profiles were obtained using the ArrayPro image analysis software. Principal Components Analysis (PCA and Hierarchical Cluster Analysis (HCA were compared for their ability to visually cluster microarray hybridization profiles based on the environmental source from which the Enterococcus sp. isolates originated. The PCA was visually superior at separating origin-specific clusters, even for as few as 3 factors. A Soft Independent Modeling (SIM classification confirmed the PCA, resulting in zero misclassifications using 5 factors for each class. The implication of these results for the application of random oligonucleotide microarrays for BST is that, given the reproducibility issues, factor-based variable selection such as in PCA and SIM greatly outperforms dendrogram-based similarity measures such as in HCA and K-Nearest Neighbor KNN.

  5. Discrimination of bacillus anthracis and closely related microorganisms by analysis of 16S and 23S rRNA with oligonucleotide microarray.

    Energy Technology Data Exchange (ETDEWEB)

    Bavykin, S. G.; Mikhailovich, V. M.; Zakharyev, V. M.; Lysov, Y. P.; Kelly, J. J.; Alferov, O. S.; Jackman, J.; Stahl, D. A.; Mirzabekov, A. D.; Gavin, I. M.; Kukhtin, A. V.; Chandler, D. (Biochip Technology Center); (Engelhardt Inst. of Molecular Biology); (Northwestern Univ.); (Georgetown Univ.)

    2008-01-30

    Analysis of 16S rRNA sequences is a commonly used method for the identification and discrimination of microorganisms. However, the high similarity of 16S and 23S rRNA sequences of Bacillus cereus group organisms (up to 99-100%) and repeatedly failed attempts to develop molecular typing systems that would use DNA sequences to discriminate between species within this group have resulted in several suggestions to consider B. cereus and B. thuringiensis, or these two species together with B. anthracis, as one species. Recently, we divided the B. cereus group into seven subgroups, Anthracis, Cereus A and B, Thuringiensis A and B, and Mycoides A and B, based on 16S rRNA, 23S rRNA and gyrB gene sequences and identified subgroup-specific makers in each of these three genes. Here we for the first time demonstrated discrimination of these seven subgroups, including subgroup Anthracis, with a 3D gel element microarray of oligonucleotide probes targeting 16S and 23S rRNA markers. This is the first microarray enabled identification of B. anthracis and discrimination of these seven subgroups in pure cell cultures and in environmental samples using rRNA sequences. The microarray bearing perfect match/mismatch (p/mm) probe pairs was specific enough to discriminate single nucleotide polymorphisms (SNPs) and was able to identify targeted organisms in 5 min. We also demonstrated the ability of the microarray to determine subgroup affiliations for B. cereus group isolates without rRNA sequencing. Correlation of these seven subgroups with groupings based on multilocus sequence typing (MLST), fluorescent amplified fragment length polymorphism analysis (AFLP) and multilocus enzyme electrophoresis (MME) analysis of a wide spectrum of different genes, and the demonstration of subgroup-specific differences in toxin profiles, psychrotolerance, and the ability to harbor some plasmids, suggest that these seven subgroups are not based solely on neutral genomic polymorphisms, but instead reflect

  6. A novel multifunctional oligonucleotide microarray for Toxoplasma gondii

    Directory of Open Access Journals (Sweden)

    Chen Feng

    2010-10-01

    Full Text Available Abstract Background Microarrays are invaluable tools for genome interrogation, SNP detection, and expression analysis, among other applications. Such broad capabilities would be of value to many pathogen research communities, although the development and use of genome-scale microarrays is often a costly undertaking. Therefore, effective methods for reducing unnecessary probes while maintaining or expanding functionality would be relevant to many investigators. Results Taking advantage of available genome sequences and annotation for Toxoplasma gondii (a pathogenic parasite responsible for illness in immunocompromised individuals and Plasmodium falciparum (a related parasite responsible for severe human malaria, we designed a single oligonucleotide microarray capable of supporting a wide range of applications at relatively low cost, including genome-wide expression profiling for Toxoplasma, and single-nucleotide polymorphism (SNP-based genotyping of both T. gondii and P. falciparum. Expression profiling of the three clonotypic lineages dominating T. gondii populations in North America and Europe provides a first comprehensive view of the parasite transcriptome, revealing that ~49% of all annotated genes are expressed in parasite tachyzoites (the acutely lytic stage responsible for pathogenesis and 26% of genes are differentially expressed among strains. A novel design utilizing few probes provided high confidence genotyping, used here to resolve recombination points in the clonal progeny of sexual crosses. Recent sequencing of additional T. gondii isolates identifies >620 K new SNPs, including ~11 K that intersect with expression profiling probes, yielding additional markers for genotyping studies, and further validating the utility of a combined expression profiling/genotyping array design. Additional applications facilitating SNP and transcript discovery, alternative statistical methods for quantifying gene expression, etc. are also pursued at

  7. The proximal chromosome 14q microdeletion syndrome: delineation of the phenotype using high resolution SNP oligonucleotide microarray analysis (SOMA) and review of the literature.

    Science.gov (United States)

    Torgyekes, Edina; Shanske, Alan L; Anyane-Yeboa, Kwame; Nahum, Odelia; Pirzadeh, Sara; Blumfield, Einat; Jobanputra, Vaidehi; Warburton, Dorothy; Levy, Brynn

    2011-08-01

    We report on two patients with overlapping small interstitial deletions involving regions 14q12 to 14q13.1. Both children had severe developmental delay, failure to thrive, microcephaly, and distinctive facial features, including abnormal spacing of the eyes, epicanthal folds, sloping forehead, low-set ears, rounded eyebrows with triangular media aspect and outer tapering, depressed and broad nasal bridge, small mouth, a long philtrum, and a prominent Cupid's bow. Brain MRI of both children showed partial agenesis of the corpus callosum. Our first patient had bilateral hypoplastic optic nerves causing blindness, mild hearing impairment, sinus arrhythmia, abnormal temperature regulation, frequent apneic episodes, myoclonic jerks, and opisthotonus. Our second patient had a seizure disorder confirmed by EEG, sleep apnea, chronic interstitial lung disease, and several episodes of pneumonia and gastroenteritis. Cytogenetic analysis showed a normal karyotype in Patient 1 and a unique apparently balanced three-way translocation in Patient 2 involving chromosomes 4, 14, and 11. High resolution SNP Oligonucleotide Microarray Analysis (SOMA) revealed a deletion in the proximal region of chromosome 14q overlapping with the deletion of our first patient, and no copy number changes in chromosomes 4 and 11. Here, we review and compare published cases with a deletion involving the 14q12-22.1 chromosomal region in an effort to correlate phenotype and genotype. We also examine the underlying genomic architecture to identify the possible mechanism of the chromosomal abnormality. Our review found a patient with a mirror duplication of our first patient's deletion, confirming the existence of an underlying genomic structural instability in the region. © 2011 Wiley-Liss, Inc.

  8. Identification of mycotoxigenic fungi using an oligonucleotide microarray

    CSIR Research Space (South Africa)

    Barros, E

    2013-01-01

    Full Text Available , numerous detection tools have been developed for the detection and analysis of various mycotoxigenic fungi. These include PCR-based assays and microarrays targeting different areas of the fungal genome depending on its application. This chapter describes...

  9. Gene expression changes in initiation and progression of oral squamous cell carcinomas revealed by laser microdissection and oligonucleotide microarray analysis.

    Science.gov (United States)

    Sumino, Jun; Uzawa, Narikazu; Okada, Norihiko; Miyaguchi, Ken; Mogushi, Kaoru; Takahashi, Ken-Ichiro; Sato, Hiroaki; Michikawa, Chieko; Nakata, Yoshimi; Tanaka, Hiroshi; Amagasa, Teruo

    2013-02-01

    Oral carcinogenesis is a complex process involving multiple genes. However, the genetic changes involved in this process are not apparent in identical oral squamous cell carcinomas (OSCCs). According to pathological characteristics, samples of normal tissue, oral dysplastic lesions (ODLs), and invasive cancers were obtained from identical OSCCs using laser microdissection (LMD). Large-scale gene expression profiling was carried out on 33 samples derived from 11 OSCCs. We analyzed genes differentially expressed in normal tissues vs. ODLs and in ODLs vs. invasive tumors and identified 15 candidate genes with continuously increasing or decreasing expression during oral carcinogenesis. One of these genes, ISG15, was chosen for further characterization. Real-time quantitative reverse transcription-polymerase chain reaction and immunohistochemical analysis confirmed that ISG15 expression consistently increased during oral tumorigenesis. An ISG15 high-expression level was significantly associated with poor prognosis (p = 0.027). In addition, patients with high-expression tumors had a poorer 5-year survival rate than patients with low expression levels (p = 0.019). In conclusion, we identified 15 genes with continuously increasing or decreasing expression during oral carcinogenesis. One of these, ISG15, is likely to be associated with both dysgenesis and tumorigenesis and may be a potential prognostic marker for oral cancer. Copyright © 2012 UICC.

  10. Identification of chromosomal errors in human preimplantation embryos with oligonucleotide DNA microarray.

    Directory of Open Access Journals (Sweden)

    Lifeng Liang

    Full Text Available A previous study comparing the performance of different platforms for DNA microarray found that the oligonucleotide (oligo microarray platform containing 385K isothermal probes had the best performance when evaluating dosage sensitivity, precision, specificity, sensitivity and copy number variations border definition. Although oligo microarray platform has been used in some research fields and clinics, it has not been used for aneuploidy screening in human embryos. The present study was designed to use this new microarray platform for preimplantation genetic screening in the human. A total of 383 blastocysts from 72 infertility patients with either advanced maternal age or with previous miscarriage were analyzed after biopsy and microarray. Euploid blastocysts were transferred to patients and clinical pregnancy and implantation rates were measured. Chromosomes in some aneuploid blastocysts were further analyzed by fluorescence in-situ hybridization (FISH to evaluate accuracy of the results. We found that most (58.1% of the blastocysts had chromosomal abnormalities that included single or multiple gains and/or losses of chromosome(s, partial chromosome deletions and/or duplications in both euploid and aneuploid embryos. Transfer of normal euploid blastocysts in 34 cycles resulted in 58.8% clinical pregnancy and 54.4% implantation rates. Examination of abnormal blastocysts by FISH showed that all embryos had matching results comparing microarray and FISH analysis. The present study indicates that oligo microarray conducted with a higher resolution and a greater number of probes is able to detect not only aneuploidy, but also minor chromosomal abnormalities, such as partial chromosome deletion and/or duplication in human embryos. Preimplantation genetic screening of the aneuploidy by DNA microarray is an advanced technology used to select embryos for transfer and improved embryo implantation can be obtained after transfer of the screened normal

  11. Strong position-dependent effects of sequence mismatches on signal ratios measured using long oligonucleotide microarrays

    Directory of Open Access Journals (Sweden)

    Hulme Helen

    2008-07-01

    Full Text Available Abstract Background Microarrays are an important and widely used tool. Applications include capturing genomic DNA for high-throughput sequencing in addition to the traditional monitoring of gene expression and identifying DNA copy number variations. Sequence mismatches between probe and target strands are known to affect the stability of the probe-target duplex, and hence the strength of the observed signals from microarrays. Results We describe a large-scale investigation of microarray hybridisations to murine probes with known sequence mismatches, demonstrating that the effect of mismatches is strongly position-dependent and for small numbers of sequence mismatches is correlated with the maximum length of perfectly matched probe-target duplex. Length of perfect match explained 43% of the variance in log2 signal ratios between probes with one and two mismatches. The correlation with maximum length of perfect match does not conform to expectations based on considering the effect of mismatches purely in terms of reducing the binding energy. However, it can be explained qualitatively by considering the entropic contribution to duplex stability from configurations of differing perfect match length. Conclusion The results of this study have implications in terms of array design and analysis. They highlight the significant effect that short sequence mismatches can have upon microarray hybridisation intensities even for long oligonucleotide probes. All microarray data presented in this study are available from the GEO database 1, under accession number [GEO: GSE9669

  12. An oligonucleotide-tagged microarray for routine diagnostics of colon cancer by genotyping KRAS mutations

    DEFF Research Database (Denmark)

    Liu, Yuliang; Guðnason, Haukur; Li, Yiping

    2014-01-01

    or spiked fecal samples. The immobilized tag-probes were stable under multiple thermal cycling treatments, allowing re-use of the tag-microarray and further optimization to solid PCR. Our results demonstrated that a novel oligonucleotide-tagged microarray system has been developed which would be suitable...

  13. A comparison of alternative 60-mer probe designs in an in-situ synthesized oligonucleotide microarray

    Directory of Open Access Journals (Sweden)

    Fairbanks Benjamin D

    2006-04-01

    Full Text Available Abstract Background DNA microarrays have proven powerful for functional genomics studies. Several technologies exist for the generation of whole-genome arrays. It is well documented that 25mer probes directed against different regions of the same gene produce variable signal intensity values. However, the extent to which this is true for probes of greater length (60mers is not well characterized. Moreover, this information has not previously been reported for whole-genome arrays designed against bacteria, whose genomes may differ substantially in characteristics directly affecting microarray performance. Results We report here an analysis of alternative 60mer probe designs for an in-situ synthesized oligonucleotide array for the GC rich, β-proteobacterium Burkholderia cenocepacia. Probes were designed using the ArrayOligoSel3.5 software package and whole-genome microarrays synthesized by Agilent, Inc. using their in-situ, ink-jet technology platform. We first validated the quality of the microarrays as demonstrated by an average signal to noise ratio of >1000. Next, we determined that the variance of replicate probes (1178 total probes examined of identical sequence was 3.8% whereas the variance of alternative probes (558 total alternative probes examined designs was 9.5%. We determined that depending upon the definition, about 2.4% of replicate and 7.8% of alternative probes produced outlier conclusions. Finally, we determined none of the probe design subscores (GC content, internal repeat, binding energy and self annealment produced by ArrayOligoSel3.5 were predictive or probes that produced outlier signals. Conclusion Our analysis demonstrated that the use of multiple probes per target sequence is not essential for in-situ synthesized 60mer oligonucleotide arrays designed against bacteria. Although probes producing outlier signals were identified, the use of ratios results in less than 10% of such outlier conclusions. We also determined that

  14. Multi-gene detection and identification of mosquito-borne RNA viruses using an oligonucleotide microarray.

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    Nathan D Grubaugh

    Full Text Available BACKGROUND: Arthropod-borne viruses are important emerging pathogens world-wide. Viruses transmitted by mosquitoes, such as dengue, yellow fever, and Japanese encephalitis viruses, infect hundreds of millions of people and animals each year. Global surveillance of these viruses in mosquito vectors using molecular based assays is critical for prevention and control of the associated diseases. Here, we report an oligonucleotide DNA microarray design, termed ArboChip5.1, for multi-gene detection and identification of mosquito-borne RNA viruses from the genera Flavivirus (family Flaviviridae, Alphavirus (Togaviridae, Orthobunyavirus (Bunyaviridae, and Phlebovirus (Bunyaviridae. METHODOLOGY/PRINCIPAL FINDINGS: The assay utilizes targeted PCR amplification of three genes from each virus genus for electrochemical detection on a portable, field-tested microarray platform. Fifty-two viruses propagated in cell-culture were used to evaluate the specificity of the PCR primer sets and the ArboChip5.1 microarray capture probes. The microarray detected all of the tested viruses and differentiated between many closely related viruses such as members of the dengue, Japanese encephalitis, and Semliki Forest virus clades. Laboratory infected mosquitoes were used to simulate field samples and to determine the limits of detection. Additionally, we identified dengue virus type 3, Japanese encephalitis virus, Tembusu virus, Culex flavivirus, and a Quang Binh-like virus from mosquitoes collected in Thailand in 2011 and 2012. CONCLUSIONS/SIGNIFICANCE: We demonstrated that the described assay can be utilized in a comprehensive field surveillance program by the broad-range amplification and specific identification of arboviruses from infected mosquitoes. Furthermore, the microarray platform can be deployed in the field and viral RNA extraction to data analysis can occur in as little as 12 h. The information derived from the ArboChip5.1 microarray can help to establish

  15. Identification of osteopontin as the most consistently over-expressed gene in intrahepatic cholangiocarcinoma:Detection by oligonucleotide microarray and real-time PCR analysis

    Institute of Scientific and Technical Information of China (English)

    Holger G Hass; Oliver Nehls; Juergen Jobst; Andrea Frilling; Ulrich Vogel; Stephan Kaiser

    2008-01-01

    AIM: To investigate the molecular pathways involved in human cholangiocarcinogenesis by gene expression profiling.METHODS: Oligonucleotide arrays (Affymetr/x U133A)were used to establish a specific gene expression profile of intrahepatic CCC in comparison to corresponding nonmalignant liver tissue.To validate the expression values of the most overexpressed genes, RT-PCR experiments were performed.RESULTS: Five hundred and fifty-two statistically differentially expressed genes/ESTs (221 probes significantly up-regulated, 331 probes down-regulated;P2;≥70%) were identified.Using these data and two-dimensional cluster analysis,a specific gene expression profile was obtained allowing fast and reproducible differentiation of CCC, which was confirmed by supervised neuronal network modelling.The most consistently overexpressed gene (median fold change 33.5, significantly overexpressed in 100%)encoded osteopontin.Furthermore, an association of various genes with the histopathological grading could be demonstrated.CONCLUSION: A highly specific gone expression profile for intrahepatic CCC was identified, allowing for its fast and reproducible discrimination against nonmalignant liver tissue and other liver masses.The most overexpressed gene in intrahepatic CCC was the gene encoding osteopontin.These data may lead to a better understanding of human cholangiocarcinogenesis.

  16. Construction and Evaluation of Desulfovibrio vulgaris Whole-Genome Oligonucleotide Microarrays

    Energy Technology Data Exchange (ETDEWEB)

    Z. He; Q. He; L. Wu; M.E. Clark; J.D. Wall; Jizhong Zhou; Matthew W. Fields

    2004-03-17

    Desulfovibrio vulgaris Hildenborough has been the focus of biochemical and physiological studies in the laboratory, and the metabolic versatility of this organism has been largely recognized, particularly the reduction of sulfate, fumarate, iron, uranium and chromium. In addition, a Desulfovibrio sp. has been shown to utilize uranium as the sole electron acceptor. D. vulgaris is a d-Proteobacterium with a genome size of 3.6 Mb and 3584 ORFs. The whole-genome microarrays of D. vulgaris have been constructed using 70mer oligonucleotides. All ORFs in the genome were represented with 3471 (97.1%) unique probes and 103 (2.9%) non-specific probes that may have cross-hybridization with other ORFs. In preparation for use of the experimental microarrays, artificial probes and targets were designed to assess specificity and sensitivity and identify optimal hybridization conditions for oligonucleotide microarrays. The results indicated that for 50mer and 70mer oligonucleotide arrays, hybridization at 45 C to 50 C, washing at 37 C and a wash time of 2.5 to 5 minutes obtained specific and strong hybridization signals. In order to evaluate the performance of the experimental microarrays, growth conditions were selected that were expected to give significant hybridization differences for different sets of genes. The initial evaluations were performed using D. vulgaris cells grown at logarithmic and stationary phases. Transcriptional analysis of D. vulgaris cells sampled during logarithmic phase growth indicated that 25% of annotated ORFs were up-regulated and 3% of annotated ORFs were downregulated compared to stationary phase cells. The up-regulated genes included ORFs predicted to be involved with acyl chain biosynthesis, amino acid ABC transporter, translational initiation factors, and ribosomal proteins. In the stationary phase growth cells, the two most up-regulated ORFs (70-fold) were annotated as a carboxynorspermidine decarboxylase and a 2C-methyl-D-erythritol-2

  17. LNA-modified isothermal oligonucleotide microarray for differentiating bacilli of similar origin.

    Science.gov (United States)

    Yan, Jing; Yuan, Ying; Mu, Runqing; Shang, Hong; Guan, Yifu

    2014-12-01

    Oligonucleotide microarray has been one of the most powerful tools in the 'Post-Genome Era' for its high sensitivity, high throughput and parallel processing capability. To achieve high detection specificity, we fabricated an isothermal microarray using locked nucleic acid (LNA)-modified oligonucleotide probes, since LNA has demonstrated the advanced ability to enhance the binding affinity toward their complementary nucleotides. After designing the nucleotide sequences of these oligonucleotide probes for gram-positive bacilli of similar origin (Bacillus subtilis, Bacillus licheniformis, Bacillus pumilus, Bacillus megaterium and Bacillus circulans), we unified the melting temperatures of these oligonucleotide probes by modifying some nucleotides using LNA. Furthermore, we optimized the experimental procedures of hydrating microarray slides, blocking side surface as well as labelling the PCR products. Experimental results revealed that KOD Dash DNA polymerase could efficiently incorporate Cy3-dCTP into the PCR products, and the LNA-isothermal oligonucleotide microarray were able to distinguish the bacilli of similar origin with a high degree of accuracy and specificity under the optimized experimental condition.

  18. LNA-modified isothermal oligonucleotide microarray for differentiating bacilli of similar origin

    Indian Academy of Sciences (India)

    Jing Yan; Ying Yuan; Runqing Mu; Hong Shang; Yifu Guan

    2014-12-01

    Oligonucleotide microarray has been one of the most powerful tools in the ‘Post-Genome Era’ for its high sensitivity, high throughput and parallel processing capability. To achieve high detection specificity, we fabricated an isothermal microarray using locked nucleic acid (LNA)-modified oligonucleotide probes, since LNA has demonstrated the advanced ability to enhance the binding affinity toward their complementary nucleotides. After designing the nucleotide sequences of these oligonucleotide probes for gram-positive bacilli of similar origin (Bacillus subtilis, Bacillus licheniformis, Bacillus pumilus, Bacillus megaterium and Bacillus circulans), we unified the melting temperatures of these oligonucleotide probes by modifying some nucleotides using LNA. Furthermore, we optimized the experimental procedures of hydrating microarray slides, blocking side surface as well as labelling the PCR products. Experimental results revealed that KOD Dash DNA polymerase could efficiently incorporate Cy3-dCTP into the PCR products, and the LNA-isothermal oligonucleotide microarray were able to distinguish the bacilli of similar origin with a high degree of accuracy and specificity under the optimized experimental condition.

  19. Microarray Analysis in Glioblastomas

    Science.gov (United States)

    Bhawe, Kaumudi M.; Aghi, Manish K.

    2016-01-01

    Microarray analysis in glioblastomas is done using either cell lines or patient samples as starting material. A survey of the current literature points to transcript-based microarrays and immunohistochemistry (IHC)-based tissue microarrays as being the preferred methods of choice in cancers of neurological origin. Microarray analysis may be carried out for various purposes including the following: To correlate gene expression signatures of glioblastoma cell lines or tumors with response to chemotherapy (DeLay et al., Clin Cancer Res 18(10):2930–2942, 2012)To correlate gene expression patterns with biological features like proliferation or invasiveness of the glioblastoma cells (Jiang et al., PLoS One 8(6):e66008, 2013)To discover new tumor classificatory systems based on gene expression signature, and to correlate therapeutic response and prognosis with these signatures (Huse et al., Annu Rev Med 64(1):59–70, 2013; Verhaak et al., Cancer Cell 17(1):98–110, 2010) While investigators can sometimes use archived tumor gene expression data available from repositories such as the NCBI Gene Expression Omnibus to answer their questions, new arrays must often be run to adequately answer specific questions. Here, we provide a detailed description of microarray methodologies, how to select the appropriate methodology for a given question, and analytical strategies that can be used. Experimental methodology for protein microarrays is outside the scope of this chapter, but basic sample preparation techniques for transcript-based microarrays are included here. PMID:26113463

  20. Direct Mutagenesis of Thousands of Genomic Targets using Microarray-derived Oligonucleotides

    DEFF Research Database (Denmark)

    Bonde, Mads; Kosuri, Sriram; Genee, Hans Jasper

    2015-01-01

    operons in E. coli using this method, which we call Microarray-Oligonucleotide (MO)-MAGE. The resulting mutant library was characterized by high-throughput sequencing to show that all attempted insertions were estimated to have occurred at an average frequency of 0.02 % per loci with 0.4 average...

  1. Optimization of single-base-pair mismatch discrimination in oligonucleotide microarrays

    NARCIS (Netherlands)

    Urakawa, H.; Fantroussi, El S.; Smidt, H.; Smoot, J.C.; Tribou, E.H.; Kelly, J.J.; Noble, P.A.; Stahl, D.A.

    2003-01-01

    The discrimination between perfect-match and single-base-pair-mismatched nucleic acid duplexes was investigated by using oligonucleotide DNA microarrays and nonequilibrium dissociation rates (melting profiles). DNA and RNA versions of two synthetic targets corresponding to the 16S rRNA sequences of

  2. Conceptual "Heat-Driven" approach to the synthesis of DNA oligonucleotides on microarrays.

    Science.gov (United States)

    Grajkowski, A; Cieślak, J; Chmielewski, M K; Marchán, V; Phillips, L R; Wilk, A; Beaucage, S L

    2003-12-01

    The discovery of deoxyribonucleoside cyclic N-acylphosphoramidites, a novel class of phosphoramidite monomers for solid-phase oligonucleotide synthesis, has led to the development of a number of phosphate protecting groups that can be cleaved from DNA oligonucleotides under thermolytic neutral conditions. These include the 2-(N-formyl-N-methyl)aminoethyl, 4-oxopentyl, 3-(N-tert-butyl)carboxamido-1-propyl, 3-(2-pyridyl)-1-propyl, 2-[N-methyl-N-(2-pyridyl)]aminoethyl, and 4-methythiobutyl groups. When used for 5'-hydroxyl protection of nucleosides, the analogous 1-phenyl-2-[N-methyl-N-(2-pyridyl)]aminoethyloxycarbonyl group exhibited excellent thermolytic properties, which may permit an iterative "heat-driven" synthesis of DNA oligonucleotides on microarrays. In this regard, progress has been made toward the use of deoxyribonucleoside cyclic N-acylphosphoramidites in solid-phase oligonucleotide syntheses without nucleobase protection. Given that deoxyribonucleoside cyclic N-acylphosphoramidites produce oligonucleotides with heat-sensitive phosphate protecting groups, blocking the 5'-hydroxyl of these monomers with, for example, the thermolabile 1-phenyl-2-[N-methyl-N-(2-pyridyl)]aminoethyloxycarbonyl group may provide a convenient thermo-controlled method for the synthesis of oligonucleotides on microarrays.

  3. Design and application of 60mer oligonucleotide microarray in SARS coronavirus detection

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    The 60mer oligonucleotide microarray was designed and applied to detecting of SARS (severe acute respiratory syndrome) coronavirus. Thirty 60mer specific oligos were designed to cover the whole genome of the first submitted coronavirus strain, according to the sequence of TOR2 (GENEBANK Accession: AY274119). These primers were synthesized and printed into a microarray with 12×12 spots. RNAs were extracted from the throat swab and gargling fluid of SARS patients and reverse-transcripted into the double strand cDNAs. The cDNAs were prepared as restricted cDNA fragments by the restriction display (RD) technique and labeled by PCR with the Cy5-universal primer. The labeled samples were then applied to the oligo microarray for hybridization. The diagnostic capability of the microarray was evaluated after the washing and scanning steps. The scanning result showed that samples of SARS patients were hybridized with multiple SARS probes on the microarray, and there is no signal on the negative and blank controls. These results indicate that the genome of SARS coronavirus can be detected in parallel by the 60mer oligonucleotide microarray, which can improve the positive ratio of the diagnosis. The oligo microarray can also be used for monitoring the behavior of the virus genes in different stages of the disease status.

  4. Oligonucleotide microarray identifies genes differentially expressed during tumorigenesis of DMBA-induced pancreatic cancer in rats.

    Directory of Open Access Journals (Sweden)

    Jun-Chao Guo

    Full Text Available The extremely dismal prognosis of pancreatic cancer (PC is attributed, at least in part, to lack of early diagnosis. Therefore, identifying differentially expressed genes in multiple steps of tumorigenesis of PC is of great interest. In the present study, a 7,12-dimethylbenzanthraene (DMBA-induced PC model was established in male Sprague-Dawley rats. The gene expression profile was screened using an oligonucleotide microarray, followed by real-time quantitative polymerase chain reaction (qRT-PCR and immunohistochemical staining validation. A total of 661 differentially expressed genes were identified in stages of pancreatic carcinogenesis. According to GO classification, these genes were involved in multiple molecular pathways. Using two-way hierarchical clustering analysis, normal pancreas, acute and chronic pancreatitis, PanIN, early and advanced pancreatic cancer were completely discriminated. Furthermore, 11 upregulated and 142 downregulated genes (probes were found by Mann-Kendall trend Monotone test, indicating homologous genes of rat and human. The qRT-PCR and immunohistochemistry analysis of CXCR7 and UBe2c, two of the identified genes, confirmed the microarray results. In human PC cell lines, knockdown of CXCR7 resulted in decreased migration and invasion. Collectively, our data identified several promising markers and therapeutic targets of PC based on a comprehensive screening and systemic validation.

  5. Oligonucleotide microarray identifies genes differentially expressed during tumorigenesis of DMBA-induced pancreatic cancer in rats.

    Science.gov (United States)

    Guo, Jun-Chao; Li, Jian; Yang, Ying-Chi; Zhou, Li; Zhang, Tai-Ping; Zhao, Yu-Pei

    2013-01-01

    The extremely dismal prognosis of pancreatic cancer (PC) is attributed, at least in part, to lack of early diagnosis. Therefore, identifying differentially expressed genes in multiple steps of tumorigenesis of PC is of great interest. In the present study, a 7,12-dimethylbenzanthraene (DMBA)-induced PC model was established in male Sprague-Dawley rats. The gene expression profile was screened using an oligonucleotide microarray, followed by real-time quantitative polymerase chain reaction (qRT-PCR) and immunohistochemical staining validation. A total of 661 differentially expressed genes were identified in stages of pancreatic carcinogenesis. According to GO classification, these genes were involved in multiple molecular pathways. Using two-way hierarchical clustering analysis, normal pancreas, acute and chronic pancreatitis, PanIN, early and advanced pancreatic cancer were completely discriminated. Furthermore, 11 upregulated and 142 downregulated genes (probes) were found by Mann-Kendall trend Monotone test, indicating homologous genes of rat and human. The qRT-PCR and immunohistochemistry analysis of CXCR7 and UBe2c, two of the identified genes, confirmed the microarray results. In human PC cell lines, knockdown of CXCR7 resulted in decreased migration and invasion. Collectively, our data identified several promising markers and therapeutic targets of PC based on a comprehensive screening and systemic validation.

  6. Identification of upper respiratory tract pathogens using electrochemical detection on an oligonucleotide microarray.

    Directory of Open Access Journals (Sweden)

    Michael J Lodes

    Full Text Available Bacterial and viral upper respiratory infections (URI produce highly variable clinical symptoms that cannot be used to identify the etiologic agent. Proper treatment, however, depends on correct identification of the pathogen involved as antibiotics provide little or no benefit with viral infections. Here we describe a rapid and sensitive genotyping assay and microarray for URI identification using standard amplification and hybridization techniques, with electrochemical detection (ECD on a semiconductor-based oligonucleotide microarray. The assay was developed to detect four bacterial pathogens (Bordetella pertussis, Streptococcus pyogenes, Chlamydia pneumoniae and Mycoplasma pneumoniae and 9 viral pathogens (adenovirus 4, coronavirus OC43, 229E and HK, influenza A and B, parainfluenza types 1, 2, and 3 and respiratory syncytial virus. This new platform forms the basis for a fully automated diagnostics system that is very flexible and can be customized to suit different or additional pathogens. Multiple probes on a flexible platform allow one to test probes empirically and then select highly reactive probes for further iterative evaluation. Because ECD uses an enzymatic reaction to create electrical signals that can be read directly from the array, there is no need for image analysis or for expensive and delicate optical scanning equipment. We show assay sensitivity and specificity that are excellent for a multiplexed format.

  7. Specific discrimination of three pathogenic Salmonella enterica subsp. enterica serotypes by carB-based oligonucleotide microarray.

    Science.gov (United States)

    Shin, Hwa Hui; Hwang, Byeong Hee; Seo, Jeong Hyun; Cha, Hyung Joon

    2014-01-01

    It is important to rapidly and selectively detect and analyze pathogenic Salmonella enterica subsp. enterica in contaminated food to reduce the morbidity and mortality of Salmonella infection and to guarantee food safety. In the present work, we developed an oligonucleotide microarray containing duplicate specific capture probes based on the carB gene, which encodes the carbamoyl phosphate synthetase large subunit, as a competent biomarker evaluated by genetic analysis to selectively and efficiently detect and discriminate three S. enterica subsp. enterica serotypes: Choleraesuis, Enteritidis, and Typhimurium. Using the developed microarray system, three serotype targets were successfully analyzed in a range as low as 1.6 to 3.1 nM and were specifically discriminated from each other without nonspecific signals. In addition, the constructed microarray did not have cross-reactivity with other common pathogenic bacteria and even enabled the clear discrimination of the target Salmonella serotype from a bacterial mixture. Therefore, these results demonstrated that our novel carB-based oligonucleotide microarray can be used as an effective and specific detection system for S. enterica subsp. enterica serotypes.

  8. Sample phenotype clusters in high-density oligonucleotide microarray data sets are revealed using Isomap, a nonlinear algorithm

    Directory of Open Access Journals (Sweden)

    Malyj Wasyl

    2005-08-01

    Full Text Available Abstract Background Life processes are determined by the organism's genetic profile and multiple environmental variables. However the interaction between these factors is inherently non-linear 1. Microarray data is one representation of the nonlinear interactions among genes and genes and environmental factors. Still most microarray studies use linear methods for the interpretation of nonlinear data. In this study, we apply Isomap, a nonlinear method of dimensionality reduction, to analyze three independent large Affymetrix high-density oligonucleotide microarray data sets. Results Isomap discovered low-dimensional structures embedded in the Affymetrix microarray data sets. These structures correspond to and help to interpret biological phenomena present in the data. This analysis provides examples of temporal, spatial, and functional processes revealed by the Isomap algorithm. In a spinal cord injury data set, Isomap discovers the three main modalities of the experiment – location and severity of the injury and the time elapsed after the injury. In a multiple tissue data set, Isomap discovers a low-dimensional structure that corresponds to anatomical locations of the source tissues. This model is capable of describing low- and high-resolution differences in the same model, such as kidney-vs.-brain and differences between the nuclei of the amygdala, respectively. In a high-throughput drug screening data set, Isomap discovers the monocytic and granulocytic differentiation of myeloid cells and maps several chemical compounds on the two-dimensional model. Conclusion Visualization of Isomap models provides useful tools for exploratory analysis of microarray data sets. In most instances, Isomap models explain more of the variance present in the microarray data than PCA or MDS. Finally, Isomap is a promising new algorithm for class discovery and class prediction in high-density oligonucleotide data sets.

  9. Improving signal intensities for genes with low-expression on oligonucleotide microarrays

    Directory of Open Access Journals (Sweden)

    Hu Limei

    2004-06-01

    Full Text Available Abstract Background DNA microarrays using long oligonucleotide probes are widely used to evaluate gene expression in biological samples. These oligonucleotides are pre-synthesized and sequence-optimized to represent specific genes with minimal cross-hybridization to homologous genes. Probe length and concentration are critical factors for signal sensitivity, particularly when genes with various expression levels are being tested. We evaluated the effects of oligonucleotide probe length and concentration on signal intensity measurements of the expression levels of genes in a target sample. Results Selected genes of various expression levels in a single cell line were hybridized to oligonucleotide arrays of four lengths and four concentrations of probes to determine how these critical parameters affected the intensity of the signal representing their expression. We found that oligonucleotides of longer length significantly increased the signals of genes with low-expression in the target. High-expressing gene signals were also boosted but to a lesser degree. Increasing the probe concentration, however, did not linearly increase the signal intensity for either low- or high-expressing genes. Conclusions We conclude that the longer the oligonuclotide probe the better the signal intensities of low expressing genes on oligonucleotide arrays.

  10. Detection and identification of intestinal pathogenic bacteria by hybridization to oligonucleotide microarrays

    Institute of Scientific and Technical Information of China (English)

    Lian-Qun Jin; Jun-Wen Li; Sheng-Qi Wang; Fu-Huan Chao; Xin-Wei Wang; Zheng-Quan Yuan

    2005-01-01

    AIM: To detect the common intestinal pathogenic bacteria quickly and accurately.METHODS: A rapid (<3 h) experimental procedure was set up based upon the gene chip technology. Target genes were amplified and hybridized by oligonucleotide microarrays.RESULTS: One hundred and seventy strains of bacteria in pure culture belonging to 11 genera were successfully discriminated under comparatively same conditions, and a series of specific hybridization maps corresponding to each kind of bacteria were obtained. When this method was applied to 26 divided cultures, 25 (96.2%) were identified.CONCLUSION: Salmonella sp., Escherichia coli, Shigella sp., Listeria monocytogenes, Vibrio parahaemolyticus,Staphylococcus aureus, Proteus sp., Bacillus cereus,Vibrio cholerae, Enterococcus faecalis, Yersinia enterocolitica, and Campylobacter jejuni can be detected and identified by our microarrays. The accuracy, range,and discrimination power of this assay can be continually improved by adding further oligonucleotides to the arrays without any significant increase of complexity or cost.

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

    OpenAIRE

    Carter, Mark G.; Sharov, Alexei A; VanBuren, Vincent; Dudekula, Dawood B.; Carmack, Condie E; Nelson, Charlie; Ko, Minoru SH

    2005-01-01

    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.

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

    Science.gov (United States)

    Carter, Mark G; Sharov, Alexei A; VanBuren, Vincent; Dudekula, Dawood B; Carmack, Condie E; Nelson, Charlie; Ko, Minoru SH

    2005-01-01

    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. PMID:15998450

  13. Application of Oligonucleotide Microarrays for Bacterial Source Tracking of Environmental Enterococcus sp. Isolates

    OpenAIRE

    Furey, John S.; Kelley Betts; Indest, Karl J.

    2005-01-01

    In an effort towards adapting new and defensible methods for assessing and managing the risk posed by microbial pollution, we evaluated the utility of oligonucleotide microarrays for bacterial source tracking (BST) of environmental Enterococcus sp. isolates derived from various host sources. Current bacterial source tracking approaches rely on various phenotypic and genotypic methods to identify sources of bacterial contamination resulting from point or non-point pollution. For this study Ent...

  14. nuID: a universal naming scheme of oligonucleotides for Illumina, Affymetrix, and other microarrays

    Directory of Open Access Journals (Sweden)

    Kibbe Warren A

    2007-05-01

    Full Text Available Abstract Background Oligonucleotide probes that are sequence identical may have different identifiers between manufacturers and even between different versions of the same company's microarray; and sometimes the same identifier is reused and represents a completely different oligonucleotide, resulting in ambiguity and potentially mis-identification of the genes hybridizing to that probe. Results We have devised a unique, non-degenerate encoding scheme that can be used as a universal representation to identify an oligonucleotide across manufacturers. We have named the encoded representation 'nuID', for nucleotide universal identifier. Inspired by the fact that the raw sequence of the oligonucleotide is the true definition of identity for a probe, the encoding algorithm uniquely and non-degenerately transforms the sequence itself into a compact identifier (a lossless compression. In addition, we added a redundancy check (checksum to validate the integrity of the identifier. These two steps, encoding plus checksum, result in an nuID, which is a unique, non-degenerate, permanent, robust and efficient representation of the probe sequence. For commercial applications that require the sequence identity to be confidential, we have an encryption schema for nuID. We demonstrate the utility of nuIDs for the annotation of Illumina microarrays, and we believe it has universal applicability as a source-independent naming convention for oligomers. Reviewers This article was reviewed by Itai Yanai, Rong Chen (nominated by Mark Gerstein, and Gregory Schuler (nominated by David Lipman.

  15. Large scale real-time PCR validation on gene expression measurements from two commercial long-oligonucleotide microarrays

    Directory of Open Access Journals (Sweden)

    Chan Frances

    2006-03-01

    Full Text Available Abstract Background DNA microarrays are rapidly becoming a fundamental tool in discovery-based genomic and biomedical research. However, the reliability of the microarray results is being challenged due to the existence of different technologies and non-standard methods of data analysis and interpretation. In the absence of a "gold standard"/"reference method" for the gene expression measurements, studies evaluating and comparing the performance of various microarray platforms have often yielded subjective and conflicting conclusions. To address this issue we have conducted a large scale TaqMan® Gene Expression Assay based real-time PCR experiment and used this data set as the reference to evaluate the performance of two representative commercial microarray platforms. Results In this study, we analyzed the gene expression profiles of three human tissues: brain, lung, liver and one universal human reference sample (UHR using two representative commercial long-oligonucleotide microarray platforms: (1 Applied Biosystems Human Genome Survey Microarrays (based on single-color detection; (2 Agilent Whole Human Genome Oligo Microarrays (based on two-color detection. 1,375 genes represented by both microarray platforms and spanning a wide dynamic range in gene expression levels, were selected for TaqMan® Gene Expression Assay based real-time PCR validation. For each platform, four technical replicates were performed on the same total RNA samples according to each manufacturer's standard protocols. For Agilent arrays, comparative hybridization was performed using incorporation of Cy5 for brain/lung/liver RNA and Cy3 for UHR RNA (common reference. Using the TaqMan® Gene Expression Assay based real-time PCR data set as the reference set, the performance of the two microarray platforms was evaluated focusing on the following criteria: (1 Sensitivity and accuracy in detection of expression; (2 Fold change correlation with real-time PCR data in pair

  16. The "Clickable" Method for Oligonucleotide Immobilization Onto Azide-Functionalized Microarrays.

    Science.gov (United States)

    Ratajczak, Tomasz; Uszczyńska, Barbara; Frydrych-Tomczak, Emilia; Chmielewski, Marcin K

    2016-01-01

    The DNA microarray technique was supposed to help identifying and analyzing the expression level of tens of thousands of genes in the whole genome. But there is a serious problem concerning fabrication of the microarrays by chemical synthesis, such as specific and efficient linking of probes to a solid support. Therefore, we reckon that applying "click" chemistry to covalently anchor oligonucleotides on chemically modified supports may help construct microarrays in applications such as gene identification. Silanization of the glass support with organofunctional silane makes it possible to link azide groups on glass surface and the nucleic acid probe that is equipped with a pentynyl group. This is followed by direct spotting of the nucleic acid on the azide-modified glass support in the presence of copper ions, and this is a frequently applied method of "click" chemistry.

  17. Development of a human mitochondrial oligonucleotide microarray (h-MitoArray and gene expression analysis of fibroblast cell lines from 13 patients with isolated F1Fo ATP synthase deficiency

    Directory of Open Access Journals (Sweden)

    Hansíková Hana

    2008-01-01

    Full Text Available Abstract Background To strengthen research and differential diagnostics of mitochondrial disorders, we constructed and validated an oligonucleotide microarray (h-MitoArray allowing expression analysis of 1632 human genes involved in mitochondrial biology, cell cycle regulation, signal transduction and apoptosis. Using h-MitoArray we analyzed gene expression profiles in 9 control and 13 fibroblast cell lines from patients with F1Fo ATP synthase deficiency consisting of 2 patients with mt9205ΔTA microdeletion and a genetically heterogeneous group of 11 patients with not yet characterized nuclear defects. Analysing gene expression profiles, we attempted to classify patients into expected defect specific subgroups, and subsequently reveal group specific compensatory changes, identify potential phenotype causing pathways and define candidate disease causing genes. Results Molecular studies, in combination with unsupervised clustering methods, defined three subgroups of patient cell lines – M group with mtDNA mutation and N1 and N2 groups with nuclear defect. Comparison of expression profiles and functional annotation, gene enrichment and pathway analyses of differentially expressed genes revealed in the M group a transcription profile suggestive of synchronized suppression of mitochondrial biogenesis and G1/S arrest. The N1 group showed elevated expression of complex I and reduced expression of complexes III, V, and V-type ATP synthase subunit genes, reduced expression of genes involved in phosphorylation dependent signaling along MAPK, Jak-STAT, JNK, and p38 MAP kinase pathways, signs of activated apoptosis and oxidative stress resembling phenotype of premature senescent fibroblasts. No specific functionally meaningful changes, except of signs of activated apoptosis, were detected in the N2 group. Evaluation of individual gene expression profiles confirmed already known ATP6/ATP8 defect in patients from the M group and indicated several candidate

  18. Improving oligonucleotide fingerprinting of rRNA genes by implementation of polony microarray technology

    Science.gov (United States)

    Ruegger, Paul M.; Bent, Elizabeth; Li, Wei; Jeske, Daniel R.; Cui, Xinping; Braun, Jonathan; Jiang, Tao; Borneman, James

    2012-01-01

    Improvements to oligonucleotide fingerprinting of rRNA genes (OFRG) were obtained by implementing polony microarray technology. OFRG is an array-based method for analyzing microbial community composition. Polonies are discrete clusters of DNA, produced by solid-phase PCR in hydrogels, and derived from individual, spatially isolated DNA molecules. The advantages of a polony-based OFRG method include higher throughput and reductions in the PCR-induced errors and compositional skew inherent in all other PCR-based community composition methods, including high throughput sequencing of rRNA genes. Given the similarities between polony microarrays and certain aspects of sequencing methods such as the Illumina platform, we suggest that if concepts presented in this study were implemented in high throughput sequencing protocols, a reduction of PCR-induced errors and compositional skew may be realized. PMID:22640891

  19. Assessment and integration of publicly available SAGE, cDNA microarray, and oligonucleotide microarray expression data for global coexpression analyses.

    Science.gov (United States)

    Griffith, Obi L; Pleasance, Erin D; Fulton, Debra L; Oveisi, Mehrdad; Ester, Martin; Siddiqui, Asim S; Jones, Steven J M

    2005-10-01

    Large amounts of gene expression data from several different technologies are becoming available to the scientific community. A common practice is to use these data to calculate global gene coexpression for validation or integration of other "omic" data. To assess the utility of publicly available datasets for this purpose we have analyzed Homo sapiens data from 1202 cDNA microarray experiments, 242 SAGE libraries, and 667 Affymetrix oligonucleotide microarray experiments. The three datasets compared demonstrate significant but low levels of global concordance (rc<0.11). Assessment against Gene Ontology (GO) revealed that all three platforms identify more coexpressed gene pairs with common biological processes than expected by chance. As the Pearson correlation for a gene pair increased it was more likely to be confirmed by GO. The Affymetrix dataset performed best individually with gene pairs of correlation 0.9-1.0 confirmed by GO in 74% of cases. However, in all cases, gene pairs confirmed by multiple platforms were more likely to be confirmed by GO. We show that combining results from different expression platforms increases reliability of coexpression. A comparison with other recently published coexpression studies found similar results in terms of performance against GO but with each method producing distinctly different gene pair lists.

  20. Reproducibility of oligonucleotide microarray transcriptome analyses - An interlaboratory comparison using chemostat cultures of Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Piper, M.D.W.; Daran-Lapujade, P.; Bro, Christoffer;

    2002-01-01

    Assessment of reproducibility of DNA-microarray analysis from published data sets is complicated by the use of different microbial strains, cultivation techniques, and analytical procedures. Because intra- and interlaboratory reproducibility is highly relevant for application of DNA-microarray an...

  1. Reproducibility of oligonucleotide microarray transcriptome analyses - An interlaboratory comparison using chemostat cultures of Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Piper, M.D.W.; Daran-Lapujade, P.; Bro, Christoffer

    2002-01-01

    Assessment of reproducibility of DNA-microarray analysis from published data sets is complicated by the use of different microbial strains, cultivation techniques, and analytical procedures. Because intra- and interlaboratory reproducibility is highly relevant for application of DNA-microarray an...

  2. Mismatch oligonucleotides in human and yeast: guidelines for probe design on tiling microarrays

    Directory of Open Access Journals (Sweden)

    Jee Justin

    2008-12-01

    Full Text Available Abstract Background Mismatched oligonucleotides are widely used on microarrays to differentiate specific from nonspecific hybridization. While many experiments rely on such oligos, the hybridization behavior of various degrees of mismatch (MM structure has not been extensively studied. Here, we present the results of two large-scale microarray experiments on S. cerevisiae and H. sapiens genomic DNA, to explore MM oligonucleotide behavior with real sample mixtures under tiling-array conditions. Results We examined all possible nucleotide substitutions at the central position of 36-nucleotide probes, and found that nonspecific binding by MM oligos depends upon the individual nucleotide substitutions they incorporate: C→A, C→G and T→A (yielding purine-purine mispairs are most disruptive, whereas A→X were least disruptive. We also quantify a marked GC skew effect: substitutions raising probe GC content exhibit higher intensity (and vice versa. This skew is small in highly-expressed regions (± 0.5% of total intensity range and large (± 2% or more elsewhere. Multiple mismatches per oligo are largely additive in effect: each MM added in a distributed fashion causes an additional 21% intensity drop relative to PM, three-fold more disruptive than adding adjacent mispairs (7% drop per MM. Conclusion We investigate several parameters for oligonucleotide design, including the effects of each central nucleotide substitution on array signal intensity and of multiple MM per oligo. To avoid GC skew, individual substitutions should not alter probe GC content. RNA sample mixture complexity may increase the amount of nonspecific hybridization, magnify GC skew and boost the intensity of MM oligos at all levels.

  3. Identification of biomarkers for cervical cancer in peripheral blood lymphocytes using oligonucleotide microarrays

    Institute of Scientific and Technical Information of China (English)

    SHENG Jie; ZHANG Wei-yuan

    2010-01-01

    Background Oligonucleotide microarrays are increasingly being used to identify gene expression profiles that associated with complex genetic diseases. Peripheral lymphocytes communicate with cells and extracellular matrixes in almost all tissues and organs in human body, suggesting that the gene expression profiles in peripheral lymphocytes may reflect the presence of disease in the body. This study aimed to identify molecular biomarkers for cervical cancer in peripheral blood lymphocytes by using oligonucleotide microarrays.Methods Total RNA was extracted from peripheral blood lymphocytes of 24 early stage cervical cancer patients and 18 healthy controls. We used 22K Human Genome microarrays to profile peripheral blood lymphocytes from 4 early stage cervical cancer patients and compared their gene expression profiles with those from 3 healthy controls. Differentially expressed genes would be identified if they had adjusted P values of less than 0.05 and a groupwise average fold change greater than 1.5 or less than 0.67. Then the selected 5 genes were validated in the remaining 20 early stage cervical cancer patients and the 15 healthy controls by using real-time reverse-transcription polymerase chain reaction (RT-PCR).Results Genes identified by the gene selection program expressed differently between the blood samples of the early stage cervical cancer patients and those of the healthy controls. To validate the gene expression data, 5 genes were analyzed by real-time RT-PCR. In three of the 5 identified genes, tenasin-c (TNC), nuceolin (NCL), and enolase 2 (ENO2) showed a significant up-regulation in the blood samples of the early stage cervical cancer patients versus that of the healthy controls.Conclusions The up-regulation of TNC, NCL, and ENO2 in peripheral blood may be used to identify novel blood biomarkers for detecting cervical cancer in a clinically accessible surrogate tissue, and thus to provide a possibility to develop a noninvasive and predictive

  4. A new oligonucleotide microarray for detection of pathogenic and non-pathogenic Legionella spp.

    Science.gov (United States)

    Cao, Boyang; Liu, Xiangqian; Yu, Xiang; Chen, Min; Feng, Lu; Wang, Lei

    2014-01-01

    Legionella pneumophila has been recognized as the major cause of legionellosis since the discovery of the deadly disease. Legionella spp. other than L. pneumophila were later found to be responsible to many non-pneumophila infections. The non-L. pneumophila infections are likely under-detected because of a lack of effective diagnosis. In this report, we have sequenced the 16S-23S rRNA gene internal transcribed spacer (ITS) of 10 Legionella species and subspecies, including L. anisa, L. bozemanii, L. dumoffii, L. fairfieldensis, L. gormanii, L. jordanis, L. maceachernii, L. micdadei, L. pneumophila subspp. fraseri and L. pneumophila subspp. pasculleii, and developed a rapid oligonucleotide microarray detection technique accordingly to identify 12 most common Legionella spp., which consist of 11 pathogenic species of L. anisa, L. bozemanii, L. dumoffii, L. gormanii, L. jordanis, L. longbeachae, L. maceachernii, L. micdadei, and L. pneumophila (including subspp. pneumophila, subspp. fraseri, and subspp. pasculleii) and one non-pathogenic species, L. fairfieldensis. Twenty-nine probes that reproducibly detected multiple Legionella species with high specificity were included in the array. A total of 52 strains, including 30 target pathogens and 22 non-target bacteria, were used to verify the oligonucleotide microarray assay. The sensitivity of the detection was at 1.0 ng with genomic DNA or 13 CFU/100 mL with Legionella cultures. The microarray detected seven samples of air conditioner-condensed water with 100% accuracy, validating the technique as a promising method for applications in basic microbiology, clinical diagnosis, food safety, and epidemiological surveillance. The phylogenetic study based on the ITS has also revealed that the non-pathogenic L. fairfieldensis is the closest to L. pneumophila than the nine other pathogenic Legionella spp.

  5. Development and validation of an oligonucleotide microarray to characterise ectomycorrhizal fungal communities

    Directory of Open Access Journals (Sweden)

    Reich Marlis

    2009-01-01

    Full Text Available Abstract Background In forest ecosystems, communities of ectomycorrhizal fungi (ECM are influenced by several biotic and abiotic factors. To understand their underlying dynamics, ECM communities have been surveyed with ribosomal DNA-based sequencing methods. However, most identification methods are both time-consuming and limited by the number of samples that can be treated in a realistic time frame. As a result of ongoing implementation, the array technique has gained throughput capacity in terms of the number of samples and the capacity for parallel identification of several species. Thus far, although phylochips (microarrays that are used to detect species have been mostly developed to trace bacterial communities or groups of specific fungi, no phylochip has been developed to carry oligonucleotides for several ectomycorrhizal species that belong to different genera. Results We have constructed a custom ribosomal DNA phylochip to identify ECM fungi. Specific oligonucleotide probes were targeted to the nuclear internal transcribed spacer (ITS regions from 95 fungal species belonging to 21 ECM fungal genera. The phylochip was first validated using PCR amplicons of reference species. Ninety-nine percent of the tested oligonucleotides generated positive hybridisation signals with their corresponding amplicons. Cross-hybridisation was mainly restricted at the genus level, particularly for Cortinarius and Lactarius species. The phylochip was subsequently tested with environmental samples that were composed of ECM fungal DNA from spruce and beech plantation fungal communities. The results were in concordance with the ITS sequencing of morphotypes and the ITS clone library sequencing results that were obtained using the same PCR products. Conclusion For the first time, we developed a custom phylochip that is specific for several ectomycorrhizal fungi. To overcome cross-hybridisation problems, specific filter and evaluation strategies that used spot

  6. Design and verification of a pangenome microarray oligonucleotide probe set for Dehalococcoides spp.

    Science.gov (United States)

    Hug, Laura A; Salehi, Maryam; Nuin, Paulo; Tillier, Elisabeth R; Edwards, Elizabeth A

    2011-08-01

    Dehalococcoides spp. are an industrially relevant group of Chloroflexi bacteria capable of reductively dechlorinating contaminants in groundwater environments. Existing Dehalococcoides genomes revealed a high level of sequence identity within this group, including 98 to 100% 16S rRNA sequence identity between strains with diverse substrate specificities. Common molecular techniques for identification of microbial populations are often not applicable for distinguishing Dehalococcoides strains. Here we describe an oligonucleotide microarray probe set designed based on clustered Dehalococcoides genes from five different sources (strain DET195, CBDB1, BAV1, and VS genomes and the KB-1 metagenome). This "pangenome" probe set provides coverage of core Dehalococcoides genes as well as strain-specific genes while optimizing the potential for hybridization to closely related, previously unknown Dehalococcoides strains. The pangenome probe set was compared to probe sets designed independently for each of the five Dehalococcoides strains. The pangenome probe set demonstrated better predictability and higher detection of Dehalococcoides genes than strain-specific probe sets on nontarget strains with pangenome probe set performs more robustly than the combined strain-specific probe sets in the detection of genes not included in the original design. The pangenome probe set represents a highly specific, universal tool for the detection and characterization of Dehalococcoides from contaminated sites. It has the potential to become a common platform for Dehalococcoides-focused research, allowing meaningful comparisons between microarray experiments regardless of the strain examined.

  7. Development of an oligonucleotide microarray for the detection and monitoring of marine dinoflagellates.

    Science.gov (United States)

    Galluzzi, Luca; Cegna, Alessandra; Casabianca, Silvia; Penna, Antonella; Saunders, Nick; Magnani, Mauro

    2011-02-01

    Harmful Algal Blooms (HABs), mainly caused by dinoflagellates and diatoms, have great economic and sanitary implications. An important contribution for the comprehension of HAB phenomena and for the identification of risks related to toxic algal species is given by the monitoring programs. In the microscopy-based monitoring methods, harmful species are distinguished through their morphological characteristics. This can be time consuming and requires great taxonomic expertise due to the existence of morphologically close-related species. The high throughput, automation possibility and specificity of microarray-based detection assay, makes this technology very promising for qualitative detection of HAB species. In this study, an oligonucleotide microarray targeted to the ITS1-5.8S-ITS2 rDNA region of nine toxic dinoflagellate species/clades was designed and evaluated. Two probes (45-47 nucleotides in length) were designed for each species/clade to reduce the potential for false positives. The specificity and sensitivity of the probes were evaluated with ITS1-5.8S-ITS2 PCR amplicons obtained from 20 dinoflagellates cultured strains. Cross hybridization experiments confirmed the probe specificity; moreover, the assay showed a good sensitivity, allowing the detection of up to 2 ng of labeled PCR product. The applicability of the assay with field samples was demonstrated using net concentrated seawater samples, un-spiked or spiked with known amounts of cultured cells. Despite the general application of microarray technology for harmful algae detection is not new, a peculiar group of target species/clades has been included in this new-format assay. Moreover, novelties regarding mainly the probes and the target rDNA region have allowed sensitivity improvements in comparison to previously published studies.

  8. Detection and identification of enterohemorrhagic Escherichia coli O157:H7 and Vibrio cholerae O139 using oligonucleotide microarray

    Directory of Open Access Journals (Sweden)

    Zhang Zheng

    2007-12-01

    Full Text Available Abstract Background The rapid and accurate detection and identification of the new subtype of the pathogens is crucial for diagnosis, treatment and control of the contagious disease outbreak. Here, in this study, an approach to detect and identify Escherichia coli O157:H7 and Vibrio cholerae O139 was established using oligonucleotide microarray. We coupled multiplex PCR with oligonucleotide microarray to construct an assay suitable for simultaneous identification of two subtypes of the pathogens. Results The stx1, stx2 gene and uidA gene having the specific mutant spot were chosen as the targets for Escherichia coli O157:H7, and meanwhile the ctxA, tcpA, and LPSgt gene for Vibrio cholerae O139. The oligonucleotide microarray was composed of eight probes including negative control and positive control from 16S rDNA gene. The six primers were designed to amplify target fragments in two triplex PCR, and then hybridized with oligonucleotide microarray. An internal control would be to run a PCR reaction in parallel. Multiplex PCR did not produce any non-specific amplicons when 149 related species or genera of standard bacteria were tested (100% specificity. In addition, Escherichia coli O157:H7 and Escherichia coli O157:non-H7, Vibrio cholerae O139 and Vibrio cholerae O1 had been discriminated respectively. Using recombinant plasmid and target pathogens, we were able to detect positive hybridization signals with 102 copies/μL and 103 cfu/mL per reaction. Conclusion The DNA microarray assay reported here could detect and identify Escherichia coli O157:H7 and Vibrio cholerae O139, and furthermore the subtype was distinguished. This assay was a specific and sensitive tool for simultaneous detection and identification of the new subtype of two pathogens causing diarrhea in human.

  9. Early changes in gene expression profiles of hepatic GVHD uncovered by oligonucleotide microarrays.

    Science.gov (United States)

    Ichiba, Tamotsu; Teshima, Takanori; Kuick, Rork; Misek, David E; Liu, Chen; Takada, Yuichiro; Maeda, Yoshinobu; Reddy, Pavan; Williams, Debra L; Hanash, Samir M; Ferrara, James L M

    2003-07-15

    The liver, skin, and gastrointestinal tract are major target organs of acute graft-versus-host disease (GVHD), the major complication of allogeneic bone marrow transplantation (BMT). In order to gain a better understanding of acute GVHD in the liver, we compared the gene expression profiles of livers after experimental allogeneic and syngeneic BMT using oligonucleotide microarray. At 35 days after allogeneic BMT when hepatic GVHD was histologically evident, genes related to cellular effectors and acute-phase proteins were up-regulated, whereas genes largely related to metabolism and endocrine function were down-regulated. At day 7 after BMT before the development of histologic changes in the liver, interferon gamma (IFN-gamma)-inducible genes, major histocompatibility (MHC) class II molecules, and genes related to leukocyte trafficking had been up-regulated. Immunohistochemistry demonstrated that expression of IFN-gamma protein itself was increased in the spleen but not in hepatic tissue. These results suggest that the increased expression of genes associated with the attraction and activation of donor T cells induced by IFN-gamma early after BMT is important in the initiation of hepatic GVHD in this model and provide new potential molecular targets for early detection and intervention of acute GVHD.

  10. Gene Expression Profile Differences in Gastric Cancer and Normal Gastric Mucosa by Oligonucleotide Microarrays

    Institute of Scientific and Technical Information of China (English)

    Chuanding Yu; Shenhua Xu; HangZhou Mou; Zhiming Jiang; Chihong Zhu; Xianglin Liu

    2006-01-01

    OBJECTIVE To study the difference of gene expression in gastric cancer (T) and normal tissue of gastric mucosa (C), and to screen for associated novel genes in gastric cancers by oligonucleotide microarrays.METHODS U133A (Affymetrix, Santa Clara, CA) gene chip was used to detect the gene expression profile difference in T and C. Bioinformatics was used to analyze the detected results.RESULTS When gastric cancers were compared with normal gastric mucosa, a total of 270 genes were found with a difference of more than 9times in expression levels. Of the 270 genes, 157 were up-regulated (Signal Log Ratio [SLR] ≥3), and 113 were down-regulated (SLR ≤-3).Using a classification of function, the highest number of gene expression differences related to enzymes and their regulatory genes (67, 24.8%),followed by signal-transduction genes (43,15.9%). The third were nucleic acid binding genes (17, 6.3%), fourth were transporter genes (15, 5.5%)and fifth were protein binding genes (12, 4.4%). In addition there were 50genes of unknown function, accounting for 18.5%. The five above mentioned groups made up 56.9% of the total gene number.CONCLUSION The 5 gene groups (enzymes and their regulatory proteins, signal transduction proteins, nucleic acid binding proteins, transporter and protein binding) were abnormally expressed and are important genes for further study in gastric cancers.

  11. Optimization of candidate-gene SNP-genotyping by flexible oligonucleotide microarrays; analyzing variations in immune regulator genes of hay-fever samples

    Directory of Open Access Journals (Sweden)

    Beier Markus

    2007-08-01

    Full Text Available Abstract Background Genetic variants in immune regulator genes have been associated with numerous diseases, including allergies and cancer. Increasing evidence suggests a substantially elevated disease risk in individuals who carry a combination of disease-relevant single nucleotide polymorphisms (SNPs. For the genotyping of immune regulator genes, such as cytokines, chemokines and transcription factors, an oligonucleotide microarray for the analysis of 99 relevant SNPs was established. Since the microarray design was based on a platform that permits flexible in situ oligonucleotide synthesis, a set of optimally performing probes could be defined by a selection approach that combined computational and experimental aspects. Results While the in silico process eliminated 9% of the initial probe set, which had been picked purely on the basis of potential association with disease, the subsequent experimental validation excluded more than twice as many. The performance of the optimized microarray was demonstrated in a pilot study. The genotypes of 19 hay-fever patients (aged 40–44 with high IgE levels against inhalant antigens were compared to the results obtained with 19 age- and sex-matched controls. For several variants, allele-frequency differences of more than 10% were identified. Conclusion Based on the ability to improve empirically a chip design, the application of candidate-SNP typing represents a viable approach in the context of molecular epidemiological studies.

  12. Combining microarrays and genetic analysis

    NARCIS (Netherlands)

    Alberts, Rudi; Fu, Jingyuan; Swertz, Morris A.; Lubbers, L. Alrik; Albers, Casper J.; Jansen, Ritsert C.

    2005-01-01

    Gene expression can be studied at a genome-wide scale with the aid of modern microarray technologies. Expression profiling of tens to hundreds of individuals in a genetic population can reveal the consequences of genetic variation. In this paper it is argued that the design and analysis of such a

  13. Combining microarrays and genetic analysis

    NARCIS (Netherlands)

    Alberts, Rudi; Fu, Jingyuan; Swertz, Morris A.; Lubbers, L. Alrik; Albers, Casper J.; Jansen, Ritsert C.

    2005-01-01

    Gene expression can be studied at a genome-wide scale with the aid of modern microarray technologies. Expression profiling of tens to hundreds of individuals in a genetic population can reveal the consequences of genetic variation. In this paper it is argued that the design and analysis of such a st

  14. Development of a Method for Profiling Protein Interactions with LNA-Modified Antisense Oligonucleotides Using Protein Microarrays.

    Science.gov (United States)

    Kakiuchi-Kiyota, Satoko; Whiteley, Lawrence O; Ryan, Anne M; Mathialagan, Nagappan

    2016-04-01

    Development of locked nucleic acid (LNA) gapmers, antisense oligonucleotides used for efficient inhibition of target RNA expression, is limited by nontarget-mediated hepatotoxicity. Increased binding of hepatocellular proteins to toxic LNA gapmers may be one of the mechanisms contributing to LNA gapmer-induced hepatotoxicity in vivo. In the present study, we investigated the protein binding propensity of nontoxic sequence-1 (NTS-1), toxic sequence-2 (TS-2), and severely highly toxic sequence-3 (HTS-3) LNA gapmers using human protein microarrays. We previously demonstrated by the transcription profiling analysis of liver RNA isolated from mice that TS-2 and HTS-3 gapmers modulate different transcriptional pathways in mice leading to hepatotoxicity. Our protein array profiling demonstrated that a greater number of proteins, including ones associated with hepatotoxicity, hepatic system disorder, and cell functions, were bound by TS-2 and HTS-3 compared with NTS-1. However, the profiles of proteins bound by TS-2 and HTS-3 were similar and did not distinguish proteins contributing to severe in vivo toxicity. These results, together with the previous transcription profiling analysis, indicate that the combination of sequence-dependent transcription modulation and increased protein binding of toxic LNA gapmers contributes to hepatotoxicity.

  15. Microarray Applications in Cancer Research

    Science.gov (United States)

    Kim, Il-Jin; Kang, Hio Chung

    2004-01-01

    DNA microarray technology permits simultaneous analysis of thousands of DNA sequences for genomic research and diagnostics applications. Microarray technology represents the most recent and exciting advance in the application of hybridization-based technology for biological sciences analysis. This review focuses on the classification (oligonucleotide vs. cDNA) and application (mutation-genotyping vs. gene expression) of microarrays. Oligonucleotide microarrays can be used both in mutation-genotyping and gene expression analysis, while cDNA microarrays can only be used in gene expression analysis. We review microarray mutation analysis, including examining the use of three oligonucleotide microarrays developed in our laboratory to determine mutations in RET, β-catenin and K-ras genes. We also discuss the use of the Affymetrix GeneChip in mutation analysis. We review microarray gene expression analysis, including the classifying of such studies into four categories: class comparison, class prediction, class discovery and identification of biomarkers. PMID:20368836

  16. Screening genetically modified organisms using multiplex-PCR coupled with oligonucleotide microarray.

    Science.gov (United States)

    Xu, Jia; Miao, Haizhen; Wu, Houfei; Huang, Wensheng; Tang, Rong; Qiu, Minyan; Wen, Jianguo; Zhu, Shuifang; Li, Yao

    2006-07-15

    In this research, we developed a multiplex polymerase chain reaction (multiplex-PCR) coupled with a DNA microarray system simultaneously aiming at many targets in a consecutive reaction to detect a genetically modified organism (GMO). There are a total of 20 probes for detecting a GMO in a DNA microarray which can be classified into three categories according to their purpose: the first for screening GMO from un-transgenic plants based on the common elements such as promoter, reporter and terminator genes; the second for specific gene confirmation based on the target gene sequences such as herbicide-resistance or insect-resistance genes; the third for species-specific genes which the sequences are unique for different plant species. To ensure the reliability of this method, different kinds of positive and negative controls were used in DNA microarray. Commercial GM soybean, maize, rapeseed and cotton were identified by means of this method and further confirmed by PCR analysis and sequencing. The results indicate that this method discriminates between the GMOs very quickly and in a cost-saving and more time efficient way. It can detect more than 95% of currently commercial GMO plants and the limits of detection are 0.5% for soybean and 1% for maize. This method is proved to be a new method for routine analysis of GMOs.

  17. Structured oligonucleotides for target indexing to allow single-vessel PCR amplification and solid support microarray hybridization.

    Science.gov (United States)

    Girard, Laurie D; Boissinot, Karel; Peytavi, Régis; Boissinot, Maurice; Bergeron, Michel G

    2015-02-07

    The combination of molecular diagnostic technologies is increasingly used to overcome limitations on sensitivity, specificity or multiplexing capabilities, and provide efficient lab-on-chip devices. Two such techniques, PCR amplification and microarray hybridization are used serially to take advantage of the high sensitivity and specificity of the former combined with high multiplexing capacities of the latter. These methods are usually performed in different buffers and reaction chambers. However, these elaborate methods have high complexity and cost related to reagent requirements, liquid storage and the number of reaction chambers to integrate into automated devices. Furthermore, microarray hybridizations have a sequence dependent efficiency not always predictable. In this work, we have developed the concept of a structured oligonucleotide probe which is activated by cleavage from polymerase exonuclease activity. This technology is called SCISSOHR for Structured Cleavage Induced Single-Stranded Oligonucleotide Hybridization Reaction. The SCISSOHR probes enable indexing the target sequence to a tag sequence. The SCISSOHR technology also allows the combination of nucleic acid amplification and microarray hybridization in a single vessel in presence of the PCR buffer only. The SCISSOHR technology uses an amplification probe that is irreversibly modified in presence of the target, releasing a single-stranded DNA tag for microarray hybridization. Each tag is composed of a 3-nucleotide sequence-dependent segment and a unique "target sequence-independent" 14-nucleotide segment allowing for optimal hybridization with minimal cross-hybridization. We evaluated the performance of five (5) PCR buffers to support microarray hybridization, compared to a conventional hybridization buffer. Finally, as a proof of concept, we developed a multiplexed assay for the amplification, detection, and identification of three (3) DNA targets. This new technology will facilitate the design

  18. Tests for differential gene expression using weights in oligonucleotide microarray experiments

    Directory of Open Access Journals (Sweden)

    Beyene Joseph

    2006-02-01

    Full Text Available Abstract Background Microarray data analysts commonly filter out genes based on a number of ad hoc criteria prior to any high-level statistical analysis. Such ad hoc approaches could lead to conflicting conclusions with no clear guidance as to which method is most likely to be reproducible. Furthermore, the number of tests performed with concomitant inflation in type I error also plagues the statistical analysis of microarray data, since the number of tested quantities in a study significantly affects the family-wise error rate. It would, therefore, be very useful to develop and adopt strategies that allow quantification of the quality of each probeset, to filter out or give little credence to low-quality or unexpressed probesets, and to incorporate these strategies into gene selection within a multiple testing framework. Results We have proposed a unified scheme for filtering and gene selection. For Affymetrix gene expression microarrays, we developed new methods for measuring the reliability of a particular probeset in a single array, and we used these to develop measures for a set of arrays. These measures are then used as weights in standard t-statistic calculations, and are incorporated into the multiple testing procedures. We demonstrated the advantages of our methods using simulated data, publicly available spiked-in data as well as data comparing normal muscle to muscle from patients with Duchenne muscular dystrophy (DMD, in which a set of truly differentially expressed genes is known. Conclusion Our quality measures provide convenient ways to search for individual genes of high quality. The quality weighting strategies we proposed for testing differential gene expression have demonstrable improvement on the traditional filtering methods, the standard t-statistic and a regularized t-statistic in Affymetrix data analysis.

  19. Detection of cancer with serum miRNAs on an oligonucleotide microarray.

    Directory of Open Access Journals (Sweden)

    Michael J Lodes

    Full Text Available Micro RNAs (miRNAs are a class of small, non-coding RNA species that play critical roles throughout cellular development and regulation. miRNA expression patterns taken from various tissue types often point to the cellular lineage of an individual tissue type, thereby being a more invariant hallmark of tissue type. Recent work has shown that these miRNA expression patterns can be used to classify tumor cells, and that this classification can be more accurate than the classification achieved by using messenger RNA gene expression patterns. One aspect of miRNA biogenesis that makes them particularly attractive as a biomarker is the fact that they are maintained in a protected state in serum and plasma, thus allowing the detection of miRNA expression patterns directly from serum. This study is focused on the evaluation of miRNA expression patterns in human serum for five types of human cancer, prostate, colon, ovarian, breast and lung, using a pan-human microRNA, high density microarray. This microarray platform enables the simultaneous analysis of all human microRNAs by either fluorescent or electrochemical signals, and can be easily redesigned to include newly identified miRNAs. We show that sufficient miRNAs are present in one milliliter of serum to detect miRNA expression patterns, without the need for amplification techniques. In addition, we are able to use these expression patterns to correctly discriminate between normal and cancer patient samples.

  20. A comparative analysis of existing oligonucleotides selection ...

    African Journals Online (AJOL)

    SERVER

    2007-07-04

    Jul 4, 2007 ... In system biology, DNA microarray technology is an indispensable tool for the ... the microarray probes are of critical importance for the hybridization experiments as ... at unraveling molecular systems (the function of the gen-.

  1. Comparison of three microarray probe annotation pipelines: differences in strategies and their effect on downstream analysis

    NARCIS (Netherlands)

    Neerincx, P.B.T.; Casel, P.; Prickett, D.; Nie, H.; Watson, M.; Leunissen, J.A.M.; Groenen, M.A.M.; Klopp, C.

    2009-01-01

    Background - Reliable annotation linking oligonucleotide probes to target genes is essential for functional biological analysis of microarray experiments. We used the IMAD, OligoRAP and sigReannot pipelines to update the annotation for the ARK-Genomics Chicken 20 K array as part of a joined EADGENE/

  2. Comparison of three microarray probe annotation pipelines: differences in strategies and their effect on downstream analysis

    NARCIS (Netherlands)

    Neerincx, P.B.T.; Casel, P.; Prickett, D.; Nie, H.; Watson, M.; Leunissen, J.A.M.; Groenen, M.A.M.; Klopp, C.

    2009-01-01

    Background - Reliable annotation linking oligonucleotide probes to target genes is essential for functional biological analysis of microarray experiments. We used the IMAD, OligoRAP and sigReannot pipelines to update the annotation for the ARK-Genomics Chicken 20 K array as part of a joined EADGENE/

  3. Three microarray platforms: an analysis of their concordance in profiling gene expression

    Directory of Open Access Journals (Sweden)

    Petersen David

    2005-05-01

    Full Text Available Abstract Background Microarrays for the analysis of gene expression are of three different types: short oligonucleotide (25–30 base, long oligonucleotide (50–80 base, and cDNA (highly variable in length. The short oligonucleotide and cDNA arrays have been the mainstay of expression analysis to date, but long oligonucleotide platforms are gaining in popularity and will probably replace cDNA arrays. As part of a validation study for the long oligonucleotide arrays, we compared and contrasted expression profiles from the three formats, testing RNA from six different cell lines against a universal reference standard. Results The three platforms had 6430 genes in common. In general, correlation of gene expression levels across the platforms was good when defined by concordance in the direction of expression difference (upregulation or downregulation, scatter plot analysis, principal component analysis, cell line correlation or quantitative RT-PCR. The overall correlations (r values between platforms were in the range 0.7 to 0.8, as determined by analysis of scatter plots. When concordance was measured for expression ratios significant at p-values of Conclusion Our results indicate that the long oligonucleotide platform is highly suitable for expression analysis and compares favorably with the cDNA and short oligonucleotide varieties. All three platforms can give similar and reproducible results if the criterion is the direction of change in gene expression and minimal emphasis is placed on the magnitude of change.

  4. An Efficient Covalent Coating on Glass Slides for Preparation of Optical Oligonucleotide Microarrays

    Directory of Open Access Journals (Sweden)

    Atefeh Pourjahed

    2013-12-01

    The agarose-PLL microarrays had the highest signal (2546 and lowest background signal (205 in hybridization, suggesting that the prepared slides are suitable in analyzing wide concentration range of analytes.

  5. Pineal function: impact of microarray analysis

    DEFF Research Database (Denmark)

    Klein, David C; Bailey, Michael J; Carter, David A

    2009-01-01

    Microarray analysis has provided a new understanding of pineal function by identifying genes that are highly expressed in this tissue relative to other tissues and also by identifying over 600 genes that are expressed on a 24-h schedule. This effort has highlighted surprising similarity...... foundation that microarray analysis has provided will broadly support future research on pineal function....

  6. Oliz, a suite of Perl scripts that assist in the design of microarrays using 50mer oligonucleotides from the 3' untranslated region

    Directory of Open Access Journals (Sweden)

    Sharp Burt M

    2002-10-01

    Full Text Available Abstract Background Identifying reliable oligonucleotide sequences for use in microarray experiments is a complex process. Two key issues are the accuracy of the input sequences and the specificity of the oligonucleotide sequences. Results We provide a suite of Perl scripts that facilitates the search for gene-specific oligonucleotides for microarray experiments. Genes of interest are first identified in the form of UniGene clusters. The sequences of these clusters were extracted and assembled into contigs to increase their accuracy. The 3' untranslated region (3'UTR of the contig was parsed. Then, multiple 50mer oligonucleotide sequences with similar melting temperature were obtained from each 3'UTR. These sequences were analyzed for gene specificity. Five Cy3-labeled cDNAs were used to empirically verify the specificity of a set of 1814 50mers. Conclusion Oliz can be used to select oligonucleotide sequences for microarrays. Oliz is freely available for academic users at http://www.utmem.edu/pharmacology/otherlinks/oliz.html

  7. High-density rhesus macaque oligonucleotide microarray design using early-stage rhesus genome sequence information and human genome annotations

    Directory of Open Access Journals (Sweden)

    Magness Charles L

    2007-01-01

    Full Text Available Abstract Background Until recently, few genomic reagents specific for non-human primate research have been available. To address this need, we have constructed a macaque-specific high-density oligonucleotide microarray by using highly fragmented low-pass sequence contigs from the rhesus genome project together with the detailed sequence and exon structure of the human genome. Using this method, we designed oligonucleotide probes to over 17,000 distinct rhesus/human gene orthologs and increased by four-fold the number of available genes relative to our first-generation expressed sequence tag (EST-derived array. Results We constructed a database containing 248,000 exon sequences from 23,000 human RefSeq genes and compared each human exon with its best matching sequence in the January 2005 version of the rhesus genome project list of 486,000 DNA contigs. Best matching rhesus exon sequences for each of the 23,000 human genes were then concatenated in the proper order and orientation to produce a rhesus "virtual transcriptome." Microarray probes were designed, one per gene, to the region closest to the 3' untranslated region (UTR of each rhesus virtual transcript. Each probe was compared to a composite rhesus/human transcript database to test for cross-hybridization potential yielding a final probe set representing 18,296 rhesus/human gene orthologs, including transcript variants, and over 17,000 distinct genes. We hybridized mRNA from rhesus brain and spleen to both the EST- and genome-derived microarrays. Besides four-fold greater gene coverage, the genome-derived array also showed greater mean signal intensities for genes present on both arrays. Genome-derived probes showed 99.4% identity when compared to 4,767 rhesus GenBank sequence tag site (STS sequences indicating that early stage low-pass versions of complex genomes are of sufficient quality to yield valuable functional genomic information when combined with finished genome information from

  8. A newly designed 45 to 60 mer oligonucleotide Agilent platform microarray for global gene expression studies of Synechocystis PCC6803: example salt stress experiment

    NARCIS (Netherlands)

    Aguirre von Wobeser, E.; Huisman, J.; Ibelings, B.; Matthijs, H.C.P.; Matthijs, H.C.P.

    2005-01-01

    A newly designed 45 to 60 mer oligonucleotide Agilent platform microarray for global gene expression studies of Synechocystis PCC6803: example salt stress experiment Eneas Aguirre-von-Wobeser 1, Jef Huisman1, Bas Ibelings2 and Hans C.P. Matthijs1 1 Universiteit van Amsterdam, Amsterdam, The Netherla

  9. The EADGENE Microarray Data Analysis Workshop

    NARCIS (Netherlands)

    Koning, de D.J.; Jaffrezic, F.; Lund, M.S.; Watson, M.; Channing, C.; Hulsegge, B.; Pool, M.H.; Buitenhuis, B.; Hedegaard, J.; Hornshoj, H.; Sorensen, P.; Marot, G.; Delmas, C.; Lê Cao, K.A.; San Cristobal, M.; Baron, M.D.; Malinverni, R.; Stella, A.; Brunner, R.M.; Seyfert, H.M.; Jensen, K.; Mouzaki, D.; Waddington, D.; Jiménez-Marín, A.; Perez-Alegre, M.; Perez-Reinado, E.; Closset, R.; Detilleux, J.C.; Dovc, P.; Lavric, M.; Nie, H.; Janss, L.

    2007-01-01

    Microarray analyses have become an important tool in animal genomics. While their use is becoming widespread, there is still a lot of ongoing research regarding the analysis of microarray data. In the context of a European Network of Excellence, 31 researchers representing 14 research groups from 10

  10. D-MaPs - DNA-microarray projects: web-based software for multi-platform microarray analysis

    Directory of Open Access Journals (Sweden)

    Marcelo F. Carazzolle

    2009-01-01

    Full Text Available The web application D-Maps provides a user-friendly interface to researchers performing studies based on microarrays. The program was developed to manage and process one- or two-color microarray data obtained from several platforms (currently, GeneTAC, ScanArray, CodeLink, NimbleGen and Affymetrix. Despite the availability of many algorithms and many software programs designed to perform microarray analysis on the internet, these usually require sophisticated knowledge of mathematics, statistics and computation. D-maps was developed to overcome the requirement of high performance computers or programming experience. D-Maps performs raw data processing, normalization and statistical analysis, allowing access to the analyzed data in text or graphical format. An original feature presented by D-Maps is GEO (Gene Expression Omnibus submission format service. The D-MaPs application was already used for analysis of oligonucleotide microarrays and PCR-spotted arrays (one- and two-color, laser and light scanner. In conclusion, D-Maps is a valuable tool for microarray research community, especially in the case of groups without a bioinformatic core.

  11. Quantitative profiling of housekeeping and Epstein-Barr virus gene transcription in Burkitt lymphoma cell lines using an oligonucleotide microarray

    Directory of Open Access Journals (Sweden)

    Niggli Felix K

    2006-06-01

    Full Text Available Abstract Background The Epstein-Barr virus (EBV is associated with lymphoid malignancies, including Burkitt's lymphoma (BL, and can transform human B cells in vitro. EBV-harboring cell lines are widely used to investigate lymphocyte transformation and oncogenesis. Qualitative EBV gene expression has been extensively described, but knowledge of quantitative transcription is lacking. We hypothesized that transcription levels of EBNA1, the gene essential for EBV persistence within an infected cell, are similar in BL cell lines. Results To compare quantitative gene transcription in the BL cell lines Namalwa, Raji, Akata, Jijoye, and P3HR1, we developed an oligonucleotide microarray chip, including 17 housekeeping genes, six latent EBV genes (EBNA1, EBNA2, EBNA3A, EBNA3C, LMP1, LMP2, and four lytic EBV genes (BZLF1, BXLF2, BKRF2, BZLF2, and used the cell line B95.8 as a reference for EBV gene transcription. Quantitative polymerase chain reaction assays were used to validate microarray results. We found that transcription levels of housekeeping genes differed considerably among BL cell lines. Using a selection of housekeeping genes with similar quantitative transcription in the tested cell lines to normalize EBV gene transcription data, we showed that transcription levels of EBNA1 were quite similar in very different BL cell lines, in contrast to transcription levels of other EBV genes. As demonstrated with Akata cells, the chip allowed us to accurately measure EBV gene transcription changes triggered by treatment interventions. Conclusion Our results suggest uniform EBNA1 transcription levels in BL and that microarray profiling can reveal novel insights on quantitative EBV gene transcription and its impact on lymphocyte biology.

  12. MARS: Microarray analysis, retrieval, and storage system

    Directory of Open Access Journals (Sweden)

    Scheideler Marcel

    2005-04-01

    Full Text Available Abstract Background Microarray analysis has become a widely used technique for the study of gene-expression patterns on a genomic scale. As more and more laboratories are adopting microarray technology, there is a need for powerful and easy to use microarray databases facilitating array fabrication, labeling, hybridization, and data analysis. The wealth of data generated by this high throughput approach renders adequate database and analysis tools crucial for the pursuit of insights into the transcriptomic behavior of cells. Results MARS (Microarray Analysis and Retrieval System provides a comprehensive MIAME supportive suite for storing, retrieving, and analyzing multi color microarray data. The system comprises a laboratory information management system (LIMS, a quality control management, as well as a sophisticated user management system. MARS is fully integrated into an analytical pipeline of microarray image analysis, normalization, gene expression clustering, and mapping of gene expression data onto biological pathways. The incorporation of ontologies and the use of MAGE-ML enables an export of studies stored in MARS to public repositories and other databases accepting these documents. Conclusion We have developed an integrated system tailored to serve the specific needs of microarray based research projects using a unique fusion of Web based and standalone applications connected to the latest J2EE application server technology. The presented system is freely available for academic and non-profit institutions. More information can be found at http://genome.tugraz.at.

  13. The EADGENE Microarray Data Analysis Workshop

    DEFF Research Database (Denmark)

    de Koning, Dirk-Jan; Jaffrézic, Florence; Lund, Mogens Sandø

    2007-01-01

    Microarray analyses have become an important tool in animal genomics. While their use is becoming widespread, there is still a lot of ongoing research regarding the analysis of microarray data. In the context of a European Network of Excellence, 31 researchers representing 14 research groups from...... 10 countries performed and discussed the statistical analyses of real and simulated 2-colour microarray data that were distributed among participants. The real data consisted of 48 microarrays from a disease challenge experiment in dairy cattle, while the simulated data consisted of 10 microarrays...... statistical weights, to omitting a large number of spots or omitting entire slides. Surprisingly, these very different approaches gave quite similar results when applied to the simulated data, although not all participating groups analysed both real and simulated data. The workshop was very successful...

  14. Cross-species hybridization of woodchuck hepatitis virus-induced hepatocellular carcinoma using human oligonucleotide microarrays

    Institute of Scientific and Technical Information of China (English)

    Paul W Anderson; Bud C Tennant; Zhenghong Lee

    2006-01-01

    AIM: To demonstrate the feasibility of using woodchuck samples on human microarrays, to provide insight into pathways involving positron emission tomography (PET) imaging tracers and to identify genes that could be potential molecular imaging targets for woodchuck hepatocellular carcinoma.METHODS: Labeled cRNA from woodchuck tissue samples were hybridized to Affymetrix U133 plus 2.0 GeneChips(R). Ten genes were selected for validation using quantitative RT-PCR and literature review was made.RESULTS: Testis enhanced gene transcript (BAX Inhibitor 1), alpha-fetoprotein, isocitrate dehydrogenase 3 (NAD+) beta, acetyl-CoA synthetase 2, carnitine palmitoyltransferase 2, and N-myc2 were up-regulated and spermidine/spermine N1-acetyltransferase was down-regulated in the woodchuck HCC. We also found previously published results supporting 8 of the 10 most up-regulated genes and all 10 of the 10 most downregulated genes.CONCLUSION: Many of our microarray results were validated using RT-PCR or literature search. Hence, we believe that woodchuck HCC and non-cancerous liver samples can be used on human microarrays to yield meaningful results.

  15. DNA sequence analysis by hybridization with oligonucleotide microchips : MALDI mass spectrometry identification of 5mers contiguously stacked to microchip oligonucleotides.

    Energy Technology Data Exchange (ETDEWEB)

    Stomakhin, A. A.; Vasiliskov, V. A.; Timofeev, E.; Schulga, D.; Cotter, R. J.; Mirzabekov, A. D.; Biochip Technology Center; Engelhardt Inst. of Molecular Biology; Moscow Inst. of Physics and Technology; Middle Atlantic Mass Spectrometry Lab.; Johns Hopkins Univ. School of Medicine

    2000-01-01

    Matrix-assisted laser desorption ionization mass spectrometry (MALDI MS) has been applied to increase the informational output from DNA sequence analysis. It has been used to analyze DNA by hybridization with microarrays of gel-immobilized oligonucleotides extended with stacked 5mers. In model experiments, a 28 nt long DNA fragment was hybridized with 10 immobilized, overlapping 8mers. Then, in a second round of hybridization DNA-8mer duplexes were hybridized with a mixture of 10 5mers. The stability of the 5mer complex with DNA was increased to raise the melting temperature of the duplex by 10-15{sup o}C as a result of stacking interaction with 8mers. Contiguous 13 bp duplexes containing an internal break were formed. MALDI MS identified one or, in some cases, two 5mers contiguously stacked to each DNA-8mer duplex formed on the microchip. Incorporating a mass label into 5mers optimized MALDI MS monitoring. This procedure enabled us to reconstitute the sequence of a model DNA fragment and identify polymorphic nucleotides. The application of MALDI MS identification of contiguously stacked 5mers to increase the length of DNA for sequence analysis is discussed.

  16. Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes

    Directory of Open Access Journals (Sweden)

    Eils Roland

    2005-11-01

    Full Text Available Abstract Background The extensive use of DNA microarray technology in the characterization of the cell transcriptome is leading to an ever increasing amount of microarray data from cancer studies. Although similar questions for the same type of cancer are addressed in these different studies, a comparative analysis of their results is hampered by the use of heterogeneous microarray platforms and analysis methods. Results In contrast to a meta-analysis approach where results of different studies are combined on an interpretative level, we investigate here how to directly integrate raw microarray data from different studies for the purpose of supervised classification analysis. We use median rank scores and quantile discretization to derive numerically comparable measures of gene expression from different platforms. These transformed data are then used for training of classifiers based on support vector machines. We apply this approach to six publicly available cancer microarray gene expression data sets, which consist of three pairs of studies, each examining the same type of cancer, i.e. breast cancer, prostate cancer or acute myeloid leukemia. For each pair, one study was performed by means of cDNA microarrays and the other by means of oligonucleotide microarrays. In each pair, high classification accuracies (> 85% were achieved with training and testing on data instances randomly chosen from both data sets in a cross-validation analysis. To exemplify the potential of this cross-platform classification analysis, we use two leukemia microarray data sets to show that important genes with regard to the biology of leukemia are selected in an integrated analysis, which are missed in either single-set analysis. Conclusion Cross-platform classification of multiple cancer microarray data sets yields discriminative gene expression signatures that are found and validated on a large number of microarray samples, generated by different laboratories and

  17. Triple X syndrome in a patient with partial lipodystrophy discovered using a high-density oligonucleotide microarray: a case report

    Directory of Open Access Journals (Sweden)

    Lanktree Matthew B

    2009-08-01

    Full Text Available Abstract Introduction Patients with lipodystrophy experience selective or generalized atrophy of adipose tissue. The disruption of lipid metabolism results in an increased risk for development of metabolic syndrome and coronary artery disease. Currently, the mutations responsible for approximately half of lipodystrophy patients are known, but new techniques and examination of different types of genetic variation may identify new disease-causing mechanisms. Case presentation A 53-year-old woman of African descent was referred to a tertiary care endocrinology clinic for treatment of severe insulin resistance, treatment-resistant hypertension and dyslipidemia. After all known lipodystrophy-causing mutations were excluded by DNA sequencing, the patient was found to have triple X syndrome after an initial investigation into copy number variation using a high-density oligonucleotide microarray. The patient also had a previously unobserved duplication of 415 kilobases of chromosome 5q33.2. This is the first case report of a patient with lipodystrophy who also had triple X syndrome. Conclusion While we cannot make a direct link between the presence of triple X syndrome and partial lipodystrophy, if unrelated, this is an extremely rare convergence of syndromes. This patient poses an interesting possibility regarding the influence triple X syndrome may have on an individual with other underlying lipodystrophy susceptibility. Finally, impending large-scale case-control and cohort copy number variation investigations will, as a by-product, further document the prevalence of triple X syndrome in various patient groups.

  18. High resolution microarray comparative genomic hybridisation analysis using spotted oligonucleotides.

    NARCIS (Netherlands)

    Carvalho, B; Ouwerkerk, E; Meijer, G.A.; Ylstra, B.

    2004-01-01

    BACKGROUND: Currently, comparative genomic hybridisation array (array CGH) is the method of choice for studying genome wide DNA copy number changes. To date, either amplified representations of bacterial artificial chromosomes (BACs)/phage artificial chromosomes (PACs) or cDNAs have been spotted as

  19. The Impact of Photobleaching on Microarray Analysis

    Directory of Open Access Journals (Sweden)

    Marcel von der Haar

    2015-09-01

    Full Text Available DNA-Microarrays have become a potent technology for high-throughput analysis of genetic regulation. However, the wide dynamic range of signal intensities of fluorophore-based microarrays exceeds the dynamic range of a single array scan by far, thus limiting the key benefit of microarray technology: parallelization. The implementation of multi-scan techniques represents a promising approach to overcome these limitations. These techniques are, in turn, limited by the fluorophores’ susceptibility to photobleaching when exposed to the scanner’s laser light. In this paper the photobleaching characteristics of cyanine-3 and cyanine-5 as part of solid state DNA microarrays are studied. The effects of initial fluorophore intensity as well as laser scanner dependent variables such as the photomultiplier tube’s voltage on bleaching and imaging are investigated. The resulting data is used to develop a model capable of simulating the expected degree of signal intensity reduction caused by photobleaching for each fluorophore individually, allowing for the removal of photobleaching-induced, systematic bias in multi-scan procedures. Single-scan applications also benefit as they rely on pre-scans to determine the optimal scanner settings. These findings constitute a step towards standardization of microarray experiments and analysis and may help to increase the lab-to-lab comparability of microarray experiment results.

  20. Microarray analysis of the developing cortex.

    Science.gov (United States)

    Semeralul, Mawahib O; Boutros, Paul C; Likhodi, Olga; Okey, Allan B; Van Tol, Hubert H M; Wong, Albert H C

    2006-12-01

    Abnormal development of the prefrontal cortex (PFC) is associated with a number of neuropsychiatric disorders that have an onset in childhood or adolescence. Although the basic laminar structure of the PFC is established in utero, extensive remodeling continues into adolescence. To map the overall pattern of changes in cortical gene transcripts during postnatal development, we made serial measurements of mRNA levels in mouse PFC using oligonucleotide microarrays. We observed changes in mRNA transcripts consistent with known postnatal morphological and biochemical events. Overall, most transcripts that changed significantly showed a progressive decrease in abundance after birth, with the majority of change between postnatal weeks 2 and 4. Genes with cell proliferative, cytoskeletal, extracellular matrix, plasma membrane lipid/transport, protein folding, and regulatory functions had decreases in mRNA levels. Quantitative PCR verified the microarray results for six selected genes: DNA methyltransferase 3A (Dnmt3a), procollagen, type III, alpha 1 (Col3a1), solute carrier family 16 (monocarboxylic acid transporters), member 1 (Slc16a1), MARCKS-like 1 (Marcksl1), nidogen 1 (Nid1) and 3-hydroxybutyrate dehydrogenase (heart, mitochondrial) (Bdh).

  1. Microarray analysis of p-anisaldehyde-induced transcriptome of Saccharomyces cerevisiae.

    Science.gov (United States)

    Yu, Lu; Guo, Na; Yang, Yi; Wu, Xiuping; Meng, Rizeng; Fan, Junwen; Ge, Fa; Wang, Xuelin; Liu, Jingbo; Deng, Xuming

    2010-03-01

    p-Anisaldehyde (4-methoxybenzaldehyde), an extract from Pimpinella anisum L. seeds, is a potential novel preservative. To reveal the possible action mechanism of p-anisaldehyde against microorganisms, yeast-based commercial oligonucleotide microarrays were used to analyze the genome-wide transcriptional changes in response to p-anisaldehyde. Quantitative real-time RT-PCR was performed for selected genes to verify the microarray results. We interpreted our microarray data with the clustering tool, T-profiler. Analysis of microarray data revealed that p-anisaldehyde induced the expression of genes related to sulphur assimilation, aromatic aldehydes metabolism, and secondary metabolism, which demonstrated that the addition of p-anisaldehyde may influence the normal metabolism of aromatic aldehydes. This genome-wide transcriptomics approach revealed first insights into the response of Saccharomyces cerevisiae (S. cerevisiae) to p-anisaldehyde challenge.

  2. Binding specificity and stability of duplexes formed by modified oligonucleotides with a 4096-hexanucleotide microarray

    Science.gov (United States)

    Timofeev, Edward; Mirzabekov, Andrei

    2001-01-01

    The binding of oligodeoxynucleotides modified with adenine 2′-O-methyl riboside, 2,6-diaminopurine 2′-O-methyl riboside, cytosine 2′-O-methyl riboside, 2,6-diaminopurine deoxyriboside or 5-bromodeoxyuridine was studied with a microarray containing all possible (4096) polyacrylamide-bound hexadeoxynucleotides (a generic microchip). The generic microchip was manufactured by using reductive immobilization of aminooligonucleotides in the activated copolymer of acrylamide, bis-acrylamide and N-(2,2-dimethoxyethyl) acrylamide. The binding of the fluorescently labeled modified octanucleotides to the array was analyzed with the use of both melting profiles and the fluorescence distribution at selected temperatures. Up to three substitutions of adenosines in the octamer sequence by adenine 2′-O-methyl ribosides (Am), 2,6-diaminopurine 2′-O-methyl ribosides (Dm) or 2,6-diaminopurine deoxyribosides (D) resulted in increased mismatch discrimination measured at the melting temperature of the corresponding perfect duplex. The stability of complexes formed by 2′-O-methyl-adenosine-modified oligodeoxynucleotides was slightly decreased with every additional substitution, yielding ∼4°C of total loss in melting temperature for three modifications, as followed from microchip thermal denaturation experiments. 2,6-Diaminopurine 2′-O-methyl riboside modifications led to considerable duplex stabilization. The cytosine 2′-O-methyl riboside and 5-bromodeoxyuridine modifications generally did not change either duplex stability or mismatch resolution. Denaturation experiments conducted with selected perfect duplexes on microchips and in solution showed similar results on thermal stabilities. Some hybridization artifacts were observed that might indicate the formation of parallel DNA. PMID:11410672

  3. Rapid identification of carbapenemase genes in gram-negative bacteria with an oligonucleotide microarray-based assay.

    Science.gov (United States)

    Braun, Sascha D; Monecke, Stefan; Thürmer, Alexander; Ruppelt, Antje; Makarewicz, Oliwia; Pletz, Mathias; Reiβig, Annett; Slickers, Peter; Ehricht, Ralf

    2014-01-01

    Rapid molecular identification of carbapenemase genes in Gram-negative bacteria is crucial for infection control and prevention, surveillance and for epidemiological purposes. Furthermore, it may have a significant impact upon determining the appropriate initial treatment and greatly benefit for critically ill patients. A novel oligonucleotide microarray-based assay was developed to simultaneously detect genes encoding clinically important carbapenemases as well as selected extended (ESBL) and narrow spectrum (NSBL) beta-lactamases directly from clonal culture material within few hours. Additionally, a panel of species specific markers was included to identify Escherichia coli, Pseudomonas aeruginosa, Citrobacter freundii/braakii, Klebsiella pneumoniae and Acinetobacter baumannii. The assay was tested using a panel of 117 isolates collected from urinary, blood and stool samples. For these isolates, phenotypic identifications and susceptibility tests were available. An independent detection of carbapenemase, ESBL and NSBL genes was carried out by various external reference laboratories using PCR methods. In direct comparison, the microarray correctly identified 98.2% of the covered carbapenemase genes. This included blaVIM (13 out of 13), blaGIM (2/2), blaKPC (27/27), blaNDM (5/5), blaIMP-2/4/7/8/13/14/15/16/31 (10/10), blaOXA-23 (12/13), blaOXA-40-group (7/7), blaOXA-48-group (32/33), blaOXA-51 (1/1) and blaOXA-58 (1/1). Furthermore, the test correctly identified additional beta-lactamases [blaOXA-1 (16/16), blaOXA-2 (4/4), blaOXA-9 (33/33), OXA-10 (3/3), blaOXA-51 (25/25), blaOXA-58 (2/2), CTX-M1/M15 (17/17) and blaVIM (1/1)]. In direct comparison to phenotypical identification obtained by VITEK or MALDI-TOF systems, 114 of 117 (97.4%) isolates, including Acinetobacter baumannii (28/28), Enterobacter spec. (5/5), Escherichia coli (4/4), Klebsiella pneumoniae (62/63), Klebsiella oxytoca (0/2), Pseudomonas aeruginosa (12/12), Citrobacter freundii (1/1) and

  4. Rapid identification of carbapenemase genes in gram-negative bacteria with an oligonucleotide microarray-based assay.

    Directory of Open Access Journals (Sweden)

    Sascha D Braun

    Full Text Available Rapid molecular identification of carbapenemase genes in Gram-negative bacteria is crucial for infection control and prevention, surveillance and for epidemiological purposes. Furthermore, it may have a significant impact upon determining the appropriate initial treatment and greatly benefit for critically ill patients. A novel oligonucleotide microarray-based assay was developed to simultaneously detect genes encoding clinically important carbapenemases as well as selected extended (ESBL and narrow spectrum (NSBL beta-lactamases directly from clonal culture material within few hours. Additionally, a panel of species specific markers was included to identify Escherichia coli, Pseudomonas aeruginosa, Citrobacter freundii/braakii, Klebsiella pneumoniae and Acinetobacter baumannii. The assay was tested using a panel of 117 isolates collected from urinary, blood and stool samples. For these isolates, phenotypic identifications and susceptibility tests were available. An independent detection of carbapenemase, ESBL and NSBL genes was carried out by various external reference laboratories using PCR methods. In direct comparison, the microarray correctly identified 98.2% of the covered carbapenemase genes. This included blaVIM (13 out of 13, blaGIM (2/2, blaKPC (27/27, blaNDM (5/5, blaIMP-2/4/7/8/13/14/15/16/31 (10/10, blaOXA-23 (12/13, blaOXA-40-group (7/7, blaOXA-48-group (32/33, blaOXA-51 (1/1 and blaOXA-58 (1/1. Furthermore, the test correctly identified additional beta-lactamases [blaOXA-1 (16/16, blaOXA-2 (4/4, blaOXA-9 (33/33, OXA-10 (3/3, blaOXA-51 (25/25, blaOXA-58 (2/2, CTX-M1/M15 (17/17 and blaVIM (1/1]. In direct comparison to phenotypical identification obtained by VITEK or MALDI-TOF systems, 114 of 117 (97.4% isolates, including Acinetobacter baumannii (28/28, Enterobacter spec. (5/5, Escherichia coli (4/4, Klebsiella pneumoniae (62/63, Klebsiella oxytoca (0/2, Pseudomonas aeruginosa (12/12, Citrobacter freundii (1/1 and Citrobacter

  5. Rapid Identification of Carbapenemase Genes in Gram-Negative Bacteria with an Oligonucleotide Microarray-Based Assay

    Science.gov (United States)

    Braun, Sascha D.; Monecke, Stefan; Thürmer, Alexander; Ruppelt, Antje; Makarewicz, Oliwia; Pletz, Mathias; Reißig, Annett; Slickers, Peter; Ehricht, Ralf

    2014-01-01

    Rapid molecular identification of carbapenemase genes in Gram-negative bacteria is crucial for infection control and prevention, surveillance and for epidemiological purposes. Furthermore, it may have a significant impact upon determining the appropriate initial treatment and greatly benefit for critically ill patients. A novel oligonucleotide microarray-based assay was developed to simultaneously detect genes encoding clinically important carbapenemases as well as selected extended (ESBL) and narrow spectrum (NSBL) beta-lactamases directly from clonal culture material within few hours. Additionally, a panel of species specific markers was included to identify Escherichia coli, Pseudomonas aeruginosa, Citrobacter freundii/braakii, Klebsiella pneumoniae and Acinetobacter baumannii. The assay was tested using a panel of 117 isolates collected from urinary, blood and stool samples. For these isolates, phenotypic identifications and susceptibility tests were available. An independent detection of carbapenemase, ESBL and NSBL genes was carried out by various external reference laboratories using PCR methods. In direct comparison, the microarray correctly identified 98.2% of the covered carbapenemase genes. This included blaVIM (13 out of 13), blaGIM (2/2), blaKPC (27/27), blaNDM (5/5), blaIMP-2/4/7/8/13/14/15/16/31 (10/10), blaOXA-23 (12/13), blaOXA-40-group (7/7), blaOXA-48-group (32/33), blaOXA-51 (1/1) and blaOXA-58 (1/1). Furthermore, the test correctly identified additional beta-lactamases [blaOXA-1 (16/16), blaOXA-2 (4/4), blaOXA-9 (33/33), OXA-10 (3/3), blaOXA-51 (25/25), blaOXA-58 (2/2), CTX-M1/M15 (17/17) and blaVIM (1/1)]. In direct comparison to phenotypical identification obtained by VITEK or MALDI-TOF systems, 114 of 117 (97.4%) isolates, including Acinetobacter baumannii (28/28), Enterobacter spec. (5/5), Escherichia coli (4/4), Klebsiella pneumoniae (62/63), Klebsiella oxytoca (0/2), Pseudomonas aeruginosa (12/12), Citrobacter freundii (1/1) and

  6. Pineal function : Impact of microarray analysis

    NARCIS (Netherlands)

    Klein, David C.; Bailey, Michael J.; Carter, David A.; Kim, Jong-so; Shi, Qiong; Ho, Anthony K.; Chik, Constance L.; Gaildrat, Pascaline; Morin, Fabrice; Ganguly, Surajit; Rath, Martin F.; Moller, Morten; Sugden, David; Rangel, Zoila G.; Munson, Peter J.; Weller, Joan L.; Coon, Steven L.

    2010-01-01

    Microarray analysis has provided a new understanding of pineal function by identifying genes that are highly expressed in this tissue relative to other tissues and also by identifying over 600 genes that are expressed on a 24-h schedule. This effort has highlighted surprising similarity to the retin

  7. Evolution of the MIDTAL microarray: the adaption and testing of oligonucleotide 18S and 28S rDNA probes and evaluation of subsequent microarray generations with Prymnesium spp. cultures and field samples.

    Science.gov (United States)

    McCoy, Gary R; Touzet, Nicolas; Fleming, Gerard T A; Raine, Robin

    2015-07-01

    The toxic microalgal species Prymnesium parvum and Prymnesium polylepis are responsible for numerous fish kills causing economic stress on the aquaculture industry and, through the consumption of contaminated shellfish, can potentially impact on human health. Monitoring of toxic phytoplankton is traditionally carried out by light microscopy. However, molecular methods of identification and quantification are becoming more common place. This study documents the optimisation of the novel Microarrays for the Detection of Toxic Algae (MIDTAL) microarray from its initial stages to the final commercial version now available from Microbia Environnement (France). Existing oligonucleotide probes used in whole-cell fluorescent in situ hybridisation (FISH) for Prymnesium species from higher group probes to species-level probes were adapted and tested on the first-generation microarray. The combination and interaction of numerous other probes specific for a whole range of phytoplankton taxa also spotted on the chip surface caused high cross reactivity, resulting in false-positive results on the microarray. The probe sequences were extended for the subsequent second-generation microarray, and further adaptations of the hybridisation protocol and incubation temperatures significantly reduced false-positive readings from the first to the second-generation chip, thereby increasing the specificity of the MIDTAL microarray. Additional refinement of the subsequent third-generation microarray protocols with the addition of a poly-T amino linker to the 5' end of each probe further enhanced the microarray performance but also highlighted the importance of optimising RNA labelling efficiency when testing with natural seawater samples from Killary Harbour, Ireland.

  8. Bioinformatics/biostatistics: microarray analysis.

    Science.gov (United States)

    Eichler, Gabriel S

    2012-01-01

    The quantity and complexity of the molecular-level data generated in both research and clinical settings require the use of sophisticated, powerful computational interpretation techniques. It is for this reason that bioinformatic analysis of complex molecular profiling data has become a fundamental technology in the development of personalized medicine. This chapter provides a high-level overview of the field of bioinformatics and outlines several, classic bioinformatic approaches. The highlighted approaches can be aptly applied to nearly any sort of high-dimensional genomic, proteomic, or metabolomic experiments. Reviewed technologies in this chapter include traditional clustering analysis, the Gene Expression Dynamics Inspector (GEDI), GoMiner (GoMiner), Gene Set Enrichment Analysis (GSEA), and the Learner of Functional Enrichment (LeFE).

  9. Microarray analysis reveals the actual specificity of enrichment media used for food safety assessment.

    Science.gov (United States)

    Kostić, Tanja; Stessl, Beatrix; Wagner, Martin; Sessitsch, Angela

    2011-06-01

    Microbial diagnostic microarrays are tools for simultaneous detection and identification of microorganisms in food, clinical, and environmental samples. In comparison to classic methods, microarray-based systems have the potential for high throughput, parallelism, and miniaturization. High specificity and high sensitivity of detection have been demonstrated. A microbial diagnostic microarray for the detection of the most relevant bacterial food- and waterborne pathogens and indicator organisms was developed and thoroughly validated. The microarray platform based on sequence-specific end labeling of oligonucleotides and the phylogenetically robust gyrB marker gene allowed a highly specific (resolution on genus and/or species level) and sensitive (0.1% relative and 10(4) CFU absolute sensitivity) detection of the target pathogens. In initial challenge studies of the applicability of microarray-based food analysis, we obtained results demonstrating the questionable specificity of standardized culture-dependent microbiological detection methods. Taking into consideration the importance of reliable food safety assessment methods, comprehensive performance assessment is essential. Results demonstrate the potential of this new pathogen diagnostic microarray to evaluate culture-based standard methods in microbiological food analysis.

  10. Analysis of oligonucleotide array experiments with repeated measures using mixed models

    Directory of Open Access Journals (Sweden)

    Getchell Thomas V

    2004-12-01

    Full Text Available Abstract Background Two or more factor mixed factorial experiments are becoming increasingly common in microarray data analysis. In this case study, the two factors are presence (Patients with Alzheimer's disease or absence (Control of the disease, and brain regions including olfactory bulb (OB or cerebellum (CER. In the design considered in this manuscript, OB and CER are repeated measurements from the same subject and, hence, are correlated. It is critical to identify sources of variability in the analysis of oligonucleotide array experiments with repeated measures and correlations among data points have to be considered. In addition, multiple testing problems are more complicated in experiments with multi-level treatments or treatment combinations. Results In this study we adopted a linear mixed model to analyze oligonucleotide array experiments with repeated measures. We first construct a generalized F test to select differentially expressed genes. The Benjamini and Hochberg (BH procedure of controlling false discovery rate (FDR at 5% was applied to the P values of the generalized F test. For those genes with significant generalized F test, we then categorize them based on whether the interaction terms were significant or not at the α-level (αnew = 0.0033 determined by the FDR procedure. Since simple effects may be examined for the genes with significant interaction effect, we adopt the protected Fisher's least significant difference test (LSD procedure at the level of αnew to control the family-wise error rate (FWER for each gene examined. Conclusions A linear mixed model is appropriate for analysis of oligonucleotide array experiments with repeated measures. We constructed a generalized F test to select differentially expressed genes, and then applied a specific sequence of tests to identify factorial effects. This sequence of tests applied was designed to control for gene based FWER.

  11. Analysis of oligonucleotide array experiments with repeated measures using mixed models.

    Science.gov (United States)

    Li, Hao; Wood, Constance L; Getchell, Thomas V; Getchell, Marilyn L; Stromberg, Arnold J

    2004-12-30

    Two or more factor mixed factorial experiments are becoming increasingly common in microarray data analysis. In this case study, the two factors are presence (Patients with Alzheimer's disease) or absence (Control) of the disease, and brain regions including olfactory bulb (OB) or cerebellum (CER). In the design considered in this manuscript, OB and CER are repeated measurements from the same subject and, hence, are correlated. It is critical to identify sources of variability in the analysis of oligonucleotide array experiments with repeated measures and correlations among data points have to be considered. In addition, multiple testing problems are more complicated in experiments with multi-level treatments or treatment combinations. In this study we adopted a linear mixed model to analyze oligonucleotide array experiments with repeated measures. We first construct a generalized F test to select differentially expressed genes. The Benjamini and Hochberg (BH) procedure of controlling false discovery rate (FDR) at 5% was applied to the P values of the generalized F test. For those genes with significant generalized F test, we then categorize them based on whether the interaction terms were significant or not at the alpha-level (alphanew = 0.0033) determined by the FDR procedure. Since simple effects may be examined for the genes with significant interaction effect, we adopt the protected Fisher's least significant difference test (LSD) procedure at the level of alphanew to control the family-wise error rate (FWER) for each gene examined. A linear mixed model is appropriate for analysis of oligonucleotide array experiments with repeated measures. We constructed a generalized F test to select differentially expressed genes, and then applied a specific sequence of tests to identify factorial effects. This sequence of tests applied was designed to control for gene based FWER.

  12. Chicken sperm transcriptome profiling by microarray analysis.

    Science.gov (United States)

    Singh, R P; Shafeeque, C M; Sharma, S K; Singh, R; Mohan, J; Sastry, K V H; Saxena, V K; Azeez, P A

    2016-03-01

    It has been confirmed that mammalian sperm contain thousands of functional RNAs, and some of them have vital roles in fertilization and early embryonic development. Therefore, we attempted to characterize transcriptome of the sperm of fertile chickens using microarray analysis. Spermatozoal RNA was pooled from 10 fertile males and used for RNA preparation. Prior to performing the microarray, RNA quality was assessed using a bioanalyzer, and gDNA and somatic cell RNA contamination was assessed by CD4 and PTPRC gene amplification. The chicken sperm transcriptome was cross-examined by analysing sperm and testes RNA on a 4 × 44K chicken array, and results were verified by RT-PCR. Microarray analysis identified 21,639 predominantly nuclear-encoded transcripts in chicken sperm. The majority (66.55%) of the sperm transcripts were shared with the testes, while surprisingly, 33.45% transcripts were detected (raw signal intensity greater than 50) only in the sperm and not in the testes. The greatest proportion of up-regulated transcripts were responsible for signal transduction (63.20%) followed by embryonic development (56.76%) and cell structure (56.25%). Of the 20 most abundant transcripts, 18 remain uncharacterized, whereas the least abundant genes were mostly associated with the ribosome. These findings lay a foundation for more detailed investigations on sperm RNAs in chickens to identify sperm-based biomarkers for fertility.

  13. Comparative analysis of copy number detection by whole-genome BAC and oligonucleotide array CGH

    Directory of Open Access Journals (Sweden)

    Bejjani Bassem A

    2010-06-01

    Full Text Available Abstract Background Microarray-based comparative genomic hybridization (aCGH is a powerful diagnostic tool for the detection of DNA copy number gains and losses associated with chromosome abnormalities, many of which are below the resolution of conventional chromosome analysis. It has been presumed that whole-genome oligonucleotide (oligo arrays identify more clinically significant copy-number abnormalities than whole-genome bacterial artificial chromosome (BAC arrays, yet this has not been systematically studied in a clinical diagnostic setting. Results To determine the difference in detection rate between similarly designed BAC and oligo arrays, we developed whole-genome BAC and oligonucleotide microarrays and validated them in a side-by-side comparison of 466 consecutive clinical specimens submitted to our laboratory for aCGH. Of the 466 cases studied, 67 (14.3% had a copy-number imbalance of potential clinical significance detectable by the whole-genome BAC array, and 73 (15.6% had a copy-number imbalance of potential clinical significance detectable by the whole-genome oligo array. However, because both platforms identified copy number variants of unclear clinical significance, we designed a systematic method for the interpretation of copy number alterations and tested an additional 3,443 cases by BAC array and 3,096 cases by oligo array. Of those cases tested on the BAC array, 17.6% were found to have a copy-number abnormality of potential clinical significance, whereas the detection rate increased to 22.5% for the cases tested by oligo array. In addition, we validated the oligo array for detection of mosaicism and found that it could routinely detect mosaicism at levels of 30% and greater. Conclusions Although BAC arrays have faster turnaround times, the increased detection rate of oligo arrays makes them attractive for clinical cytogenetic testing.

  14. Microarray analysis of genes associated with cell surface NIS protein levels in breast cancer

    Directory of Open Access Journals (Sweden)

    Richardson Andrea L

    2011-10-01

    Full Text Available Abstract Background Na+/I- symporter (NIS-mediated iodide uptake allows radioiodine therapy for thyroid cancer. NIS is also expressed in breast tumors, raising potential for radionuclide therapy of breast cancer. However, NIS expression in most breast cancers is low and may not be sufficient for radionuclide therapy. We aimed to identify biomarkers associated with NIS expression such that mechanisms underlying NIS modulation in human breast tumors may be elucidated. Methods Published oligonucleotide microarray data within the National Center for Biotechnology Information Gene Expression Omnibus database were analyzed to identify gene expression tightly correlated with NIS mRNA level among human breast tumors. NIS immunostaining was performed in a tissue microarray composed of 28 human breast tumors which had corresponding oligonucleotide microarray data available for each tumor such that gene expression associated with cell surface NIS protein level could be identified. Results and Discussion NIS mRNA levels do not vary among breast tumors or when compared to normal breast tissues when detected by Affymetrix oligonucleotide microarray platforms. Cell surface NIS protein levels are much more variable than their corresponding NIS mRNA levels. Despite a limited number of breast tumors examined, our analysis identified cysteinyl-tRNA synthetase as a biomarker that is highly associated with cell surface NIS protein levels in the ER-positive breast cancer subtype. Conclusions Further investigation on genes associated with cell surface NIS protein levels within each breast cancer molecular subtype may lead to novel targets for selectively increasing NIS expression/function in a subset of breast cancers patients.

  15. Microarray Я US: a user-friendly graphical interface to Bioconductor tools that enables accurate microarray data analysis and expedites comprehensive functional analysis of microarray results

    Directory of Open Access Journals (Sweden)

    Dai Yilin

    2012-06-01

    Full Text Available Abstract Background Microarray data analysis presents a significant challenge to researchers who are unable to use the powerful Bioconductor and its numerous tools due to their lack of knowledge of R language. Among the few existing software programs that offer a graphic user interface to Bioconductor packages, none have implemented a comprehensive strategy to address the accuracy and reliability issue of microarray data analysis due to the well known probe design problems associated with many widely used microarray chips. There is also a lack of tools that would expedite the functional analysis of microarray results. Findings We present Microarray Я US, an R-based graphical user interface that implements over a dozen popular Bioconductor packages to offer researchers a streamlined workflow for routine differential microarray expression data analysis without the need to learn R language. In order to enable a more accurate analysis and interpretation of microarray data, we incorporated the latest custom probe re-definition and re-annotation for Affymetrix and Illumina chips. A versatile microarray results output utility tool was also implemented for easy and fast generation of input files for over 20 of the most widely used functional analysis software programs. Conclusion Coupled with a well-designed user interface, Microarray Я US leverages cutting edge Bioconductor packages for researchers with no knowledge in R language. It also enables a more reliable and accurate microarray data analysis and expedites downstream functional analysis of microarray results.

  16. Digital microarray analysis for digital artifact genomics

    Science.gov (United States)

    Jaenisch, Holger; Handley, James; Williams, Deborah

    2013-06-01

    We implement a Spatial Voting (SV) based analogy of microarray analysis for digital gene marker identification in malware code sections. We examine a famous set of malware formally analyzed by Mandiant and code named Advanced Persistent Threat (APT1). APT1 is a Chinese organization formed with specific intent to infiltrate and exploit US resources. Manidant provided a detailed behavior and sting analysis report for the 288 malware samples available. We performed an independent analysis using a new alternative to the traditional dynamic analysis and static analysis we call Spatial Analysis (SA). We perform unsupervised SA on the APT1 originating malware code sections and report our findings. We also show the results of SA performed on some members of the families associated by Manidant. We conclude that SV based SA is a practical fast alternative to dynamics analysis and static analysis.

  17. Microarray analysis of Escherichia coli0157:H7

    Institute of Scientific and Technical Information of China (English)

    Hui-Ying Jin; Kai-Hua Tao; Yue-Xi Li; Fa-Qing Li; Su-Qin Li

    2005-01-01

    AIM: To establish the rapid, specific, and sensitive method for detecting O157:H7 with DNA microchips.METHODS: Specific oligonucleotide probes (26-28 nt) of bacterial antigenic and virulent genes of E. coli O157:H7 and other related pathogen genes were pre-synthesized and immobilized on a solid support to make microchips. The four genes encoding O157 somatic antigen (rfbE), H7 fiagellar antigen (fliC) and toxins (SLT1, SLT2) were monitored by multiplex PCR with four pairs of specific primers. Fluorescence-Cy3 labeled samples for hybridization were generated by PCR with Cy3-labeled single prime. Hybridization was performed for 60 min at 45 ℃. Microchip images were taken using a confocal fluorescent scanner.RESULTS: Twelve different bacterial strains were detected with various combinations of four virulent genes. All the O157:H7 strains yielded positive results by multiplex PCR.The size of the PCR products generated with these primers varied from 210 to 678 bp. All the rfbE/fliC/SLT1/SLT2 probes specifically recognized Cy3-labeled fluorescent samples from O157:H7 strains, or strains containing O157 and H7 genes. No cross hybridization of O157:H7 fluorescent samples occurred in other probes. Non-O157:H7 pathogens failed to yield any signal under comparable conditions. If the Cy3-labeled fluorescent product of O157 single PCR was diluted 50-fold, no signal was found in agarose gel electrophoresis, but a positive signal was found in microarray hybridization.CONCLUSION: Microarray analysis of O157:H7 is a rapid,specific, and efficient method for identification and detection of bacterial pathogens.

  18. Microarray analysis in caudal medulla of cattle orally challenged with bovine spongiform encephalopathy.

    Science.gov (United States)

    Almeida, L M; Basu, U; Williams, J L; Moore, S S; Guan, L L

    2011-10-25

    Bovine spongiform encephalopathy (BSE) is a fatal disorder in cattle characterized by progressive neurodegeneration of the central nervous system. We investigated the molecular mechanisms involved in neurodegeneration during prion infection through the identification of genes that are differentially expressed (DE) between experimentally infected and non-challenged cattle. Gene expression of caudal medulla from control and orally infected animals was compared by microarray analysis using 24,000 bovine oligonucleotides representing 16,846 different genes to identify DE genes associated with BSE disease. In total, 182 DE genes were identified between normal and BSE-infected tissues (>2.0-fold change, P bovine species.

  19. The IronChip evaluation package: a package of perl modules for robust analysis of custom microarrays

    Directory of Open Access Journals (Sweden)

    Brazma Alvis

    2010-03-01

    Full Text Available Abstract Background Gene expression studies greatly contribute to our understanding of complex relationships in gene regulatory networks. However, the complexity of array design, production and manipulations are limiting factors, affecting data quality. The use of customized DNA microarrays improves overall data quality in many situations, however, only if for these specifically designed microarrays analysis tools are available. Results The IronChip Evaluation Package (ICEP is a collection of Perl utilities and an easy to use data evaluation pipeline for the analysis of microarray data with a focus on data quality of custom-designed microarrays. The package has been developed for the statistical and bioinformatical analysis of the custom cDNA microarray IronChip but can be easily adapted for other cDNA or oligonucleotide-based designed microarray platforms. ICEP uses decision tree-based algorithms to assign quality flags and performs robust analysis based on chip design properties regarding multiple repetitions, ratio cut-off, background and negative controls. Conclusions ICEP is a stand-alone Windows application to obtain optimal data quality from custom-designed microarrays and is freely available here (see "Additional Files" section and at: http://www.alice-dsl.net/evgeniy.vainshtein/ICEP/

  20. DNA microarray synthesis by using PDMS molecular stamp (II) -- Oligonucleotide on-chip synthesis using PDMS stamp

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Based on the standard phosphoramidites chemistry protocol, two oligonucleotides synthetic routes were studied by contact stamping reactants to a modified glass slide. Route A was a contact coupling reaction, in which a nucleoside monomer was transferred and coupled to reactive groups (OH) on a substrate by spreading the nucleoside activated with tetrazole on a polydimethylsiloxane (PDMS) stamp. Route B was a contact detritylation, in which one nucleoside was fixed on the desired synthesis regions where dimethoxytrityl (DMT) protecting groups on the 5′-hydroxyl of the support-bound nucleoside were removed by stamping trichloroacetic acid (TCA) distributed on features on a PDMS stamp. Experiments showed that the synthetic yield and the reaction speed of route A were higher than those of route B. It was shown that 20 mer oligonucleotide arrays immobilized on the glass slide were successfully synthesized using the PDMS stamps, and the coupling efficiency showed no difference between the PDMS stamping and the conventional synthesis methods.

  1. Microbial distributions detected by an oligonucleotide microarray across geochemical zones associated with methane in marine sediments from the Ulleung Basin

    Energy Technology Data Exchange (ETDEWEB)

    Briggs, Brandon R; Graw, Michael; Brodie, Eoin L; Bahk, Jang-Jun; Kim, Sung-Han; Hyun, Jung-Ho; Kim, Ji-Hoon; Torres, Marta; Colwell, Frederick S

    2013-11-01

    The biogeochemical processes that occur in marine sediments on continental margins are complex; however, from one perspective they can be considered with respect to three geochemical zones based on the presence and form of methane: sulfate–methane transition (SMTZ), gas hydrate stability zone (GHSZ), and free gas zone (FGZ). These geochemical zones may harbor distinct microbial communities that are important in biogeochemical carbon cycles. The objective of this study was to describe the microbial communities in sediments from the SMTZ, GHSZ, and FGZ using molecular ecology methods (i.e. PhyloChip microarray analysis and terminal restriction fragment length polymorphism (T-RFLP)) and examining the results in the context of non-biological parameters in the sediments. Non-metric multidimensional scaling and multi-response permutation procedures were used to determine whether microbial community compositions were significantly different in the three geochemical zones and to correlate samples with abiotic characteristics of the sediments. This analysis indicated that microbial communities from all three zones were distinct from one another and that variables such as sulfate concentration, hydrate saturation of the nearest gas hydrate layer, and depth (or unmeasured variables associated with depth e.g. temperature, pressure) were correlated to differences between the three zones. The archaeal anaerobic methanotrophs typically attributed to performing anaerobic oxidation of methane were not detected in the SMTZ; however, the marine benthic group-B, which is often found in SMTZ, was detected. Within the GHSZ, samples that were typically closer to layers that contained higher hydrate saturation had indicator sequences related to Vibrio-type taxa. These results suggest that the biogeographic patterns of microbial communities in marine sediments are distinct based on geochemical zones defined by methane.

  2. Transcript-based redefinition of grouped oligonucleotide probe sets using AceView: High-resolution annotation for microarrays

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    Cam Margaret C

    2007-03-01

    Full Text Available Abstract Background Extracting biological information from high-density Affymetrix arrays is a multi-step process that begins with the accurate annotation of microarray probes. Shortfalls in the original Affymetrix probe annotation have been described; however, few studies have provided rigorous solutions for routine data analysis. Results Using AceView, a comprehensive human transcript database, we have reannotated the probes by matching them to RNA transcripts instead of genes. Based on this transcript-level annotation, a new probe set definition was created in which every probe in a probe set maps to a common set of AceView gene transcripts. In addition, using artificial data sets we identified that a minimal probe set size of 4 is necessary for reliable statistical summarization. We further demonstrate that applying the new probe set definition can detect specific transcript variants contributing to differential expression and it also improves cross-platform concordance. Conclusion We conclude that our transcript-level reannotation and redefinition of probe sets complement the original Affymetrix design. Redefinitions introduce probe sets whose sizes may not support reliable statistical summarization; therefore, we advocate using our transcript-level mapping redefinition in a secondary analysis step rather than as a replacement. Knowing which specific transcripts are differentially expressed is important to properly design probe/primer pairs for validation purposes. For convenience, we have created custom chip-description-files (CDFs and annotation files for our new probe set definitions that are compatible with Bioconductor, Affymetrix Expression Console or third party software.

  3. Design Considerations for Array CGH to OligonucleotideArrays

    Energy Technology Data Exchange (ETDEWEB)

    Baldocchi, R.A.; Glynne, R.J.; Chin, K.; Kowbel, D.; Collins, C.; Mack, D.H.; Gray, J.W.

    2005-03-04

    Background: Representational oligonucleotide microarray analysis has been developed for detection of single nucleotide polymorphisms and/or for genome copy number changes. In this process, the intensity of hybridization to oligonucleotides arrays is increased by hybridizing a polymerase chain reaction (PCR)-amplified representation of reduced genomic complexity. However, hybridization to some oligonucleotides is not sufficiently high to allow precise analysis of that portion of the genome. Methods: In an effort to identify aspects of oligonucleotide hybridization affecting signal intensity, we explored the importance of the PCR product strand to which each oligonucleotide is homologous and the sequence of the array oligonucleotides. We accomplished this by hybridizing multiple PCR-amplified products to oligonucleotide arrays carrying two sense and two antisense 50-mer oligonucleotides for each PCR amplicon. Results: In some cases, hybridization intensity depended more strongly on the PCR amplicon strand (i.e., sense vs. antisense) than on the detection oligonucleotide sequence. In other cases, the oligonucleotide sequence seemed to dominate. Conclusion: Oligonucleotide arrays for analysis of DNA copy number or for single nucleotide polymorphism content should be designed to carry probes to sense and antisense strands of each PCR amplicon to ensure sufficient hybridization and signal intensity.

  4. Extended -Regular Sequence for Automated Analysis of Microarray Images

    Directory of Open Access Journals (Sweden)

    Jin Hee-Jeong

    2006-01-01

    Full Text Available Microarray study enables us to obtain hundreds of thousands of expressions of genes or genotypes at once, and it is an indispensable technology for genome research. The first step is the analysis of scanned microarray images. This is the most important procedure for obtaining biologically reliable data. Currently most microarray image processing systems require burdensome manual block/spot indexing work. Since the amount of experimental data is increasing very quickly, automated microarray image analysis software becomes important. In this paper, we propose two automated methods for analyzing microarray images. First, we propose the extended -regular sequence to index blocks and spots, which enables a novel automatic gridding procedure. Second, we provide a methodology, hierarchical metagrid alignment, to allow reliable and efficient batch processing for a set of microarray images. Experimental results show that the proposed methods are more reliable and convenient than the commercial tools.

  5. Gene ARMADA: an integrated multi-analysis platform for microarray data implemented in MATLAB.

    Science.gov (United States)

    Chatziioannou, Aristotelis; Moulos, Panagiotis; Kolisis, Fragiskos N

    2009-10-27

    The microarray data analysis realm is ever growing through the development of various tools, open source and commercial. However there is absence of predefined rational algorithmic analysis workflows or batch standardized processing to incorporate all steps, from raw data import up to the derivation of significantly differentially expressed gene lists. This absence obfuscates the analytical procedure and obstructs the massive comparative processing of genomic microarray datasets. Moreover, the solutions provided, heavily depend on the programming skills of the user, whereas in the case of GUI embedded solutions, they do not provide direct support of various raw image analysis formats or a versatile and simultaneously flexible combination of signal processing methods. We describe here Gene ARMADA (Automated Robust MicroArray Data Analysis), a MATLAB implemented platform with a Graphical User Interface. This suite integrates all steps of microarray data analysis including automated data import, noise correction and filtering, normalization, statistical selection of differentially expressed genes, clustering, classification and annotation. In its current version, Gene ARMADA fully supports 2 coloured cDNA and Affymetrix oligonucleotide arrays, plus custom arrays for which experimental details are given in tabular form (Excel spreadsheet, comma separated values, tab-delimited text formats). It also supports the analysis of already processed results through its versatile import editor. Besides being fully automated, Gene ARMADA incorporates numerous functionalities of the Statistics and Bioinformatics Toolboxes of MATLAB. In addition, it provides numerous visualization and exploration tools plus customizable export data formats for seamless integration by other analysis tools or MATLAB, for further processing. Gene ARMADA requires MATLAB 7.4 (R2007a) or higher and is also distributed as a stand-alone application with MATLAB Component Runtime. Gene ARMADA provides a

  6. Application of functional genomics to the chimeric mouse model of HCV infection: optimization of microarray protocols and genomics analysis

    Directory of Open Access Journals (Sweden)

    Smith Maria W

    2006-05-01

    Full Text Available Abstract Background Many model systems of human viral disease involve human-mouse chimeric tissue. One such system is the recently developed SCID-beige/Alb-uPA mouse model of hepatitis C virus (HCV infection which involves a human-mouse chimeric liver. The use of functional genomics to study HCV infection in these chimeric tissues is complicated by the potential cross-hybridization of mouse mRNA on human oligonucleotide microarrays. To identify genes affected by mouse liver mRNA hybridization, mRNA from identical human liver samples labeled with either Cy3 or Cy5 was compared in the presence and absence of known amounts of mouse liver mRNA labeled in only one dye. Results The results indicate that hybridization of mouse mRNA to the corresponding human gene probe on Agilent Human 22 K oligonucleotide microarray does occur. The number of genes affected by such cross-hybridization was subsequently reduced to approximately 300 genes both by increasing the hybridization temperature and using liver samples which contain at least 80% human tissue. In addition, Real Time quantitative RT-PCR using human specific probes was shown to be a valid method to verify the expression level in human cells of known cross-hybridizing genes. Conclusion The identification of genes affected by cross-hybridization of mouse liver RNA on human oligonucleotide microarrays makes it feasible to use functional genomics approaches to study the chimeric SCID-beige/Alb-uPA mouse model of HCV infection. This approach used to study cross-species hybridization on oligonucleotide microarrays can be adapted to other chimeric systems of viral disease to facilitate selective analysis of human gene expression.

  7. Identification of candidate genes in osteoporosis by integrated microarray analysis

    OpenAIRE

    Li, J J; Wang, B. Q.; Fei, Q.; Yang, Y; Li, D.

    2017-01-01

    Objectives In order to screen the altered gene expression profile in peripheral blood mononuclear cells of patients with osteoporosis, we performed an integrated analysis of the online microarray studies of osteoporosis. Methods We searched the Gene Expression Omnibus (GEO) database for microarray studies of peripheral blood mononuclear cells in patients with osteoporosis. Subsequently, we integrated gene expression data sets from multiple microarray studies to obtain differentially expressed...

  8. Ontology-Based Analysis of Microarray Data.

    Science.gov (United States)

    Giuseppe, Agapito; Milano, Marianna

    2016-01-01

    The importance of semantic-based methods and algorithms for the analysis and management of biological data is growing for two main reasons. From a biological side, knowledge contained in ontologies is more and more accurate and complete, from a computational side, recent algorithms are using in a valuable way such knowledge. Here we focus on semantic-based management and analysis of protein interaction networks referring to all the approaches of analysis of protein-protein interaction data that uses knowledge encoded into biological ontologies. Semantic approaches for studying high-throughput data have been largely used in the past to mine genomic and expression data. Recently, the emergence of network approaches for investigating molecular machineries has stimulated in a parallel way the introduction of semantic-based techniques for analysis and management of network data. The application of these computational approaches to the study of microarray data can broad the application scenario of them and simultaneously can help the understanding of disease development and progress.

  9. Microarray BASICA: Background Adjustment, Segmentation, Image Compression and Analysis of Microarray Images

    Directory of Open Access Journals (Sweden)

    Jianping Hua

    2004-01-01

    Full Text Available This paper presents microarray BASICA: an integrated image processing tool for background adjustment, segmentation, image compression, and analysis of cDNA microarray images. BASICA uses a fast Mann-Whitney test-based algorithm to segment cDNA microarray images, and performs postprocessing to eliminate the segmentation irregularities. The segmentation results, along with the foreground and background intensities obtained with the background adjustment, are then used for independent compression of the foreground and background. We introduce a new distortion measurement for cDNA microarray image compression and devise a coding scheme by modifying the embedded block coding with optimized truncation (EBCOT algorithm (Taubman, 2000 to achieve optimal rate-distortion performance in lossy coding while still maintaining outstanding lossless compression performance. Experimental results show that the bit rate required to ensure sufficiently accurate gene expression measurement varies and depends on the quality of cDNA microarray images. For homogeneously hybridized cDNA microarray images, BASICA is able to provide from a bit rate as low as 5 bpp the gene expression data that are 99% in agreement with those of the original 32 bpp images.

  10. Analysis Method of Citrus Genome Microarray%浅谈柑橘基因组芯片分析方法

    Institute of Scientific and Technical Information of China (English)

    杨雪莲; 贝学军; 朱友娟

    2012-01-01

    cDNA microarray and oligonucleotide microarray are currently used for analysing citrus gene expression profile.The data analysis of genome microarray include data preprocessing,screening differential expression genes,and further analysing the differential expression genes.Through data analysis and integration of biological information,this paper studies the plant physiological changes.%指出了cDNA芯片和寡核苷酸芯片是目前用于柑橘基因表达谱分析的方法,基因组芯片数据分析主要包括数据预处理,筛选差异基因,差异基因再进一步分析。通过数据分析及整合样点的生物学信息,研究了植物生理变化。

  11. Differential analysis for high density tiling microarray data

    Directory of Open Access Journals (Sweden)

    Kapranov Philipp

    2007-09-01

    Full Text Available Abstract Background High density oligonucleotide tiling arrays are an effective and powerful platform for conducting unbiased genome-wide studies. The ab initio probe selection method employed in tiling arrays is unbiased, and thus ensures consistent sampling across coding and non-coding regions of the genome. These arrays are being increasingly used to study the associated processes of transcription, transcription factor binding, chromatin structure and their association. Studies of differential expression and/or regulation provide critical insight into the mechanics of transcription and regulation that occurs during the developmental program of a cell. The time-course experiment, which comprises an in-vivo system and the proposed analyses, is used to determine if annotated and un-annotated portions of genome manifest coordinated differential response to the induced developmental program. Results We have proposed a novel approach, based on a piece-wise function – to analyze genome-wide differential response. This enables segmentation of the response based on protein-coding and non-coding regions; for genes the methodology also partitions differential response with a 5' versus 3' versus intra-genic bias. Conclusion The algorithm built upon the framework of Significance Analysis of Microarrays, uses a generalized logic to define regions/patterns of coordinated differential change. By not adhering to the gene-centric paradigm, discordant differential expression patterns between exons and introns have been identified at a FDR of less than 12 percent. A co-localization of differential binding between RNA Polymerase II and tetra-acetylated histone has been quantified at a p-value -13. The prototype R code has been made available as supplementary material [see Additional file 1]. Additional file 1 gsam_prototypercode.zip. File archive comprising of prototype R code for gSAM implementation including readme and examples. Click here for file

  12. Differential analysis for high density tiling microarray data.

    Science.gov (United States)

    Ghosh, Srinka; Hirsch, Heather A; Sekinger, Edward A; Kapranov, Philipp; Struhl, Kevin; Gingeras, Thomas R

    2007-09-24

    High density oligonucleotide tiling arrays are an effective and powerful platform for conducting unbiased genome-wide studies. The ab initio probe selection method employed in tiling arrays is unbiased, and thus ensures consistent sampling across coding and non-coding regions of the genome. These arrays are being increasingly used to study the associated processes of transcription, transcription factor binding, chromatin structure and their association. Studies of differential expression and/or regulation provide critical insight into the mechanics of transcription and regulation that occurs during the developmental program of a cell. The time-course experiment, which comprises an in-vivo system and the proposed analyses, is used to determine if annotated and un-annotated portions of genome manifest coordinated differential response to the induced developmental program. We have proposed a novel approach, based on a piece-wise function - to analyze genome-wide differential response. This enables segmentation of the response based on protein-coding and non-coding regions; for genes the methodology also partitions differential response with a 5' versus 3' versus intra-genic bias. The algorithm built upon the framework of Significance Analysis of Microarrays, uses a generalized logic to define regions/patterns of coordinated differential change. By not adhering to the gene-centric paradigm, discordant differential expression patterns between exons and introns have been identified at a FDR of less than 12 percent. A co-localization of differential binding between RNA Polymerase II and tetra-acetylated histone has been quantified at a p-value < 0.003; it is most significant at the 5' end of genes, at a p-value < 10-13. The prototype R code has been made available as supplementary material [see Additional file 1].

  13. Microarrays--analysis of signaling pathways.

    Science.gov (United States)

    Ramachandran, Anassuya; Black, Michael A; Shelling, Andrew N; Love, Donald R

    2008-01-01

    Microarrays provide a powerful means of analyzing the expression level of multiple transcripts in two sample populations. In this study, we have used microarray technology to identify genes that are differentially regulated in response to activin-treated ovarian cancer cells. We find a number of biologically relevant genes that are involved in regulating activin signaling and genes potentially contributing to activin-mediated growth arrest appear to be differentially regulated. Thus, microarrays are an important tool for dissecting gene expression changes in normal physiological processes and disease.

  14. Application of the Taguchi method to the analysis of the deposition step in microarray production.

    Science.gov (United States)

    Severgnini, Marco; Pattini, Linda; Consolandi, Clarissa; Rizzi, Ermanno; Battaglia, Cristina; De Bellis, Gianluca; Cerutti, Sergio

    2006-09-01

    Every microarray experiment is affected by many possible sources of variability that may even corrupt biological evidence on analyzed sequences. We applied a "Taguchi method" strategy, based on the use of orthogonal arrays to optimize the deposition step of oligonucleotide sequences on glass slides. We chose three critical deposition parameters (humidity, surface, and buffer) at two levels each, in order to establish optimum settings. A L8 orthogonal array was used in order to monitor both the main effects and interactions on the deposition of a 25 mer oligonucleotide hybridized to its fluorescent-labeled complementary. Signal-background ratio and deposition homogeneity in terms of mean intensity and spot diameter were considered as significant outputs. An analysis of variance (ANOVA) was applied to raw data and to mean results for each slide and experimental run. Finally we calculated an overall evaluation coefficient to group together important outputs in one number. Environmental humidity and surface-buffer interaction were recognized as the most critical factors, for which a 50% humidity, associated to a chitosan-covered slide and a sodium phosphate + 25% dimethyl sulfoxide (DMSO) buffer gave best performances. Our results also suggested that Taguchi methods can be efficiently applied in optimization of microarray procedures.

  15. Transcriptome analysis of zebrafish embryogenesis using microarrays.

    Directory of Open Access Journals (Sweden)

    2005-08-01

    Full Text Available Zebrafish (Danio rerio is a well-recognized model for the study of vertebrate developmental genetics, yet at the same time little is known about the transcriptional events that underlie zebrafish embryogenesis. Here we have employed microarray analysis to study the temporal activity of developmentally regulated genes during zebrafish embryogenesis. Transcriptome analysis at 12 different embryonic time points covering five different developmental stages (maternal, blastula, gastrula, segmentation, and pharyngula revealed a highly dynamic transcriptional profile. Hierarchical clustering, stage-specific clustering, and algorithms to detect onset and peak of gene expression revealed clearly demarcated transcript clusters with maximum gene activity at distinct developmental stages as well as co-regulated expression of gene groups involved in dedicated functions such as organogenesis. Our study also revealed a previously unidentified cohort of genes that are transcribed prior to the mid-blastula transition, a time point earlier than when the zygotic genome was traditionally thought to become active. Here we provide, for the first time to our knowledge, a comprehensive list of developmentally regulated zebrafish genes and their expression profiles during embryogenesis, including novel information on the temporal expression of several thousand previously uncharacterized genes. The expression data generated from this study are accessible to all interested scientists from our institute resource database (http://giscompute.gis.a-star.edu.sg/~govind/zebrafish/data_download.html.

  16. Transcriptome analysis of zebrafish embryogenesis using microarrays.

    Directory of Open Access Journals (Sweden)

    Sinnakaruppan Mathavan

    2005-08-01

    Full Text Available Zebrafish (Danio rerio is a well-recognized model for the study of vertebrate developmental genetics, yet at the same time little is known about the transcriptional events that underlie zebrafish embryogenesis. Here we have employed microarray analysis to study the temporal activity of developmentally regulated genes during zebrafish embryogenesis. Transcriptome analysis at 12 different embryonic time points covering five different developmental stages (maternal, blastula, gastrula, segmentation, and pharyngula revealed a highly dynamic transcriptional profile. Hierarchical clustering, stage-specific clustering, and algorithms to detect onset and peak of gene expression revealed clearly demarcated transcript clusters with maximum gene activity at distinct developmental stages as well as co-regulated expression of gene groups involved in dedicated functions such as organogenesis. Our study also revealed a previously unidentified cohort of genes that are transcribed prior to the mid-blastula transition, a time point earlier than when the zygotic genome was traditionally thought to become active. Here we provide, for the first time to our knowledge, a comprehensive list of developmentally regulated zebrafish genes and their expression profiles during embryogenesis, including novel information on the temporal expression of several thousand previously uncharacterized genes. The expression data generated from this study are accessible to all interested scientists from our institute resource database (http://giscompute.gis.a-star.edu.sg/~govind/zebrafish/data_download.html.

  17. Automatic Spot Identification for High Throughput Microarray Analysis

    Science.gov (United States)

    Wu, Eunice; Su, Yan A.; Billings, Eric; Brooks, Bernard R.; Wu, Xiongwu

    2013-01-01

    High throughput microarray analysis has great potential in scientific research, disease diagnosis, and drug discovery. A major hurdle toward high throughput microarray analysis is the time and effort needed to accurately locate gene spots in microarray images. An automatic microarray image processor will allow accurate and efficient determination of spot locations and sizes so that gene expression information can be reliably extracted in a high throughput manner. Current microarray image processing tools require intensive manual operations in addition to the input of grid parameters to correctly and accurately identify gene spots. This work developed a method, herein called auto-spot, to automate the spot identification process. Through a series of correlation and convolution operations, as well as pixel manipulations, this method makes spot identification an automatic and accurate process. Testing with real microarray images has demonstrated that this method is capable of automatically extracting subgrids from microarray images and determining spot locations and sizes within each subgrid, regardless of variations in array patterns and background noises. With this method, we are one step closer to the goal of high throughput microarray analysis. PMID:24298393

  18. Advantages of ion-exchange chromatography for oligonucleotide analysis.

    Science.gov (United States)

    Cook, Ken; Thayer, Jim

    2011-05-01

    The rapid development of therapeutic oligonucleotides (ONs) has created a need for in-depth characterization of ONs, beyond previous requirements. The natural migration to LC-MS requires the use of chromatography with MS-compatible eluents to introduce the large, highly charged biopolymers into the mass spectrometer. Most frequently this employs ion-pair reversed-phase liquid chromatography, which may leave gaps in the characterization, but these can be filled with the use of high-resolution ion-exchange chromatography. Several classes of isobaric isomers are among the impurities that will require further separation prior to MS analysis. This review shows how the use of ion exchange as an additional orthogonal analytical method can be used as standalone or interfaced with MS to achieve the highest possible analytical coverage in the characterization and quantification of impurities present in single- and double-stranded ON formulations. Some of these techniques have been in use for some time and the importance of others is just being recognized.

  19. Application of heteronuclear couplings to conformational analysis of oligonucleotides

    Energy Technology Data Exchange (ETDEWEB)

    Zhu, G. [Univ. of Maryland, College Park, MD (United States); Live, D. [Memorial Sloan-Kettering Cancer Center, New York, NY (United States); Bax, A. [NIDDK National Institutes of Health, Bethesda, MD (United States)

    1994-12-01

    The value of vicinal coupling constants extracted from NMR spectra in deducing torsion angles for conformational analysis is well recognized. Due to the abundance of protons, their couplings have been mostly widely used. In many instances, couplings between protons and other nuclei may be a valuable complement to proton-proton couplings or, in some instances, may be the only coupling available to characterize the torsion angle about a bond. Recently, heteronuclear couplings have been used to great benefit in studies of isotopically enriched proteins, and this general approach has been extended to peptides at natural abundance. The possibility of using this approach to study oligonucleotides is also attractive but has not as yet been widely exploited. With the development of strategies for labeling such molecules, particularly RNAs, this may become an important component in conformational analysis. For DNA, labeling is less accessible, but sufficient quantities of unlabeled material are readily available for measuring these couplings at natural abundance. We chose several DNA systems to explore the usefulness of heteronuclear couplings in addressing the sugar conformation and the glycosidic torsion angle. Intensities of cross peaks in long-range HMQC experiments can be related to the couplings. Crosspeaks involving H1{prime} and C1{prime} atoms have been emphasized because of the superior shift dispersion at these positions between sugar protons and carbon atoms. Results will be shown for the self-complementary Dickerson duplex dodecamer sequence d(CGCGAATTCGCG) and for d(GGTCGG), which dimerizes to form a G-tetrad structure incorporating both syn and anti base orientations. The couplings provide a clear discrimination between presence of C3{prime}-endo and C2{prime}-endo conformations of the sugars and syn and anti bases arrangements.

  20. Immune and inflammatory gene signature in rat cerebrum in subarachnoid hemorrhage with microarray analysis.

    Science.gov (United States)

    Lee, Chu-I; Chou, An-Kuo; Lin, Ching-Chih; Chou, Chia-Hua; Loh, Joon-Khim; Lieu, Ann-Shung; Wang, Chih-Jen; Huang, Chi-Ying F; Howng, Shen-Long; Hong, Yi-Ren

    2012-01-01

    Cerebral vasospasm following subarachnoid hemorrhage (SAH) has been studied in terms of a contraction of the major cerebral arteries, but the effect of cerebrum tissue in SAH is not yet well understood. To gain insight into the biology of SAH-expressing cerebrum, we employed oligonucleotide microarrays to characterize the gene expression profiles of cerebrum tissue at the early stage of SAH. Functional gene expression in the cerebrum was analyzed 2 h following stage 1-hemorrhage in Sprague-Dawley rats. mRNA was investigated by performing microarray and quantitative real-time PCR analyses, and protein expression was determined by Western blot analysis. In this study, 18 upregulated and 18 downregulated genes displayed at least a 1.5-fold change. Five genes were verified by real-time PCR, including three upregulated genes [prostaglandin E synthase (PGES), CD14 antigen, and tissue inhibitor of metalloproteinase 1 (TIMP1)] as well as two downregulated genes [KRAB-zinc finger protein-2 (KZF-2) and γ-aminobutyric acid B receptor 1 (GABA B receptor)]. Notably, there were functional implications for the three upregulated genes involved in the inflammatory SAH process. However, the mechanisms leading to decreased KZF-2 and GABA B receptor expression in SAH have never been characterized. We conclude that oligonucleotide microarrays have the potential for use as a method to identify candidate genes associated with SAH and to provide novel investigational targets, including genes involved in the immune and inflammatory response. Furthermore, understanding the regulation of MMP9/TIMP1 during the early stages of SAH may elucidate the pathophysiological mechanisms in SAH rats.

  1. Glycan microarray analysis of Candida glabrata adhesin ligand specificity

    National Research Council Canada - National Science Library

    Zupancic, Margaret L; Frieman, Matthew; Smith, David; Alvarez, Richard A; Cummings, Richard D; Cormack, Brendan P

    2008-01-01

    ...) family responsible for mediating adherence to host cells. To better understand the mechanism by which the Epa proteins contribute to pathogenesis, we have used glycan microarray analysis to characterize their carbohydrate...

  2. Comparison of gene expression of mitogenic kinin path in adherent and non-adherent CD 34-stem cells using oligonucleotide microarrays.

    Directory of Open Access Journals (Sweden)

    Krzysztof Machaj

    2008-02-01

    Full Text Available One of the more interesting cells present in the umbilical cord blood - as far as their potential clinical use is concerned - are stem cells not presenting the CD34 antigen. These are the pluripotential cells with their biological properties similar to mesenchymal stem cells, with the ability to differentiate into such tissue types as bone, cartilage, nervous (to some extent, glia and muscle. The authors compared the activity of genes coding the proteins in mitogenic signal paths activated by kinin receptors using oligonucleotide microarrays in adherent and non-adherent CD 34- cells derived from umbilical cord blood. In the linear regression model with a 95% prognosis area for differentiating genes outside this area, the following genes were selected: c-jun (present in 3 isoforms and c-fos. The fos and jun genes create the AP-1 transcriptive factor which regulates the expression of genes taking part in numerous cellular processes, including the cell cycle and mitosis. The obtained results shed some light on the molecular processes behind the MSC proliferation and are a starting point for further studies on the mesenchymal stem cell biology.

  3. The EADGENE Microarray Data Analysis Workshop (Open Access publication

    Directory of Open Access Journals (Sweden)

    Jiménez-Marín Ángeles

    2007-11-01

    Full Text Available Abstract Microarray analyses have become an important tool in animal genomics. While their use is becoming widespread, there is still a lot of ongoing research regarding the analysis of microarray data. In the context of a European Network of Excellence, 31 researchers representing 14 research groups from 10 countries performed and discussed the statistical analyses of real and simulated 2-colour microarray data that were distributed among participants. The real data consisted of 48 microarrays from a disease challenge experiment in dairy cattle, while the simulated data consisted of 10 microarrays from a direct comparison of two treatments (dye-balanced. While there was broader agreement with regards to methods of microarray normalisation and significance testing, there were major differences with regards to quality control. The quality control approaches varied from none, through using statistical weights, to omitting a large number of spots or omitting entire slides. Surprisingly, these very different approaches gave quite similar results when applied to the simulated data, although not all participating groups analysed both real and simulated data. The workshop was very successful in facilitating interaction between scientists with a diverse background but a common interest in microarray analyses.

  4. Genomic Imbalances in Neonates With Birth Defects: High Detection Rates by Using Chromosomal Microarray Analysis

    Science.gov (United States)

    Lu, Xin-Yan; Phung, Mai T.; Shaw, Chad A.; Pham, Kim; Neil, Sarah E.; Patel, Ankita; Sahoo, Trilochan; Bacino, Carlos A.; Stankiewicz, Pawel; Lee Kang, Sung-Hae; Lalani, Seema; Chinault, A. Craig; Lupski, James R.; Cheung, Sau W.; Beaudet, Arthur L.

    2009-01-01

    OBJECTIVES Our aim was to determine the frequency of genomic imbalances in neonates with birth defects by using targeted array-based comparative genomic hybridization, also known as chromosomal microarray analysis. METHODS Between March 2006 and September 2007, 638 neonates with various birth defects were referred for chromosomal microarray analysis. Three consecutive chromosomal microarray analysis versions were used: bacterial artificial chromosome-based versions V5 and V6 and bacterial artificial chromosome emulated oligonucleotide-based version V6 Oligo. Each version had targeted but increasingly extensive genomic coverage and interrogated >150 disease loci with enhanced coverage in genomic rearrangement-prone pericentromeric and subtelomeric regions. RESULTS Overall, 109 (17.1%) patients were identified with clinically significant abnormalities with detection rates of 13.7%, 16.6%, and 19.9% on V5, V6, and V6 Oligo, respectively. The majority of these abnormalities would not be defined by using karyotype analysis. The clinically significant detection rates by use of chromosomal microarray analysis for various clinical indications were 66.7% for “possible chromosomal abnormality” ± “others” (other clinical indications), 33.3% for ambiguous genitalia ± others, 27.1% for dysmorphic features + multiple congenital anomalies ± others, 24.6% for dysmorphic features ± others, 21.8% for congenital heart disease ± others, 17.9% for multiple congenital anomalies ± others, and 9.5% for the patients referred for others that were different from the groups defined. In all, 16 (2.5%) patients had chromosomal aneuploidies, and 81 (12.7%) patients had segmental aneusomies including common microdeletion or microduplication syndromes and other genomic disorders. Chromosomal mosaicism was found in 12 (1.9%) neonates. CONCLUSIONS Chromosomal microarray analysis is a valuable clinical diagnostic tool that allows precise and rapid identification of genomic imbalances

  5. Weighted analysis of general microarray experiments

    Directory of Open Access Journals (Sweden)

    Kristiansson Erik

    2007-10-01

    Full Text Available Abstract Background In DNA microarray experiments, measurements from different biological samples are often assumed to be independent and to have identical variance. For many datasets these assumptions have been shown to be invalid and typically lead to too optimistic p-values. A method called WAME has been proposed where a variance is estimated for each sample and a covariance is estimated for each pair of samples. The current version of WAME is, however, limited to experiments with paired design, e.g. two-channel microarrays. Results The WAME procedure is extended to general microarray experiments, making it capable of handling both one- and two-channel datasets. Two public one-channel datasets are analysed and WAME detects both unequal variances and correlations. WAME is compared to other common methods: fold-change ranking, ordinary linear model with t-tests, LIMMA and weighted LIMMA. The p-value distributions are shown to differ greatly between the examined methods. In a resampling-based simulation study, the p-values generated by WAME are found to be substantially more correct than the alternatives when a relatively small proportion of the genes is regulated. WAME is also shown to have higher power than the other methods. WAME is available as an R-package. Conclusion The WAME procedure is generalized and the limitation to paired-design microarray datasets is removed. The examined other methods produce invalid p-values in many cases, while WAME is shown to produce essentially valid p-values when a relatively small proportion of genes is regulated. WAME is also shown to have higher power than the examined alternative methods.

  6. Microarchitecture of a MultiCore SoC for Data Analysis of a Lab-on-Chip Microarray

    Directory of Open Access Journals (Sweden)

    S. Blionas

    2008-07-01

    Full Text Available This paper presents a reconfigurable architecture of a lab-on-chip (LoC microarray device capable to process data either in genotyping or in gene expression applications in a fraction of the time that is required by the usual software methods running on a standard computer. The entire LoC consists of a microfluidics part for the sample preparation and hybridization, a microsystem part including the application specific array of sensors for the electronic detection, and finally a reconfigurable processing part for the data analysis. The proposed data processing and analysis electronic module are an embedded multicore reconfigurable system-on-chip designed to analyze data from the forthcoming high-density oligonucleotide microarrays. The proposed architecture employs reconfigurable technology and has the capacity to process data from microarrays of various sizes from small size ones used in genotyping up to large-scale gene expression arrays. Additionally, the embedded processing cores feature reconfigurable circuitry for implementing the intense part of the processing, supplementing the various computational needs of the diverse applications for microarray real-time data processing and for a scalable reconfigurable architecture to handle also the future high-density microarrays.

  7. arrayCGHbase: an analysis platform for comparative genomic hybridization microarrays

    Directory of Open Access Journals (Sweden)

    Moreau Yves

    2005-05-01

    Full Text Available Abstract Background The availability of the human genome sequence as well as the large number of physically accessible oligonucleotides, cDNA, and BAC clones across the entire genome has triggered and accelerated the use of several platforms for analysis of DNA copy number changes, amongst others microarray comparative genomic hybridization (arrayCGH. One of the challenges inherent to this new technology is the management and analysis of large numbers of data points generated in each individual experiment. Results We have developed arrayCGHbase, a comprehensive analysis platform for arrayCGH experiments consisting of a MIAME (Minimal Information About a Microarray Experiment supportive database using MySQL underlying a data mining web tool, to store, analyze, interpret, compare, and visualize arrayCGH results in a uniform and user-friendly format. Following its flexible design, arrayCGHbase is compatible with all existing and forthcoming arrayCGH platforms. Data can be exported in a multitude of formats, including BED files to map copy number information on the genome using the Ensembl or UCSC genome browser. Conclusion ArrayCGHbase is a web based and platform independent arrayCGH data analysis tool, that allows users to access the analysis suite through the internet or a local intranet after installation on a private server. ArrayCGHbase is available at http://medgen.ugent.be/arrayCGHbase/.

  8. Genome-wide identification of specific oligonucleotides using artificial neural network and computational genomic analysis

    Directory of Open Access Journals (Sweden)

    Chen Jiun-Ching

    2007-05-01

    Full Text Available Abstract Background Genome-wide identification of specific oligonucleotides (oligos is a computationally-intensive task and is a requirement for designing microarray probes, primers, and siRNAs. An artificial neural network (ANN is a machine learning technique that can effectively process complex and high noise data. Here, ANNs are applied to process the unique subsequence distribution for prediction of specific oligos. Results We present a novel and efficient algorithm, named the integration of ANN and BLAST (IAB algorithm, to identify specific oligos. We establish the unique marker database for human and rat gene index databases using the hash table algorithm. We then create the input vectors, via the unique marker database, to train and test the ANN. The trained ANN predicted the specific oligos with high efficiency, and these oligos were subsequently verified by BLAST. To improve the prediction performance, the ANN over-fitting issue was avoided by early stopping with the best observed error and a k-fold validation was also applied. The performance of the IAB algorithm was about 5.2, 7.1, and 6.7 times faster than the BLAST search without ANN for experimental results of 70-mer, 50-mer, and 25-mer specific oligos, respectively. In addition, the results of polymerase chain reactions showed that the primers predicted by the IAB algorithm could specifically amplify the corresponding genes. The IAB algorithm has been integrated into a previously published comprehensive web server to support microarray analysis and genome-wide iterative enrichment analysis, through which users can identify a group of desired genes and then discover the specific oligos of these genes. Conclusion The IAB algorithm has been developed to construct SpecificDB, a web server that provides a specific and valid oligo database of the probe, siRNA, and primer design for the human genome. We also demonstrate the ability of the IAB algorithm to predict specific oligos through

  9. Advanced spot quality analysis in two-colour microarray experiments

    Directory of Open Access Journals (Sweden)

    Vetter Guillaume

    2008-09-01

    Full Text Available Abstract Background Image analysis of microarrays and, in particular, spot quantification and spot quality control, is one of the most important steps in statistical analysis of microarray data. Recent methods of spot quality control are still in early age of development, often leading to underestimation of true positive microarray features and, consequently, to loss of important biological information. Therefore, improving and standardizing the statistical approaches of spot quality control are essential to facilitate the overall analysis of microarray data and subsequent extraction of biological information. Findings We evaluated the performance of two image analysis packages MAIA and GenePix (GP using two complementary experimental approaches with a focus on the statistical analysis of spot quality factors. First, we developed control microarrays with a priori known fluorescence ratios to verify the accuracy and precision of the ratio estimation of signal intensities. Next, we developed advanced semi-automatic protocols of spot quality evaluation in MAIA and GP and compared their performance with available facilities of spot quantitative filtering in GP. We evaluated these algorithms for standardised spot quality analysis in a whole-genome microarray experiment assessing well-characterised transcriptional modifications induced by the transcription regulator SNAI1. Using a set of RT-PCR or qRT-PCR validated microarray data, we found that the semi-automatic protocol of spot quality control we developed with MAIA allowed recovering approximately 13% more spots and 38% more differentially expressed genes (at FDR = 5% than GP with default spot filtering conditions. Conclusion Careful control of spot quality characteristics with advanced spot quality evaluation can significantly increase the amount of confident and accurate data resulting in more meaningful biological conclusions.

  10. Analysis of mutations in oral poliovirus vaccine by hybridization with generic oligonucleotide microchips.

    Energy Technology Data Exchange (ETDEWEB)

    Proudnikov, D.; Kirillov, E.; Chumakov, K.; Donion, J.; Rezapkin, G.; Mirzabekov, A.; Biochip Technology Center; Engelhardt Inst. of Molecular Biology; Center for Biologics Evaluation and Research

    2000-01-01

    This paper describes use of a new technology of hybridization with a micro-array of immobilized oligonucleotides for detection and quantification of neurovirulent mutants in Oral Poliovirus Vaccine (OPV). We used a micro-array consisting of three-dimensional gel-elements containing all possible hexamers (total of 4096 probes). Hybridization of fluorescently labelled viral cDNA samples with such microchips resulted in a pattern of spots that was registered and quantified by a computer-linked CCD camera, so that the sequence of the original cDNA could be deduced. The method could reliably identify single point mutations, since each of them affected fluorescence intensity of 12 micro-array elements. Micro-array hybridization of DNA mixtures with varying contents of point mutants demonstrated that the method can detect as little as 10% of revertants in a population of vaccine virus. This new technology should be useful for quality control of live viral vaccines, as well as for other applications requiring identification and quantification of point mutations.

  11. PCR amplfication on a microarray of gel-immobilized oligonucleotides : detection of bacterial toxin- and drug-resistent genes and their mutations.

    Energy Technology Data Exchange (ETDEWEB)

    Strizhkov, B. N.; Drobyshev, A. L.; Mikhailovich, V. M.; Mirzabekov, A. D.; Biochip Technology Center; Engelhardt Inst. of Molecular Biology

    2000-10-01

    PCR amplification on a microarray of gel-immobilized primers (microchip) has been developed. One of a pair of PCR primers was immobilized inside a separate microchip polyacrylamide porous gel pad of 0.1 x 0.1 x 0.02 (or 0.04) micron in size and 0.2 (or 0.4) nL in volume. The amplification was carried out simultaneously both in solution covering the microchip array and inside gel pads. Each gel pad contained the immobilized forward primers, while the fluorescently labeled reverse primers, as well as all components of the amplification reaction, diffused into the gel pads from the solution. To increase the amplification efficiency, the forward primers were also added into the solution. The kinetics of amplification was measured in real time in parallel for all gel pads with a fluorescent microscope equipped with a charge-coupled device (CCD) camera. The accuracy of the amplification was assessed by using the melting curves obtained for the duplexes formed by the labeled amplification product and the gel-immobilized primers during the amplification process; alternatively, the duplexes were produced by hybridization of the extended immobilized primers with labeled oligonucleotide probes. The on-chip amplification was applied to detect the anthrax toxin genes and the plasmid-borne beta-lactamase gene responsible for bacterial ampicillin resistance. The allele-specific type of PCR amplification was used to identify the Shiga toxin gene and discriminate it from the Shiga-like one. The genomic mutations responsible for rifampicin resistance of the Mycobacterium tuberculosis strains were detected by the same type of PCR amplification of the rpoB gene fragment isolated from sputum of tuberculosis patients. The on-chip PCR amplification has been shown to be a rapid, inexpensive and powerful tool to test genes responsible for bacterial toxin production and drug resistance, as well as to reveal point nucleotide mutations.

  12. Use of a rainbow trout oligonucleotide microarray to determine transcriptional patterns in aflatoxin B1-induced hepatocellular carcinoma compared to adjacent liver.

    Science.gov (United States)

    Tilton, Susan C; Gerwick, Lena G; Hendricks, Jerry D; Rosato, Caprice S; Corley-Smith, Graham; Givan, Scott A; Bailey, George S; Bayne, Christopher J; Williams, David E

    2005-12-01

    Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide, and its occurrence is associated with a number of environmental factors including ingestion of the dietary contaminant aflatoxin B(1) (AFB(1)). Research over the last 40 years has revealed rainbow trout (Oncorhynchus mykiss) to be an excellent research model for study of AFB(1)-induced hepatocarcinogenesis; however, little is known about changes at the molecular level in trout tumors. We have developed a rainbow trout oligonucleotide array containing 1672 elements representing over 1400 genes of known or probable relevance to toxicology, comparative immunology, carcinogenesis, endocrinology, and stress physiology. In this study, we applied microarray technology to examine gene expression of AFB(1)-induced HCC in the rainbow trout tumor model. Carcinogenesis was initiated in trout embryos with 50 ppb AFB(1), and after 13 months control livers, tumors, and tumor-adjacent liver tissues were isolated from juvenile fish. Global gene expression was determined in histologically confirmed HCCs compared to noncancerous adjacent tissue and sham-initiated control liver. We observed distinct gene regulation patterns in HCC compared to noncancerous tissue including upregulation of genes important for cell cycle control, transcription, cytoskeletal formation, and the acute phase response and downregulation of genes involved in drug metabolism, lipid metabolism, and retinol metabolism. Interestingly, the expression profiles observed in trout HCC are similar to the transcriptional signatures found in human and rodent HCC, further supporting the validity of the model. Overall, these findings contribute to a better understanding of the mechanism of AFB(1)-induced hepatocarcinogenesis in trout and identify conserved genes important for carcinogenesis in species separated evolutionarily by more than 400 million years.

  13. Comparative analysis of genomic signal processing for microarray data clustering.

    Science.gov (United States)

    Istepanian, Robert S H; Sungoor, Ala; Nebel, Jean-Christophe

    2011-12-01

    Genomic signal processing is a new area of research that combines advanced digital signal processing methodologies for enhanced genetic data analysis. It has many promising applications in bioinformatics and next generation of healthcare systems, in particular, in the field of microarray data clustering. In this paper we present a comparative performance analysis of enhanced digital spectral analysis methods for robust clustering of gene expression across multiple microarray data samples. Three digital signal processing methods: linear predictive coding, wavelet decomposition, and fractal dimension are studied to provide a comparative evaluation of the clustering performance of these methods on several microarray datasets. The results of this study show that the fractal approach provides the best clustering accuracy compared to other digital signal processing and well known statistical methods.

  14. Biological networks to the analysis of microarray data

    Institute of Scientific and Technical Information of China (English)

    FANG Zhuo; LUO Qingming; ZHANG Guoqing; LI Yixue

    2006-01-01

    Microarray technology, which permits rapid and large-scale screening for patterns of gene expressions, usually generates a large amount of data. How to mine the biological meanings under these data is one of the main challenges in bioinformatics. Compared to the pure mathematical techniques, those methods incorporated with some prior biological knowledge generally bring better interpretations.Recently, a new analysis, in which the knowledge of biological networks such as metabolic network and protein interaction network is introduced, is widely applied to microarray data analysis. The microarray data analysis based on biological networks contains two main research aspects: identification of active components in biological networks and assessment of gene sets significance. In this paper, we briefly review the progress of these two categories of analyses, especially some representative methods.

  15. Comparative linkage analysis and visualization of high-density oligonucleotide SNP array data

    Directory of Open Access Journals (Sweden)

    Smith Richard JH

    2005-02-01

    Full Text Available Abstract Background The identification of disease-associated genes using single nucleotide polymorphisms (SNPs has been increasingly reported. In particular, the Affymetrix Mapping 10 K SNP microarray platform uses one PCR primer to amplify the DNA samples and determine the genotype of more than 10,000 SNPs in the human genome. This provides the opportunity for large scale, rapid and cost-effective genotyping assays for linkage analysis. However, the analysis of such datasets is nontrivial because of the large number of markers, and visualizing the linkage scores in the context of genome maps remains less automated using the current linkage analysis software packages. For example, the haplotyping results are commonly represented in the text format. Results Here we report the development of a novel software tool called CompareLinkage for automated formatting of the Affymetrix Mapping 10 K genotype data into the "Linkage" format and the subsequent analysis with multi-point linkage software programs such as Merlin and Allegro. The new software has the ability to visualize the results for all these programs in dChip in the context of genome annotations and cytoband information. In addition we implemented a variant of the Lander-Green algorithm in the dChipLinkage module of dChip software (V1.3 to perform parametric linkage analysis and haplotyping of SNP array data. These functions are integrated with the existing modules of dChip to visualize SNP genotype data together with LOD score curves. We have analyzed three families with recessive and dominant diseases using the new software programs and the comparison results are presented and discussed. Conclusions The CompareLinkage and dChipLinkage software packages are freely available. They provide the visualization tools for high-density oligonucleotide SNP array data, as well as the automated functions for formatting SNP array data for the linkage analysis programs Merlin and Allegro and calling

  16. Significance analysis of lexical bias in microarray data

    Directory of Open Access Journals (Sweden)

    Falkow Stanley

    2003-04-01

    Full Text Available Abstract Background Genes that are determined to be significantly differentially regulated in microarray analyses often appear to have functional commonalities, such as being components of the same biochemical pathway. This results in certain words being under- or overrepresented in the list of genes. Distinguishing between biologically meaningful trends and artifacts of annotation and analysis procedures is of the utmost importance, as only true biological trends are of interest for further experimentation. A number of sophisticated methods for identification of significant lexical trends are currently available, but these methods are generally too cumbersome for practical use by most microarray users. Results We have developed a tool, LACK, for calculating the statistical significance of apparent lexical bias in microarray datasets. The frequency of a user-specified list of search terms in a list of genes which are differentially regulated is assessed for statistical significance by comparison to randomly generated datasets. The simplicity of the input files and user interface targets the average microarray user who wishes to have a statistical measure of apparent lexical trends in analyzed datasets without the need for bioinformatics skills. The software is available as Perl source or a Windows executable. Conclusion We have used LACK in our laboratory to generate biological hypotheses based on our microarray data. We demonstrate the program's utility using an example in which we confirm significant upregulation of SPI-2 pathogenicity island of Salmonella enterica serovar Typhimurium by the cation chelator dipyridyl.

  17. Multiple platform assessment of the EGF dependent transcriptome by microarray and deep tag sequencing analysis

    Directory of Open Access Journals (Sweden)

    Iraola Susana

    2011-06-01

    Full Text Available Abstract Background Epidermal Growth Factor (EGF is a key regulatory growth factor activating many processes relevant to normal development and disease, affecting cell proliferation and survival. Here we use a combined approach to study the EGF dependent transcriptome of HeLa cells by using multiple long oligonucleotide based microarray platforms (from Agilent, Operon, and Illumina in combination with digital gene expression profiling (DGE with the Illumina Genome Analyzer. Results By applying a procedure for cross-platform data meta-analysis based on RankProd and GlobalAncova tests, we establish a well validated gene set with transcript levels altered after EGF treatment. We use this robust gene list to build higher order networks of gene interaction by interconnecting associated networks, supporting and extending the important role of the EGF signaling pathway in cancer. In addition, we find an entirely new set of genes previously unrelated to the currently accepted EGF associated cellular functions. Conclusions We propose that the use of global genomic cross-validation derived from high content technologies (microarrays or deep sequencing can be used to generate more reliable datasets. This approach should help to improve the confidence of downstream in silico functional inference analyses based on high content data.

  18. Microarray analysis in the archaeon Halobacterium salinarum strain R1.

    Directory of Open Access Journals (Sweden)

    Jens Twellmeyer

    Full Text Available BACKGROUND: Phototrophy of the extremely halophilic archaeon Halobacterium salinarum was explored for decades. The research was mainly focused on the expression of bacteriorhodopsin and its functional properties. In contrast, less is known about genome wide transcriptional changes and their impact on the physiological adaptation to phototrophy. The tool of choice to record transcriptional profiles is the DNA microarray technique. However, the technique is still rarely used for transcriptome analysis in archaea. METHODOLOGY/PRINCIPAL FINDINGS: We developed a whole-genome DNA microarray based on our sequence data of the Hbt. salinarum strain R1 genome. The potential of our tool is exemplified by the comparison of cells growing under aerobic and phototrophic conditions, respectively. We processed the raw fluorescence data by several stringent filtering steps and a subsequent MAANOVA analysis. The study revealed a lot of transcriptional differences between the two cell states. We found that the transcriptional changes were relatively weak, though significant. Finally, the DNA microarray data were independently verified by a real-time PCR analysis. CONCLUSION/SIGNIFICANCE: This is the first DNA microarray analysis of Hbt. salinarum cells that were actually grown under phototrophic conditions. By comparing the transcriptomics data with current knowledge we could show that our DNA microarray tool is well applicable for transcriptome analysis in the extremely halophilic archaeon Hbt. salinarum. The reliability of our tool is based on both the high-quality array of DNA probes and the stringent data handling including MAANOVA analysis. Among the regulated genes more than 50% had unknown functions. This underlines the fact that haloarchaeal phototrophy is still far away from being completely understood. Hence, the data recorded in this study will be subject to future systems biology analysis.

  19. Construction of Whole Genome Microarrays, and Expression Analysis of Desulfovibrio vulgaris cells in Metal-Reducing Conditions (Uranium and Chromium)

    Energy Technology Data Exchange (ETDEWEB)

    Fields, Matthew W.

    2005-06-01

    One of the major goals of the project is to construct whole-genome microarrays for Desulfovibrio vulgaris. Previous whole-genome microarrays constructed at ORNL have been PCR-amplimer based, and we wanted to re-evaluate the type of microarrays being built because oligonucleotide probes have several advantages. Microarrays have been generally constructed with two types of probes, PCR-generated probes that typically range in size between 200 and 2000 bp, and oligonucleotide probes with typical size of 20-70 nt. Producing PCR product-based DNA arrays can be a time-consuming procedure that includes PCR primer design, amplification, size verification, product purification, and product quantification. Also, some ORFs are difficult to amplify and thus the construction of comprehensive arrays can be a challenge. Recently, to alleviate some of the problems associated with PCR product-based microarrays, oligonucleotide microarrays that contain probes longer than 40 nt have been evaluated and used for whole genome expression studies. These microarrays should have higher specificity and are easy to construct, and can thus provide an important alternative approach to monitor gene expression. However, due to the smaller probe size, it is expected that the detection sensitivity of oligonucleotide arrays will be lower than PCR product-based probes.

  20. Independent component analysis of Alzheimer's DNA microarray gene expression data

    Directory of Open Access Journals (Sweden)

    Vanderburg Charles R

    2009-01-01

    Full Text Available Abstract Background Gene microarray technology is an effective tool to investigate the simultaneous activity of multiple cellular pathways from hundreds to thousands of genes. However, because data in the colossal amounts generated by DNA microarray technology are usually complex, noisy, high-dimensional, and often hindered by low statistical power, their exploitation is difficult. To overcome these problems, two kinds of unsupervised analysis methods for microarray data: principal component analysis (PCA and independent component analysis (ICA have been developed to accomplish the task. PCA projects the data into a new space spanned by the principal components that are mutually orthonormal to each other. The constraint of mutual orthogonality and second-order statistics technique within PCA algorithms, however, may not be applied to the biological systems studied. Extracting and characterizing the most informative features of the biological signals, however, require higher-order statistics. Results ICA is one of the unsupervised algorithms that can extract higher-order statistical structures from data and has been applied to DNA microarray gene expression data analysis. We performed FastICA method on DNA microarray gene expression data from Alzheimer's disease (AD hippocampal tissue samples and consequential gene clustering. Experimental results showed that the ICA method can improve the clustering results of AD samples and identify significant genes. More than 50 significant genes with high expression levels in severe AD were extracted, representing immunity-related protein, metal-related protein, membrane protein, lipoprotein, neuropeptide, cytoskeleton protein, cellular binding protein, and ribosomal protein. Within the aforementioned categories, our method also found 37 significant genes with low expression levels. Moreover, it is worth noting that some oncogenes and phosphorylation-related proteins are expressed in low levels. In

  1. Classification analysis of microarray data based on ontological engineering

    Institute of Scientific and Technical Information of China (English)

    LI Guo-qi; SHENG Huan-ye

    2007-01-01

    Background knowledge is important for data mining, especially in complicated situation. Ontological engineering is the successor of knowledge engineering. The sharable knowledge bases built on ontology can be used to provide background knowledge to direct the process of data mining. This paper gives a common introduction to the method and presents a practical analysis example using SVM (support vector machine) as the classifier. Gene Ontology and the accompanying annotations compose a big knowledge base, on which many researches have been carried out. Microarray dataset is the output of DNA chip.With the help of Gene Ontology we present a more elaborate analysis on microarray data than former researchers. The method can also be used in other fields with similar scenario.

  2. MAGMA: analysis of two-channel microarrays made easy.

    Science.gov (United States)

    Rehrauer, Hubert; Zoller, Stefan; Schlapbach, Ralph

    2007-07-01

    The web application MAGMA provides a simple and intuitive interface to identify differentially expressed genes from two-channel microarray data. While the underlying algorithms are not superior to those of similar web applications, MAGMA is particularly user friendly and can be used without prior training. The user interface guides the novice user through the most typical microarray analysis workflow consisting of data upload, annotation, normalization and statistical analysis. It automatically generates R-scripts that document MAGMA's entire data processing steps, thereby allowing the user to regenerate all results in his local R installation. The implementation of MAGMA follows the model-view-controller design pattern that strictly separates the R-based statistical data processing, the web-representation and the application logic. This modular design makes the application flexible and easily extendible by experts in one of the fields: statistical microarray analysis, web design or software development. State-of-the-art Java Server Faces technology was used to generate the web interface and to perform user input processing. MAGMA's object-oriented modular framework makes it easily extendible and applicable to other fields and demonstrates that modern Java technology is also suitable for rather small and concise academic projects. MAGMA is freely available at www.magma-fgcz.uzh.ch.

  3. Coupled Two-Way Clustering Analysis of Gene Microarray Data

    CERN Document Server

    Getz, G; Domany, E

    2000-01-01

    We present a novel coupled two-way clustering approach to gene microarray data analysis. The main idea is to identify subsets of the genes and samples, such that when one of these is used to cluster the other, stable and significant partitions emerge. The search for such subsets is a computationally complex task: we present an algorithm, based on iterative clustering, which performs such a search. This analysis is especially suitable for gene microarray data, where the contributions of a variety of biological mechanisms to the gene expression levels are entangled in a large body of experimental data. The method was applied to two gene microarray data sets, on colon cancer and leukemia. By identifying relevant subsets of the data and focusing on them we were able to discover partitions and correlations that were masked and hidden when the full dataset was used in the analysis. Some of these partitions have clear biological interpretation; others can serve to identify possible directions for future research.

  4. Coupled two-way clustering analysis of gene microarray data

    Science.gov (United States)

    Getz, Gad; Levine, Erel; Domany, Eytan

    2000-10-01

    We present a coupled two-way clustering approach to gene microarray data analysis. The main idea is to identify subsets of the genes and samples, such that when one of these is used to cluster the other, stable and significant partitions emerge. The search for such subsets is a computationally complex task. We present an algorithm, based on iterative clustering, that performs such a search. This analysis is especially suitable for gene microarray data, where the contributions of a variety of biological mechanisms to the gene expression levels are entangled in a large body of experimental data. The method was applied to two gene microarray data sets, on colon cancer and leukemia. By identifying relevant subsets of the data and focusing on them we were able to discover partitions and correlations that were masked and hidden when the full dataset was used in the analysis. Some of these partitions have clear biological interpretation; others can serve to identify possible directions for future research.

  5. Microarray Analysis of the Developing Rat Mandible

    Institute of Scientific and Technical Information of China (English)

    Hideo KABURAGI; Naoyuki SUGANO; Maiko OSHIKAWA; Ryosuke KOSHI; Naoki SENDA; Kazuhiro KAWAMOTO; Koichi ITO

    2007-01-01

    To analyze the molecular events that occur in the developing mandible, we examined the expression of 8803 genes from samples taken at different time points during rat postnatal mandible development.Total RNA was extracted from the mandibles of 1-day-old, 1-week-old, and 2-week-old rats. Complementary RNA (cRNA) was synthesized from cDNA and biotinylated. Fragmented cRNA was hybridized to RGU34A GeneChip arrays. Among the 8803 genes tested, 4344 were detectable. We identified 148 genes with significantly increased expression, and 19 genes with significantly decreased expression. A comprehensive analysis appears to be an effective method of studying the complex process of development.

  6. Identification of candidate genes in osteoporosis by integrated microarray analysis

    Science.gov (United States)

    Li, J. J.; Wang, B. Q.; Yang, Y.; Li, D.

    2016-01-01

    Objectives In order to screen the altered gene expression profile in peripheral blood mononuclear cells of patients with osteoporosis, we performed an integrated analysis of the online microarray studies of osteoporosis. Methods We searched the Gene Expression Omnibus (GEO) database for microarray studies of peripheral blood mononuclear cells in patients with osteoporosis. Subsequently, we integrated gene expression data sets from multiple microarray studies to obtain differentially expressed genes (DEGs) between patients with osteoporosis and normal controls. Gene function analysis was performed to uncover the functions of identified DEGs. Results A total of three microarray studies were selected for integrated analysis. In all, 1125 genes were found to be significantly differentially expressed between osteoporosis patients and normal controls, with 373 upregulated and 752 downregulated genes. Positive regulation of the cellular amino metabolic process (gene ontology (GO): 0033240, false discovery rate (FDR) = 1.00E + 00) was significantly enriched under the GO category for biological processes, while for molecular functions, flavin adenine dinucleotide binding (GO: 0050660, FDR = 3.66E-01) and androgen receptor binding (GO: 0050681, FDR = 6.35E-01) were significantly enriched. DEGs were enriched in many osteoporosis-related signalling pathways, including those of mitogen-activated protein kinase (MAPK) and calcium. Protein-protein interaction (PPI) network analysis showed that the significant hub proteins contained ubiquitin specific peptidase 9, X-linked (Degree = 99), ubiquitin specific peptidase 19 (Degree = 57) and ubiquitin conjugating enzyme E2 B (Degree = 57). Conclusion Analysis of gene function of identified differentially expressed genes may expand our understanding of fundamental mechanisms leading to osteoporosis. Moreover, significantly enriched pathways, such as MAPK and calcium, may involve in osteoporosis through osteoblastic differentiation and

  7. Identification biomarkers for cervical cancer in peripheral blood lymphocytes by oligonucleotide microarrays%应用寡核苷酸芯片筛选宫颈癌患者外周血生物标志物的研究

    Institute of Scientific and Technical Information of China (English)

    盛洁; 张为远

    2010-01-01

    Objective To identify the molecular biomarkers for cervical cancer in peripheral blood lymphocytes by oligonucleatide microarrays. Methods Human genome oligonucleotide microarray analysis included 4 early-stage cervical cancer patients and 3 controls. The selected genes from the microarray analysis were validated in additional 20 early-stage cervical cancer patients and 15 controls by real-time reverse-transcription polymerase chain reaction (RT-PCR). Results Genes identified by gene selection program were expressed differently in the blood samples of early-stage cervical cancer from those of healthy controls. To validate the gene expression data, 5 genes were analyzed by real-time RT-PCR. In three of 5 identified genes, tenasin-c, nucleolin, and enolase 2 (ENO2) showed a significant up-regulation in blood samples of early-stage cervical cancer patients versus that of the controls. Conclusion The up-regulation of tenasin-c, nucleolin and ENO2 in peripheral blood may be used to identify novel blood biomarkers for detecting cervical cancer in a clinically accessible surrogate tissue. Thus it may offer a possibility of developing a non-invasive and predictive diagnostic tool for the disease.%目的 应用人类全基因组寡核苷酸芯片技术在宫颈癌患者外周血中确定生物分子标志物.方法 从24例早期宫颈癌患者和18例正常对照者的外周血淋巴细胞中提取总RNA.应用微阵列技术,采用人类全基因组寡核苷酸芯片检测4例宫颈癌患者和3例正常对照者的差异表达基因,再对20例宫颈癌患者和15例正常对照者将初步筛选出的5个候选基因用实时定量逆转录多聚酶链反应(RT-PCR)的方法进行验证.结果 筛选得到57个差异表达基因,其中38个基因表达上调,19个基因表达下调;对初步筛选出的5个候选基因经实时定量逆转录多聚酶链反应的方法进行验证后发现黏合素-C、核仁素和磷酸丙酮酸水合酶2(enolase 2,ENO2)基因在宫

  8. GenePublisher: automated analysis of DNA microarray data

    DEFF Research Database (Denmark)

    Knudsen, Steen; Workman, Christopher; Sicheritz-Ponten, T.

    2003-01-01

    GenePublisher, a system for automatic analysis of data from DNA microarray experiments, has been implemented with a web interface at http://www.cbs.dtu.dk/services/GenePublisher. Raw data are uploaded to the server together with aspecification of the data. The server performs normalization......, statistical analysis and visualization of the data. The results are run against databases of signal transduction pathways, metabolic pathways and promoter sequences in order to extract more information. The results of the entire analysis are summarized in report form and returned to the user....

  9. Improved elucidation of biological processes linked to diabetic nephropathy by single probe-based microarray data analysis.

    Directory of Open Access Journals (Sweden)

    Clemens D Cohen

    Full Text Available BACKGROUND: Diabetic nephropathy (DN is a complex and chronic metabolic disease that evolves into a progressive fibrosing renal disorder. Effective transcriptomic profiling of slowly evolving disease processes such as DN can be problematic. The changes that occur are often subtle and can escape detection by conventional oligonucleotide DNA array analyses. METHODOLOGY/PRINCIPAL FINDINGS: We examined microdissected human renal tissue with or without DN using Affymetrix oligonucleotide microarrays (HG-U133A by standard Robust Multi-array Analysis (RMA. Subsequent gene ontology analysis by Database for Annotation, Visualization and Integrated Discovery (DAVID showed limited detection of biological processes previously identified as central mechanisms in the development of DN (e.g. inflammation and angiogenesis. This apparent lack of sensitivity may be associated with the gene-oriented averaging of oligonucleotide probe signals, as this includes signals from cross-hybridizing probes and gene annotation that is based on out of date genomic data. We then examined the same CEL file data using a different methodology to determine how well it could correlate transcriptomic data with observed biology. ChipInspector (CI is based on single probe analysis and de novo gene annotation that bypasses probe set definitions. Both methods, RMA and CI, used at default settings yielded comparable numbers of differentially regulated genes. However, when verified by RT-PCR, the single probe based analysis demonstrated reduced background noise with enhanced sensitivity and fewer false positives. CONCLUSIONS/SIGNIFICANCE: Using a single probe based analysis approach with de novo gene annotation allowed an improved representation of the biological processes linked to the development and progression of DN. The improved analysis was exemplified by the detection of Wnt signaling pathway activation in DN, a process not previously reported to be involved in this disease.

  10. The Role of Fluorinated Alcohols as Mobile Phase Modifiers for LC-MS Analysis of Oligonucleotides

    Science.gov (United States)

    Basiri, Babak; van Hattum, Hilde; van Dongen, William D.; Murph, Mandi M.; Bartlett, Michael G.

    2016-09-01

    Hexafluoroisopropanol (HFIP) has been widely used as an acidic modifier for mobile phases for liquid chromatography-mass spectrometry (LC-MS) analysis of oligonucleotides ever since the first report of its use for this purpose. This is not surprising, considering the exceptional performance of HFIP compared with carboxylic acids, which cause significant MS signal suppression in electrospray ionization. However, we have found that other fluorinated alcohols can also be utilized for mobile phase preparation and the choice of optimal fluorinated alcohol is determined by the ion-pairing (IP) agent. Although HFIP is a very good choice to be used alongside less hydrophobic IP agents, other fluorinated alcohols such as 1,1,1,3,3,3-hexafluoro-2-methyl-2-propanol (HFMIP) can significantly outperform HFIP when used with more hydrophobic IP agents. We also found that more acidic fluorinated alcohols assist with the transfer of oligonucleotides with secondary structure (e.g., folded strands and hairpins) into the gas phase.

  11. A predictive factor of the quality of microarray comparative genomic hybridization analysis for formalin-fixed paraffin-embedded archival tissue.

    Science.gov (United States)

    Nakao, Kenjiro; Oikawa, Masahiro; Arai, Junichi; Mussazhanova, Zhanna; Kondo, Hisayoshi; Shichijo, Kazuko; Nakashima, Masahiro; Hayashi, Tomayoshi; Yoshiura, Koh-Ichiro; Hatachi, Toshiko; Nagayasu, Takeshi

    2013-09-01

    Utilizing formalin-fixed paraffin-embedded (FFPE) archival tissue, the most common form of tissue preservation in routine practice, for cytogenetic analysis using microarray comparative genomic hybridization (aCGH) remains challenging. We searched for a predictive factor of the performance of FFPE DNA in aCGH analysis. DNA was extracted from 63 FFPE archival tissue samples of various tissue types (31 breast cancers, 24 lung cancers, and 8 thyroid tumors), followed by aCGH analysis using high-density oligonucleotide microarrays. Tumor DNA from matched frozen samples and from FFPE samples after whole-genome amplification were also analyzed in 2 and 4 case, respectively. The derivative log ratio spread (DLRSpread) was used to assess the overall quality of each aCGH result. The DLRSpread correlated significantly with the double-stranded DNA ratio of tumor DNA, storage time, and the degree of labeling with Cy5 (Parchival tissue samples can be utilized for aCGH analysis.

  12. A universal oligonucleotide microarray with a minimal number of probes for the detection and identification of viroids at the genus level.

    Directory of Open Access Journals (Sweden)

    Yongjiang Zhang

    Full Text Available A major challenge in the agricultural industry is the development of techniques that can screen plant samples for viroid infection. Microarrays are promising in this regard, as their high throughput nature can potentially allow for the detection of a range of viroids in a single test. In this paper we present a microarray that can detect a wide spectrum of all 8 reported viroid genera including 37 known plant viroid species. The array was constructed using an automated probe design protocol which generated a minimal number of probes to detect viroids at the genus level. The designed microarray showed a high specificity and sensitivity when tested with a set of standard virus samples. Finally, the microarray was applied to screen infected field samples, with Hop stunt viroid infection identified as the major disease causing pathogen for an infected citrus sample.

  13. Microarray-based transcriptomic analysis of differences between long-term gregarious and solitarious desert locusts.

    Directory of Open Access Journals (Sweden)

    Liesbeth Badisco

    Full Text Available Desert locusts (Schistocerca gregaria show an extreme form of phenotypic plasticity and can transform between a cryptic solitarious phase and a swarming gregarious phase. The two phases differ extensively in behavior, morphology and physiology but very little is known about the molecular basis of these differences. We used our recently generated Expressed Sequence Tag (EST database derived from S. gregaria central nervous system (CNS to design oligonucleotide microarrays and compare the expression of thousands of genes in the CNS of long-term gregarious and solitarious adult desert locusts. This identified 214 differentially expressed genes, of which 40% have been annotated to date. These include genes encoding proteins that are associated with CNS development and modeling, sensory perception, stress response and resistance, and fundamental cellular processes. Our microarray analysis has identified genes whose altered expression may enable locusts of either phase to deal with the different challenges they face. Genes for heat shock proteins and proteins which confer protection from infection were upregulated in gregarious locusts, which may allow them to respond to acute physiological challenges. By contrast the longer-lived solitarious locusts appear to be more strongly protected from the slowly accumulating effects of ageing by an upregulation of genes related to anti-oxidant systems, detoxification and anabolic renewal. Gregarious locusts also had a greater abundance of transcripts for proteins involved in sensory processing and in nervous system development and plasticity. Gregarious locusts live in a more complex sensory environment than solitarious locusts and may require a greater turnover of proteins involved in sensory transduction, and possibly greater neuronal plasticity.

  14. Improved statistical analysis of budding yeast TAG microarrays revealed by defined spike-in pools.

    Science.gov (United States)

    Peyser, Brian D; Irizarry, Rafael A; Tiffany, Carol W; Chen, Ou; Yuan, Daniel S; Boeke, Jef D; Spencer, Forrest A

    2005-09-15

    Saccharomyces cerevisiae knockout collection TAG microarrays are an emergent platform for rapid, genome-wide functional characterization of yeast genes. TAG arrays report abundance of unique oligonucleotide 'TAG' sequences incorporated into each deletion mutation of the yeast knockout collection, allowing measurement of relative strain representation across experimental conditions for all knockout mutants simultaneously. One application of TAG arrays is to perform genome-wide synthetic lethality screens, known as synthetic lethality analyzed by microarray (SLAM). We designed a fully defined spike-in pool to resemble typical SLAM experiments and performed TAG microarray hybridizations. We describe a method for analyzing two-color array data to efficiently measure the differential knockout strain representation across two experimental conditions, and use the spike-in pool to show that the sensitivity and specificity of this method exceed typical current approaches.

  15. Visualization methods for statistical analysis of microarray clusters

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    Li Kai

    2005-05-01

    Full Text Available Abstract Background The most common method of identifying groups of functionally related genes in microarray data is to apply a clustering algorithm. However, it is impossible to determine which clustering algorithm is most appropriate to apply, and it is difficult to verify the results of any algorithm due to the lack of a gold-standard. Appropriate data visualization tools can aid this analysis process, but existing visualization methods do not specifically address this issue. Results We present several visualization techniques that incorporate meaningful statistics that are noise-robust for the purpose of analyzing the results of clustering algorithms on microarray data. This includes a rank-based visualization method that is more robust to noise, a difference display method to aid assessments of cluster quality and detection of outliers, and a projection of high dimensional data into a three dimensional space in order to examine relationships between clusters. Our methods are interactive and are dynamically linked together for comprehensive analysis. Further, our approach applies to both protein and gene expression microarrays, and our architecture is scalable for use on both desktop/laptop screens and large-scale display devices. This methodology is implemented in GeneVAnD (Genomic Visual ANalysis of Datasets and is available at http://function.princeton.edu/GeneVAnD. Conclusion Incorporating relevant statistical information into data visualizations is key for analysis of large biological datasets, particularly because of high levels of noise and the lack of a gold-standard for comparisons. We developed several new visualization techniques and demonstrated their effectiveness for evaluating cluster quality and relationships between clusters.

  16. Microarray-based analysis of differential gene expression between infective and noninfective larvae of Strongyloides stercoralis.

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    Roshan Ramanathan

    Full Text Available BACKGROUND: Differences between noninfective first-stage (L1 and infective third-stage (L3i larvae of parasitic nematode Strongyloides stercoralis at the molecular level are relatively uncharacterized. DNA microarrays were developed and utilized for this purpose. METHODS AND FINDINGS: Oligonucleotide hybridization probes for the array were designed to bind 3,571 putative mRNA transcripts predicted by analysis of 11,335 expressed sequence tags (ESTs obtained as part of the Nematode EST project. RNA obtained from S. stercoralis L3i and L1 was co-hybridized to each array after labeling the individual samples with different fluorescent tags. Bioinformatic predictions of gene function were developed using a novel cDNA Annotation System software. We identified 935 differentially expressed genes (469 L3i-biased; 466 L1-biased having two-fold expression differences or greater and microarray signals with a p value<0.01. Based on a functional analysis, L1 larvae have a larger number of genes putatively involved in transcription (p = 0.004, and L3i larvae have biased expression of putative heat shock proteins (such as hsp-90. Genes with products known to be immunoreactive in S. stercoralis-infected humans (such as SsIR and NIE had L3i biased expression. Abundantly expressed L3i contigs of interest included S. stercoralis orthologs of cytochrome oxidase ucr 2.1 and hsp-90, which may be potential chemotherapeutic targets. The S. stercoralis ortholog of fatty acid and retinol binding protein-1, successfully used in a vaccine against Ancylostoma ceylanicum, was identified among the 25 most highly expressed L3i genes. The sperm-containing glycoprotein domain, utilized in a vaccine against the nematode Cooperia punctata, was exclusively found in L3i biased genes and may be a valuable S. stercoralis target of interest. CONCLUSIONS: A new DNA microarray tool for the examination of S. stercoralis biology has been developed and provides new and valuable insights

  17. Increased expression of matrix extracellular phosphoglycoprotein (MEPE in cortical bone of the rat tibia after mechanical loading: identification by oligonucleotide microarray.

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    Christianne M A Reijnders

    Full Text Available Skeletal integrity in humans and animals is maintained by daily mechanical loading. It has been widely accepted that osteocytes function as mechanosensors. Many biochemical signaling molecules are involved in the response of osteocytes to mechanical stimulation. The aim of this study was to identify genes involved in the translation of mechanical stimuli into bone formation. The four-point bending model was used to induce a single period of mechanical loading on the right tibia, while the contra lateral left tibia served as control. Six hours after loading, the effects of mechanical loading on gene-expression were determined with microarray analysis. Protein expression of differentially regulated genes was evaluated with immunohistochemistry. Nine genes were found to exhibit a significant differential gene expression in LOAD compared to control. MEPE, Garnl1, V2R2B, and QFG-TN1 olfactory receptor were up-regulated, and creatine kinase (muscle form, fibrinogen-B beta-polypeptide, monoamine oxidase A, troponin-C and kinesin light chain-C were down-regulated. Validation with real-time RT-PCR analysis confirmed the up-regulation of MEPE and the down-regulation of creatine kinase (muscle form and troponin-C in the loaded tibia. Immunohistochemistry showed that the increase of MEPE protein expression was already detectable six hours after mechanical loading. In conclusion, these genes probably play a role during translation of mechanical stimuli six hours after mechanical loading. The modulation of MEPE expression may indicate a connection between bone mineralization and bone formation after mechanical stimulation.

  18. Genome-wide mapping of protein-DNA interaction by chromatin immunoprecipitation and DNA microarray hybridization (ChIP-chip). Part B: ChIP-chip data analysis.

    Science.gov (United States)

    Göbel, Ulrike; Reimer, Julia; Turck, Franziska

    2010-01-01

    Genome-wide targets of chromatin-associated factors can be identified by a combination of chromatin-immunoprecipitation and oligonucleotide microarray hybridization. Genome-wide mircoarray data analysis represents a major challenge for the experimental biologist. This chapter introduces ChIPR, a package written in the R statistical programming language that facilitates the analysis of two-color microarrays from Roche-Nimblegen. The workflow of ChIPR is illustrated with sample data from Arabidopsis thaliana. However, ChIPR supports ChIP-chip data preprocessing, target identification, and cross-annotation of any species for which genome annotation data is available in GFF format. This chapter describes how to use ChIPR as a software tool without the requirement for programming skills in the R language.

  19. Analysis of gene expression in resynthesized Brassica napus Allopolyploids using arabidopsis 70mer oligo microarrays.

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    Robert T Gaeta

    Full Text Available BACKGROUND: Studies in resynthesized Brassica napus allopolyploids indicate that homoeologous chromosome exchanges in advanced generations (S(5ratio6 alter gene expression through the loss and doubling of homoeologous genes within the rearrangements. Rearrangements may also indirectly affect global gene expression if homoeologous copies of gene regulators within rearrangements have differential affects on the transcription of genes in networks. METHODOLOGY/PRINCIPAL FINDINGS: We utilized Arabidopsis 70mer oligonucleotide microarrays for exploring gene expression in three resynthesized B. napus lineages at the S(0ratio1 and S(5ratio6 generations as well as their diploid progenitors B. rapa and B. oleracea. Differential gene expression between the progenitors and additive (midparent expression in the allopolyploids were tested. The S(5ratio6 lines differed in the number of genetic rearrangements, allowing us to test if the number of genes displaying nonadditive expression was related to the number of rearrangements. Estimates using per-gene and common variance ANOVA models indicated that 6-15% of 26,107 genes were differentially expressed between the progenitors. Individual allopolyploids showed nonadditive expression for 1.6-32% of all genes. Less than 0.3% of genes displayed nonadditive expression in all S(0ratio1 lines and 0.1-0.2% were nonadditive among all S(5ratio6 lines. Differentially expressed genes in the polyploids were over-represented by genes differential between the progenitors. The total number of differentially expressed genes was correlated with the number of genetic changes in S(5ratio6 lines under the common variance model; however, there was no relationship using a per-gene variance model, and many genes showed nonadditive expression in S(0ratio1 lines. CONCLUSIONS/SIGNIFICANCE: Few genes reproducibly demonstrated nonadditive expression among lineages, suggesting few changes resulted from a general response to polyploidization

  20. DNA Microarray Data Analysis: A Novel Biclustering Algorithm Approach

    Science.gov (United States)

    Tchagang, Alain B.; Tewfik, Ahmed H.

    2006-12-01

    Biclustering algorithms refer to a distinct class of clustering algorithms that perform simultaneous row-column clustering. Biclustering problems arise in DNA microarray data analysis, collaborative filtering, market research, information retrieval, text mining, electoral trends, exchange analysis, and so forth. When dealing with DNA microarray experimental data for example, the goal of biclustering algorithms is to find submatrices, that is, subgroups of genes and subgroups of conditions, where the genes exhibit highly correlated activities for every condition. In this study, we develop novel biclustering algorithms using basic linear algebra and arithmetic tools. The proposed biclustering algorithms can be used to search for all biclusters with constant values, biclusters with constant values on rows, biclusters with constant values on columns, and biclusters with coherent values from a set of data in a timely manner and without solving any optimization problem. We also show how one of the proposed biclustering algorithms can be adapted to identify biclusters with coherent evolution. The algorithms developed in this study discover all valid biclusters of each type, while almost all previous biclustering approaches will miss some.

  1. DNA Microarray Data Analysis: A Novel Biclustering Algorithm Approach

    Directory of Open Access Journals (Sweden)

    Tewfik Ahmed H

    2006-01-01

    Full Text Available Biclustering algorithms refer to a distinct class of clustering algorithms that perform simultaneous row-column clustering. Biclustering problems arise in DNA microarray data analysis, collaborative filtering, market research, information retrieval, text mining, electoral trends, exchange analysis, and so forth. When dealing with DNA microarray experimental data for example, the goal of biclustering algorithms is to find submatrices, that is, subgroups of genes and subgroups of conditions, where the genes exhibit highly correlated activities for every condition. In this study, we develop novel biclustering algorithms using basic linear algebra and arithmetic tools. The proposed biclustering algorithms can be used to search for all biclusters with constant values, biclusters with constant values on rows, biclusters with constant values on columns, and biclusters with coherent values from a set of data in a timely manner and without solving any optimization problem. We also show how one of the proposed biclustering algorithms can be adapted to identify biclusters with coherent evolution. The algorithms developed in this study discover all valid biclusters of each type, while almost all previous biclustering approaches will miss some.

  2. Chromosomal microarray analysis of consecutive individuals with autism spectrum disorders or learning disability presenting for genetic services.

    Science.gov (United States)

    Roberts, Jennifer L; Hovanes, Karine; Dasouki, Majed; Manzardo, Ann M; Butler, Merlin G

    2014-02-01

    Chromosomal microarray analysis is now commonly used in clinical practice to identify copy number variants (CNVs) in the human genome. We report our experience with the use of the 105 K and 180K oligonucleotide microarrays in 215 consecutive patients referred with either autism or autism spectrum disorders (ASD) or developmental delay/learning disability for genetic services at the University of Kansas Medical Center during the past 4 years (2009-2012). Of the 215 patients [140 males and 75 females (male/female ratio=1.87); 65 with ASD and 150 with learning disability], abnormal microarray results were seen in 45 individuals (21%) with a total of 49 CNVs. Of these findings, 32 represented a known diagnostic CNV contributing to the clinical presentation and 17 represented non-diagnostic CNVs (variants of unknown significance). Thirteen patients with ASD had a total of 14 CNVs, 6 CNVs recognized as diagnostic and 8 as non-diagnostic. The most common chromosome involved in the ASD group was chromosome 15. For those with a learning disability, 32 patients had a total of 35 CNVs. Twenty-six of the 35 CNVs were classified as a known diagnostic CNV, usually a deletion (n=20). Nine CNVs were classified as an unknown non-diagnostic CNV, usually a duplication (n=8). For the learning disability subgroup, chromosomes 2 and 22 were most involved. Thirteen out of 65 patients (20%) with ASD had a CNV compared with 32 out of 150 patients (21%) with a learning disability. The frequency of chromosomal microarray abnormalities compared by subject group or gender was not statistically different. A higher percentage of individuals with a learning disability had clinical findings of seizures, dysmorphic features and microcephaly, but not statistically significant. While both groups contained more males than females, a significantly higher percentage of males were present in the ASD group.

  3. 基于16S和23S rDNA基因芯片检测和鉴定七种临床常见病原菌%Detection and identification of seven clinical common pathogenic bacteria by oligonucleotide microarray

    Institute of Scientific and Technical Information of China (English)

    邢建明; 张甦; 张红河; 沈翠芬; 毕丹; 李刚; 姚丽惠

    2008-01-01

    Objective Using 16S rDNA and 23S rDNA genes as the target sequences to develop a system based on oligonucleotide microarray and to detect the seven clinical pathogenic bacteria, commonly seen. Methods Double polymerase chain reaction(PCR) was applied to amplify the segments of 16S rDNA and 23S rDNA genes of the target bacteria. An oligonucleotide microarray was constructed to simultaneously detect EHEC O157:H7, Vibrio parahaemolyticus , Saimonella sp., Vibrio cholerae ,Listeria monocytogenes, Campylobacter jejuni and Shigella sp. Specificity, sensitivity and reproducibility of the microarray during detection were checked. And then microarray was used to detect the microbes in stool specimens of 81 patients with diarrhea and vomiting. Results The double PCR method could simultaneously amplify the target sequences of 16S rDNA and 23S rDNA genes of the seven pathogens. The sensitivity of the developed oligonueleotide microarray could reach 103 cfu/ml but no positive results were presented for non-targeted bacteria. The coefficients of differentiation in one lot or among different lots of the microarray slices were 3.89%-5.81%. The positive detection rate of the stool specimens by oligonucleotide microarray was 39.5 % (32/81), with a coincidence of 96.3 % (78/81) for the patients and another coincidence of 96.8% (31/32) for bacterial genus or species identification, when comparing to the results by routine bacteriological examinations. Conclusion The established assay in this study based on oligonucleotide microarray to detect the seven pathogenic bacteria has many advantages such as convenient,rapid, accurate, stable and high flux, which is suitable for clinical specimen examination and epidemiological field investigation.%目的 以细菌16S rDNA和23S rDNA基因为靶序列建立可检测临床七种常见病原菌寡核苷酸芯片系统.方法 采用双重PCR扩增标本中靶细菌16S和23S rDNA基因片段.构建能同时检测肠出血性大肠埃希菌O157:H7

  4. Empirical Evaluation of a New Method for Calculating Signal to Noise Ratio (SNR) for Microarray Data Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Jizhong; He, Zhili; Zhou, Jizhong

    2008-03-06

    Signal-to-noise-ratio (SNR) thresholds for microarray data analysis were experimentally determined with an oligonucleotide array that contained perfect match (PM) and mismatch (MM) probes based upon four genes from Shewanella oneidensis MR-1. A new SNR calculation, called signal to both standard deviations ratio (SSDR) was developed, and evaluated along with other two methods, signal to standard deviation ratio (SSR), and signal to background ratio (SBR). At a low stringency, the thresholds of SSR, SBR, and SSDR were 2.5, 1.60 and 0.80 with oligonucleotide and PCR amplicon as target templates, and 2.0, 1.60 and 0.70 with genomic DNA as target templates. Slightly higher thresholds were obtained at the high stringency condition. The thresholds of SSR and SSDR decreased with an increase in the complexity of targets (e.g., target types), and the presence of background DNA, and a decrease in the composition of targets, while SBR remained unchanged under all situations. The lowest percentage of false positives (FP) and false negatives (FN) was observed with the SSDR calculation method, suggesting that it may be a better SNR calculation for more accurate determination of SNR thresholds. Positive spots identified by SNR thresholds were verified by the Student t-test, and consistent results were observed. This study provides general guidance for users to select appropriate SNR thresholds for different samples under different hybridization conditions.

  5. Identification of Novel Epithelial Ovarian Cancer Biomarkers by Cross-laboratory Microarray Analysis

    Institute of Scientific and Technical Information of China (English)

    蒋学锋; 朱涛; 杨洁; 李双; 叶双梅; 廖书杰; 孟力; 卢运萍; 马丁

    2010-01-01

    The purpose of this study was to pool information in epithelial ovarian cancer by combining studies using Affymetrix expression microarray datasets made at different laboratories to identify novel biomarkers.Epithelial microarray expression information across laboratories was screened and combined after preprocessing raw microarray data,then ANOVA and unpaired T test statistical analysis was performed for identifying differentially expressed genes(DEGs),followed by clustering and pathway analysis for these ...

  6. Optimization of Cyanine Dye Stability and Analysis of FRET Interaction on DNA Microarrays.

    Science.gov (United States)

    von der Haar, Marcel; Heuer, Christopher; Pähler, Martin; von der Haar, Kathrin; Lindner, Patrick; Scheper, Thomas; Stahl, Frank

    2016-11-30

    The application of DNA microarrays for high throughput analysis of genetic regulation is often limited by the fluorophores used as markers. The implementation of multi-scan techniques is limited by the fluorophores' susceptibility to photobleaching when exposed to the scanner laser light. This paper presents combined mechanical and chemical strategies which enhance the photostability of cyanine 3 and cyanine 5 as part of solid state DNA microarrays. These strategies are based on scanning the microarrays while the hybridized DNA is still in an aqueous solution with the presence of a reductive/oxidative system (ROXS). Furthermore, the experimental setup allows for the analysis and eventual normalization of Förster-resonance-energy-transfer (FRET) interaction of cyanine-3/cyanine-5 dye combinations on the microarray. These findings constitute a step towards standardization of microarray experiments and analysis and may help to increase the comparability of microarray experiment results between labs.

  7. Optimization of Cyanine Dye Stability and Analysis of FRET Interaction on DNA Microarrays

    Directory of Open Access Journals (Sweden)

    Marcel von der Haar

    2016-11-01

    Full Text Available The application of DNA microarrays for high throughput analysis of genetic regulation is often limited by the fluorophores used as markers. The implementation of multi-scan techniques is limited by the fluorophores’ susceptibility to photobleaching when exposed to the scanner laser light. This paper presents combined mechanical and chemical strategies which enhance the photostability of cyanine 3 and cyanine 5 as part of solid state DNA microarrays. These strategies are based on scanning the microarrays while the hybridized DNA is still in an aqueous solution with the presence of a reductive/oxidative system (ROXS. Furthermore, the experimental setup allows for the analysis and eventual normalization of Förster-resonance-energy-transfer (FRET interaction of cyanine-3/cyanine-5 dye combinations on the microarray. These findings constitute a step towards standardization of microarray experiments and analysis and may help to increase the comparability of microarray experiment results between labs.

  8. Microarray gene expression profiling and analysis in renal cell carcinoma

    Directory of Open Access Journals (Sweden)

    Sadhukhan Provash

    2004-06-01

    Full Text Available Abstract Background Renal cell carcinoma (RCC is the most common cancer in adult kidney. The accuracy of current diagnosis and prognosis of the disease and the effectiveness of the treatment for the disease are limited by the poor understanding of the disease at the molecular level. To better understand the genetics and biology of RCC, we profiled the expression of 7,129 genes in both clear cell RCC tissue and cell lines using oligonucleotide arrays. Methods Total RNAs isolated from renal cell tumors, adjacent normal tissue and metastatic RCC cell lines were hybridized to affymatrix HuFL oligonucleotide arrays. Genes were categorized into different functional groups based on the description of the Gene Ontology Consortium and analyzed based on the gene expression levels. Gene expression profiles of the tissue and cell line samples were visualized and classified by singular value decomposition. Reverse transcription polymerase chain reaction was performed to confirm the expression alterations of selected genes in RCC. Results Selected genes were annotated based on biological processes and clustered into functional groups. The expression levels of genes in each group were also analyzed. Seventy-four commonly differentially expressed genes with more than five-fold changes in RCC tissues were identified. The expression alterations of selected genes from these seventy-four genes were further verified using reverse transcription polymerase chain reaction (RT-PCR. Detailed comparison of gene expression patterns in RCC tissue and RCC cell lines shows significant differences between the two types of samples, but many important expression patterns were preserved. Conclusions This is one of the initial studies that examine the functional ontology of a large number of genes in RCC. Extensive annotation, clustering and analysis of a large number of genes based on the gene functional ontology revealed many interesting gene expression patterns in RCC. Most

  9. A statistical framework for differential network analysis from microarray data

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    Datta Somnath

    2010-02-01

    Full Text Available Abstract Background It has been long well known that genes do not act alone; rather groups of genes act in consort during a biological process. Consequently, the expression levels of genes are dependent on each other. Experimental techniques to detect such interacting pairs of genes have been in place for quite some time. With the advent of microarray technology, newer computational techniques to detect such interaction or association between gene expressions are being proposed which lead to an association network. While most microarray analyses look for genes that are differentially expressed, it is of potentially greater significance to identify how entire association network structures change between two or more biological settings, say normal versus diseased cell types. Results We provide a recipe for conducting a differential analysis of networks constructed from microarray data under two experimental settings. At the core of our approach lies a connectivity score that represents the strength of genetic association or interaction between two genes. We use this score to propose formal statistical tests for each of following queries: (i whether the overall modular structures of the two networks are different, (ii whether the connectivity of a particular set of "interesting genes" has changed between the two networks, and (iii whether the connectivity of a given single gene has changed between the two networks. A number of examples of this score is provided. We carried out our method on two types of simulated data: Gaussian networks and networks based on differential equations. We show that, for appropriate choices of the connectivity scores and tuning parameters, our method works well on simulated data. We also analyze a real data set involving normal versus heavy mice and identify an interesting set of genes that may play key roles in obesity. Conclusions Examining changes in network structure can provide valuable information about the

  10. [Differential gene expression in incompatible interaction between Lilium regale Wilson and Fusarium oxysporum f. sp. lilii revealed by combined SSH and microarray analysis].

    Science.gov (United States)

    Rao, J; Liu, D; Zhang, N; He, H; Ge, F; Chen, C

    2014-01-01

    Fusarium wilt, caused by a soilborne pathogen Fusarium oxysporum f. sp. lilii, is the major disease of lily (Lilium L.). In order to isolate the genes differentially expressed in a resistant reaction to F. oxysporum in L. regale Wilson, a cDNA library was constructed with L. regale root during F. oxysporum infection using the suppression subtractive hybridization (SSH), and a total of 585 unique expressed sequence tags (ESTs) were obtained. Furthermore, the gene expression profiles in the incompatible interaction between L. regale and F. oxysporum were revealed by oligonucleotide microarray analysis of 585 unique ESTs comparison to the compatible interaction between a susceptible Lilium Oriental Hybrid 'Siberia' and F. oxysporum. The result of expression profile analysis indicated that the genes encoding pathogenesis-related proteins (PRs), antioxidative stress enzymes, secondary metabolism enzymes, transcription factors, signal transduction proteins as well as a large number of unknown genes were involved in early defense response of L. regale to F. oxysporum infection. Moreover, the following quantitative reverse transcription PCR (QRT-PCR) analysis confirmed reliability of the oligonucleotide microarray data. In the present study, isolation of differentially expressed genes in L. regale during response to F. oxysporum helped to uncover the molecular mechanism associated with the resistance of L. regale against F. oxysporum.

  11. Whole genome microarray analysis, from neonatal blood cards

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    Hogan Michael E

    2009-07-01

    Full Text Available Abstract Background Neonatal blood, obtained from a heel stick and stored dry on paper cards, has been the standard for birth defects screening for 50 years. Such dried blood samples are used, primarily, for analysis of small-molecule analytes. More recently, the DNA complement of such dried blood cards has been used for targeted genetic testing, such as for single nucleotide polymorphism in cystic fibrosis. Expansion of such testing to include polygenic traits, and perhaps whole genome scanning, has been discussed as a formal possibility. However, until now the amount of DNA that might be obtained from such dried blood cards has been limiting, due to inefficient DNA recovery technology. Results A new technology is employed for efficient DNA release from a standard neonatal blood card. Using standard Guthrie cards, stored an average of ten years post-collection, about 1/40th of the air-dried neonatal blood specimen (two 3 mm punches was processed to obtain DNA that was sufficient in mass and quality for direct use in microarray-based whole genome scanning. Using that same DNA release technology, it is also shown that approximately 1/250th of the original purified DNA (about 1 ng could be subjected to whole genome amplification, thus yielding an additional microgram of amplified DNA product. That amplified DNA product was then used in microarray analysis and yielded statistical concordance of 99% or greater to the primary, unamplified DNA sample. Conclusion Together, these data suggest that DNA obtained from less than 10% of a standard neonatal blood specimen, stored dry for several years on a Guthrie card, can support a program of genome-wide neonatal genetic testing.

  12. Towards standardization of microarray-based genotyping of Salmonella

    DEFF Research Database (Denmark)

    Löfström, Charlotta; Grønlund, Hugo Ahlm; Riber, Leise

    2010-01-01

    Genotyping is becoming an increasingly important tool to improve risk assessments of Salmonella. DNA microarray technology is a promising diagnostic tool that can provide high resolution genomic profile of many genes simultaneously. However, standardization of DNA microarray analysis is needed...... of Salmonella at two different laboratories. The low-density array contained 281 of 57-60-mer oligonucleotide probes for detecting a wide range of specific genomic markers associated with antibiotic resistance, cell envelope structures, mobile genetic elements and pathogenicity. Several test parameters...... for a decentralized and simple-to-implement DNA microarray as part of a pan-European source-attribution model for risk assessment of Salmonella....

  13. Genome-wide identification of gene expression in the epididymis of infertile rat induced by alpha-chlorohydrin using oligonucleotide microarray

    Institute of Scientific and Technical Information of China (English)

    XIE Shu-wu; ZHU Yan; MA Li; LI Zhi-ling; GUI You-lun; LU Ying-ying; ZHAO Zhi-fang; CAO Lin

    2008-01-01

    Objective To establish a rat model of sterility associated with epididymis and epididymal gene expression profiles relation to fertility by alpha-chlorohydrin. Methods Rats were treated with 10 mg·kg-1. d-1. alpha-chlorohydrin for 10 consecutive days. Sperm maturation and other fertility parameters were analyzed. The sperm motility and morphology were evaluated by computer-assisted sperm analysis (CASA);sperm survival rate was assessed by SYBR-14 and propidium iodide (PI) fluorescent staining; the weights of testes, epididymides, prostates and seminal vesicles were determined by electronic balance; histological examination of above tissues were evaluated by HE staining;and serumal dihydrotestosterone (DHT) and testosterone (T) of rats were detected by enzyme-labeled immunoassay. Each male rat was paired with 2 female rats in proestrus. Female rats were examined the next morning for the presence of sperm in vaginal smears and underwent a cesarean section on day 12 of gestation. Finally the reproductive indices were calculated as follows: copulation index (number of sperm positive females / number of pairings), pregnancy index (number of pregnancies / number of sperm positive females), and fertility index (number of pregnancies / number of pairings). After that we used Affymetrix Rat 230 2.0 oligo-microarray to identify epididymal special genes associated with fertility. Finally, we validated some of these genes by Real-Time quantitative polymerase chain reaction. Results The motility of spermatozoa from the cauda epididymidis of treated rats showed a significant decrease in percentage of motile, progressively motile sperm, and sperm survival rate. At the same time, the morphology of cauda epididymal spermatozoa was also adversely affected by the treatment. In addition, the serumal androgen levels of treated animals weren' t changed compared with the control group. Accordingly, matings with treated males resulted in no successful pregnancy. Then, we classified

  14. The application of phenotypic microarray analysis to anti-fungal drug development.

    Science.gov (United States)

    Greetham, Darren; Lappin, David F; Rajendran, Ranjith; O'Donnell, Lindsay; Sherry, Leighann; Ramage, Gordon; Nile, Christopher

    2017-03-01

    Candida albicans metabolic activity in the presence and absence of acetylcholine was measured using phenotypic microarray analysis. Acetylcholine inhibited C. albicans biofilm formation by slowing metabolism independent of biofilm forming capabilities. Phenotypic microarray analysis can therefore be used for screening compound libraries for novel anti-fungal drugs and measuring antifungal resistance.

  15. Experimental Approaches to Microarray Analysis of Tumor Samples

    Science.gov (United States)

    Furge, Laura Lowe; Winter, Michael B.; Meyers, Jacob I.; Furge, Kyle A.

    2008-01-01

    Comprehensive measurement of gene expression using high-density nucleic acid arrays (i.e. microarrays) has become an important tool for investigating the molecular differences in clinical and research samples. Consequently, inclusion of discussion in biochemistry, molecular biology, or other appropriate courses of microarray technologies has…

  16. High throughput genetic analysis of congenital myasthenic syndromes using resequencing microarrays.

    Directory of Open Access Journals (Sweden)

    Lisa Denning

    Full Text Available BACKGROUND: The use of resequencing microarrays for screening multiple, candidate disease loci is a promising alternative to conventional capillary sequencing. We describe the performance of a custom resequencing microarray for mutational analysis of Congenital Myasthenic Syndromes (CMSs, a group of disorders in which the normal process of neuromuscular transmission is impaired. METHODOLOGY/PRINCIPAL FINDINGS: Our microarray was designed to assay the exons and flanking intronic regions of 8 genes linked to CMSs. A total of 31 microarrays were hybridized with genomic DNA from either individuals with known CMS mutations or from healthy controls. We estimated an overall microarray call rate of 93.61%, and we found the percentage agreement between the microarray and capillary sequencing techniques to be 99.95%. In addition, our microarray exhibited 100% specificity and 99.99% reproducibility. Finally, the microarray detected 22 out of the 23 known missense mutations, but it failed to detect all 7 known insertion and deletion (indels mutations, indicating an overall sensitivity of 73.33% and a sensitivity with respect to missense mutations of 95.65%. CONCLUSIONS/SIGNIFICANCE: Overall, our microarray prototype exhibited strong performance and proved highly efficient for screening genes associated with CMSs. Until indels can be efficiently assayed with this technology, however, we recommend using resequencing microarrays for screening CMS mutations after common indels have been first assayed by capillary sequencing.

  17. Detection of gene expression in an individual cell type within a cell mixture using microarray analysis.

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    Penelope A Bryant

    Full Text Available BACKGROUND: A central issue in the design of microarray-based analysis of global gene expression is the choice between using cells of single type and a mixture of cells. This study quantified the proportion of lipopolysaccharide (LPS induced differentially expressed monocyte genes that could be measured in peripheral blood mononuclear cells (PBMC, and determined the extent to which gene expression in the non-monocyte cell fraction diluted or obscured fold changes that could be detected in the cell mixture. METHODOLOGY/PRINCIPAL FINDINGS: Human PBMC were stimulated with LPS, and monocytes were then isolated by positive (Mono+ or negative (Mono- selection. The non-monocyte cell fraction (MonoD remaining after positive selection of monocytes was used to determine the effect of non-monocyte cells on overall expression. RNA from LPS-stimulated PBMC, Mono+, Mono- and MonoD samples was co-hybridised with unstimulated RNA for each cell type on oligonucleotide microarrays. There was a positive correlation in gene expression between PBMC and both Mono+ (0.77 and Mono- (0.61-0.67 samples. Analysis of individual genes that were differentially expressed in Mono+ and Mono- samples showed that the ability to detect expression of some genes was similar when analysing PBMC, but for others, differential expression was either not detected or changed in the opposite direction. As a result of the dilutional or obscuring effect of gene expression in non-monocyte cells, overall about half of the statistically significant LPS-induced changes in gene expression in monocytes were not detected in PBMC. However, 97% of genes with a four fold or greater change in expression in monocytes after LPS stimulation, and almost all (96-100% of the top 100 most differentially expressed monocyte genes were detected in PBMC. CONCLUSIONS/SIGNIFICANCE: The effect of non-responding cells in a mixture dilutes or obscures the detection of subtle changes in gene expression in an individual

  18. A factorial analysis of silanization conditions for the immobilization of oligonucleotides on glass surfaces.

    Science.gov (United States)

    Halliwell, C M; Cass, A E

    2001-06-01

    The modification of glass surfaces with (3-mercaptopropyl)trimethoxysilane and the application of this to DNA chip technology are described. A range of factors influencing the silanization method, and hence the number of surface-bound, chemically active thiol groups, were investigated using a design of experiment approach based on analysis of variance. The number of thiol groups introduced on glass substrates were measured directly using a specific radiolabel, [14C]cysteamine hydrochloride. For liquid-phase silanization, the number of surface-bound thiol groups was found to be dependent on both postsilanization thermal curing and silanization time and relatively independent of silane concentration, reaction temperature, and sample pretreatment. Depending on the conditions used in liquid-phase silanization, (1.3-9.0) x 10(12) thiol groups/cm2 on the glass samples were bound. The reliability and repeatability of liquid- and vacuum-phase silanization were also investigated. Eighteen-base oligonucleotide probes were covalently attached to the modified surfaces via a 3'-amino modification on the DNA and subsequent reaction with the cross-linking reagent N-(gamma-maleimidobutyryloxy) succinimide ester (GMBS). The resulting probe levels were determined and found to be stoichiometric with that of the introduced thiol groups. These results demonstrate that silanization of glass surfaces under specific conditions, prior to probe attachment, is of great importance in the development of DNA chips that use the simple concept of the covalent attachment of presynthesized oligonucleotides to silicon oxide surfaces.

  19. On the Statics for Micro-Array Data Analysis

    Science.gov (United States)

    Urushibara, Tomoko; Akasaka, Shizu; Ito, Makiko; Suzuki, Tomonori; Miyazaki, Satoru

    2010-01-01

    data, we might get a different result because the distinct definition for micro array data has not been set yet. It means that from the same data we will get different results depending on researchers. We are afraid that this problem will have a big effect on developing new medicines and to progress the next step, like a 2nd screening. So, we suggest that we should have certain guidelines to analyze Micro-Array data validly with statistic method and it will surely be helpful for Micro-Array analysis for medical studies in the future.

  20. Overview of Microarray Analysis of Gene Expression and its Applications to Cervical Cancer Investigation

    Directory of Open Access Journals (Sweden)

    Angel Chao

    2007-12-01

    Full Text Available Cervical cancer is one of the leading female cancers in Taiwan and ranks as the fifth cause of cancer death in the female population. Human papillomavirus has been established as the causative agent for cervical neoplasia and cervical cancer. However, the tumor biology involved in the prognoses of different cell types in early cancers and tumor responses to radiation in advanced cancers remain largely unknown. The introduction of microarray technologies in the 1990s has provided genome-wide strategies for searching tens of thousands of genes simultaneously. In this review, we first summarize the two types of microarrays: oligonucleotides microarray and cDNA microarray. Then, we review the studies of functional genomics in cervical cancer. Gene expression studies that involved cervical cancer cell lines, cervical cells of cancer versus normal ectocervix, cancer tissues of different histology, radioresistant versus radiosensitive patients, and the combinatorial gene expression associated with chromosomal amplifications are discussed. In particular, CEACAM5, TACSTD1, S100P, and MSLN have shown to be upregulated in adenocarcinoma, and increased expression levels of CEACAM5 and TACSTD1 were significantly correlated with poorer patient outcomes. On the other hand, 35 genes, including apoptotic genes (e.g. BIK, TEGT, SSI-3, hypoxia-inducible genes (e.g. HIF1A, CA12, and tumor cell invasion and metastasis genes (e.g. CTSL, CTSB, PLAU, CD44, have been noted to echo the hypothesis that increased tumor hypoxia leads to radiation resistance in cervical cancer during radiation.

  1. Application of microarray analysis on computer cluster and cloud platforms.

    Science.gov (United States)

    Bernau, C; Boulesteix, A-L; Knaus, J

    2013-01-01

    Analysis of recent high-dimensional biological data tends to be computationally intensive as many common approaches such as resampling or permutation tests require the basic statistical analysis to be repeated many times. A crucial advantage of these methods is that they can be easily parallelized due to the computational independence of the resampling or permutation iterations, which has induced many statistics departments to establish their own computer clusters. An alternative is to rent computing resources in the cloud, e.g. at Amazon Web Services. In this article we analyze whether a selection of statistical projects, recently implemented at our department, can be efficiently realized on these cloud resources. Moreover, we illustrate an opportunity to combine computer cluster and cloud resources. In order to compare the efficiency of computer cluster and cloud implementations and their respective parallelizations we use microarray analysis procedures and compare their runtimes on the different platforms. Amazon Web Services provide various instance types which meet the particular needs of the different statistical projects we analyzed in this paper. Moreover, the network capacity is sufficient and the parallelization is comparable in efficiency to standard computer cluster implementations. Our results suggest that many statistical projects can be efficiently realized on cloud resources. It is important to mention, however, that workflows can change substantially as a result of a shift from computer cluster to cloud computing.

  2. Rapid and quantitative quality control of microarrays using cationic nanoparticles.

    Science.gov (United States)

    Sun, Ye; Fan, Wenhua; McCann, Michael P; Golovlev, Val

    2009-02-15

    The fabrication quality of microarrays significantly influences the accuracy and reproducibility of microarray experiments. In this report, we present a simple and fast quality control (QC) method for spotted oligonucleotide and cDNA microarrays. It employs a nonspecific electrostatic interaction of colloidal gold nanoparticles with the chemical groups of DNA molecules and other biomolecules immobilized on the microarray surface that bear positive or negative charges. An inexpensive flatbed scanner is used to visualize and quantify the binding of cationic gold particles to the anionic DNA probes on the microarray surface. An image analysis software was designed to assess the various parameters of the array spots including spot intensity, shape and array homogeneity, calculate the overall array quality score, and save the detailed array quality report in an Excel file. The gold staining technique is fast and sensitive. It can be completed in 10 min and detect less than 1% of the probe amount commonly recommended for microarrays. Compared to the current microarray QC method that utilizes the hybridization of probes with short random sequence oligonucleotides labeled with fluorophore, our gold staining method requires less time for the analysis, reduces the reagent cost, and eliminates the need for the expensive laser scanner.

  3. Microarray-based analysis of IncA/C plasmid-associated genes from multidrug-resistant Salmonella enterica.

    Science.gov (United States)

    Lindsey, Rebecca L; Frye, Jonathan G; Fedorka-Cray, Paula J; Meinersmann, Richard J

    2011-10-01

    In the family Enterobacteriaceae, plasmids have been classified according to 27 incompatibility (Inc) or replicon types that are based on the inability of different plasmids with the same replication mechanism to coexist in the same cell. Certain replicon types such as IncA/C are associated with multidrug resistance (MDR). We developed a microarray that contains 286 unique 70-mer oligonucleotide probes based on sequences from five IncA/C plasmids: pYR1 (Yersinia ruckeri), pPIP1202 (Yersinia pestis), pP99-018 (Photobacterium damselae), pSN254 (Salmonella enterica serovar Newport), and pP91278 (Photobacterium damselae). DNA from 59 Salmonella enterica isolates was hybridized to the microarray and analyzed for the presence or absence of genes. These isolates represented 17 serovars from 14 different animal hosts and from different geographical regions in the United States. Qualitative cluster analysis was performed using CLUSTER 3.0 to group microarray hybridization results. We found that IncA/C plasmids occurred in two lineages distinguished by a major insertion-deletion (indel) region that contains genes encoding mostly hypothetical proteins. The most variable genes were represented by transposon-associated genes as well as four antimicrobial resistance genes (aphA, merP, merA, and aadA). Sixteen mercury resistance genes were identified and highly conserved, suggesting that mercury ion-related exposure is a stronger pressure than anticipated. We used these data to construct a core IncA/C genome and an accessory genome. The results of our studies suggest that the transfer of antimicrobial resistance determinants by transfer of IncA/C plasmids is somewhat less common than exchange within the plasmids orchestrated by transposable elements, such as transposons, integrating and conjugative elements (ICEs), and insertion sequence common regions (ISCRs), and thus pose less opportunity for exchange of antimicrobial resistance.

  4. A universal assay for detection of oncogenic fusion transcripts by oligo microarray analysis

    Directory of Open Access Journals (Sweden)

    Ribeiro Franclim R

    2009-01-01

    Full Text Available Abstract Background The ability to detect neoplasia-specific fusion genes is important not only in cancer research, but also increasingly in clinical settings to ensure that correct diagnosis is made and the optimal treatment is chosen. However, the available methodologies to detect such fusions all have their distinct short-comings. Results We describe a novel oligonucleotide microarray strategy whereby one can screen for all known oncogenic fusion transcripts in a single experiment. To accomplish this, we combine measurements of chimeric transcript junctions with exon-wise measurements of individual fusion partners. To demonstrate the usefulness of the approach, we designed a DNA microarray containing 68,861 oligonucleotide probes that includes oligos covering all combinations of chimeric exon-exon junctions from 275 pairs of fusion genes, as well as sets of oligos internal to all the exons of the fusion partners. Using this array, proof of principle was demonstrated by detection of known fusion genes (such as TCF3:PBX1, ETV6:RUNX1, and TMPRSS2:ERG from all six positive controls consisting of leukemia cell lines and prostate cancer biopsies. Conclusion This new method bears promise of an important complement to currently used diagnostic and research tools for the detection of fusion genes in neoplastic diseases.

  5. Bulk segregant analysis using single nucleotide polymorphism microarrays.

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    Anthony Becker

    Full Text Available Bulk segregant analysis (BSA using microarrays, and extreme array mapping (XAM have recently been used to rapidly identify genomic regions associated with phenotypes in multiple species. These experiments, however, require the identification of single feature polymorphisms (SFP between the cross parents for each new combination of genotypes, which raises the cost of experiments. The availability of the genomic polymorphism data in Arabidopsis thaliana, coupled with the efficient designs of Single Nucleotide Polymorphism (SNP genotyping arrays removes the requirement for SFP detection and lowers the per array cost, thereby lowering the overall cost per experiment. To demonstrate that these approaches would be functional on SNP arrays and determine confidence intervals, we analyzed hybridizations of natural accessions to the Arabidopsis ATSNPTILE array and simulated BSA or XAM given a variety of gene models, populations, and bulk selection parameters. Our results show a striking degree of correlation between the genotyping output of both methods, which suggests that the benefit of SFP genotyping in context of BSA can be had with the cheaper, more efficient SNP arrays. As a final proof of concept, we hybridized the DNA from bulks of an F2 mapping population of a Sulfur and Selenium ionomics mutant to both the Arabidopsis ATTILE1R and ATSNPTILE arrays, which produced almost identical results. We have produced R scripts that prompt the user for the required parameters and perform the BSA analysis using the ATSNPTILE1 array and have provided them as supplemental data files.

  6. A comparative analysis of DNA barcode microarray feature size

    Directory of Open Access Journals (Sweden)

    Smith Andrew M

    2009-10-01

    Full Text Available Abstract Background Microarrays are an invaluable tool in many modern genomic studies. It is generally perceived that decreasing the size of microarray features leads to arrays with higher resolution (due to greater feature density, but this increase in resolution can compromise sensitivity. Results We demonstrate that barcode microarrays with smaller features are equally capable of detecting variation in DNA barcode intensity when compared to larger feature sizes within a specific microarray platform. The barcodes used in this study are the well-characterized set derived from the Yeast KnockOut (YKO collection used for screens of pooled yeast (Saccharomyces cerevisiae deletion mutants. We treated these pools with the glycosylation inhibitor tunicamycin as a test compound. Three generations of barcode microarrays at 30, 8 and 5 μm features sizes independently identified the primary target of tunicamycin to be ALG7. Conclusion We show that the data obtained with 5 μm feature size is of comparable quality to the 30 μm size and propose that further shrinking of features could yield barcode microarrays with equal or greater resolving power and, more importantly, higher density.

  7. ArrayNinja: An Open Source Platform for Unified Planning and Analysis of Microarray Experiments.

    Science.gov (United States)

    Dickson, B M; Cornett, E M; Ramjan, Z; Rothbart, S B

    2016-01-01

    Microarray-based proteomic platforms have emerged as valuable tools for studying various aspects of protein function, particularly in the field of chromatin biochemistry. Microarray technology itself is largely unrestricted in regard to printable material and platform design, and efficient multidimensional optimization of assay parameters requires fluidity in the design and analysis of custom print layouts. This motivates the need for streamlined software infrastructure that facilitates the combined planning and analysis of custom microarray experiments. To this end, we have developed ArrayNinja as a portable, open source, and interactive application that unifies the planning and visualization of microarray experiments and provides maximum flexibility to end users. Array experiments can be planned, stored to a private database, and merged with the imaged results for a level of data interaction and centralization that is not currently attainable with available microarray informatics tools.

  8. Glycan microarray analysis of Candida glabrata adhesin ligand specificity.

    Science.gov (United States)

    Zupancic, Margaret L; Frieman, Matthew; Smith, David; Alvarez, Richard A; Cummings, Richard D; Cormack, Brendan P

    2008-05-01

    The Candida glabrata genome encodes at least 23 members of the EPA (epithelial adhesin) family responsible for mediating adherence to host cells. To better understand the mechanism by which the Epa proteins contribute to pathogenesis, we have used glycan microarray analysis to characterize their carbohydrate-binding specificities. Using Saccharomyces cerevisiae strains surface-expressing the N-terminal ligand-binding domain of the Epa proteins, we found that the three Epa family members functionally identified as adhesins in Candida glabrata (Epa1, Epa6 and Epa7) bind to ligands containing a terminal galactose residue. However, the specificity of the three proteins for glycans within this class varies, with Epa6 having a broader specificity range than Epa1 or Epa7. This result is intriguing given the close homology between Epa6 and Epa7, which are 92% identical at the amino acid level. We have mapped a five-amino-acid region within the N-terminal ligand-binding domain that accounts for the difference in specificity of Epa6 and Epa7 and show that these residues contribute to adherence to both epithelial and endothelial cell lines in vitro.

  9. Gene Expression Signature in Endemic Osteoarthritis by Microarray Analysis

    Directory of Open Access Journals (Sweden)

    Xi Wang

    2015-05-01

    Full Text Available Kashin-Beck Disease (KBD is an endemic osteochondropathy with an unknown pathogenesis. Diagnosis of KBD is effective only in advanced cases, which eliminates the possibility of early treatment and leads to an inevitable exacerbation of symptoms. Therefore, we aim to identify an accurate blood-based gene signature for the detection of KBD. Previously published gene expression profile data on cartilage and peripheral blood mononuclear cells (PBMCs from adults with KBD were compared to select potential target genes. Microarray analysis was conducted to evaluate the expression of the target genes in a cohort of 100 KBD patients and 100 healthy controls. A gene expression signature was identified using a training set, which was subsequently validated using an independent test set with a minimum redundancy maximum relevance (mRMR algorithm and support vector machine (SVM algorithm. Fifty unique genes were differentially expressed between KBD patients and healthy controls. A 20-gene signature was identified that distinguished between KBD patients and controls with 90% accuracy, 85% sensitivity, and 95% specificity. This study identified a 20-gene signature that accurately distinguishes between patients with KBD and controls using peripheral blood samples. These results promote the further development of blood-based genetic biomarkers for detection of KBD.

  10. Microarray analysis of human epithelial cell responses to bacterial interaction.

    Science.gov (United States)

    Mans, Jeffrey J; Lamont, Richard J; Handfield, Martin

    2006-09-01

    Host-pathogen interactions are inherently complex and dynamic. The recent use of human microarrays has been invaluable to monitor the effects of various bacterial and viral pathogens upon host cell gene expression programs. This methodology has allowed the host response transcriptome of several cell lines to be studied on a global scale. To this point, the great majority of reports have focused on the response of immune cells, including macrophages and dendritic cells. These studies revealed that the immune response to microbial pathogens is tailored to different microbial challenges. Conversely, the paradigm for epithelial cells has--until recently--held that the epithelium mostly served as a relatively passive physical barrier to infection. It is now generally accepted that the epithelial barrier contributes more actively to signaling events in the immune response. In light of this shift, this review will compare transcriptional profiling data from studies that involved host-pathogen interactions occurring with epithelial cells. Experiments that defined both a common core response, as well as pathogen-specific host responses will be discussed. This review will also summarize the contributions that transcriptional profiling analysis has made to our understanding of bacterial physio-pathogensis of infection. This will include a discussion of how host transcriptional responses can be used to infer the function of virulence determinants from bacterial pathogens interacting with epithelial mucosa. In particular, we will expand upon the lessons that have been learned from gastro-intestinal and oral pathogens, as well as from members of the commensal flora.

  11. DNA microarray analysis of fim mutations in Escherichia coli

    DEFF Research Database (Denmark)

    Schembri, Mark; Ussery, David; Workman, Christopher

    2002-01-01

    Bacterial adhesion is often mediated by complex polymeric surface structures referred to as fimbriae. Type I fimbriae of Escherichia coli represent the archetypical and best characterised fimbrial system. These adhesive organelles mediate binding to D-mannose and are directly associated with viru...... the number of fimbriae expressed on the cell surface. The use of high-resolution oligonucleotide arrays for defining points of transcription initiation and termination is also demonstrated....

  12. Carbohydrate microarrays

    DEFF Research Database (Denmark)

    Park, Sungjin; Gildersleeve, Jeffrey C; Blixt, Klas Ola

    2012-01-01

    -based technology has been widely employed for rapid analysis of the glycan binding properties of lectins and antibodies, the quantitative measurements of glycan-protein interactions, detection of cells and pathogens, identification of disease-related anti-glycan antibodies for diagnosis, and fast assessment...... of substrate specificities of glycosyltransferases. This review covers the construction of carbohydrate microarrays, detection methods of carbohydrate microarrays and their applications in biological and biomedical research.......In the last decade, carbohydrate microarrays have been core technologies for analyzing carbohydrate-mediated recognition events in a high-throughput fashion. A number of methods have been exploited for immobilizing glycans on the solid surface in a microarray format. This microarray...

  13. A genome-wide 20 K citrus microarray for gene expression analysis.

    Science.gov (United States)

    Martinez-Godoy, M Angeles; Mauri, Nuria; Juarez, Jose; Marques, M Carmen; Santiago, Julia; Forment, Javier; Gadea, Jose

    2008-07-03

    Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genome-wide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. We have designed and constructed a publicly available genome-wide cDNA microarray that include 21,081 putative unigenes of citrus. As a functional companion to the microarray, a web-browsable database 1 was created and populated with information about the unigenes represented in the microarray, including cDNA libraries, isolated clones, raw and processed nucleotide and protein sequences, and results of all the structural and functional annotation of the unigenes, like general description, BLAST hits, putative Arabidopsis orthologs, microsatellites, putative SNPs, GO classification and PFAM domains. We have performed a Gene Ontology comparison with the full set of Arabidopsis proteins to estimate the genome coverage of the microarray. We have also performed microarray hybridizations to check its usability. This new cDNA microarray replaces the first 7K microarray generated two years ago and allows gene expression analysis at a more global scale. We have followed a rational design to minimize cross-hybridization while maintaining its utility for different citrus species. Furthermore, we also provide access to a website with full structural and functional annotation of the unigenes represented in the microarray, along with the ability to use this site to directly perform gene expression analysis using standard tools at different publicly available servers. Furthermore, we show how this microarray offers a good representation of the citrus genome and present the usefulness of this genomic tool for global studies in citrus by using it to catalogue genes expressed in

  14. A genome-wide 20 K citrus microarray for gene expression analysis

    Directory of Open Access Journals (Sweden)

    Gadea Jose

    2008-07-01

    Full Text Available Abstract Background Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genome-wide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. Results We have designed and constructed a publicly available genome-wide cDNA microarray that include 21,081 putative unigenes of citrus. As a functional companion to the microarray, a web-browsable database 1 was created and populated with information about the unigenes represented in the microarray, including cDNA libraries, isolated clones, raw and processed nucleotide and protein sequences, and results of all the structural and functional annotation of the unigenes, like general description, BLAST hits, putative Arabidopsis orthologs, microsatellites, putative SNPs, GO classification and PFAM domains. We have performed a Gene Ontology comparison with the full set of Arabidopsis proteins to estimate the genome coverage of the microarray. We have also performed microarray hybridizations to check its usability. Conclusion This new cDNA microarray replaces the first 7K microarray generated two years ago and allows gene expression analysis at a more global scale. We have followed a rational design to minimize cross-hybridization while maintaining its utility for different citrus species. Furthermore, we also provide access to a website with full structural and functional annotation of the unigenes represented in the microarray, along with the ability to use this site to directly perform gene expression analysis using standard tools at different publicly available servers. Furthermore, we show how this microarray offers a good representation of the citrus genome and present the usefulness of this genomic tool for global

  15. EST and microarray analysis of horn development in Onthophagus beetles

    Directory of Open Access Journals (Sweden)

    Tang Zuojian

    2009-10-01

    Full Text Available Abstract Background The origin of novel traits and their subsequent diversification represent central themes in evo-devo and evolutionary ecology. Here we explore the genetic and genomic basis of a class of traits that is both novel and highly diverse, in a group of organisms that is ecologically complex and experimentally tractable: horned beetles. Results We developed two high quality, normalized cDNA libraries for larval and pupal Onthophagus taurus and sequenced 3,488 ESTs that assembled into 451 contigs and 2,330 singletons. We present the annotation and a comparative analysis of the conservation of the sequences. Microarrays developed from the combined libraries were then used to contrast the transcriptome of developing primordia of head horns, prothoracic horns, and legs. Our experiments identify a first comprehensive list of candidate genes for the evolution and diversification of beetle horns. We find that developing horns and legs show many similarities as well as important differences in their transcription profiles, suggesting that the origin of horns was mediated partly, but not entirely, by the recruitment of genes involved in the formation of more traditional appendages such as legs. Furthermore, we find that horns developing from the head and prothorax differ in their transcription profiles to a degree that suggests that head and prothoracic horns are not serial homologs, but instead may have evolved independently from each other. Conclusion We have laid the foundation for a systematic analysis of the genetic basis of horned beetle development and diversification with the potential to contribute significantly to several major frontiers in evolutionary developmental biology.

  16. Statistical approaches for the analysis of DNA methylation microarray data.

    Science.gov (United States)

    Siegmund, Kimberly D

    2011-06-01

    Following the rapid development and adoption in DNA methylation microarray assays, we are now experiencing a growth in the number of statistical tools to analyze the resulting large-scale data sets. As is the case for other microarray applications, biases caused by technical issues are of concern. Some of these issues are old (e.g., two-color dye bias and probe- and array-specific effects), while others are new (e.g., fragment length bias and bisulfite conversion efficiency). Here, I highlight characteristics of DNA methylation that suggest standard statistical tools developed for other data types may not be directly suitable. I then describe the microarray technologies most commonly in use, along with the methods used for preprocessing and obtaining a summary measure. I finish with a section describing downstream analyses of the data, focusing on methods that model percentage DNA methylation as the outcome, and methods for integrating DNA methylation with gene expression or genotype data.

  17. Microarray gene expression analysis of uterosacral ligaments in uterine prolapse.

    Science.gov (United States)

    Ak, Handan; Zeybek, Burak; Atay, Sevcan; Askar, Niyazi; Akdemir, Ali; Aydin, Hikmet Hakan

    2016-11-01

    Pelvic organ prolapse (POP) is a major health problem that impairs the quality of life with a wide clinical spectrum. Since the uterosacral ligaments provide primary support for the uterus and the upper vagina, we hypothesize that the disruption of these ligaments may lead to a loss of support and eventually contribute to POP. In this study, we therefore investigated whether there are any differences in the transcription profile of uterosacral ligaments in patients with POP when compared to those of the control samples. Seventeen women with POP and 8 non-POP controls undergoing hysterectomy for benign conditions were included in the study. Affymetrix® Gene Chip microarrays (Human Hu 133 plus 2.0) were used for whole genome gene expression profiling analysis. There was 1 significantly down-regulated gene, NKX2-3 in patients with POP compared to the controls (p=4.28464e-013). KIF11 gene was found to be significantly down-regulated in patients with ≥3 deliveries compared to patients with <3 deliveries (p=0.0156237). UGT1A1 (p=2.43388e-005), SCARB1 (p=1.19001e-006) and NKX2-3 (p=2.17966e-013) genes were found to be significantly down-regulated in the premenopausal patients compared to the premenopausal controls. UGT1A1 gene was also found to be significantly down-regulated in the post menopausal patients compared to the postmenopausal controls (p=0.0005). This study provides evidence for a significant down-regulation of the genes that take role in cell cycle, proliferation and embryonic development along with cell adhesion process on the development of POP for the first time. Copyright © 2016 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

  18. Microarray analysis of genes affected by salt stress in tomato | Zhou ...

    African Journals Online (AJOL)

    Microarray analysis of genes affected by salt stress in tomato. ... African Journal of Environmental Science and Technology ... key enzyme genes in the metabolic pathways of carbohydrates, amino acids, and fatty acids, were also affected by ...

  19. Versatile High Throughput Microarray Analysis for Marine Glycobiology

    DEFF Research Database (Denmark)

    Asunción Salmeán, Armando

    to concept proof that is possible to use the Comprehensive Microarray Polymer Profiling (CoMPP) as a tool for other extracellular matrixes such as marine animals and not only for algal or plant cell walls. Thus, we discovered fucoidan and cellulose epitopes in several tissues of various marine animals from...

  20. Quantitative analysis of tumor mitochondrial RNA using microarray

    Institute of Scientific and Technical Information of China (English)

    Cheng-Bo Han; Xiao-Yun Mao; Yan Xin; Shao-Cheng Wang; Jia-Ming Ma; Yu-Jie Zhao

    2005-01-01

    AIM: To design a novel method to rapidly detect the quantitative alteration of mtRNA in patients with tumors.METHODS: Oligo 6.22 and Primer Premier 5.0 bio-soft were used to design 15 pairs of primers of mtRNA cDNA probes in light of the functional and structural property of mtDNA, and then RT-PCR amplification was used to produce 15 probes of mtRNA from one normal gastric mucosal tissue. Total RNA extracted from 9 gastric cancers and corresponding normal gastric mucosal tissues was reverse transcribed into cDNA labeled with fluorescein. The spotted mtDNA microarrays were made and hybridized. Finally,the microarrays were scanned with a GeneTACTM laser scanner to get the hybridized results. Northern blot was used to confirm the microarray results.RESULTS: The hybridized spots were distinct with clear and consistent backgrounds. After data was standardized according to the housekeeping genes, the results showed that the expression levels of some mitochondrial genes in gastric carcinoma were different from those in the corresponding non-cancerous regions.CONCLUSION: The mtDNA expression microarray can rapidly, massively and exactly detect the quantity of mtRNA in tissues and cells. In addition, the whole expressive information of mtRNA from a tumor patient on just one slide can be obtained using this method, providing an effective method to investigate the relationship between mtDNA expression and tumorigenesis.

  1. VIPR: A probabilistic algorithm for analysis of microbial detection microarrays

    Directory of Open Access Journals (Sweden)

    Holbrook Michael R

    2010-07-01

    Full Text Available Abstract Background All infectious disease oriented clinical diagnostic assays in use today focus on detecting the presence of a single, well defined target agent or a set of agents. In recent years, microarray-based diagnostics have been developed that greatly facilitate the highly parallel detection of multiple microbes that may be present in a given clinical specimen. While several algorithms have been described for interpretation of diagnostic microarrays, none of the existing approaches is capable of incorporating training data generated from positive control samples to improve performance. Results To specifically address this issue we have developed a novel interpretive algorithm, VIPR (Viral Identification using a PRobabilistic algorithm, which uses Bayesian inference to capitalize on empirical training data to optimize detection sensitivity. To illustrate this approach, we have focused on the detection of viruses that cause hemorrhagic fever (HF using a custom HF-virus microarray. VIPR was used to analyze 110 empirical microarray hybridizations generated from 33 distinct virus species. An accuracy of 94% was achieved as measured by leave-one-out cross validation. Conclusions VIPR outperformed previously described algorithms for this dataset. The VIPR algorithm has potential to be broadly applicable to clinical diagnostic settings, wherein positive controls are typically readily available for generation of training data.

  2. A web-based platform for rice microarray annotation and data analysis

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Rice(Oryza sativa) feeds over half of the global population.A web-based integrated platform for rice microarray annotation and data analysis in various biological contexts is presented,which provides a convenient query for comprehensive annotation compared with similar databases.Coupled with existing rice microarray data,it provides online analysis methods from the perspective of bioinformatics.This comprehensive bioinformatics analysis platform is composed of five modules,including data retrieval,microarray annotation,sequence analysis,results visualization and data analysis.The BioChip module facilitates the retrieval of microarray data information via identifiers of "Probe Set ID","Locus ID" and "Analysis Name".The BioAnno module is used to annotate the gene or probe set based on the gene function,the domain information,the KEGG biochemical and regulatory pathways and the potential microRNA which regulates the genes.The BioSeq module lists all of the related sequence information by a microarray probe set.The BioView module provides various visual results for the microarray data.The BioAnaly module is used to analyze the rice microarray’s data set.

  3. Comparative analysis of methods for gene transcription profiling data derived from different microarray technologies in rat and mouse models of diabetes

    Directory of Open Access Journals (Sweden)

    Bihoreau Marie-Thérèse

    2009-02-01

    Full Text Available Abstract Background Microarray technologies are widely used to quantify the abundance of transcripts corresponding to thousands of genes. To maximise the robustness of transcriptome results, we have tested the performance and reproducibility of rat and mouse gene expression data obtained with Affymetrix, Illumina and Operon platforms. Results We present a thorough analysis of the degree of reproducibility provided by analysing the transcriptomic profile of the same animals of several experimental groups under different popular microarray technologies in different tissues. Concordant results from inter- and intra-platform comparisons were maximised by testing many popular computational methods for generating fold changes and significances and by only considering oligonucleotides giving high expression levels. The choice of Affymetrix signal extraction technique was shown to have the greatest effect on the concordance across platforms. In both species, when choosing optimal methods, the agreement between data generated on the Affymetrix and Illumina was excellent; this was verified using qRT-PCR on a selection of genes present on all platforms. Conclusion This study provides an extensive assessment of analytical methods best suited for processing data from different microarray technologies and can assist integration of technologically different gene expression datasets in biological systems.

  4. Microarray analysis of gene expression by skeletal muscle of three mouse models of Kennedy disease/spinal bulbar muscular atrophy.

    Directory of Open Access Journals (Sweden)

    Kaiguo Mo

    Full Text Available BACKGROUND: Emerging evidence implicates altered gene expression within skeletal muscle in the pathogenesis of Kennedy disease/spinal bulbar muscular atrophy (KD/SBMA. We therefore broadly characterized gene expression in skeletal muscle of three independently generated mouse models of this disease. The mouse models included a polyglutamine expanded (polyQ AR knock-in model (AR113Q, a polyQ AR transgenic model (AR97Q, and a transgenic mouse that overexpresses wild type AR solely in skeletal muscle (HSA-AR. HSA-AR mice were included because they substantially reproduce the KD/SBMA phenotype despite the absence of polyQ AR. METHODOLOGY/PRINCIPAL FINDINGS: We performed microarray analysis of lower hindlimb muscles taken from these three models relative to wild type controls using high density oligonucleotide arrays. All microarray comparisons were made with at least 3 animals in each condition, and only those genes having at least 2-fold difference and whose coefficient of variance was less than 100% were considered to be differentially expressed. When considered globally, there was a similar overlap in gene changes between the 3 models: 19% between HSA-AR and AR97Q, 21% between AR97Q and AR113Q, and 17% between HSA-AR and AR113Q, with 8% shared by all models. Several patterns of gene expression relevant to the disease process were observed. Notably, patterns of gene expression typical of loss of AR function were observed in all three models, as were alterations in genes involved in cell adhesion, energy balance, muscle atrophy and myogenesis. We additionally measured changes similar to those observed in skeletal muscle of a mouse model of Huntington's Disease, and to those common to muscle atrophy from diverse causes. CONCLUSIONS/SIGNIFICANCE: By comparing patterns of gene expression in three independent models of KD/SBMA, we have been able to identify candidate genes that might mediate the core myogenic features of KD/SBMA.

  5. Putative psychosis genes in the prefrontal cortex: combined analysis of gene expression microarrays

    Directory of Open Access Journals (Sweden)

    Yolken Robert H

    2008-11-01

    Full Text Available Abstract Background Recent studies have shown similarities between schizophrenia and bipolar disorder in phenotypes and in genotypes, and those studies have contributed to an ongoing re-evaluation of the traditional dichotomy between schizophrenia and bipolar disorder. Bipolar disorder with psychotic features may be closely related to schizophrenia and therefore, psychosis may be an alternative phenotype compared to the traditional diagnosis categories. Methods We performed a cross-study analysis of 7 gene expression microarrays that include both psychosis and non-psychosis subjects. These studies include over 400 microarray samples (163 individual subjects on 3 different Affymetrix microarray platforms. Results We found that 110 transcripts are differentially regulated (p Conclusion This study demonstrates the advantages of cross-study analysis in detecting consensus changes in gene expression across multiple microarray studies. Differential gene expression between individuals with and without psychosis suggests that psychosis may be a useful phenotypic variable to complement the traditional diagnosis categories.

  6. The Current Status of DNA Microarrays

    Science.gov (United States)

    Shi, Leming; Perkins, Roger G.; Tong, Weida

    DNA microarray technology that allows simultaneous assay of thousands of genes in a single experiment has steadily advanced to become a mainstream method used in research, and has reached a stage that envisions its use in medical applications and personalized medicine. Many different strategies have been developed for manufacturing DNA microarrays. In this chapter, we discuss the manufacturing characteristics of seven microarray platforms that were used in a recently completed large study by the MicroArray Quality Control (MAQC) consortium, which evaluated the concordance of results across these platforms. The platforms can be grouped into three categories: (1) in situ synthesis of oligonucleotide probes on microarrays (Affymetrix GeneChip® arrays based on photolithography synthesis and Agilent's arrays based on inkjet synthesis); (2) spotting of presynthesized oligonucleotide probes on microarrays (GE Healthcare's CodeLink system, Applied Biosystems' Genome Survey Microarrays, and the custom microarrays printed with Operon's oligonucleotide set); and (3) deposition of presynthesized oligonucleotide probes on bead-based microarrays (Illumina's BeadChip microarrays). We conclude this chapter with our views on the challenges and opportunities toward acceptance of DNA microarray data in clinical and regulatory settings.

  7. Filtering for increased power for microarray data analysis

    Directory of Open Access Journals (Sweden)

    Hess Ann M

    2009-01-01

    Full Text Available Abstract Background Due to the large number of hypothesis tests performed during the process of routine analysis of microarray data, a multiple testing adjustment is certainly warranted. However, when the number of tests is very large and the proportion of differentially expressed genes is relatively low, the use of a multiple testing adjustment can result in very low power to detect those genes which are truly differentially expressed. Filtering allows for a reduction in the number of tests and a corresponding increase in power. Common filtering methods include filtering by variance, average signal or MAS detection call (for Affymetrix arrays. We study the effects of filtering in combination with the Benjamini-Hochberg method for false discovery rate control and q-value for false discovery rate estimation. Results Three case studies are used to compare three different filtering methods in combination with the two false discovery rate methods and three different preprocessing methods. For the case studies considered, filtering by detection call and variance (on the original scale consistently led to an increase in the number of differentially expressed genes identified. On the other hand, filtering by variance on the log2 scale had a detrimental effect when paired with MAS5 or PLIER preprocessing methods, even when the testing was done on the log2 scale. A simulation study was done to further examine the effect of filtering by variance. We find that filtering by variance leads to higher power, often with a decrease in false discovery rate, when paired with either of the false discovery rate methods considered. This holds regardless of the proportion of genes which are differentially expressed or whether we assume dependence or independence among genes. Conclusion The case studies show that both detection call and variance filtering are viable methods of filtering which can increase the number of differentially expressed genes identified. The

  8. EMAAS: An extensible grid-based Rich Internet Application for microarray data analysis and management

    Directory of Open Access Journals (Sweden)

    Aitman T

    2008-11-01

    Full Text Available Abstract Background Microarray experimentation requires the application of complex analysis methods as well as the use of non-trivial computer technologies to manage the resultant large data sets. This, together with the proliferation of tools and techniques for microarray data analysis, makes it very challenging for a laboratory scientist to keep up-to-date with the latest developments in this field. Our aim was to develop a distributed e-support system for microarray data analysis and management. Results EMAAS (Extensible MicroArray Analysis System is a multi-user rich internet application (RIA providing simple, robust access to up-to-date resources for microarray data storage and analysis, combined with integrated tools to optimise real time user support and training. The system leverages the power of distributed computing to perform microarray analyses, and provides seamless access to resources located at various remote facilities. The EMAAS framework allows users to import microarray data from several sources to an underlying database, to pre-process, quality assess and analyse the data, to perform functional analyses, and to track data analysis steps, all through a single easy to use web portal. This interface offers distance support to users both in the form of video tutorials and via live screen feeds using the web conferencing tool EVO. A number of analysis packages, including R-Bioconductor and Affymetrix Power Tools have been integrated on the server side and are available programmatically through the Postgres-PLR library or on grid compute clusters. Integrated distributed resources include the functional annotation tool DAVID, GeneCards and the microarray data repositories GEO, CELSIUS and MiMiR. EMAAS currently supports analysis of Affymetrix 3' and Exon expression arrays, and the system is extensible to cater for other microarray and transcriptomic platforms. Conclusion EMAAS enables users to track and perform microarray data

  9. Microarray expression analysis of epithelial ovarian cancer with distinct differentiation

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    To identify gene expression profiling in epithelial ovarian cancer and to explore its correlation with histopathology characterization and prognosis. Gene expression profiles were generated from 10 human ovarian frozen tissue specimens using Agilent Human 1A microarrays. Strikingly, clear differences of gene expression patterns were observed in ovarian cancer as compared to normal tissues. Unique gene profiles were observed in moderately and poorly differentiated epithelial ovarian cancer. It is concluded that different histopathology characterization likely exists extensive molecular heterogeneity.

  10. Evaluation of a gene information summarization system by users during the analysis process of microarray datasets.

    Science.gov (United States)

    Yang, Jianji; Cohen, Aaron; Hersh, William

    2009-02-05

    Summarization of gene information in the literature has the potential to help genomics researchers translate basic research into clinical benefits. Gene expression microarrays have been used to study biomarkers for disease and discover novel types of therapeutics and the task of finding information in journal articles on sets of genes is common for translational researchers working with microarray data. However, manually searching and scanning the literature references returned from PubMed is a time-consuming task for scientists. We built and evaluated an automatic summarizer of information on genes studied in microarray experiments. The Gene Information Clustering and Summarization System (GICSS) is a system that integrates two related steps of the microarray data analysis process: functional gene clustering and gene information gathering. The system evaluation was conducted during the process of genomic researchers analyzing their own experimental microarray datasets. The clusters generated by GICSS were validated by scientists during their microarray analysis process. In addition, presenting sentences in the abstract provided significantly more important information to the users than just showing the title in the default PubMed format. The evaluation results suggest that GICSS can be useful for researchers in genomic area. In addition, the hybrid evaluation method, partway between intrinsic and extrinsic system evaluation, may enable researchers to gauge the true usefulness of the tool for the scientists in their natural analysis workflow and also elicit suggestions for future enhancements. GICSS can be accessed online at: http://ir.ohsu.edu/jianji/index.html.

  11. Genomewide expression analysis in amino acid-producing bacteria using DNA microarrays.

    Science.gov (United States)

    Polen, Tino; Wendisch, Volker F

    2004-01-01

    DNA microarray technology has become an important research tool for biotechnology and microbiology. It is now possible to characterize genetic diversity and gene expression in a genomewide manner. DNA microarrays have been applied extensively to study the biology of many bacteria including Escherichia coli, but only recently have they been developed for the Gram-positive Corynebacterium glutamicum. Both bacteria are widely used for biotechnological amino acid production. In this article, in addition to the design and generation of microarrays as well as their use in hybridization experiments and subsequent data analysis, we describe recent applications of DNA microarray technology regarding amino acid production in C. glutamicum and E. coli. We also discuss the impact of functional genomics studies on fundamental as well as applied aspects of amino acid production with C. glutamicum and E. coli.

  12. BASE--2nd generation software for microarray data management and analysis.

    Science.gov (United States)

    Vallon-Christersson, Johan; Nordborg, Nicklas; Svensson, Martin; Häkkinen, Jari

    2009-10-12

    Microarray experiments are increasing in size and samples are collected asynchronously over long time. Available data are re-analysed as more samples are hybridized. Systematic use of collected data requires tracking of biomaterials, array information, raw data, and assembly of annotations. To meet the information tracking and data analysis challenges in microarray experiments we reimplemented and improved BASE version 1.2. The new BASE presented in this report is a comprehensive annotable local microarray data repository and analysis application providing researchers with an efficient information management and analysis tool. The information management system tracks all material from biosource, via sample and through extraction and labelling to raw data and analysis. All items in BASE can be annotated and the annotations can be used as experimental factors in downstream analysis. BASE stores all microarray experiment related data regardless if analysis tools for specific techniques or data formats are readily available. The BASE team is committed to continue improving and extending BASE to make it usable for even more experimental setups and techniques, and we encourage other groups to target their specific needs leveraging on the infrastructure provided by BASE. BASE is a comprehensive management application for information, data, and analysis of microarray experiments, available as free open source software at http://base.thep.lu.se under the terms of the GPLv3 license.

  13. BASE - 2nd generation software for microarray data management and analysis

    Directory of Open Access Journals (Sweden)

    Nordborg Nicklas

    2009-10-01

    Full Text Available Abstract Background Microarray experiments are increasing in size and samples are collected asynchronously over long time. Available data are re-analysed as more samples are hybridized. Systematic use of collected data requires tracking of biomaterials, array information, raw data, and assembly of annotations. To meet the information tracking and data analysis challenges in microarray experiments we reimplemented and improved BASE version 1.2. Results The new BASE presented in this report is a comprehensive annotable local microarray data repository and analysis application providing researchers with an efficient information management and analysis tool. The information management system tracks all material from biosource, via sample and through extraction and labelling to raw data and analysis. All items in BASE can be annotated and the annotations can be used as experimental factors in downstream analysis. BASE stores all microarray experiment related data regardless if analysis tools for specific techniques or data formats are readily available. The BASE team is committed to continue improving and extending BASE to make it usable for even more experimental setups and techniques, and we encourage other groups to target their specific needs leveraging on the infrastructure provided by BASE. Conclusion BASE is a comprehensive management application for information, data, and analysis of microarray experiments, available as free open source software at http://base.thep.lu.se under the terms of the GPLv3 license.

  14. Synthesis of triazole-linked oligonucleotides with high affinity to DNA complements and an analysis of their compatibility with biosystems.

    Science.gov (United States)

    Varizhuk, Anna M; Kaluzhny, Dmitry N; Novikov, Roman A; Chizhov, Alexandr O; Smirnov, Igor P; Chuvilin, Andrey N; Tatarinova, Olga N; Fisunov, Gleb Y; Pozmogova, Galina E; Florentiev, Vladimir L

    2013-06-21

    New oligonucleotide analogues with triazole internucleotide linkages were synthesized, and their hybridization properties were studied. The analogues demonstrated DNA binding affinities similar to those of unmodified oligonucleotides. The modification was shown to protect the oligonucleotides from nuclease hydrolysis. The modified oligonucleotides were tested as PCR primers. Modifications remote from the 3'-terminus were tolerated by polymerases. Our results suggest that these new oligonucleotide analogues are among the most promising triazole DNA mimics characterized to date.

  15. A microarray analysis of two distinct lymphatic endothelial cell populations

    Directory of Open Access Journals (Sweden)

    Bernhard Schweighofer

    2015-06-01

    Full Text Available We have recently identified lymphatic endothelial cells (LECs to form two morphologically different populations, exhibiting significantly different surface protein expression levels of podoplanin, a major surface marker for this cell type. In vitro shockwave treatment (IVSWT of LECs resulted in enrichment of the podoplaninhigh cell population and was accompanied by markedly increased cell proliferation, as well as 2D and 3D migration. Gene expression profiles of these distinct populations were established using Affymetrix microarray analyses. Here we provide additional details about our dataset (NCBI GEO accession number GSE62510 and describe how we analyzed the data to identify differently expressed genes in these two LEC populations.

  16. THEME: a web tool for loop-design microarray data analysis.

    Science.gov (United States)

    Chen, Chaang-Ray; Shu, Wun-Yi; Tsai, Min-Lung; Cheng, Wei-Chung; Hsu, Ian C

    2012-02-01

    A number of recent studies have shown that loop-design is more efficient than reference control design. Data analysis for loop-design microarray experiments is commonly undertaken using linear models and statistical tests. These techniques require specialized knowledge in statistical programming. However, limited loop-design web-based tools are available. We have developed the THEME (Tsing Hua Engine of Microarray Experiment) that exploits all necessary data analysis tools for loop-design microarray studies. THEME allows users to construct linear models and to apply multiple user-defined statistical tests of hypotheses for detection of DEG (differentially expressed genes). Users can modify entries of design matrix for experimental design as well as that of contrast matrix for statistical tests of hypotheses. The output of multiple user-defined statistical tests of hypotheses, DEG lists, can be cross-validated. The web platform provides data assessment and visualization tools that significantly assist users when evaluating the performance of microarray experimental procedures. THEME is also a MIAME (Minimal Information About a Microarray Experiment) compliant system, which enables users to export formatted files for GEO (Gene Expression Omnibus) submission. THEME offers comprehensive web services to biologists for data analysis of loop-design microarray experiments. This web-based resource is especially useful for core facility service as well as collaboration projects when researchers are not at the same site. Data analysis procedures, starting from uploading raw data files to retrieving DEG lists, can be flexibly operated with natural workflows. These features make THEME a reliable and powerful on-line system for data analysis of loop-design microarrays. The THEME server is available at http://metadb.bmes.nthu.edu.tw/theme/.

  17. Variance estimation in the analysis of microarray data

    KAUST Repository

    Wang, Yuedong

    2009-04-01

    Microarrays are one of the most widely used high throughput technologies. One of the main problems in the area is that conventional estimates of the variances that are required in the t-statistic and other statistics are unreliable owing to the small number of replications. Various methods have been proposed in the literature to overcome this lack of degrees of freedom problem. In this context, it is commonly observed that the variance increases proportionally with the intensity level, which has led many researchers to assume that the variance is a function of the mean. Here we concentrate on estimation of the variance as a function of an unknown mean in two models: the constant coefficient of variation model and the quadratic variance-mean model. Because the means are unknown and estimated with few degrees of freedom, naive methods that use the sample mean in place of the true mean are generally biased because of the errors-in-variables phenomenon. We propose three methods for overcoming this bias. The first two are variations on the theme of the so-called heteroscedastic simulation-extrapolation estimator, modified to estimate the variance function consistently. The third class of estimators is entirely different, being based on semiparametric information calculations. Simulations show the power of our methods and their lack of bias compared with the naive method that ignores the measurement error. The methodology is illustrated by using microarray data from leukaemia patients.

  18. ArrayQuest: a web resource for the analysis of DNA microarray data

    Directory of Open Access Journals (Sweden)

    Barth Jeremy L

    2005-12-01

    Full Text Available Abstract Background Numerous microarray analysis programs have been created through the efforts of Open Source software development projects. Providing browser-based interfaces that allow these programs to be executed over the Internet enhances the applicability and utility of these analytic software tools. Results Here we present ArrayQuest, a web-based DNA microarray analysis process controller. Key features of ArrayQuest are that (1 it is capable of executing numerous analysis programs such as those written in R, BioPerl and C++; (2 new analysis programs can be added to ArrayQuest Methods Library at the request of users or developers; (3 input DNA microarray data can be selected from public databases (i.e., the Medical University of South Carolina (MUSC DNA Microarray Database or Gene Expression Omnibus (GEO or it can be uploaded to the ArrayQuest center-point web server into a password-protected area; and (4 analysis jobs are distributed across computers configured in a backend cluster. To demonstrate the utility of ArrayQuest we have populated the methods library with methods for analysis of Affymetrix DNA microarray data. Conclusion ArrayQuest enables browser-based implementation of DNA microarray data analysis programs that can be executed on a Linux-based platform. Importantly, ArrayQuest is a platform that will facilitate the distribution and implementation of new analysis algorithms and is therefore of use to both developers of analysis applications as well as users. ArrayQuest is freely available for use at http://proteogenomics.musc.edu/arrayquest.html.

  19. Typing of enteroviruses by use of microwell oligonucleotide arrays.

    Science.gov (United States)

    Susi, P; Hattara, L; Waris, M; Luoma-Aho, T; Siitari, H; Hyypiä, T; Saviranta, P

    2009-06-01

    We have developed a straightforward assay for the rapid typing of enteroviruses using oligonucleotide arrays in microtiter wells. The viral nucleic acids are concomitantly amplified and labeled during reverse transcription-PCR, and unpurified PCR products are used for hybridization. DNA strands are separated by alkaline denaturation, and hybridization is started by neutralization. The microarray hybridization reactions and the subsequent washes are performed in standard 96-well microtiter plates, which makes the method easily adaptable to high-throughput analysis. We describe here the assay principle and its potential in clinical laboratory use by correctly identifying 10 different enterovirus reference strains. Furthermore, we explore the detection of unknown sequence variants using serotype consensus oligonucleotide probes. With just two consensus probes for the coxsackievirus A9 (CVA9) serotype, we detected 23 out of 25 highly diverse CVA9 isolates. Overall, the assay involves several features aiming at ease of performance, robustness, and applicability to large-scale studies.

  20. Treatment of allergic rhinitis with acupoint herbal plaster: an oligonucleotide chip analysis.

    Science.gov (United States)

    Shiue, Horng-Sheng; Lee, Yun-Shien; Tsai, Chi-Neu; Chang, Hen-Hong

    2016-11-04

    Allergic rhinitis is regarded as an imbalanced Th1/Th2 cell-mediated response. The present study used microarray analysis to compare gene expression levels between allergic rhinitis patients before and after a series of acupoint herbal plaster applications. In this experimental pilot study, volunteers experiencing sneezing, runny nose, and congestion for more than 9 months in the year following initial diagnoses were included after diagnostic confirmation by otolaryngologists to exclude patients with sinusitis and nasal polyps. Patients with persistent allergic rhinitis each received four acupoint herbal plaster treatments applied using the moxibustion technique. Clinical outcomes were evaluated using the Rhinitis Quality of Life Questionnaire (RQLQ). Peripheral blood samples were analyzed using an ImmunoCAP Phadiatop test, and patients were classified as phadiatop (Ph)-positive or -negative. Microarray results were analyzed for genes that were differentially expressed between (1) Ph-positive and -negative patients treated with herbal plaster; and (2) before and after herbal plaster treatment in the Ph-positive patient group. Unsupervised and supervised methods were used for gene-expression data analysis. Nineteen Ph-positive and four Ph-negative participants with persistent allergic rhinitis were included in the study. RQLQ results indicated that the 19 Ph-positive volunteers experienced improvement in six of seven categories following acupoint herbal plaster treatments, whereas the four Ph-negative participants reported improvement in only two categories. Hierarchical clustering and principle component analysis of the gene expression profiles of Ph-positive and -negative participants indicated the groups exhibited distinct physiological responses to acupoint herbal treatment. Evaluation of gene networks using MetaCore identified that the "Immune response_IL-13 signaling via JAK-STAT" and the "Inflammation_Interferon signaling" were down- and up

  1. Design and analysis of effects of triplet repeat oligonucleotides in cell models for myotonic dystrophy

    NARCIS (Netherlands)

    Gonzalez-Barriga, A.; Mulders, S.A.M.; Giessen, J. van der; Hooijer, J.D.; Bijl, S.; Kessel, I.D.G. van; Beers, J. van; Deutekom, J.C. van; Fransen, J.A.M.; Wieringa, B.; Wansink, D.G.

    2013-01-01

    Myotonic dystrophy type 1 (DM1) is caused by DM protein kinase (DMPK) transcripts containing an expanded (CUG)n repeat. Antisense oligonucleotide (AON)-mediated suppression of these mutant RNAs is considered a promising therapeutic strategy for this severe disorder. Earlier, we identified a 2'-O-met

  2. Design and analysis of effects of triplet repeat oligonucleotides in cell models for myotonic dystrophy

    NARCIS (Netherlands)

    Gonzalez-Barriga, A.; Mulders, S.A.M.; Giessen, J. van der; Hooijer, J.D.; Bijl, S.; Kessel, I.D.G. van; Beers, J. van; Deutekom, J.C. van; Fransen, J.A.M.; Wieringa, B.; Wansink, D.G.

    2013-01-01

    Myotonic dystrophy type 1 (DM1) is caused by DM protein kinase (DMPK) transcripts containing an expanded (CUG)n repeat. Antisense oligonucleotide (AON)-mediated suppression of these mutant RNAs is considered a promising therapeutic strategy for this severe disorder. Earlier, we identified a 2'-O-met

  3. Enhancing interdisciplinary mathematics and biology education: a microarray data analysis course bridging these disciplines.

    Science.gov (United States)

    Tra, Yolande V; Evans, Irene M

    2010-01-01

    BIO2010 put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on microarray data analysis. We started using Genome Consortium for Active Teaching (GCAT) materials and Microarray Genome and Clustering Tool software and added R statistical software along with Bioconductor packages. In response to student feedback, one microarray data set was fully analyzed in class, starting from preprocessing to gene discovery to pathway analysis using the latter software. A class project was to conduct a similar analysis where students analyzed their own data or data from a published journal paper. This exercise showed the impact that filtering, preprocessing, and different normalization methods had on gene inclusion in the final data set. We conclude that this course achieved its goals to equip students with skills to analyze data from a microarray experiment. We offer our insight about collaborative teaching as well as how other faculty might design and implement a similar interdisciplinary course.

  4. Enhancing Interdisciplinary Mathematics and Biology Education: A Microarray Data Analysis Course Bridging These Disciplines

    Science.gov (United States)

    Evans, Irene M.

    2010-01-01

    BIO2010 put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on microarray data analysis. We started using Genome Consortium for Active Teaching (GCAT) materials and Microarray Genome and Clustering Tool software and added R statistical software along with Bioconductor packages. In response to student feedback, one microarray data set was fully analyzed in class, starting from preprocessing to gene discovery to pathway analysis using the latter software. A class project was to conduct a similar analysis where students analyzed their own data or data from a published journal paper. This exercise showed the impact that filtering, preprocessing, and different normalization methods had on gene inclusion in the final data set. We conclude that this course achieved its goals to equip students with skills to analyze data from a microarray experiment. We offer our insight about collaborative teaching as well as how other faculty might design and implement a similar interdisciplinary course. PMID:20810954

  5. Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient.

    Science.gov (United States)

    Yao, Jianchao; Chang, Chunqi; Salmi, Mari L; Hung, Yeung Sam; Loraine, Ann; Roux, Stanley J

    2008-06-18

    Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient) using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. This study shows that SCC is an alternative to the Pearson

  6. Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient

    Directory of Open Access Journals (Sweden)

    Loraine Ann

    2008-06-01

    Full Text Available Abstract Background Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. Results In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC, that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. Conclusion

  7. The use of microarrays in microbial ecology

    Energy Technology Data Exchange (ETDEWEB)

    Andersen, G.L.; He, Z.; DeSantis, T.Z.; Brodie, E.L.; Zhou, J.

    2009-09-15

    Microarrays have proven to be a useful and high-throughput method to provide targeted DNA sequence information for up to many thousands of specific genetic regions in a single test. A microarray consists of multiple DNA oligonucleotide probes that, under high stringency conditions, hybridize only to specific complementary nucleic acid sequences (targets). A fluorescent signal indicates the presence and, in many cases, the abundance of genetic regions of interest. In this chapter we will look at how microarrays are used in microbial ecology, especially with the recent increase in microbial community DNA sequence data. Of particular interest to microbial ecologists, phylogenetic microarrays are used for the analysis of phylotypes in a community and functional gene arrays are used for the analysis of functional genes, and, by inference, phylotypes in environmental samples. A phylogenetic microarray that has been developed by the Andersen laboratory, the PhyloChip, will be discussed as an example of a microarray that targets the known diversity within the 16S rRNA gene to determine microbial community composition. Using multiple, confirmatory probes to increase the confidence of detection and a mismatch probe for every perfect match probe to minimize the effect of cross-hybridization by non-target regions, the PhyloChip is able to simultaneously identify any of thousands of taxa present in an environmental sample. The PhyloChip is shown to reveal greater diversity within a community than rRNA gene sequencing due to the placement of the entire gene product on the microarray compared with the analysis of up to thousands of individual molecules by traditional sequencing methods. A functional gene array that has been developed by the Zhou laboratory, the GeoChip, will be discussed as an example of a microarray that dynamically identifies functional activities of multiple members within a community. The recent version of GeoChip contains more than 24,000 50mer

  8. Mayday SeaSight: combined analysis of deep sequencing and microarray data.

    Directory of Open Access Journals (Sweden)

    Florian Battke

    Full Text Available Recently emerged deep sequencing technologies offer new high-throughput methods to quantify gene expression, epigenetic modifications and DNA-protein binding. From a computational point of view, the data is very different from that produced by the already established microarray technology, providing a new perspective on the samples under study and complementing microarray gene expression data. Software offering the integrated analysis of data from different technologies is of growing importance as new data emerge in systems biology studies. Mayday is an extensible platform for visual data exploration and interactive analysis and provides many methods for dissecting complex transcriptome datasets. We present Mayday SeaSight, an extension that allows to integrate data from different platforms such as deep sequencing and microarrays. It offers methods for computing expression values from mapped reads and raw microarray data, background correction and normalization and linking microarray probes to genomic coordinates. It is now possible to use Mayday's wealth of methods to analyze sequencing data and to combine data from different technologies in one analysis.

  9. Microarray analysis of potential genes in the pathogenesis of recurrent oral ulcer.

    Science.gov (United States)

    Han, Jingying; He, Zhiwei; Li, Kun; Hou, Lu

    2015-01-01

    Recurrent oral ulcer seriously threatens patients' daily life and health. This study investigated potential genes and pathways that participate in the pathogenesis of recurrent oral ulcer by high throughput bioinformatic analysis. RT-PCR and Western blot were applied to further verify screened interleukins effect. Recurrent oral ulcer related genes were collected from websites and papers, and further found out from Human Genome 280 6.0 microarray data. Each pathway of recurrent oral ulcer related genes were got through chip hybridization. RT-PCR was applied to test four recurrent oral ulcer related genes to verify the microarray data. Data transformation, scatter plot, clustering analysis, and expression pattern analysis were used to analyze recurrent oral ulcer related gene expression changes. Recurrent oral ulcer gene microarray was successfully established. Microarray showed that 551 genes involved in recurrent oral ulcer activity and 196 genes were recurrent oral ulcer related genes. Of them, 76 genes up-regulated, 62 genes down-regulated, and 58 genes up-/down-regulated. Total expression level up-regulated 752 times (60%) and down-regulated 485 times (40%). IL-2 plays an important role in the occurrence, development and recurrence of recurrent oral ulcer on the mRNA and protein levels. Gene microarray can be used to analyze potential genes and pathways in recurrent oral ulcer. IL-2 may be involved in the pathogenesis of recurrent oral ulcer.

  10. Evaluation criteria of rat hepatocytes transcriptome analysis under the influence of interferon alpha by DNA microarray

    Directory of Open Access Journals (Sweden)

    Kuklin A. V.

    2013-10-01

    Full Text Available The changes induced in transcriptome of rat hepatocytes treated with interferon alpha (IFN during three and six hours were analyzed by DNA microarray. Aim. To conduct a stepwise analysis of the results of microarray experiment and to determine whether they meet/fail to the conventional requirements. Methods. The files obtained after scanning microarrays were subjected to the analysis in statistical environment R by Bioconductor’s packages «affy», «simpleaffy», «affyPLM» and BRB Array Tools software for paired T-test. Results. All microarrays had quality metrics lying within recommended ranges, passed quality control, were normalized and are comparable with each other. The T-test revealed 28 and 124 differentially expressed genes after three and six hours of cells cultivation with IFNα , respectively. Conclusions. The obtained data meet the conventional criteria of quality and are applicable for further evaluation of their biological significance. The R-codes used in this study can be used for the analysis of the microarrays data.

  11. Automating dChip: toward reproducible sharing of microarray data analysis

    Directory of Open Access Journals (Sweden)

    Li Cheng

    2008-05-01

    Full Text Available Abstract Background During the past decade, many software packages have been developed for analysis and visualization of various types of microarrays. We have developed and maintained the widely used dChip as a microarray analysis software package accessible to both biologist and data analysts. However, challenges arise when dChip users want to analyze large number of arrays automatically and share data analysis procedures and parameters. Improvement is also needed when the dChip user support team tries to identify the causes of reported analysis errors or bugs from users. Results We report here implementation and application of the dChip automation module. Through this module, dChip automation files can be created to include menu steps, parameters, and data viewpoints to run automatically. A data-packaging function allows convenient transfer from one user to another of the dChip software, microarray data, and analysis procedures, so that the second user can reproduce the entire analysis session of the first user. An analysis report file can also be generated during an automated run, including analysis logs, user comments, and viewpoint screenshots. Conclusion The dChip automation module is a step toward reproducible research, and it can prompt a more convenient and reproducible mechanism for sharing microarray software, data, and analysis procedures and results. Automation data packages can also be used as publication supplements. Similar automation mechanisms could be valuable to the research community if implemented in other genomics and bioinformatics software packages.

  12. Final Report Construction of Whole Genome Microarrays, and Expression Analysis of Desulfovibrio vulgaris cells in Metal-Reducing Conditions

    Energy Technology Data Exchange (ETDEWEB)

    M.W. Fields; J.D. Wall; J. Keasling; J. Zhou

    2008-05-15

    We continue to utilize the oligonucleotide microarrays that were constructed through funding with this project to characterize growth responses of Desulfovibrio vulgaris relevant to metal-reducing conditions. To effectively immobilize heavy metals and radionuclides via sulfate-reduction, it is important to understand the cellular responses to adverse factors observed at contaminated subsurface environments (e.g., nutrients, pH, contaminants, growth requirements and products). One of the major goals of the project is to construct whole-genome microarrays for Desulfovibrio vulgaris. First, in order to experimentally establish the criteria for designing gene-specific oligonucleotide probes, an oligonucleotide array was constructed that contained perfect match (PM) and mismatch (MM) probes (50mers and 70mers) based upon 4 genes. The effects of probe-target identity, continuous stretch, mismatch position, and hybridization free energy on specificity were examined. Little hybridization was observed at a probe-target identity of <85% for both 50mer and 70mer probes. 33 to 48% of the PM signal intensities were detected at a probe-target identity of 94% for 50mer oligonucleotides, and 43 to 55% for 70mer probes at a probe-target identity of 96%. When the effects of sequence identity and continuous stretch were considered independently, a stretch probe (>15 bases) contributed an additional 9% of the PM signal intensity compared to a non-stretch probe (< 15 bases) at the same identity level. Cross-hybridization increased as the length of continuous stretch increased. A 35-base stretch for 50mer probes or a 50-base stretch for 70mer probes had approximately 55% of the PM signal. Mismatches should be as close to the middle position of an oligonucleotide probe as possible to minimize cross-hybridization. Little cross-hybridization was observed for probes with a minimal binding free energy greater than -30 kcal/mol for 50mer probes or -40 kcal/mol for 70mer probes. Based on the

  13. Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data.

    Science.gov (United States)

    Tan, Qihua; Thomassen, Mads; Burton, Mark; Mose, Kristian Fredløv; Andersen, Klaus Ejner; Hjelmborg, Jacob; Kruse, Torben

    2017-06-06

    Modeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health.

  14. Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data

    DEFF Research Database (Denmark)

    Tan, Qihua; Thomassen, Mads; Burton, Mark

    2017-01-01

    Modeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering...... the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray...... time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health....

  15. Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data

    DEFF Research Database (Denmark)

    Tan, Qihua; Thomassen, Mads; Burton, Mark

    2017-01-01

    Modeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering...... the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray...

  16. A process for analysis of microarray comparative genomics hybridisation studies for bacterial genomes

    Directory of Open Access Journals (Sweden)

    Woodward Martin J

    2008-01-01

    Full Text Available Abstract Background Microarray based comparative genomic hybridisation (CGH experiments have been used to study numerous biological problems including understanding genome plasticity in pathogenic bacteria. Typically such experiments produce large data sets that are difficult for biologists to handle. Although there are some programmes available for interpretation of bacterial transcriptomics data and CGH microarray data for looking at genetic stability in oncogenes, there are none specifically to understand the mosaic nature of bacterial genomes. Consequently a bottle neck still persists in accurate processing and mathematical analysis of these data. To address this shortfall we have produced a simple and robust CGH microarray data analysis process that may be automated in the future to understand bacterial genomic diversity. Results The process involves five steps: cleaning, normalisation, estimating gene presence and absence or divergence, validation, and analysis of data from test against three reference strains simultaneously. Each stage of the process is described and we have compared a number of methods available for characterising bacterial genomic diversity, for calculating the cut-off between gene presence and absence or divergence, and shown that a simple dynamic approach using a kernel density estimator performed better than both established, as well as a more sophisticated mixture modelling technique. We have also shown that current methods commonly used for CGH microarray analysis in tumour and cancer cell lines are not appropriate for analysing our data. Conclusion After carrying out the analysis and validation for three sequenced Escherichia coli strains, CGH microarray data from 19 E. coli O157 pathogenic test strains were used to demonstrate the benefits of applying this simple and robust process to CGH microarray studies using bacterial genomes.

  17. Significance of genomic instability in breast cancer in atomic bomb survivors: analysis of microarray-comparative genomic hybridization.

    Science.gov (United States)

    Oikawa, Masahiro; Yoshiura, Koh-ichiro; Kondo, Hisayoshi; Miura, Shiro; Nagayasu, Takeshi; Nakashima, Masahiro

    2011-12-07

    It has been postulated that ionizing radiation induces breast cancers among atomic bomb (A-bomb) survivors. We have reported a higher incidence of HER2 and C-MYC oncogene amplification in breast cancers from A-bomb survivors. The purpose of this study was to clarify the effect of A-bomb radiation exposure on genomic instability (GIN), which is an important hallmark of carcinogenesis, in archival formalin-fixed paraffin-embedded (FFPE) tissues of breast cancer by using microarray-comparative genomic hybridization (aCGH). Tumor DNA was extracted from FFPE tissues of invasive ductal cancers from 15 survivors who were exposed at 1.5 km or less from the hypocenter and 13 calendar year-matched non-exposed patients followed by aCGH analysis using a high-density oligonucleotide microarray. The total length of copy number aberrations (CNA) was used as an indicator of GIN, and correlation with clinicopathological factors were statistically tested. The mean of the derivative log ratio spread (DLRSpread), which estimates the noise by calculating the spread of log ratio differences between consecutive probes for all chromosomes, was 0.54 (range, 0.26 to 1.05). The concordance of results between aCGH and fluorescence in situ hybridization (FISH) for HER2 gene amplification was 88%. The incidence of HER2 amplification and histological grade was significantly higher in the A-bomb survivors than control group (P = 0.04, respectively). The total length of CNA tended to be larger in the A-bomb survivors (P = 0.15). Correlation analysis of CNA and clinicopathological factors revealed that DLRSpread was negatively correlated with that significantly (P = 0.034, r = -0.40). Multivariate analysis with covariance revealed that the exposure to A-bomb was a significant (P = 0.005) independent factor which was associated with larger total length of CNA of breast cancers. Thus, archival FFPE tissues from A-bomb survivors are useful for genome-wide aCGH analysis. Our results suggested that A

  18. Significance of genomic instability in breast cancer in atomic bomb survivors: analysis of microarray-comparative genomic hybridization

    Directory of Open Access Journals (Sweden)

    Oikawa Masahiro

    2011-12-01

    Full Text Available Abstract Background It has been postulated that ionizing radiation induces breast cancers among atomic bomb (A-bomb survivors. We have reported a higher incidence of HER2 and C-MYC oncogene amplification in breast cancers from A-bomb survivors. The purpose of this study was to clarify the effect of A-bomb radiation exposure on genomic instability (GIN, which is an important hallmark of carcinogenesis, in archival formalin-fixed paraffin-embedded (FFPE tissues of breast cancer by using microarray-comparative genomic hybridization (aCGH. Methods Tumor DNA was extracted from FFPE tissues of invasive ductal cancers from 15 survivors who were exposed at 1.5 km or less from the hypocenter and 13 calendar year-matched non-exposed patients followed by aCGH analysis using a high-density oligonucleotide microarray. The total length of copy number aberrations (CNA was used as an indicator of GIN, and correlation with clinicopathological factors were statistically tested. Results The mean of the derivative log ratio spread (DLRSpread, which estimates the noise by calculating the spread of log ratio differences between consecutive probes for all chromosomes, was 0.54 (range, 0.26 to 1.05. The concordance of results between aCGH and fluorescence in situ hybridization (FISH for HER2 gene amplification was 88%. The incidence of HER2 amplification and histological grade was significantly higher in the A-bomb survivors than control group (P = 0.04, respectively. The total length of CNA tended to be larger in the A-bomb survivors (P = 0.15. Correlation analysis of CNA and clinicopathological factors revealed that DLRSpread was negatively correlated with that significantly (P = 0.034, r = -0.40. Multivariate analysis with covariance revealed that the exposure to A-bomb was a significant (P = 0.005 independent factor which was associated with larger total length of CNA of breast cancers. Conclusions Thus, archival FFPE tissues from A-bomb survivors are useful for

  19. Immunohistochemistry - Microarray Analysis of Patients with Peritoneal Metastases of Appendiceal or Colorectal Origin

    Directory of Open Access Journals (Sweden)

    Danielle E Green

    2015-01-01

    Full Text Available BackgroundThe value of immunohistochemistry (IHC-microarray analysis of pathological specimens in the management of patients is controversial although preliminary data suggests potential benefit. We describe the characteristics of patients undergoing a commercially available IHC-microarray method in patients with peritoneal metastases (PM and the feasibility of this technique in this population.MethodsWe retrospectively analyzed consecutive patients with pathologically confirmed PM from appendiceal or colorectal primary who underwent Caris Molecular IntelligenceTM testing. IHC, microarray, FISH and mutational analysis were included and stratified by PCI score, histology and treatment characteristics. Statistical analysis was performed using non-parametric tests.ResultsOur study included 5 patients with appendiceal and 11 with colorectal PM. The median age of patients was 51 (IQR 39-65 years, with 11(68% female. The median PCI score of the patients was 17(IQR 10-25. Hyperthermic intra-peritoneal chemoperfusion (HIPEC was performed in 4 (80% patients with appendiceal primary tumors and 4 (36% with colorectal primary. KRAS mutations were encountered in 40% of appendiceal vs. 30% colorectal tumors, while BRAF mutations were seen in 40% of colorectal PM and none of the patients with appendiceal PM (p=0.06. IHC biomarker expression was not significantly different between the two primaries. Sufficient tumor for microarray analysis was found in 44% (n=7 patients, which was not associated with previous use of chemotherapy (p>0.20 for 5-FU/LV, Irinotecan and Oxaliplatin.ConclusionsIn a small sample of patients with peritoneal metastases, the feasibility and results of IHC-microarray staining based on a commercially available test is reported. The apparent high incidence of the BRAF mutation in patients with PM may potentially offer opportunities for novel therapeutics and suggest that IHC-microarray is a method that can be used in this population.

  20. Meta-analysis of breast cancer microarray studies in conjunction with conserved cis-elements suggest patterns for coordinate regulation

    Directory of Open Access Journals (Sweden)

    Lundberg Cathryn

    2008-01-01

    Full Text Available Abstract Background Gene expression measurements from breast cancer (BrCa tumors are established clinical predictive tools to identify tumor subtypes, identify patients showing poor/good prognosis, and identify patients likely to have disease recurrence. However, diverse breast cancer datasets in conjunction with diagnostic clinical arrays show little overlap in the sets of genes identified. One approach to identify a set of consistently dysregulated candidate genes in these tumors is to employ meta-analysis of multiple independent microarray datasets. This allows one to compare expression data from a diverse collection of breast tumor array datasets generated on either cDNA or oligonucleotide arrays. Results We gathered expression data from 9 published microarray studies examining estrogen receptor positive (ER+ and estrogen receptor negative (ER- BrCa tumor cases from the Oncomine database. We performed a meta-analysis and identified genes that were universally up or down regulated with respect to ER+ versus ER- tumor status. We surveyed both the proximal promoter and 3' untranslated regions (3'UTR of our top-ranking genes in each expression group to test whether common sequence elements may contribute to the observed expression patterns. Utilizing a combination of known transcription factor binding sites (TFBS, evolutionarily conserved mammalian promoter and 3'UTR motifs, and microRNA (miRNA seed sequences, we identified numerous motifs that were disproportionately represented between the two gene classes suggesting a common regulatory network for the observed gene expression patterns. Conclusion Some of the genes we identified distinguish key transcripts previously seen in array studies, while others are newly defined. Many of the genes identified as overexpressed in ER- tumors were previously identified as expression markers for neoplastic transformation in multiple human cancers. Moreover, our motif analysis identified a collection of

  1. Microarray analysis of microbiota of gingival lesions in noma patients.

    Directory of Open Access Journals (Sweden)

    Antoine Huyghe

    Full Text Available Noma (cancrum oris is a gangrenous disease of unknown etiology affecting the maxillo-facial region of young children in extremely limited resource countries. In an attempt to better understand the microbiological events occurring during this disease, we used phylogenetic and low-density microarrays targeting the 16S rRNA gene to characterize the gingival flora of acute noma and acute necrotizing gingivitis (ANG lesions, and compared them to healthy control subjects of the same geographical and social background. Our observations raise doubts about Fusobacterium necrophorum, a previously suspected causative agent of noma, as this species was not associated with noma lesions. Various oral pathogens were more abundant in noma lesions, notably Atopobium spp., Prevotella intermedia, Peptostreptococcus spp., Streptococcus pyogenes and Streptococcus anginosus. On the other hand, pathogens associated with periodontal diseases such as Aggregatibacter actinomycetemcomitans, Capnocytophaga spp., Porphyromonas spp. and Fusobacteriales were more abundant in healthy controls. Importantly, the overall loss of bacterial diversity observed in noma samples as well as its homology to that of ANG microbiota supports the hypothesis that ANG might be the immediate step preceding noma.

  2. DNA microarray analysis of genes differentially expressed in adipocyte differentiation

    Indian Academy of Sciences (India)

    Chunyan Yin; Yanfeng Xiao; Wei Zhang; Erdi Xu; Weihua Liu; Xiaoqing Yi; Ming Chang

    2014-06-01

    In the present study, the human liposarcoma cell line SW872 was used to identify global changes in gene expression profiles occurring during adipogenesis. We further explored some of the genes expressed during the late phase of adipocyte differentiation. These genes may play a major role in promoting excessive proliferation and accumulation of lipid droplets, which contribute to the development of obesity. By using microarray-based technology, we examined differential gene expression in early differentiated adipocytes and late differentiated adipocytes. Validated genes exhibited a ≥ 10-fold increase in the late phase of adipocyte differentiation by polymerase chain reaction (RT-PCR). Compared with undifferentiated preadipocytes, we found that 763 genes were increased in early differentiated adipocytes, and 667 genes were increased in later differentiated adipocytes. Furthermore, 21 genes were found being expressed 10-fold higher in the late phase of adipocyte differentiation. The results were in accordance with the RT-PCR test, which validated 11 genes, namely, CIDEC, PID1, LYRM1, ADD1, PPAR2, ANGPTL4, ADIPOQ, ACOX1, FIP1L1, MAP3K2 and PEX14. Most of these genes were found being expressed in the later phase of adipocyte differentiation involved in obesity-related diseases. The findings may help to better understand the mechanism of obesity and related diseases.

  3. Microarray Analysis of the Microflora of Root Caries in Elderly

    Science.gov (United States)

    Preza, Dorita; Olsen, Ingar; Willumsen, Tiril; Boches, Susan K.; Cotton, Sean L.; Grinde, Bjørn; Paster, Bruce J.

    2009-01-01

    Purpose The present study used a new 16S rRNA-based microarray with probes for over 300 bacterial species better define the bacterial profiles of healthy root surfaces and root caries (RC) in the elderly. Materials Supragingival plaque was collected from 20 healthy subjects (Controls) and from healthy and carious roots and carious dentin from 21 RC subjects (Patients). Results Collectively, 179 bacterial species and species groups were detected. A higher bacterial diversity was observed in the Controls as compared to Patients. Lactobacillus casei/paracasei/rhamnosus and Pseudoramibacter alactolyticus were notably associated with most root caries samples. Streptococcus mutans was detected more frequently in the infected dentin than in the other samples, but the difference was not significant. Actinomyces were found more frequently in Controls. Conclusion Actinomyces and S. mutans may play a limited role as pathogens of RC. The results from this study were in agreement with those of our previous study based on 16S rRNA gene sequencing with 72% of the species being detected with both methods. PMID:19039610

  4. DNA microarray analysis of genes differentially expressed in adipocyte differentiation.

    Science.gov (United States)

    Yin, Chunyan; Xiao, Yanfeng; Zhang, Wei; Xu, Erdi; Liu, Weihua; Yi, Xiaoqing; Chang, Ming

    2014-06-01

    In the present study, the human liposarcoma cell line SW872 was used to identify global changes in gene expression profiles occurring during adipogenesis. We further explored some of the genes expressed during the late phase of adipocyte differentiation. These genes may play a major role in promoting excessive proliferation and accumulation of lipid droplets, which contribute to the development of obesity. By using microarray-based technology, we examined differential gene expression in early differentiated adipocytes and late differentiated adipocytes. Validated genes exhibited a greater than or equal to 10-fold increase in the late phase of adipocyte differentiation by polymerase chain reaction (RT-PCR). Compared with undifferentiated preadipocytes, we found that 763 genes were increased in early differentiated adipocytes, and 667 genes were increased in later differentiated adipocytes. Furthermore, 21 genes were found being expressed 10-fold higher in the late phase of adipocyte differentiation. The results were in accordance with the RTPCR test, which validated 11 genes, namely, CIDEC, PID1, LYRM1, ADD1, PPAR?2, ANGPTL4, ADIPOQ, ACOX1, FIP1L1, MAP3K2 and PEX14. Most of these genes were found being expressed in the later phase of adipocyte differentiation involved in obesity-related diseases. The findings may help to better understand the mechanism of obesity and related diseases.

  5. Microarray analysis of microbiota of gingival lesions in noma patients.

    Science.gov (United States)

    Huyghe, Antoine; François, Patrice; Mombelli, Andrea; Tangomo, Manuela; Girard, Myriam; Baratti-Mayer, Denise; Bolivar, Ignacio; Pittet, Didier; Schrenzel, Jacques

    2013-01-01

    Noma (cancrum oris) is a gangrenous disease of unknown etiology affecting the maxillo-facial region of young children in extremely limited resource countries. In an attempt to better understand the microbiological events occurring during this disease, we used phylogenetic and low-density microarrays targeting the 16S rRNA gene to characterize the gingival flora of acute noma and acute necrotizing gingivitis (ANG) lesions, and compared them to healthy control subjects of the same geographical and social background. Our observations raise doubts about Fusobacterium necrophorum, a previously suspected causative agent of noma, as this species was not associated with noma lesions. Various oral pathogens were more abundant in noma lesions, notably Atopobium spp., Prevotella intermedia, Peptostreptococcus spp., Streptococcus pyogenes and Streptococcus anginosus. On the other hand, pathogens associated with periodontal diseases such as Aggregatibacter actinomycetemcomitans, Capnocytophaga spp., Porphyromonas spp. and Fusobacteriales were more abundant in healthy controls. Importantly, the overall loss of bacterial diversity observed in noma samples as well as its homology to that of ANG microbiota supports the hypothesis that ANG might be the immediate step preceding noma.

  6. Evaluation of a gene information summarization system by users during the analysis process of microarray datasets

    Directory of Open Access Journals (Sweden)

    Cohen Aaron

    2009-02-01

    Full Text Available Abstract Background Summarization of gene information in the literature has the potential to help genomics researchers translate basic research into clinical benefits. Gene expression microarrays have been used to study biomarkers for disease and discover novel types of therapeutics and the task of finding information in journal articles on sets of genes is common for translational researchers working with microarray data. However, manually searching and scanning the literature references returned from PubMed is a time-consuming task for scientists. We built and evaluated an automatic summarizer of information on genes studied in microarray experiments. The Gene Information Clustering and Summarization System (GICSS is a system that integrates two related steps of the microarray data analysis process: functional gene clustering and gene information gathering. The system evaluation was conducted during the process of genomic researchers analyzing their own experimental microarray datasets. Results The clusters generated by GICSS were validated by scientists during their microarray analysis process. In addition, presenting sentences in the abstract provided significantly more important information to the users than just showing the title in the default PubMed format. Conclusion The evaluation results suggest that GICSS can be useful for researchers in genomic area. In addition, the hybrid evaluation method, partway between intrinsic and extrinsic system evaluation, may enable researchers to gauge the true usefulness of the tool for the scientists in their natural analysis workflow and also elicit suggestions for future enhancements. Availability GICSS can be accessed online at: http://ir.ohsu.edu/jianji/index.html

  7. A probabilistic framework for microarray data analysis: fundamental probability models and statistical inference.

    Science.gov (United States)

    Ogunnaike, Babatunde A; Gelmi, Claudio A; Edwards, Jeremy S

    2010-05-21

    Gene expression studies generate large quantities of data with the defining characteristic that the number of genes (whose expression profiles are to be determined) exceed the number of available replicates by several orders of magnitude. Standard spot-by-spot analysis still seeks to extract useful information for each gene on the basis of the number of available replicates, and thus plays to the weakness of microarrays. On the other hand, because of the data volume, treating the entire data set as an ensemble, and developing theoretical distributions for these ensembles provides a framework that plays instead to the strength of microarrays. We present theoretical results that under reasonable assumptions, the distribution of microarray intensities follows the Gamma model, with the biological interpretations of the model parameters emerging naturally. We subsequently establish that for each microarray data set, the fractional intensities can be represented as a mixture of Beta densities, and develop a procedure for using these results to draw statistical inference regarding differential gene expression. We illustrate the results with experimental data from gene expression studies on Deinococcus radiodurans following DNA damage using cDNA microarrays.

  8. Microarray and KOG analysis of Acanthamoeba healyi genes up-regulated by mouse-brain passage.

    Science.gov (United States)

    Moon, Eun-Kyung; Xuan, Ying-Hua; Kong, Hyun-Hee

    2014-08-01

    Long-term cultivation in a laboratory could reduce the virulence of Acanthamoeba. To identify virulence factors of Acanthamoeba, the authors compared the transcription profiles of long-term cultivated Acanthamoeba healyi (OLD) and three times mouse-brain passaged A. healyi (MBP) using microarray analysis and eukaryotic orthologous group (KOG) assignments. Microarray analysis revealed that 601 genes were up-regulated by mouse-brain passage. The results of real-time PCR of 8 randomly selected genes up-regulated in the MBP strain confirmed microarray analysis findings. KOG assignments showed relatively higher percentages of the MBP strain up-regulated genes in T article (signal transduction mechanism), O article (posttranslational modification, protein turnover, chaperones), C article (energy production and conversion), and J article (translation, ribosomal structure and biogenesis). In particular, the MBP strain showed higher expressions of cysteine protease and metalloprotease. A comparison of KOG assignments by microarray analysis and previous EST (expressed sequence tags) analysis showed similar populations of up-regulated genes. These results provide important information regarding the identification of virulence factors of pathogenic Acanthamoeba.

  9. The effect of oxythioquinox exposure on normal human mammary epithelial cell gene expression: A microarray analysis study

    Directory of Open Access Journals (Sweden)

    Weston Ainsley

    2004-09-01

    Full Text Available Abstract Background Inter-individual variation in normal human mammary epithelial cells in response to oxythioquinox (OTQ is reported. Gene expression signatures resulting from chemical exposures are generally created from analysis of exposures in rat, mouse or other genetically similar animal models, limiting information about inter-individual variations. This study focused on the effect of inter-individual variation in gene expression signatures. Methods Gene expression was studied in primary normal human mammary epithelial cells (NHMECs derived from four women undergoing reduction mammoplasty [Cooperative Human Tissue Network (National Cancer Institute and National Disease Research Interchange]. Gene transcription in each cell strain was analyzed using high-density oligonucleotide DNA microarrays (HuGeneFL, Affymetrix™ and changes in the expression of selected genes were verified by real-time polymerase chain reaction at extended time points (ABI. DNA microarrays were hybridized to materials prepared from total RNA that was collected after OTQ treatment for 15, 60 and 120 min. RNA was harvested from the vehicle control (DMSO at 120 min. The gene expression profile included all genes altered by at least a signal log ratio (SLR of ± 0.6 and p value ≤ 0.05 in three of four cell strains analyzed. Results RNA species were clustered in various patterns of expression highlighting genes with altered expression in one or more of the cell strains, including metabolic enzymes and transcription factors. Of the clustered RNA species, only 36 were found to be altered at one time point in three or more of the cell strains analyzed (13 up-regulated, 23 down-regulated. Cluster analysis examined the effects of OTQ on the cells with specific p53 polymorphisms. The two strains expressing the major variant of p53 had 83 common genes altered (35 increased, 48 decreased at one or more time point by at least a 0.6 signal log ratio (SLR. The intermediate variant

  10. Comparative analysis of Lactobacillus plantarum WCFS1 transcriptomes using DNA microarray and next generation sequencing technologies

    NARCIS (Netherlands)

    Leimena, M.M.; Wels, M.; Bongers, R.; Smid, E.J.; Zoetendal, E.G.; Kleerebezem, M.

    2012-01-01

    RNA sequencing is starting to compete with the use of DNA microarrays for transcription analysis in eukaryotes as well as in prokaryotes. Application of RNA sequencing in prokaryotes requires additional steps in the RNA preparation procedure to increase the relative abundance of mRNA and cannot

  11. Pathways analysis: combining microarray data and physiological data to study myogenesis

    NARCIS (Netherlands)

    Pas, te M.F.W.; Hulsegge, B.; Pool, M.H.

    2007-01-01

    Microarray experiments investigate the changes in the expression of the transcriptome of a tissue during biological processes such as development of the tissue. Analysis usually produces a list of up and down regulated genes. While this in itself mayhighlight important biological processes taking

  12. Tissue microarray analysis as a screening tool for neuroendocrine carcinoma of the breast

    DEFF Research Database (Denmark)

    Brask, Julie Benedicte; Talman, Maj-Lis Møller; Wielenga, Vera Timmermans

    2014-01-01

    by investigating the usefulness of tissue microarray (TMA) analysis as a screening tool. We present our findings with regard to sensitivity and specificity compared with whole-mount sections. The material consists of 240 cases of breast cancer divided into 20 TMA blocks that were all immunohistochemically stained...

  13. Microarray analysis of gender- and parasite-specific gene transcription in Strongyloides ratti

    NARCIS (Netherlands)

    Evans, Helen; Mello, Luciane V.; Fang, Yongxiang; Wit, Ernst; Thompson, Fiona J.; Viney, Mark E.; Paterson, Steve

    2008-01-01

    The molecular mechanisms by which parasitic nematodes reproduce and have adapted to life within a host are unclear. In the present study, microarray analysis was used to explore differential transcription among the different stages and sexes of Strongyloides ratti, a parasitic nematode of brown rats

  14. Gene expression analysis of strawberry achene and receptacle maturation using DNA microarrays

    NARCIS (Netherlands)

    Aharoni, A.; O'Connell, A.P.

    2002-01-01

    Large-scale, single pass sequencing and parallel gene expression analysis using DNA microarrays were employed for the comprehensive investigation of ripening in strawberry fruit. A total of 1701 cDNA clones (comprising 1100 strawberry ESTs and 601 unsequenced cDNAs) obtained from a strawberry (Fraga

  15. The Utility of Chromosomal Microarray Analysis in Developmental and Behavioral Pediatrics

    Science.gov (United States)

    Beaudet, Arthur L.

    2013-01-01

    Chromosomal microarray analysis (CMA) has emerged as a powerful new tool to identify genomic abnormalities associated with a wide range of developmental disabilities including congenital malformations, cognitive impairment, and behavioral abnormalities. CMA includes array comparative genomic hybridization (CGH) and single nucleotide polymorphism…

  16. Scanometric analysis of DNA microarrays using DNA intercalator-conjugated gold nanoparticles.

    Science.gov (United States)

    Cho, Hyunmin; Jung, Juyeon; Chung, Bong Hyun

    2012-08-07

    We introduce a scanometric detection method for the analysis of DNA microarrays using DNA intercalator-conjugated gold nanoparticles that can be analyzed with the naked eye or with an optical scanner after the enhancement of the AuNPs. Moreover, we successfully detected a hemagglutinin-subtyping DNA array using this method.

  17. Analysis of tiling microarray data by learning vector quantization and relevance learning

    NARCIS (Netherlands)

    Biehl, Michael; Breitling, Rainer; Li, Yang; Yin, H; Tino, P; Corchado, E; Byrne, W; Yao,

    2007-01-01

    We apply learning vector quantization to the analysis of tiling microarray data. As an example we consider the classification of C. elegans genomic probes as intronic or exonic. Training is based on the current annotation of the genome. Relevance learning techniques are used to weight and select fea

  18. MicA microarray analysis of hepatotoxicity in vivo and in vitro

    NARCIS (Netherlands)

    Elferink, Marieke; Olinga, Peter; Draaisma, Annelies; Merema, M.T.; Bauerschmidt, Susanne; Polman, Jan; Schoonen, Willem; Groothuis, Geny

    2007-01-01

    In the process of drug discovery it is of great importance to develop methods to determine early markers for druginduced toxicity. The microarray technology, developed for the simultaneous analysis of a large number of genes, may be useful for the detection of toxicity in an early stage of the devel

  19. Diagnostic Yield of Chromosomal Microarray Analysis in an Autism Primary Care Practice: Which Guidelines to Implement?

    Science.gov (United States)

    McGrew, Susan G.; Peters, Brittany R.; Crittendon, Julie A.; Veenstra-VanderWeele, Jeremy

    2012-01-01

    Genetic testing is recommended for patients with ASD; however specific recommendations vary by specialty. American Academy of Pediatrics and American Academy of Neurology guidelines recommend G-banded karyotype and Fragile X DNA. The American College of Medical Genetics recommends Chromosomal Microarray Analysis (CMA). We determined the yield of…

  20. Candidate genes for the progression of malignant gliomas identified by microarray analysis.

    Science.gov (United States)

    Bozinov, Oliver; Köhler, Sylvia; Samans, Birgit; Benes, Ludwig; Miller, Dorothea; Ritter, Markus; Sure, Ulrich; Bertalanffy, Helmut

    2008-01-01

    Malignant astrocytomas of World Health Organization (WHO) grade III or IV have a reduced median survival time, and possible pathways have been described for the progression of anaplastic astrocytomas and glioblastomas, but the molecular basis of malignant astrocytoma progression is still poorly understood. Microarray analysis provides the chance to accelerate studies by comparison of the expression of thousands of genes in these tumours and consequently identify targeting genes. We compared the transcriptional profile of 4,608 genes in tumours of 15 patients including 6 anaplastic astrocytomas (WHO grade III) and 9 glioblastomas (WHO grade IV) using microarray analysis. The microarray data were corroborated by real-time reverse transcription-polymerase chain reaction analysis of two selected genes. We identified 166 gene alterations with a fold change of 2 and higher whose mRNA levels differed (absolute value of the t statistic of 1.96) between the two malignant glioma groups. Further analyses confirmed same transcription directions for Olig2 and IL-13Ralpha2 in anaplastic astrocytomas as compared to glioblastomas. Microarray analyses with a close binary question reveal numerous interesting candidate genes, which need further histochemical testing after selection for confirmation. IL-13Ralpha2 and Olig2 have been identified and confirmed to be interesting candidate genes whose differential expression likely plays a role in malignant progression of astrocytomas.

  1. Array2BIO: A Comprehensive Suite of Utilities for the Analysis of Microarray Data

    Energy Technology Data Exchange (ETDEWEB)

    Loots, G G; Chain, P G; Mabery, S; Rasley, A; Garcia, E; Ovcharenko, I

    2006-02-13

    We have developed an integrative and automated toolkit for the analysis of Affymetrix microarray data, named Array2BIO. It identifies groups of coexpressed genes using two complementary approaches--comparative analysis of signal versus control microarrays and clustering analysis of gene expression across different conditions. The identified genes are assigned to functional categories based on the Gene Ontology classification, and a detection of corresponding KEGG protein interaction pathways. Array2BIO reliably handles low-expressor genes and provides a set of statistical methods to quantify the odds of observations, including the Benjamini-Hochberg and Bonferroni multiple testing corrections. Automated interface with the ECR Browser provides evolutionary conservation analysis of identified gene loci while the interconnection with Creme allows high-throughput analysis of human promoter regions and prediction of gene regulatory elements that underlie the observed expression patterns. Array2BIO is publicly available at http://array2bio.dcode.org.

  2. Robust gene selection methods using weighting schemes for microarray data analysis.

    Science.gov (United States)

    Kang, Suyeon; Song, Jongwoo

    2017-09-02

    A common task in microarray data analysis is to identify informative genes that are differentially expressed between two different states. Owing to the high-dimensional nature of microarray data, identification of significant genes has been essential in analyzing the data. However, the performances of many gene selection techniques are highly dependent on the experimental conditions, such as the presence of measurement error or a limited number of sample replicates. We have proposed new filter-based gene selection techniques, by applying a simple modification to significance analysis of microarrays (SAM). To prove the effectiveness of the proposed method, we considered a series of synthetic datasets with different noise levels and sample sizes along with two real datasets. The following findings were made. First, our proposed methods outperform conventional methods for all simulation set-ups. In particular, our methods are much better when the given data are noisy and sample size is small. They showed relatively robust performance regardless of noise level and sample size, whereas the performance of SAM became significantly worse as the noise level became high or sample size decreased. When sufficient sample replicates were available, SAM and our methods showed similar performance. Finally, our proposed methods are competitive with traditional methods in classification tasks for microarrays. The results of simulation study and real data analysis have demonstrated that our proposed methods are effective for detecting significant genes and classification tasks, especially when the given data are noisy or have few sample replicates. By employing weighting schemes, we can obtain robust and reliable results for microarray data analysis.

  3. De novo Transcriptome Sequencing and Development of Abscission Zone-Specific Microarray as a New Molecular Tool for Analysis of Tomato Organ Abscission

    Science.gov (United States)

    Sundaresan, Srivignesh; Philosoph-Hadas, Sonia; Riov, Joseph; Mugasimangalam, Raja; Kuravadi, Nagesh A.; Kochanek, Bettina; Salim, Shoshana; Tucker, Mark L.; Meir, Shimon

    2016-01-01

    Abscission of flower pedicels and leaf petioles of tomato (Solanum lycopersicum) can be induced by flower removal or leaf deblading, respectively, which leads to auxin depletion, resulting in increased sensitivity of the abscission zone (AZ) to ethylene. However, the molecular mechanisms that drive the acquisition of abscission competence and its modulation by auxin gradients are not yet known. We used RNA-Sequencing (RNA-Seq) to obtain a comprehensive transcriptome of tomato flower AZ (FAZ) and leaf AZ (LAZ) during abscission. RNA-Seq was performed on a pool of total RNA extracted from tomato FAZ and LAZ, at different abscission stages, followed by de novo assembly. The assembled clusters contained transcripts that are already known in the Solanaceae (SOL) genomics and NCBI databases, and over 8823 identified novel tomato transcripts of varying sizes. An AZ-specific microarray, encompassing the novel transcripts identified in this study and all known transcripts from the SOL genomics and NCBI databases, was constructed to study the abscission process. Multiple probes for longer genes and key AZ-specific genes, including antisense probes for all transcripts, make this array a unique tool for studying abscission with a comprehensive set of transcripts, and for mining for naturally occurring antisense transcripts. We focused on comparing the global transcriptomes generated from the FAZ and the LAZ to establish the divergences and similarities in their transcriptional networks, and particularly to characterize the processes and transcriptional regulators enriched in gene clusters that are differentially regulated in these two AZs. This study is the first attempt to analyze the global gene expression in different AZs in tomato by combining the RNA-Seq technique with oligonucleotide microarrays. Our AZ-specific microarray chip provides a cost-effective approach for expression profiling and robust analysis of multiple samples in a rapid succession. PMID:26834766

  4. De novo transcriptome sequencing and development of abscission zone-specific microarray as a new molecular tool for analysis of tomato organ abscission

    Directory of Open Access Journals (Sweden)

    Srivignesh eSundaresan

    2016-01-01

    Full Text Available Abscission of flower pedicels and leaf petioles of tomato (Solanum lycopersicum can be induced by flower removal or leaf deblading, respectively, leading to auxin depletion, which results in increased sensitivity of the abscission zone (AZ to ethylene. However, the molecular mechanisms that drive the acquisition of abscission competence and its modulation by auxin gradients are not yet known. We used RNA-Sequencing (RNA-Seq to obtain the comprehensive transcriptome of tomato flower AZ (FAZ and leaf AZ (LAZ during abscission. RNA-Seq was performed on a pool of total RNA extracted from different abscission stages of tomato FAZ and LAZ, followed by de novo assembly. The assembled clusters contained transcripts that are already known in Solanaceae (SOL genomics database and NCBI databases, and over 8,823 identified novel tomato transcripts of varying sizes. An AZ-specific microarray, encompassing these novel transcripts identified in this study and all known transcripts from the SOL genomics and NCBI databases, was constructed to study the abscission process. Multiple probes for longer genes and key AZ-specific genes, including antisense probes for all transcripts, make this array a unique tool for studying abscission with a comprehensive set of transcripts, and for mining for naturally occurring antisense transcripts. We focused on comparing the global transcriptomes generated from the FAZ and the LAZ to establish the divergences and similarities in their transcriptional networks, and particularly to characterize the processes and transcriptional regulators enriched in gene clusters that are differentially regulated in these two AZs. This study is the first attempt to analyze the global gene expression in different AZs in tomato by combining the RNA-Seq technique with oligonucleotide microarrays. Our AZ-specific microarray chip provides a cost-effective approach for expression profiling and robust analysis of multiple samples in a rapid succession.

  5. Microarray meta-analysis database (M2DB: a uniformly pre-processed, quality controlled, and manually curated human clinical microarray database

    Directory of Open Access Journals (Sweden)

    Cheng Wei-Chung

    2010-08-01

    Full Text Available Abstract Background Over the past decade, gene expression microarray studies have greatly expanded our knowledge of genetic mechanisms of human diseases. Meta-analysis of substantial amounts of accumulated data, by integrating valuable information from multiple studies, is becoming more important in microarray research. However, collecting data of special interest from public microarray repositories often present major practical problems. Moreover, including low-quality data may significantly reduce meta-analysis efficiency. Results M2DB is a human curated microarray database designed for easy querying, based on clinical information and for interactive retrieval of either raw or uniformly pre-processed data, along with a set of quality-control metrics. The database contains more than 10,000 previously published Affymetrix GeneChip arrays, performed using human clinical specimens. M2DB allows online querying according to a flexible combination of five clinical annotations describing disease state and sampling location. These annotations were manually curated by controlled vocabularies, based on information obtained from GEO, ArrayExpress, and published papers. For array-based assessment control, the online query provides sets of QC metrics, generated using three available QC algorithms. Arrays with poor data quality can easily be excluded from the query interface. The query provides values from two algorithms for gene-based filtering, and raw data and three kinds of pre-processed data for downloading. Conclusion M2DB utilizes a user-friendly interface for QC parameters, sample clinical annotations, and data formats to help users obtain clinical metadata. This database provides a lower entry threshold and an integrated process of meta-analysis. We hope that this research will promote further evolution of microarray meta-analysis.

  6. Gene microarray data analysis using parallel point-symmetry-based clustering.

    Science.gov (United States)

    Sarkar, Anasua; Maulik, Ujjwal

    2015-01-01

    Identification of co-expressed genes is the central goal in microarray gene expression analysis. Point-symmetry-based clustering is an important unsupervised learning technique for recognising symmetrical convex- or non-convex-shaped clusters. To enable fast clustering of large microarray data, we propose a distributed time-efficient scalable approach for point-symmetry-based K-Means algorithm. A natural basis for analysing gene expression data using symmetry-based algorithm is to group together genes with similar symmetrical expression patterns. This new parallel implementation also satisfies linear speedup in timing without sacrificing the quality of clustering solution on large microarray data sets. The parallel point-symmetry-based K-Means algorithm is compared with another new parallel symmetry-based K-Means and existing parallel K-Means over eight artificial and benchmark microarray data sets, to demonstrate its superiority, in both timing and validity. The statistical analysis is also performed to establish the significance of this message-passing-interface based point-symmetry K-Means implementation. We also analysed the biological relevance of clustering solutions.

  7. Informatics enhanced SNP microarray analysis of 30 miscarriage samples compared to routine cytogenetics.

    Directory of Open Access Journals (Sweden)

    Ruth B Lathi

    Full Text Available PURPOSE: The metaphase karyotype is often used as a diagnostic tool in the setting of early miscarriage; however this technique has several limitations. We evaluate a new technique for karyotyping that uses single nucleotide polymorphism microarrays (SNP. This technique was compared in a blinded, prospective fashion, to the traditional metaphase karyotype. METHODS: Patients undergoing dilation and curettage for first trimester miscarriage between February and August 2010 were enrolled. Samples of chorionic villi were equally divided and sent for microarray testing in parallel with routine cytogenetic testing. RESULTS: Thirty samples were analyzed, with only four discordant results. Discordant results occurred when the entire genome was duplicated or when a balanced rearrangement was present. Cytogenetic karyotyping took an average of 29 days while microarray-based karytoyping took an average of 12 days. CONCLUSIONS: Molecular karyotyping of POC after missed abortion using SNP microarray analysis allows for the ability to detect maternal cell contamination and provides rapid results with good concordance to standard cytogenetic analysis.

  8. NMD Microarray Analysis for Rapid Genome-Wide Screen of Mutated Genes in Cancer

    Directory of Open Access Journals (Sweden)

    Maija Wolf

    2005-01-01

    Full Text Available Gene mutations play a critical role in cancer development and progression, and their identification offers possibilities for accurate diagnostics and therapeutic targeting. Finding genes undergoing mutations is challenging and slow, even in the post-genomic era. A new approach was recently developed by Noensie and Dietz to prioritize and focus the search, making use of nonsense-mediated mRNA decay (NMD inhibition and microarray analysis (NMD microarrays in the identification of transcripts containing nonsense mutations. We combined NMD microarrays with array-based CGH (comparative genomic hybridization in order to identify inactivation of tumor suppressor genes in cancer. Such a “mutatomics” screening of prostate cancer cell lines led to the identification of inactivating mutations in the EPHB2 gene. Up to 8% of metastatic uncultured prostate cancers also showed mutations of this gene whose loss of function may confer loss of tissue architecture. NMD microarray analysis could turn out to be a powerful research method to identify novel mutated genes in cancer cell lines, providing targets that could then be further investigated for their clinical relevance and therapeutic potential.

  9. Goober: a fully integrated and user-friendly microarray data management and analysis solution for core labs and bench biologists.

    Science.gov (United States)

    Luo, Wen; Gudipati, Murali; Jung, Kevin; Chen, Mao; Marschke, Keith B

    2009-08-23

    Despite the large number of software tools developed to address different areas of microarray data analysis, very few offer an all-in-one solution with little learning curve. For microarray core labs, there are even fewer software packages available to help with their routine but critical tasks, such as data quality control (QC) and inventory management. We have developed a simple-to-use web portal to allow bench biologists to analyze and query complicated microarray data and related biological pathways without prior training. Both experiment-based and gene-based analysis can be easily performed, even for the first-time user, through the intuitive multi-layer design and interactive graphic links. While being friendly to inexperienced users, most parameters in Goober can be easily adjusted via drop-down menus to allow advanced users to tailor their needs and perform more complicated analysis. Moreover, we have integrated graphic pathway analysis into the website to help users examine microarray data within the relevant biological content. Goober also contains features that cover most of the common tasks in microarray core labs, such as real time array QC, data loading, array usage and inventory tracking. Overall, Goober is a complete microarray solution to help biologists instantly discover valuable information from a microarray experiment and enhance the quality and productivity of microarray core labs. The whole package is freely available at http://sourceforge.net/projects/goober. A demo web server is available at http://www.goober-array.org.

  10. Comparative analysis of gene expression by microarray analysis of male and female flowers of Asparagus officinalis.

    Science.gov (United States)

    Gao, Wu-Jun; Li, Shu-Fen; Zhang, Guo-Jun; Wang, Ning-Na; Deng, Chuan-Liang; Lu, Long-Dou

    2013-01-01

    To identify rapidly a number of genes probably involved in sex determination and differentiation of the dioecious plant Asparagus officinalis, gene expression profiles in early flower development for male and female plants were investigated by microarray assay with 8,665 probes. In total, 638 male-biased and 543 female-biased genes were identified. These genes with biased-expression for male and female were involved in a variety of processes associated with molecular functions, cellular components, and biological processes, suggesting that a complex mechanism underlies the sex development of asparagus. Among the differentially expressed genes involved in the reproductive process, a number of genes associated with floral development were identified. Reverse transcription-PCR was performed for validation, and the results were largely consistent with those obtained by microarray analysis. The findings of this study might contribute to understanding of the molecular mechanisms of sex determination and differentiation in dioecious asparagus and provide a foundation for further studies of this plant.

  11. Dry-reagent disposable biosensor for visual genotyping of single nucleotide polymorphisms by oligonucleotide ligation reaction: application to pharmacogenetic analysis.

    Science.gov (United States)

    Toubanaki, Dimitra K; Christopoulos, Theodore K; Ioannou, Penelope C; Gravanis, Achille

    2008-08-01

    Most genotyping methods for known single-nucleotide polymorphisms (SNPs) are based on hybridization with allele-specific probes, oligonucleotide ligation reaction (OLR), primer extension or invasive cleavage. OLR offers superior specificity because it involves two recognition events; namely, the hybridization of an allele-specific probe and a common probe to adjacent positions on target DNA. OLR products can be detected by microtiter well-based colorimetric, time-resolved fluorimetric or chemiluminometric assays, electrophoresis, microarrays, microspheres, and homogeneous fluorimetric or colorimetric assays. We have developed a simple, robust, and low-cost disposable biosensor in dry-reagent format, which allows visual genotyping with no need for instrumentation. The OLR mixture contains a biotinylated common probe and an allele-specific probe with a (dA)(20) segment at the 3'-end. OLR products are denatured and applied to the biosensor next to gold nanoparticles that are decorated with oligo(dT) strands. The sensor is immersed in the appropriate buffer and all components migrate by capillary action. The OLR product is captured by immobilized streptavidin at the test zone (TZ) of the sensor and hybridizes with the oligo(dT) strands of the nanoparticles. A characteristic red line is generated due to the accumulation of nanoparticles. The excess nanoparticles are captured by immobilized oligo(dA) at the control zone of the strip, giving a second red line. We have applied successfully the proposed OLR-dipstick assay to the genotyping of four SNPs in the drug-metabolizing enzyme genes CYP2D6 ((*)3 and (*)4) and CYP2C19 ((*)2 and (*)3). The results were in agreement with direct sequencing.

  12. Combining gene expression data from different generations of oligonucleotide arrays

    Directory of Open Access Journals (Sweden)

    Kong Sek

    2004-10-01

    Full Text Available Abstract Background One of the important challenges in microarray analysis is to take full advantage of previously accumulated data, both from one's own laboratory and from public repositories. Through a comparative analysis on a variety of datasets, a more comprehensive view of the underlying mechanism or structure can be obtained. However, as we discover in this work, continual changes in genomic sequence annotations and probe design criteria make it difficult to compare gene expression data even from different generations of the same microarray platform. Results We first describe the extent of discordance between the results derived from two generations of Affymetrix oligonucleotide arrays, as revealed in cluster analysis and in identification of differentially expressed genes. We then propose a method for increasing comparability. The dataset we use consists of a set of 14 human muscle biopsy samples from patients with inflammatory myopathies that were hybridized on both HG-U95Av2 and HG-U133A human arrays. We find that the use of the probe set matching table for comparative analysis provided by Affymetrix produces better results than matching by UniGene or LocusLink identifiers but still remains inadequate. Rescaling of expression values for each gene across samples and data filtering by expression values enhance comparability but only for few specific analyses. As a generic method for improving comparability, we select a subset of probes with overlapping sequence segments in the two array types and recalculate expression values based only on the selected probes. We show that this filtering of probes significantly improves the comparability while retaining a sufficient number of probe sets for further analysis. Conclusions Compatibility between high-density oligonucleotide arrays is significantly affected by probe-level sequence information. With a careful filtering of the probes based on their sequence overlaps, data from different

  13. Discovery and analysis of pancreatic adenocarcinoma genes using cDNA microarrays

    Institute of Scientific and Technical Information of China (English)

    Gang Jin; Xian-Gui Hu; Kang Ying; Yan Tang; Rui Liu; Yi-Jie Zhang; Zai-Ping Jing; Yi Xie; Yu-Min Mao

    2005-01-01

    AIM: To study the pathogenetic processes and the role of gene expression by microarray analyses in expediting our understanding of the molecular pathophysiology of pancreatic adenocarcinoma, and to identify the novel cancer-associated genes.METHODS: Nine histologically defined pancreatic head adenocarcinoma specimens associated with clinical data were studied. Total RNA and mRNA were isolated and labeled by reverse transcription reaction with Cy5 and Cy3 for cDNA probe. The cDNA microarrays that represent a set of 4 096 human genes were hybridized with labeled cDNA probe and screened for molecular profiling analyses.RESULTS: Using this methodology, 184 genes were screened out for differences in gene expression level after nine couples of hybridizations. Of the 184 genes,87 were upregulated and 97 downregulated, including 11 novel human genes. In pancreatic adenocarcinoma tissue, several invasion and metastasis related genes showed their high expression levels, suggesting that poor prognosis of pancreatic adenocarcinoma might have a solid molecular biological basis.CONCLUSION: The application of cDNA microarray technique for analysis of gene expression patterns is a powerful strategy to identify novel cancer-associated genes, and to rapidly explore their role in clinical pancreatic adenocarcinoma. Microarray profiles provide us new insights into the carcinogenesis and invasive process of pancreatic adenocarcinoma. Our results suggest that a highly organized and structured process of tumor invasion exists in the pancreas.

  14. A non-parametric meta-analysis approach for combining independent microarray datasets: application using two microarray datasets pertaining to chronic allograft nephropathy

    Directory of Open Access Journals (Sweden)

    Archer Kellie J

    2008-02-01

    Full Text Available Abstract Background With the popularity of DNA microarray technology, multiple groups of researchers have studied the gene expression of similar biological conditions. Different methods have been developed to integrate the results from various microarray studies, though most of them rely on distributional assumptions, such as the t-statistic based, mixed-effects model, or Bayesian model methods. However, often the sample size for each individual microarray experiment is small. Therefore, in this paper we present a non-parametric meta-analysis approach for combining data from independent microarray studies, and illustrate its application on two independent Affymetrix GeneChip studies that compared the gene expression of biopsies from kidney transplant recipients with chronic allograft nephropathy (CAN to those with normal functioning allograft. Results The simulation study comparing the non-parametric meta-analysis approach to a commonly used t-statistic based approach shows that the non-parametric approach has better sensitivity and specificity. For the application on the two CAN studies, we identified 309 distinct genes that expressed differently in CAN. By applying Fisher's exact test to identify enriched KEGG pathways among those genes called differentially expressed, we found 6 KEGG pathways to be over-represented among the identified genes. We used the expression measurements of the identified genes as predictors to predict the class labels for 6 additional biopsy samples, and the predicted results all conformed to their pathologist diagnosed class labels. Conclusion We present a new approach for combining data from multiple independent microarray studies. This approach is non-parametric and does not rely on any distributional assumptions. The rationale behind the approach is logically intuitive and can be easily understood by researchers not having advanced training in statistics. Some of the identified genes and pathways have been

  15. A non-parametric meta-analysis approach for combining independent microarray datasets: application using two microarray datasets pertaining to chronic allograft nephropathy.

    Science.gov (United States)

    Kong, Xiangrong; Mas, Valeria; Archer, Kellie J

    2008-02-26

    With the popularity of DNA microarray technology, multiple groups of researchers have studied the gene expression of similar biological conditions. Different methods have been developed to integrate the results from various microarray studies, though most of them rely on distributional assumptions, such as the t-statistic based, mixed-effects model, or Bayesian model methods. However, often the sample size for each individual microarray experiment is small. Therefore, in this paper we present a non-parametric meta-analysis approach for combining data from independent microarray studies, and illustrate its application on two independent Affymetrix GeneChip studies that compared the gene expression of biopsies from kidney transplant recipients with chronic allograft nephropathy (CAN) to those with normal functioning allograft. The simulation study comparing the non-parametric meta-analysis approach to a commonly used t-statistic based approach shows that the non-parametric approach has better sensitivity and specificity. For the application on the two CAN studies, we identified 309 distinct genes that expressed differently in CAN. By applying Fisher's exact test to identify enriched KEGG pathways among those genes called differentially expressed, we found 6 KEGG pathways to be over-represented among the identified genes. We used the expression measurements of the identified genes as predictors to predict the class labels for 6 additional biopsy samples, and the predicted results all conformed to their pathologist diagnosed class labels. We present a new approach for combining data from multiple independent microarray studies. This approach is non-parametric and does not rely on any distributional assumptions. The rationale behind the approach is logically intuitive and can be easily understood by researchers not having advanced training in statistics. Some of the identified genes and pathways have been reported to be relevant to renal diseases. Further study on the

  16. From hybridization theory to microarray data analysis: performance evaluation

    Directory of Open Access Journals (Sweden)

    Berger Fabrice

    2011-12-01

    Full Text Available Abstract Background Several preprocessing methods are available for the analysis of Affymetrix Genechips arrays. The most popular algorithms analyze the measured fluorescence intensities with statistical methods. Here we focus on a novel algorithm, AffyILM, available from Bioconductor, which relies on inputs from hybridization thermodynamics and uses an extended Langmuir isotherm model to compute transcript concentrations. These concentrations are then employed in the statistical analysis. We compared the performance of AffyILM and other traditional methods both in the old and in the newest generation of GeneChips. Results Tissue mixture and Latin Square datasets (provided by Affymetrix were used to assess the performances of the differential expression analysis depending on the preprocessing strategy. A correlation analysis conducted on the tissue mixture data reveals that the median-polish algorithm allows to best summarize AffyILM concentrations computed at the probe-level. Those correlation results are equivalent to the best correlations observed using popular preprocessing methods relying on intensity values. The performances of each tested preprocessing algorithm were quantified using the Latin Square HG-U133A dataset, thanks to the comparison of differential analysis results with the list of spiked genes. The figures of merit generated illustrates that the performances associated to AffyILM(medianpolish, inferred from the present statistical analysis, are comparable to the best performing strategies previously reported. Conclusions Converting probe intensities to estimates of target concentrations prior to the statistical analysis, AffyILM(medianpolish is one of the best performing strategy currently available. Using hybridization theory, probe-level estimates of target concentrations should be identically distributed. In the future, a probe-level multivariate analysis of the concentrations should be compared to the univariate analysis of

  17. Data in support of a functional analysis of splicing mutations in the IDS gene and the use of antisense oligonucleotides to exploit an alternative therapy for MPS II

    Directory of Open Access Journals (Sweden)

    Liliana Matos

    2015-12-01

    The interpretation of these data and further extensive experiments into the analysis of these three mutations and also into the methodology applied to correct one of them can be found in “Functional analysis of splicing mutations in the IDS gene and the use of antisense oligonucleotides to exploit an alternative therapy for MPS II” Matos et al. (2015 [1].

  18. GEPAS, a web-based tool for microarray data analysis and interpretation

    Science.gov (United States)

    Tárraga, Joaquín; Medina, Ignacio; Carbonell, José; Huerta-Cepas, Jaime; Minguez, Pablo; Alloza, Eva; Al-Shahrour, Fátima; Vegas-Azcárate, Susana; Goetz, Stefan; Escobar, Pablo; Garcia-Garcia, Francisco; Conesa, Ana; Montaner, David; Dopazo, Joaquín

    2008-01-01

    Gene Expression Profile Analysis Suite (GEPAS) is one of the most complete and extensively used web-based packages for microarray data analysis. During its more than 5 years of activity it has continuously been updated to keep pace with the state-of-the-art in the changing microarray data analysis arena. GEPAS offers diverse analysis options that include well established as well as novel algorithms for normalization, gene selection, class prediction, clustering and functional profiling of the experiment. New options for time-course (or dose-response) experiments, microarray-based class prediction, new clustering methods and new tests for differential expression have been included. The new pipeliner module allows automating the execution of sequential analysis steps by means of a simple but powerful graphic interface. An extensive re-engineering of GEPAS has been carried out which includes the use of web services and Web 2.0 technology features, a new user interface with persistent sessions and a new extended database of gene identifiers. GEPAS is nowadays the most quoted web tool in its field and it is extensively used by researchers of many countries and its records indicate an average usage rate of 500 experiments per day. GEPAS, is available at http://www.gepas.org. PMID:18508806

  19. DNA Microarray-based Ecotoxicological Biomarker Discovery in a Small Fish Model Species

    Science.gov (United States)

    This paper addresses several issues critical to use of zebrafish oligonucleotide microarrays for computational toxicology research on endocrine disrupting chemicals using small fish models, and more generally, the use of microarrays in aquatic toxicology.

  20. Genomic analysis by oligonucleotide array Comparative Genomic Hybridization utilizing formalin-fixed, paraffin-embedded tissues.

    Science.gov (United States)

    Savage, Stephanie J; Hostetter, Galen

    2011-01-01

    Formalin fixation has been used to preserve tissues for more than a hundred years, and there are currently more than 300 million archival samples in the United States alone. The application of genomic protocols such as high-density oligonucleotide array Comparative Genomic Hybridization (aCGH) to formalin-fixed, paraffin-embedded (FFPE) tissues, therefore, opens an untapped resource of available tissues for research and facilitates utilization of existing clinical data in a research sample set. However, formalin fixation results in cross-linking of proteins and DNA, typically leading to such a significant degradation of DNA template that little is available for use in molecular applications. Here, we describe a protocol to circumvent formalin fixation artifact by utilizing enzymatic reactions to obtain quality DNA from a wide range of FFPE tissues for successful genome-wide discovery of gene dosage alterations in archival clinical samples.

  1. A flexible representation of omic knowledge for thorough analysis of microarray data

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    Demura Taku

    2006-03-01

    Full Text Available Abstract Background In order to understand microarray data reasonably in the context of other existing biological knowledge, it is necessary to conduct a thorough examination of the data utilizing every aspect of available omic knowledge libraries. So far, a number of bioinformatics tools have been developed. However, each of them is restricted to deal with one type of omic knowledge, e.g., pathways, interactions or gene ontology. Now that the varieties of omic knowledge are expanding, analysis tools need a way to deal with any type of omic knowledge. Hence, we have designed the Omic Space Markup Language (OSML that can represent a wide range of omic knowledge, and also, we have developed a tool named GSCope3, which can statistically analyze microarray data in comparison with the OSML-formatted omic knowledge data. Results In order to test the applicability of OSML to represent a variety of omic knowledge specifically useful for analysis of Arabidopsis thaliana microarray data, we have constructed a Biological Knowledge Library (BiKLi by converting eight different types of omic knowledge into OSML-formatted datasets. We applied GSCope3 and BiKLi to previously reported A. thaliana microarray data, so as to extract any additional insights from the data. As a result, we have discovered a new insight that lignin formation resists drought stress and activates transcription of many water channel genes to oppose drought stress; and most of the 20S proteasome subunit genes show similar expression profiles under drought stress. In addition to this novel discovery, similar findings previously reported were also quickly confirmed using GSCope3 and BiKLi. Conclusion GSCope3 can statistically analyze microarray data in the context of any OSML-represented omic knowledge. OSML is not restricted to a specific data type structure, but it can represent a wide range of omic knowledge. It allows us to convert new types of omic knowledge into datasets that can be

  2. New molecular phenotypes in the dst mutants of Arabidopsis revealed by DNA microarray analysis.

    Science.gov (United States)

    Pérez-Amador, M A; Lidder, P; Johnson, M A; Landgraf, J; Wisman, E; Green, P J

    2001-12-01

    In this study, DNA microarray analysis was used to expand our understanding of the dst1 mutant of Arabidopsis. The dst (downstream) mutants were isolated originally as specifically increasing the steady state level and the half-life of DST-containing transcripts. As such, txhey offer a unique opportunity to study rapid sequence-specific mRNA decay pathways in eukaryotes. These mutants show a threefold to fourfold increase in mRNA abundance for two transgenes and an endogenous gene, all containing DST elements, when examined by RNA gel blot analysis; however, they show no visible aberrant phenotype. Here, we use DNA microarrays to identify genes with altered expression levels in dst1 compared with the parental plants. In addition to verifying the increase in the transgene mRNA levels, which were used to isolate these mutants, we were able to identify new genes with altered mRNA abundance in dst1. RNA gel blot analysis confirmed the microarray data for all genes tested and also was used to catalog the first molecular differences in gene expression between the dst1 and dst2 mutants. These differences revealed previously unknown molecular phenotypes for the dst mutants that will be helpful in future analyses. Cluster analysis of genes altered in dst1 revealed new coexpression patterns that prompt new hypotheses regarding the nature of the dst1 mutation and a possible role of the DST-mediated mRNA decay pathway in plants.

  3. Microarray analysis of differentially expressed genes between cysts and trophozoites of Acanthamoeba castellanii.

    Science.gov (United States)

    Moon, Eun-Kyung; Xuan, Ying-Hua; Chung, Dong-Il; Hong, Yeonchul; Kong, Hyun-Hee

    2011-12-01

    Acanthamoeba infection is difficult to treat because of the resistance property of Acanthamoeba cyst against the host immune system, diverse antibiotics, and therapeutic agents. To identify encystation mediating factors of Acanthamoeba, we compared the transcription profile between cysts and trophozoites using microarray analysis. The DNA chip was composed of 12,544 genes based on expressed sequence tag (EST) from an Acanthamoeba ESTs database (DB) constructed in our laboratory, genetic information of Acanthamoeba from TBest DB, and all of Acanthamoeba related genes registered in the NCBI. Microarray analysis indicated that 701 genes showed higher expression than 2 folds in cysts than in trophozoites, and 859 genes were less expressed in cysts than in trophozoites. The results of real-time PCR analysis of randomly selected 9 genes of which expression was increased during cyst formation were coincided well with the microarray results. Eukaryotic orthologous groups (KOG) analysis showed an increment in T article (signal transduction mechanisms) and O article (posttranslational modification, protein turnover, and chaperones) whereas significant decrement of C article (energy production and conversion) during cyst formation. Especially, cystein proteinases showed high expression changes (282 folds) with significant increases in real-time PCR, suggesting a pivotal role of this proteinase in the cyst formation of Acanthamoeba. The present study provides important clues for the identification and characterization of encystation mediating factors of Acanthamoeba.

  4. Multi-membership gene regulation in pathway based microarray analysis

    OpenAIRE

    2011-01-01

    This article is available through the Brunel Open Access Publishing Fund. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background: Gene expression analysis has been intensively researched for more than a decade. Recently, there has been elevated interest in the inte...

  5. Food Microbial Pathogen Detection and Analysis Using DNA Microarray Technologies

    OpenAIRE

    Rasooly, Avraham; Herold, Keith E.

    2008-01-01

    Culture-based methods used for microbial detection and identification are simple to use, relatively inexpensive, and sensitive. However, culture-based methods are too time-consuming for high-throughput testing and too tedious for analysis of samples with multiple organisms and provide little clinical information regarding the pathogen (e.g., antibiotic resistance genes, virulence factors, or strain subtype). DNA-based methods, such as polymerase chain reaction (PCR), overcome some these limit...

  6. Statistical analysis of efficient unbalanced factorial designs for two-color microarray experiments.

    Science.gov (United States)

    Tempelman, Robert J

    2008-01-01

    Experimental designs that efficiently embed a fixed effects treatment structure within a random effects design structure typically require a mixed-model approach to data analyses. Although mixed model software tailored for the analysis of two-color microarray data is increasingly available, much of this software is generally not capable of correctly analyzing the elaborate incomplete block designs that are being increasingly proposed and used for factorial treatment structures. That is, optimized designs are generally unbalanced as it pertains to various treatment comparisons, with different specifications of experimental variability often required for different treatment factors. This paper uses a publicly available microarray dataset, as based upon an efficient experimental design, to demonstrate a proper mixed model analysis of a typical unbalanced factorial design characterized by incomplete blocks and hierarchical levels of variability.

  7. Integrated Microfluidic Devices for Automated Microarray-Based Gene Expression and Genotyping Analysis

    Science.gov (United States)

    Liu, Robin H.; Lodes, Mike; Fuji, H. Sho; Danley, David; McShea, Andrew

    Microarray assays typically involve multistage sample processing and fluidic handling, which are generally labor-intensive and time-consuming. Automation of these processes would improve robustness, reduce run-to-run and operator-to-operator variation, and reduce costs. In this chapter, a fully integrated and self-contained microfluidic biochip device that has been developed to automate the fluidic handling steps for microarray-based gene expression or genotyping analysis is presented. The device consists of a semiconductor-based CustomArray® chip with 12,000 features and a microfluidic cartridge. The CustomArray was manufactured using a semiconductor-based in situ synthesis technology. The micro-fluidic cartridge consists of microfluidic pumps, mixers, valves, fluid channels, and reagent storage chambers. Microarray hybridization and subsequent fluidic handling and reactions (including a number of washing and labeling steps) were performed in this fully automated and miniature device before fluorescent image scanning of the microarray chip. Electrochemical micropumps were integrated in the cartridge to provide pumping of liquid solutions. A micromixing technique based on gas bubbling generated by electrochemical micropumps was developed. Low-cost check valves were implemented in the cartridge to prevent cross-talk of the stored reagents. Gene expression study of the human leukemia cell line (K562) and genotyping detection and sequencing of influenza A subtypes have been demonstrated using this integrated biochip platform. For gene expression assays, the microfluidic CustomArray device detected sample RNAs with a concentration as low as 0.375 pM. Detection was quantitative over more than three orders of magnitude. Experiment also showed that chip-to-chip variability was low indicating that the integrated microfluidic devices eliminate manual fluidic handling steps that can be a significant source of variability in genomic analysis. The genotyping results showed

  8. TMA Navigator: network inference, patient stratification and survival analysis with tissue microarray data

    OpenAIRE

    Lubbock, A. L. R.; Katz, E; Harrison, D J; Overton, I M

    2013-01-01

    Scottish Funding Council (SFC) and the Chief Scientist’s Office (CSO) (to D.H.); Royal Society of Edinburgh Scottish Government Fellowship co-funded by Marie Curie Actions and the UK Medical Research Council (MRC) (to I.O.). Funding for open access charge: Royal Society of Edinburgh. Tissue microarrays (TMAs) allow multiplexed analysis of tissue samples and are frequently used to estimate biomarker protein expression in tumour biopsies. TMA Navigator (www.tmanavigator.org) is an open acces...

  9. Single primer amplification (SPA) of cDNA for microarray expression analysis

    OpenAIRE

    2003-01-01

    The potential of expression analysis using cDNA microarrays to address complex problems in a wide variety of biological contexts is now being realised. A limiting factor in such analyses is often the amount of RNA required, usually tens of micrograms. To address this problem researchers have turned to methods of improving detection sensitivity, either through increasing fluorescent signal output per mRNA molecule or increasing the amount of target available for labelling by use of an amplific...

  10. A genome-wide 20 K citrus microarray for gene expression analysis

    OpenAIRE

    Gadea Jose; Forment Javier; Santiago Julia; Marques M Carmen; Juarez Jose; Mauri Nuria; Martinez-Godoy M Angeles

    2008-01-01

    Abstract Background Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genome-wide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. Results We have designed and constructed a publicly available genome-...

  11. A genome-wide 20 K citrus microarray for gene expression analysis

    OpenAIRE

    Martinez-Godoy, M Angeles; Mauri, Nuria; Juarez, Jose; Marques, M Carmen; Santiago, Julia; Forment, Javier; Gadea, Jose

    2008-01-01

    Background Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genome-wide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. Results We have designed and constructed a publicly available genome-wide cDNA...

  12. A genome-wide 20 K citrus microarray for gene expression analysis

    OpenAIRE

    Martínez-Godoy, M. Ángeles; Mauri, Nuria; Juárez, José; Marqués, M. Carmen; Santiago, Julia; Forment, Javier; Gadea Vacas, José

    2008-01-01

    Background: Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genomewide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. Results: We have designed and constructed a publicly available ...

  13. High Throughput Phenotypic Analysis of Mycobacterium tuberculosis and Mycobacterium bovis Strains' Metabolism Using Biolog Phenotype Microarrays

    OpenAIRE

    Khatri, Bhagwati; Fielder, Mark; Jones, Gareth; Newell, William; Abu-Oun, Manal; Wheeler, Paul R.

    2013-01-01

    Tuberculosis is a major human and animal disease of major importance worldwide. Genetically, the closely related strains within the Mycobacterium tuberculosis complex which cause disease are well-characterized but there is an urgent need better to understand their phenotypes. To search rapidly for metabolic differences, a working method using Biolog Phenotype MicroArray analysis was developed. Of 380 substrates surveyed, 71 permitted tetrazolium dye reduction, the readout over 7 days in the m...

  14. Clinical Presentation and Microarray Analysis of Peruvian Children with Atypical Development and/or Aberrant Behavior

    Directory of Open Access Journals (Sweden)

    Merlin G. Butler

    2014-01-01

    Full Text Available We report our experience with high resolution microarray analysis in infants and young children with developmental disability and/or aberrant behavior enrolled at the Centro Ann Sullivan del Peru in Lima, Peru, a low income country. Buccal cells were collected with cotton swabs from 233 participants for later DNA isolation and identification of copy number variation (deletions/duplications and regions of homozygosity (ROH for estimating consanguinity status in 15 infants and young children (12 males, 3 females; mean age ± SD = 28.1 m ±   7.9 m; age range 14 m–41 m randomly selected for microarray analysis. An adequate DNA yield was found in about one-half of the enrolled participants. Ten participants showed deletions or duplications containing candidate genes reported to impact behavior or cognitive development. Five children had ROHs which could have harbored recessive gene alleles contributing to their clinical presentation. The coefficient of inbreeding was calculated and three participants showed first-second cousin relationships, indicating consanguinity. Our preliminary study showed that DNA isolated from buccal cells using cotton swabs was suboptimal, but yet in a subset of participants the yield was adequate for high resolution microarray analysis and several genes were found that impact development and behavior and ROHs identified to determine consanguinity status.

  15. "Harshlighting" small blemishes on microarrays

    Directory of Open Access Journals (Sweden)

    Wittkowski Knut M

    2005-03-01

    Full Text Available Abstract Background Microscopists are familiar with many blemishes that fluorescence images can have due to dust and debris, glass flaws, uneven distribution of fluids or surface coatings, etc. Microarray scans show similar artefacts, which affect the analysis, particularly when one tries to detect subtle changes. However, most blemishes are hard to find by the unaided eye, particularly in high-density oligonucleotide arrays (HDONAs. Results We present a method that harnesses the statistical power provided by having several HDONAs available, which are obtained under similar conditions except for the experimental factor. This method "harshlights" blemishes and renders them evident. We find empirically that about 25% of our chips are blemished, and we analyze the impact of masking them on screening for differentially expressed genes. Conclusion Experiments attempting to assess subtle expression changes should be carefully screened for blemishes on the chips. The proposed method provides investigators with a novel robust approach to improve the sensitivity of microarray analyses. By utilizing topological information to identify and mask blemishes prior to model based analyses, the method prevents artefacts from confounding the process of background correction, normalization, and summarization.

  16. Label-free detection of hybridization of oligonucleotides by oblique-incidence reflectivity difference method

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    The microarrays of 20-base oligonucleotide with different concentrations are detected before and after hybridization by the oblique-incidence reflectivity difference (OI-RD) method. The experimental results prove that OI-RD is a label-free method which can not only distinguish the concentration difference of oligonucleotides before and after the hybridization but also detect the hybridization of short oligonucleotides. At present the OI-RD method can detect 0.39 μmol/L 20-base oligonucleotide or less. These results suggest that the OI-RD method is a promising and potential technique for label-free detection of biological microarrays.

  17. Bayesian meta-analysis models for microarray data: a comparative study

    Directory of Open Access Journals (Sweden)

    Song Joon J

    2007-03-01

    Full Text Available Abstract Background With the growing abundance of microarray data, statistical methods are increasingly needed to integrate results across studies. Two common approaches for meta-analysis of microarrays include either combining gene expression measures across studies or combining summaries such as p-values, probabilities or ranks. Here, we compare two Bayesian meta-analysis models that are analogous to these methods. Results Two Bayesian meta-analysis models for microarray data have recently been introduced. The first model combines standardized gene expression measures across studies into an overall mean, accounting for inter-study variability, while the second combines probabilities of differential expression without combining expression values. Both models produce the gene-specific posterior probability of differential expression, which is the basis for inference. Since the standardized expression integration model includes inter-study variability, it may improve accuracy of results versus the probability integration model. However, due to the small number of studies typical in microarray meta-analyses, the variability between studies is challenging to estimate. The probability integration model eliminates the need to model variability between studies, and thus its implementation is more straightforward. We found in simulations of two and five studies that combining probabilities outperformed combining standardized gene expression measures for three comparison values: the percent of true discovered genes in meta-analysis versus individual studies; the percent of true genes omitted in meta-analysis versus separate studies, and the number of true discovered genes for fixed levels of Bayesian false discovery. We identified similar results when pooling two independent studies of Bacillus subtilis. We assumed that each study was produced from the same microarray platform with only two conditions: a treatment and control, and that the data sets

  18. Outcome-Driven Cluster Analysis with Application to Microarray Data.

    Directory of Open Access Journals (Sweden)

    Jessie J Hsu

    Full Text Available One goal of cluster analysis is to sort characteristics into groups (clusters so that those in the same group are more highly correlated to each other than they are to those in other groups. An example is the search for groups of genes whose expression of RNA is correlated in a population of patients. These genes would be of greater interest if their common level of RNA expression were additionally predictive of the clinical outcome. This issue arose in the context of a study of trauma patients on whom RNA samples were available. The question of interest was whether there were groups of genes that were behaving similarly, and whether each gene in the cluster would have a similar effect on who would recover. For this, we develop an algorithm to simultaneously assign characteristics (genes into groups of highly correlated genes that have the same effect on the outcome (recovery. We propose a random effects model where the genes within each group (cluster equal the sum of a random effect, specific to the observation and cluster, and an independent error term. The outcome variable is a linear combination of the random effects of each cluster. To fit the model, we implement a Markov chain Monte Carlo algorithm based on the likelihood of the observed data. We evaluate the effect of including outcome in the model through simulation studies and describe a strategy for prediction. These methods are applied to trauma data from the Inflammation and Host Response to Injury research program, revealing a clustering of the genes that are informed by the recovery outcome.

  19. Membrane gene ontology bias in sequencing and microarray obtained by housekeeping-gene analysis.

    Science.gov (United States)

    Zhang, Yijuan; Akintola, Oluwafemi S; Liu, Ken J A; Sun, Bingyun

    2016-01-10

    Microarray (MA) and high-throughput sequencing are two commonly used detection systems for global gene expression profiling. Although these two systems are frequently used in parallel, the differences in their final results have not been examined thoroughly. Transcriptomic analysis of housekeeping (HK) genes provides a unique opportunity to reliably examine the technical difference between these two systems. We investigated here the structure, genome location, expression quantity, microarray probe coverage, as well as biological functions of differentially identified human HK genes by 9 MA and 6 sequencing studies. These in-depth analyses allowed us to discover, for the first time, a subset of transcripts encoding membrane, cell surface and nuclear proteins that were prone to differential identification by the two platforms. We hope that the discovery can aid the future development of these technologies for comprehensive transcriptomic studies. Copyright © 2015 Elsevier B.V. All rights reserved.

  20. Multicriteria Gene Screening for Analysis of Differential Expression with DNA Microarrays

    Directory of Open Access Journals (Sweden)

    Alfred O. Hero

    2004-01-01

    Full Text Available This paper introduces a statistical methodology for the identification of differentially expressed genes in DNA microarray experiments based on multiple criteria. These criteria are false discovery rate (FDR, variance-normalized differential expression levels (paired t statistics, and minimum acceptable difference (MAD. The methodology also provides a set of simultaneous FDR confidence intervals on the true expression differences. The analysis can be implemented as a two-stage algorithm in which there is an initial screen that controls only FDR, which is then followed by a second screen which controls both FDR and MAD. It can also be implemented by computing and thresholding the set of FDR P values for each gene that satisfies the MAD criterion. We illustrate the procedure to identify differentially expressed genes from a wild type versus knockout comparison of microarray data.

  1. Global pathway analysis using DNA microarrays in skeletal muscle of women with polycystic ovary syndrome

    DEFF Research Database (Denmark)

    Skov, Vibe

    2007-01-01

    Polycystic ovary syndrome (PCOS) affects 5-10 % of women during their reproductive age and the incidence of the disease is increasing worldwide. More than 50 % of women with PCOS are insulin resistant leading to an increased risk of type 2 diabetes (T2D) and cardiovascular diseases. However...... 1 and 2, the application of gene expression microarrays from Affymetrix was combined with global pathway analysis using GenMAPP and GSEA and subsequent validation by quantitative real-time PCR (q-RT-PCR). Impaired insulin-stimulated glucose metabolism in women with PCOS was associated with reduced...... comparable to other commercial and custom made microarrays and is a cost-effective alternative especially in larger epidemiological studies....

  2. Application of microarray analysis of foodborne Salmonella in poultry production: a review.

    Science.gov (United States)

    Ricke, Steven C; Khatiwara, Anita; Kwon, Young Min

    2013-09-01

    Salmonellosis in the United States is one of the most costly foodborne diseases. Given that Salmonella can originate from a wide variety of environments, reduction of this organism at all stages of poultry production is critical. Salmonella species can encounter various environmental stress conditions that can dramatically influence their survival and virulence. Previous knowledge of Salmonella species genomic regulation of metabolism and physiology in relation to poultry is based on limited information of a few well-characterized genes. Consequently, although there is some information about environmental signals that control Salmonella growth and pathogenesis, much still remains unknown. Advancements in DNA sequencing technologies revolutionized the way bacteria were studied and molecular tools such as microarrays have subsequently been used for comprehensive transcriptomic analysis of Salmonella. With microarray analysis, the expression levels of each single gene in the Salmonella genome can be directly assessed and previously unknown genetic systems that are required for Salmonella growth and survival in the poultry production cycle can be elucidated. This represents an opportunity for development of novel approaches for limiting Salmonella establishment in all phases of poultry production. In this review, recent advances in transcriptome-microarray technologies that are facilitating a better understanding of Salmonella biology in poultry production and processing are discussed.

  3. Kinetic analysis of Yersinia pestis DNA adenine methyltransferase activity using a hemimethylated molecular break light oligonucleotide.

    Directory of Open Access Journals (Sweden)

    Robert J Wood

    Full Text Available BACKGROUND: DNA adenine methylation plays an important role in several critical bacterial processes including mismatch repair, the timing of DNA replication and the transcriptional control of gene expression. The dependence of bacterial virulence on DNA adenine methyltransferase (Dam has led to the proposal that selective Dam inhibitors might function as broad spectrum antibiotics. METHODOLOGY/PRINCIPAL FINDINGS: Herein we report the expression and purification of Yersinia pestis Dam and the development of a continuous fluorescence based assay for DNA adenine methyltransferase activity that is suitable for determining the kinetic parameters of the enzyme and for high throughput screening against potential Dam inhibitors. The assay utilised a hemimethylated break light oligonucleotide substrate containing a GATC methylation site. When this substrate was fully methylated by Dam, it became a substrate for the restriction enzyme DpnI, resulting in separation of fluorophore (fluorescein and quencher (dabcyl and therefore an increase in fluorescence. The assays were monitored in real time using a fluorescence microplate reader in 96 well format and were used for the kinetic characterisation of Yersinia pestis Dam, its substrates and the known Dam inhibitor, S-adenosylhomocysteine. The assay has been validated for high throughput screening, giving a Z-factor of 0.71+/-0.07 indicating that it is a sensitive assay for the identification of inhibitors. CONCLUSIONS/SIGNIFICANCE: The assay is therefore suitable for high throughput screening for inhibitors of DNA adenine methyltransferases and the kinetic characterisation of the inhibition.

  4. Analysis of Structural Flexibility of Damaged DNA Using Thiol-Tethered Oligonucleotide Duplexes.

    Directory of Open Access Journals (Sweden)

    Masashi Fujita

    Full Text Available Bent structures are formed in DNA by the binding of small molecules or proteins. We developed a chemical method to detect bent DNA structures. Oligonucleotide duplexes in which two mercaptoalkyl groups were attached to the positions facing each other across the major groove were prepared. When the duplex contained the cisplatin adduct, which was proved to induce static helix bending, interstrand disulfide bond formation under an oxygen atmosphere was detected by HPLC analyses, but not in the non-adducted duplex, when the two thiol-tethered nucleosides were separated by six base pairs. When the insert was five and seven base pairs, the disulfide bond was formed and was not formed, respectively, regardless of the cisplatin adduct formation. The same reaction was observed in the duplexes containing an abasic site analog and the (6–4 photoproduct. Compared with the cisplatin case, the disulfide bond formation was slower in these duplexes, but the reaction rate was nearly independent of the linker length. These results indicate that dynamic structural changes of the abasic site- and (6–4 photoproduct-containing duplexes could be detected by our method. It is strongly suggested that the UV-damaged DNA-binding protein, which specifically binds these duplexes and functions at the first step of global-genome nucleotide excision repair, recognizes the easily bendable nature of damaged DNA.

  5. Neural network analysis of lymphoma microarray data: prognosis and diagnosis near-perfect

    Directory of Open Access Journals (Sweden)

    Song Li

    2003-04-01

    Full Text Available Abstract Background Microarray chips are being rapidly deployed as a major tool in genomic research. To date most of the analysis of the enormous amount of information provided on these chips has relied on clustering techniques and other standard statistical procedures. These methods, particularly with regard to cancer patient prognosis, have generally been inadequate in providing the reduced gene subsets required for perfect classification. Results Networks trained on microarray data from DLBCL lymphoma patients have, for the first time, been able to predict the long-term survival of individual patients with 100% accuracy. Other networks were able to distinguish DLBCL lymphoma donors from other donors, including donors with other lymphomas, with 99% accuracy. Differentiating the trained network can narrow the gene profile to less than three dozen genes for each classification. Conclusions Here we show that artificial neural networks are a superior tool for digesting microarray data both with regard to making distinctions based on the data and with regard to providing very specific reference as to which genes were most important in making the correct distinction in each case.

  6. RL-SAGE and microarray analysis of the rice transcriptome after Rhizoctonia solani infection.

    Science.gov (United States)

    Venu, R C; Jia, Yulin; Gowda, Malali; Jia, Melissa H; Jantasuriyarat, Chatchawan; Stahlberg, Eric; Li, Huameng; Rhineheart, Andrew; Boddhireddy, Prashanth; Singh, Pratibha; Rutger, Neil; Kudrna, David; Wing, Rod; Nelson, James C; Wang, Guo-Liang

    2007-10-01

    Sheath blight caused by the fungal pathogen Rhizoctonia solani is an emerging problem in rice production worldwide. To elucidate the molecular basis of rice defense to the pathogen, RNA isolated from R. solani-infected leaves of Jasmine 85 was used for both RL-SAGE library construction and microarray hybridization. RL-SAGE sequence analysis identified 20,233 and 24,049 distinct tags from the control and inoculated libraries, respectively. Nearly half of the significant tags (> or =2 copies) from both libraries matched TIGR annotated genes and KOME full-length cDNAs. Among them, 42% represented sense and 7% antisense transcripts, respectively. Interestingly, 60% of the library-specific (> or =10 copies) and differentially expressed (>4.0-fold change) tags were novel transcripts matching genomic sequence but not annotated genes. About 70% of the genes identified in the SAGE libraries showed similar expression patterns (up or down-regulated) in the microarray data obtained from three biological replications. Some candidate RL-SAGE tags and microarray genes were located in known sheath blight QTL regions. The expression of ten differentially expressed RL-SAGE tags was confirmed with RT-PCR. The defense genes associated with resistance to R. solani identified in this study are useful genomic materials for further elucidation of the molecular basis of the defense response to R. solani and fine mapping of target sheath blight QTLs.

  7. ZODET: software for the identification, analysis and visualisation of outlier genes in microarray expression data.

    Directory of Open Access Journals (Sweden)

    Daniel L Roden

    Full Text Available Complex human diseases can show significant heterogeneity between patients with the same phenotypic disorder. An outlier detection strategy was developed to identify variants at the level of gene transcription that are of potential biological and phenotypic importance. Here we describe a graphical software package (z-score outlier detection (ZODET that enables identification and visualisation of gross abnormalities in gene expression (outliers in individuals, using whole genome microarray data. Mean and standard deviation of expression in a healthy control cohort is used to detect both over and under-expressed probes in individual test subjects. We compared the potential of ZODET to detect outlier genes in gene expression datasets with a previously described statistical method, gene tissue index (GTI, using a simulated expression dataset and a publicly available monocyte-derived macrophage microarray dataset. Taken together, these results support ZODET as a novel approach to identify outlier genes of potential pathogenic relevance in complex human diseases. The algorithm is implemented using R packages and Java.The software is freely available from http://www.ucl.ac.uk/medicine/molecular-medicine/publications/microarray-outlier-analysis.

  8. Triple-target microarray experiments: a novel experimental strategy

    Directory of Open Access Journals (Sweden)

    Cooke Howard J

    2004-02-01

    Full Text Available Abstract Background High-throughput, parallel gene expression analysis by means of microarray technology has become a widely used technique in recent years. There are currently two main dye-labelling strategies for microarray studies based on custom-spotted cDNA or oligonucleotides arrays: (I Dye-labelling of a single target sample with a particular dye, followed by subsequent hybridisation to a single microarray slide, (II Dye-labelling of two different target samples with two different dyes, followed by subsequent co-hybridisation to a single microarray slide. The two dyes most frequently used for either method are Cy3 and Cy5. We propose and evaluate a novel experiment set-up utilising three differently labelled targets co-hybridised to one microarray slide. In addition to Cy3 and Cy5, this incorporates Alexa 594 as a third dye-label. We evaluate this approach in line with current data processing and analysis techniques for microarrays, and run separate analyses on Alexa 594 used in single-target, dual-target and the intended triple-target experiment set-ups (a total of 18 microarray slides. We follow this by pointing out practical applications and suitable analysis methods, and conclude that triple-target microarray experiments can add value to microarray research by reducing material costs for arrays and related processes, and by increasing the number of options for pragmatic experiment design. Results The addition of Alexa 594 as a dye-label for an additional – third – target sample works within the framework of more commonplace Cy5/Cy3 labelled target sample combinations. Standard normalisation methods are still applicable, and the resulting data can be expected to allow identification of expression differences in a biological experiment, given sufficient levels of biological replication (as is necessary for most microarray experiments. Conclusion The use of three dye-labelled target samples can be a valuable addition to the standard

  9. Exploratory Visual Analysis of Statistical Results from Microarray Experiments Comparing High and Low Grade Glioma

    Directory of Open Access Journals (Sweden)

    Jason H. Moore

    2007-01-01

    Full Text Available The biological interpretation of gene expression microarray results is a daunting challenge. For complex diseases such as cancer, wherein the body of published research is extensive, the incorporation of expert knowledge provides a useful analytical framework. We have previously developed the Exploratory Visual Analysis (EVA software for exploring data analysis results in the context of annotation information about each gene, as well as biologically relevant groups of genes. We present EVA as a fl exible combination of statistics and biological annotation that provides a straightforward visual interface for the interpretation of microarray analyses of gene expression in the most commonly occurring class of brain tumors, glioma. We demonstrate the utility of EVA for the biological interpretation of statistical results by analyzing publicly available gene expression profi les of two important glial tumors. The results of a statistical comparison between 21 malignant, high-grade glioblastoma multiforme (GBM tumors and 19 indolent, low-grade pilocytic astrocytomas were analyzed using EVA. By using EVA to examine the results of a relatively simple statistical analysis, we were able to identify tumor class-specifi c gene expression patterns having both statistical and biological signifi cance. Our interactive analysis highlighted the potential importance of genes involved in cell cycle progression, proliferation, signaling, adhesion, migration, motility, and structure, as well as candidate gene loci on a region of Chromosome 7 that has been implicated in glioma. Because EVA does not require statistical or computational expertise and has the fl exibility to accommodate any type of statistical analysis, we anticipate EVA will prove a useful addition to the repertoire of computational methods used for microarray data analysis. EVA is available at no charge to academic users and can be found at http://www.epistasis.org.

  10. Identification of Differentially Expressed Genes in Pituitary Adenomas by Integrating Analysis of Microarray Data

    Directory of Open Access Journals (Sweden)

    Peng Zhao

    2015-01-01

    Full Text Available Pituitary adenomas, monoclonal in origin, are the most common intracranial neoplasms. Altered gene expression as well as somatic mutations is detected frequently in pituitary adenomas. The purpose of this study was to detect differentially expressed genes (DEGs and biological processes during tumor formation of pituitary adenomas. We performed an integrated analysis of publicly available GEO datasets of pituitary adenomas to identify DEGs between pituitary adenomas and normal control (NC tissues. Gene function analysis including Gene Ontology (GO, Kyoto Encyclopedia of Genes and Genomes (KEGG pathway enrichment analysis, and protein-protein interaction (PPI networks analysis was conducted to interpret the biological role of those DEGs. In this study we detected 3994 DEGs (2043 upregulated and 1951 downregulated in pituitary adenoma through an integrated analysis of 5 different microarray datasets. Gene function analysis revealed that the functions of those DEGs were highly correlated with the development of pituitary adenoma. This integrated analysis of microarray data identified some genes and pathways associated with pituitary adenoma, which may help to understand the pathology underlying pituitary adenoma and contribute to the successful identification of therapeutic targets for pituitary adenoma.

  11. Development of a novel multiplex DNA microarray for Fusarium graminearum and analysis of azole fungicide responses

    Directory of Open Access Journals (Sweden)

    Deising Holger B

    2011-01-01

    Full Text Available Abstract Background The toxigenic fungal plant pathogen Fusarium graminearum compromises wheat production worldwide. Azole fungicides play a prominent role in controlling this pathogen. Sequencing of its genome stimulated the development of high-throughput technologies to study mechanisms of coping with fungicide stress and adaptation to fungicides at a previously unprecedented precision. DNA-microarrays have been used to analyze genome-wide gene expression patterns and uncovered complex transcriptional responses. A recently developed one-color multiplex array format allowed flexible, effective, and parallel examinations of eight RNA samples. Results We took advantage of the 8 × 15 k Agilent format to design, evaluate, and apply a novel microarray covering the whole F. graminearum genome to analyze transcriptional responses to azole fungicide treatment. Comparative statistical analysis of expression profiles uncovered 1058 genes that were significantly differentially expressed after azole-treatment. Quantitative RT-PCR analysis for 31 selected genes indicated high conformity to results from the microarray hybridization. Among the 596 genes with significantly increased transcript levels, analyses using GeneOntology and FunCat annotations detected the ergosterol-biosynthesis pathway genes as the category most significantly responding, confirming the mode-of-action of azole fungicides. Cyp51A, which is one of the three F. graminearum paralogs of Cyp51 encoding the target of azoles, was the most consistently differentially expressed gene of the entire study. A molecular phylogeny analyzing the relationships of the three CYP51 proteins in the context of 38 fungal genomes belonging to the Pezizomycotina indicated that CYP51C (FGSG_11024 groups with a new clade of CYP51 proteins. The transcriptional profiles for genes encoding ABC transporters and transcription factors suggested several involved in mechanisms alleviating the impact of the fungicide

  12. High-content single-cell analysis on-chip using a laser microarray scanner.

    Science.gov (United States)

    Zhou, Jing; Wu, Yu; Lee, Sang-Kwon; Fan, Rong

    2012-12-07

    High-content cellomic analysis is a powerful tool for rapid screening of cellular responses to extracellular cues and examination of intracellular signal transduction pathways at the single-cell level. In conjunction with microfluidics technology that provides unique advantages in sample processing and precise control of fluid delivery, it holds great potential to transform lab-on-a-chip systems for high-throughput cellular analysis. However, high-content imaging instruments are expensive, sophisticated, and not readily accessible. Herein, we report on a laser scanning cytometry approach that exploits a bench-top microarray scanner as an end-point reader to perform rapid and automated fluorescence imaging of cells cultured on a chip. Using high-content imaging analysis algorithms, we demonstrated multiplexed measurements of morphometric and proteomic parameters from all single cells. Our approach shows the improvement of both sensitivity and dynamic range by two orders of magnitude as compared to conventional epifluorescence microscopy. We applied this technology to high-throughput analysis of mesenchymal stem cells on an extracellular matrix protein array and characterization of heterotypic cell populations. This work demonstrates the feasibility of a laser microarray scanner for high-content cellomic analysis and opens up new opportunities to conduct informative cellular analysis and cell-based screening in the lab-on-a-chip systems.

  13. Extending the Interpretation of Gene Profiling Microarray Experiments to Pathway Analysis Through the Use of Gene Ontology Terms

    Science.gov (United States)

    Chatziioannou, Aristotelis; Moulos, Panagiotis

    Microarray technology allows the survey of gene expression at a global level by measuring mRNA abundance. However, the grand complexity characterizing a microarray experiment entails the development of computationally powerful tools apt for probing the biological problem studied. Here we propose a suite for flexible, adaptable to a wide range of possible needs of the biological end-user, data-driven interpretation of microarray experiments. The suite is implemented in MATLAB and is making use of two modules, able to perform all steps of typical microarray data analysis starting from data standardization and normalization up to statistical selection and pathway analysis utilizing Gene Ontology Term annotations for the species genomes interrogated, whereas due to its modular structure it is scalable thus enabling the incorporation or its seamless assembly with other existing tools.

  14. Screening for candidate genes related to breast cancer with cDNA microarray analysis

    Institute of Scientific and Technical Information of China (English)

    Yu-Juan Xiang; Zhi-Gang Yu; Ming-Ming Guo; Qin-Ye Fu; Zhong-Bing Ma; De-Zong Gao; Qiang Zhang; Yu-Yang Li; Liang Li; Lu Liu; Chun-Miao Ye

    2015-01-01

    Objective: The aim of this study was to reveal the exact changes during the occurrence of breast cancer to explore significant new and promising genes or factors related to this disease. Methods: We compared the gene expression profiles of breast cancer tissues with its uninvolved normal breast tissues as controls using the cDNA microarray analysis in seven breast cancer patients. Further, one representative gene, named IFI30, was quanti-tatively analyzed by real-time PCR to confirm the result of the cDNA microarray analysis. Results: A total of 427 genes were identified with significantly differential expression, 221 genes were up-regulated and 206 genes were down-regulated. And the result of cDNA microarray analysis was validated by detection of IFI30 mRNA level changes by real-time PCR. Genes for cell proliferation, cell cycle, cell division, mitosis, apoptosis, and immune response were enriched in the up-regulated genes, while genes for cell adhesion, proteolysis, and transport were significantly enriched in the down-regulated genes in breast cancer tissues compared with normal breast tissues by a gene ontology analysis. Conclusion: Our present study revealed a range of differentially expressed genes between breast cancer tissues and normal breast tissues, and provide candidate genes for further study focusing on the pathogenesis and new biomarkers for breast cancer. Copyright © 2015, Chinese Medical Association Production. Production and hosting by Elsevier B.V. on behalf of KeAi Communications Co., Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

  15. Microarray-Based Gene Expression Analysis for Veterinary Pathologists: A Review.

    Science.gov (United States)

    Raddatz, Barbara B; Spitzbarth, Ingo; Matheis, Katja A; Kalkuhl, Arno; Deschl, Ulrich; Baumgärtner, Wolfgang; Ulrich, Reiner

    2017-09-01

    High-throughput, genome-wide transcriptome analysis is now commonly used in all fields of life science research and is on the cusp of medical and veterinary diagnostic application. Transcriptomic methods such as microarrays and next-generation sequencing generate enormous amounts of data. The pathogenetic expertise acquired from understanding of general pathology provides veterinary pathologists with a profound background, which is essential in translating transcriptomic data into meaningful biological knowledge, thereby leading to a better understanding of underlying disease mechanisms. The scientific literature concerning high-throughput data-mining techniques usually addresses mathematicians or computer scientists as the target audience. In contrast, the present review provides the reader with a clear and systematic basis from a veterinary pathologist's perspective. Therefore, the aims are (1) to introduce the reader to the necessary methodological background; (2) to introduce the sequential steps commonly performed in a microarray analysis including quality control, annotation, normalization, selection of differentially expressed genes, clustering, gene ontology and pathway analysis, analysis of manually selected genes, and biomarker discovery; and (3) to provide references to publically available and user-friendly software suites. In summary, the data analysis methods presented within this review will enable veterinary pathologists to analyze high-throughput transcriptome data obtained from their own experiments, supplemental data that accompany scientific publications, or public repositories in order to obtain a more in-depth insight into underlying disease mechanisms.

  16. Microarray analysis of prostate cancer progression to reduced androgen dependence: studies in unique models contrasts early and late molecular events.

    Science.gov (United States)

    Sirotnak, F M; She, Yuhong; Khokhar, Nushmia Z; Hayes, Paula; Gerald, William; Scher, Howard I

    2004-11-01

    Three unique variants of the CWR22 human prostate cancer xenograft model (CWR22LD1, LD2, and LD3) with a decrease in dependence on androgens were selected under noncastrate conditions, i.e., by outgrowth after transplantation into male NCR (AT) nu mice without testosterone supplementation. These variants were unable to grow in castrated male mice. For comparison, a second set of variants with even less dependence on androgens (castrate-resistant) were derived following outgrowth from CWR22 (CWR22Rv1 and RC) or CWRLD1 (CWR22RS) after transplantion in castrated male mice. The androgen receptor (AR) gene in the CWR22LD variants was transcriptionally active and was neither mutated nor significantly overexpressed compared to CWR22. Oligonucleotide microarray analysis showed distinctly different profiles of dysregulated gene expression among the CWR22LD variants. Groups of only 26-41 genes were dysregulated greater than threefold with a different proportion of up versus downregulated genes in each variant. Only one of the castrate-resistant variants (CWR22Rv1) had a highly overexpressed AR gene but AR in this variant and the two other castrate-resistant variants, CWR22 RS and RC, was not mutated beyond that seen in CWR22. In contrast to the CWR22LD variants, a total of 342, 295, and 222 genes were dysregulated at least threefold in CWR22Rv1, CWR22RS, and CWR22RC, respectively, differing as well in the proportion of up versus downregulated genes. Many of the genes dysregulated in CWR22LD1, LD2, and LD3 were further dysregulated in CWR22Rv1, RC, or RS. The most downregulated gene was microseminoprotein beta (MSPB). Along with cyclin D1, the most upregulated gene by an order of magnitude compared to other upregulated genes was hepatocyte growth factor (HGF) (scatter factor). These results suggest that the onset in the loss of androgen dependence in CWR22 proceeds through multiple pathways and does not require any direct change in the status of AR. However, upregulation of

  17. Identification of differentially expressed genes in mouse kidney after irradiation using microarray analysis.

    Science.gov (United States)

    Kruse, Jacqueline J C M; te Poele, Johannes A M; Velds, Arno; Kerkhoven, Ron M; Boersma, Liesbeth J; Russell, Nicola S; Stewart, Fiona A

    2004-01-01

    Irradiation of the kidney induces dose-dependent, progressive renal functional impairment, which is partly mediated by vascular damage. The molecular mechanisms underlying the development of radiation-induced nephropathy are unclear. Given the complexity of radiation-induced responses, microarrays may offer new opportunities to identify a wider range of genes involved in the development of radiation injury. The aim of the present study was to determine whether microarrays are a useful tool for identifying time-related changes in gene expression and potential mechanisms of radiation-induced nephropathy. Microarray experiments were performed using amplified RNA from irradiated mouse kidneys (1 x 16 Gy) and from sham-irradiated control tissue at different intervals (1-30 weeks) after irradiation. After normalization procedures (using information from straight-color, color-reverse and self-self experiments), the differentially expressed genes were identified. Control and repeat experiments were done to confirm that the observations were not artifacts of the array procedure (RNA amplification, probe synthesis, hybridizations and data analysis). To provide independent confirmation of microarray data, semi-quantitative PCR was performed on a selection of genes. At 1 week after irradiation (before the onset of vascular and functional damage), 16 genes were significantly up-regulated and 9 genes were down-regulated. During the period of developing nephropathy (10 to 20 weeks), 31 and 42 genes were up-regulated and 9 and 4 genes were down-regulated. At the later time of 30 weeks, the vast majority of differentially expressed genes (191 out of 203) were down-regulated. Potential genes of interest included TSA-1 (also known as Ly6e) and Jagged 1 (Jag1). Increased expression of TSA-1, a member of the Ly-6 family, has previously been reported in response to proteinuria. Jagged 1, a ligand for the Notch receptor, is known to play a role in angiogenesis, and is particularly

  18. Analysis of DNA strand-specific differential expression with high density tiling microarrays

    Directory of Open Access Journals (Sweden)

    Antequera Francisco

    2010-03-01

    Full Text Available Abstract Background DNA microarray technology allows the analysis of genome structure and dynamics at genome-wide scale. Expression microarrays (EMA contain probes for annotated open reading frames (ORF and are widely used for the analysis of differential gene expression. By contrast, tiling microarrays (TMA have a much higher probe density and provide unbiased genome-wide coverage. The purpose of this study was to develop a protocol to exploit the high resolution of TMAs for quantitative measurement of DNA strand-specific differential expression of annotated and non-annotated transcripts. Results We extensively filtered probes present in Affymetrix Genechip Yeast Genome 2.0 expression and GeneChip S. pombe 1.0FR tiling microarrays to generate custom Chip Description Files (CDF in order to compare their efficiency. We experimentally tested the potential of our approach by measuring the differential expression of 4904 genes in the yeast Schizosaccharomyces pombe growing under conditions of oxidative stress. The results showed a Pearson correlation coefficient of 0.943 between both platforms, indicating that TMAs are as reliable as EMAs for quantitative expression analysis. A significant advantage of TMAs over EMAs is the possibility of detecting non-annotated transcripts generated only under specific physiological conditions. To take full advantage of this property, we have used a target-labelling protocol that preserves the original polarity of the transcripts and, therefore, allows the strand-specific differential expression of non-annotated transcripts to be determined. By using a segmentation algorithm prior to generating the corresponding custom CDFs, we identified and quantitatively measured the expression of 510 transcripts longer than 180 nucleotides and not overlapping previously annotated ORFs that were differentially expressed at least 2-fold under oxidative stress. Conclusions We show that the information derived from TMA

  19. Analysis of microarray leukemia data using an efficient MapReduce-based K-nearest-neighbor classifier.

    Science.gov (United States)

    Kumar, Mukesh; Rath, Nitish Kumar; Rath, Santanu Kumar

    2016-04-01

    Microarray-based gene expression profiling has emerged as an efficient technique for classification, prognosis, diagnosis, and treatment of cancer. Frequent changes in the behavior of this disease generates an enormous volume of data. Microarray data satisfies both the veracity and velocity properties of big data, as it keeps changing with time. Therefore, the analysis of microarray datasets in a small amount of time is essential. They often contain a large amount of expression, but only a fraction of it comprises genes that are significantly expressed. The precise identification of genes of interest that are responsible for causing cancer are imperative in microarray data analysis. Most existing schemes employ a two-phase process such as feature selection/extraction followed by classification. In this paper, various statistical methods (tests) based on MapReduce are proposed for selecting relevant features. After feature selection, a MapReduce-based K-nearest neighbor (mrKNN) classifier is also employed to classify microarray data. These algorithms are successfully implemented in a Hadoop framework. A comparative analysis is done on these MapReduce-based models using microarray datasets of various dimensions. From the obtained results, it is observed that these models consume much less execution time than conventional models in processing big data. Copyright © 2016 Elsevier Inc. All rights reserved.

  20. From RNA isolation to microarray analysis: Comparison of methods in FFPE tissues.

    Science.gov (United States)

    Belder, Nevin; Coskun, Öznur; Doganay Erdogan, Beyza; Ilk, Ozlem; Savas, Berna; Ensari, Arzu; Özdağ, Hilal

    2016-08-01

    Genome-wide gene expression profiling analysis of FFPE tissue samples is indispensable for cancer research and provides the opportunity to evaluate links between molecular and clinical information, however, working with FFPE samples is challenging due to extensive cross-linking, fragmentation and limited quantities of nucleic acid. Thus, processing of FFPE tissue samples from RNA extraction to microarray analysis still needs optimization. In this study, a modified deparaffinization protocol was conducted prior to RNA isolation. Trizol, Qiagen RNeasy FFPE and Arcturus PicoPure RNA Isolation kits were used in parallel to compare their impact on RNA isolation. We also evaluated the effect of two different cRNA/cDNA preparation and labeling protocols with two different array platforms (Affymetrix Human Genome U133 Plus 2.0 and U133_X3P) on the percentage of present calls. Our optimization study shows that the Qiagen RNeasy FFPE kit with modified deparaffinization step gives better results (RNA quantity and quality) than the other two isolation kits. The Ribo-SPIA protocol gave a significantly higher percentage of present calls than the 3' IVT cDNA amplification and labeling system. However, no significant differences were found between the two array platforms. Our study paves the way for future high-throughput transcriptional analysis by optimizing FFPE tissue sample processing from RNA isolation to microarray analysis. Copyright © 2016 Elsevier GmbH. All rights reserved.

  1. Histological and microarray analysis of the direct effect of water shortage alone or combined with heat on early grain development in wheat (Triticum aestivum).

    Science.gov (United States)

    Szucs, Attila; Jäger, Katalin; Jurca, Manuela E; Fábián, Attila; Bottka, Sándor; Zvara, Agnes; Barnabás, Beáta; Fehér, Attila

    2010-10-01

    Based on the in silico analysis of the representation of expressed sequence tags (ESTs) in wheat grain-related cDNA libraries, a specific 15k oligonucleotide microarray has been developed in order to monitor environmental stress-dependent gene expression changes in the wheat caryopses. Using this array, the effect of water withdrawal, with and without additional heat stress, has been investigated during the first five days of kernel development on two wheat cultivars differing in their drought sensitivity. Water shortage affected (more than twofold change) the expression of only 0.5% of the investigated genes. A parallel heat treatment increased the ratio of responding genes to 5-7% because of the temperature stress and/or the increased water deficit because of enhanced evaporation. It could be established that the two cultivars, differing in their long-term adaptation capabilities to drought, responded to the short and direct stress treatments on the same way. In response to the combined drought and heat treatment, the coordinately altered expression of genes coding for storage proteins, enzymes involved in sugar/starch metabolism, histone proteins, heat shock proteins, proteases, tonoplast aquaporins as well as several transcription factors has been observed. These gene expression changes were in agreement with histological data that demonstrated the accelerated development of the embryo as well as the endosperm. Copyright © Physiologia Plantarum 2010.

  2. Tumour class prediction and discovery by microarray-based DNA methylation analysis

    OpenAIRE

    Adorján, Péter; Distler, Jürgen; Lipscher, Evelyne; Model, Fabian; Müller, Jürgen; Pelet, Cécile; Braun, Aron; Florl, Andrea R.; Gütig, David; Grabs, Gabi; Howe, André; Kursar, Mischo; Lesche, Ralf; Leu, Erik; Lewin, André

    2002-01-01

    Aberrant DNA methylation of CpG sites is among the earliest and most frequent alterations in cancer. Several studies suggest that aberrant methylation occurs in a tumour type-specific manner. However, large-scale analysis of candidate genes has so far been hampered by the lack of high throughput assays for methylation detection. We have developed the first microarray-based technique which allows genome-wide assessment of selected CpG dinucleotides as well as quantification of methylation at e...

  3. Microarray analysis of gene expression profiles in the bovine mammary gland during lactation

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Mammary glands undergo functional and metabolic changes during virgin,lactation and dry periods.A total of 122 genes were identified as differentially expressed,including 79 up-regulated and 43 down-regulated genes during lactation compared with virgin and dry periods.Gene ontology analysis showed the functional classification of the up-regulated genes in lactation,including transport,biosynthetic process,signal transduction,catalytic activity,immune system process,cell death,and positive regulation of the developmental process.Microarray data clarified molecular events in bovine mammary gland lactation.

  4. Introduction to microarray technology.

    Science.gov (United States)

    Dufva, Martin

    2009-01-01

    DNA microarrays can be used for large number of application where high-throughput is needed. The ability to probe a sample for hundred to million different molecules at once has made DNA microarray one of the fastest growing techniques since its introduction about 15 years ago. Microarray technology can be used for large scale genotyping, gene expression profiling, comparative genomic hybridization and resequencing among other applications. Microarray technology is a complex mixture of numerous technology and research fields such as mechanics, microfabrication, chemistry, DNA behaviour, microfluidics, enzymology, optics and bioinformatics. This chapter will give an introduction to each five basic steps in microarray technology that includes fabrication, target preparation, hybridization, detection and data analysis. Basic concepts and nomenclature used in the field of microarray technology and their relationships will also be explained.

  5. Differentiating pancreatic lesions by Microarray and QPCR analysis of pancreatic juice RNAs

    NARCIS (Netherlands)

    C.D. Rogers; N. Fukushima; N. Sato; C. Shi; N. Prasad; S.R. Hustinx; H. Matsubayashi; M. Canto; J.R. Eshleman; R.H. Hruban; M. Goggins

    2006-01-01

    Background: The gene expression profile of pancreatic cancer is significantly different from that of normal pancreas. Differences in gene expression are detectable using microarrays, but microarrays have traditionally been applied to pancreatic cancer tissue obtained from surgical resection. We hypo

  6. Carbohydrate microarrays

    DEFF Research Database (Denmark)

    Park, Sungjin; Gildersleeve, Jeffrey C; Blixt, Klas Ola;

    2012-01-01

    In the last decade, carbohydrate microarrays have been core technologies for analyzing carbohydrate-mediated recognition events in a high-throughput fashion. A number of methods have been exploited for immobilizing glycans on the solid surface in a microarray format. This microarray-based technol...

  7. Use of culture, PCR analysis, and DNA microarrays for detection of Campylobacter jejuni and Campylobacter coli from chicken feces

    DEFF Research Database (Denmark)

    Keramas, Georgios; Bang, Dang Duong; Lund, Marianne

    2004-01-01

    A DNA microarray for detection of Campylobacter spp. was recently developed and applied to detect Campylobacter spp. directly from chicken feces. Sixty-five pooled chicken cloacal swab samples from 650 individual broiler chickens were included in the study. The results of Campylobacter sp....... detection obtained with DNA microarrays were compared to those obtained by conventional culture and gel electrophoresis. By conventional culture, 60% of the samples were positive for either Campylobacter jejuni or Campylobacter coli. By PCR and capillary electrophoresis, 95% of the samples were positive...... for Campylobacter spp., whereas with DNA microarrays all samples were positive for Campylobacter spp. By application of DNA microarray analysis, the isolates in 4 samples (6%) could not be identified to the species level, whereas by PCR-capillary electrophoresis, the isolates in 12 samples (19%) remained...

  8. Microarray analysis of androgen-regulated gene expression in testis: the use of the androgen-binding protein (ABP-transgenic mouse as a model

    Directory of Open Access Journals (Sweden)

    Grossman Gail

    2005-12-01

    Full Text Available Abstract Background Spermatogenesis is an androgen-dependent process, yet the molecular mechanisms of androgens' actions in testis are poorly understood. Transgenic mice overexpressing rat androgen-binding protein (ABP in their testes have reduced levels of intratesticular androgens and, as a result, show a progressive impairment of spermatogenesis. We used this model to characterize changes in global gene expression in testis in response to reduced bioavailability of androgens. Methods Total RNA was extracted from testes of 30-day old transgenic and wild-type control mice, converted to cRNA, labeled with biotin, and hybridized to oligonucleotide microarrays. Microarray results were confirmed by real-time reverse transcription polymerase chain reaction. Results Three-hundred-eighty-one genes (3.05% of all transcripts represented on the chips were up-regulated and 198 genes (1.59% were down-regulated by at least a factor of 2 in the androgen-deficient animals compared to controls. Genes encoding membrane proteins, intracellular signaling molecules, enzymes, proteins participating in the immune response, and those involved in cytoskeleton organization were significantly overrepresented in the up-regulated group. Among the down-regulated transcripts, those coding for extracellular proteins were overrepresented most dramatically, followed by those related to proteolysis, cell adhesion, immune response, and growth factor, cytokine, and ion channel activities. Transcripts with the greatest potential impact on cellular activities included several transcription factors, intracellular signal transducers, secreted signaling molecules and enzymes, and various cell surface molecules. Major nodes in the up-regulated network were IL-6, AGT, MYC, and A2M, those in the down-regulated network were IL-2, -4, and -10, MAPK8, SOCS1, and CREB1. Conclusion Microarray analysis followed by gene ontology profiling and connectivity analysis identified several functional

  9. DNA Microarray Technique

    Directory of Open Access Journals (Sweden)

    Thakare SP

    2012-11-01

    Full Text Available DNA Microarray is the emerging technique in Biotechnology. The many varieties of DNA microarray or DNA chip devices and systems are described along with their methods for fabrication and their use. It also includes screening and diagnostic applications. The DNA microarray hybridization applications include the important areas of gene expression analysis and genotyping for point mutations, single nucleotide polymorphisms (SNPs, and short tandem repeats (STRs. In addition to the many molecular biological and genomic research uses, this review covers applications of microarray devices and systems for pharmacogenomic research and drug discovery, infectious and genetic disease and cancer diagnostics, and forensic and genetic identification purposes.

  10. Utilization of a labeled tracking oligonucleotide for visualization and quality control of spotted 70-mer arrays

    Directory of Open Access Journals (Sweden)

    Khan Shehnaz

    2004-02-01

    Full Text Available Abstract Background Spotted 70-mer oligonucleotide arrays offer potentially greater specificity and an alternative to expensive cDNA library maintenance and amplification. Since microarray fabrication is a considerable source of data variance, we previously directly tagged cDNA probes with a third fluorophore for prehybridization quality control. Fluorescently modifying oligonucleotide sets is cost prohibitive, therefore, a co-spotted Staphylococcus aureus-specific fluorescein-labeled "tracking" oligonucleotide is described to monitor fabrication variables of a Mycobacterium tuberculosis oligonucleotide microarray. Results Significantly (p M. tuberculosis H37Rv and M. tuberculosis mprA. Linearity between the mean log Cy3/Cy5 ratios of genes differentially expressed from arrays either possessing or lacking the tracking oligonucleotide was observed (R2 = 0.90, p Conclusions This novel approach enables prehybridization array visualization for spotted oligonucleotide arrays and sets the stage for more sophisticated slide qualification and data filtering applications.

  11. Microarray data integration for genome-wide analysis of human tissue-selective gene expression

    OpenAIRE

    Wang, Liangjiang; Srivastava, Anand K; Schwartz, Charles E

    2010-01-01

    Background Microarray gene expression data are accumulating in public databases. The expression profiles contain valuable information for understanding human gene expression patterns. However, the effective use of public microarray data requires integrating the expression profiles from heterogeneous sources. Results In this study, we have compiled a compendium of microarray expression profiles of various human tissue samples. The microarray raw data generated in different research laboratorie...

  12. Comprehensive Analysis of Prokaryotes in Environmental Water Using DNA Microarray Analysis and Whole Genome Amplification

    Directory of Open Access Journals (Sweden)

    Norihisa Ishii

    2013-10-01

    Full Text Available The microflora in environmental water consists of a high density and diversity of bacterial species that form the foundation of the water ecosystem. Because the majority of these species cannot be cultured in vitro, a different approach is needed to identify prokaryotes in environmental water. A novel DNA microarray was developed as a simplified detection protocol. Multiple DNA probes were designed against each of the 97,927 sequences in the DNA Data Bank of Japan and mounted on a glass chip in duplicate. Evaluation of the microarray was performed using the DNA extracted from one liter of environmental water samples collected from seven sites in Japan. The extracted DNA was uniformly amplified using whole genome amplification (WGA, labeled with Cy3-conjugated 16S rRNA specific primers and hybridized to the microarray. The microarray successfully identified soil bacteria and environment-specific bacteria clusters. The DNA microarray described herein can be a useful tool in evaluating the diversity of prokaryotes and assessing environmental changes such as global warming.

  13. Investigating the effect of paralogs on microarray gene-set analysis

    LENUS (Irish Health Repository)

    Faure, Andre J

    2011-01-24

    Abstract Background In order to interpret the results obtained from a microarray experiment, researchers often shift focus from analysis of individual differentially expressed genes to analyses of sets of genes. These gene-set analysis (GSA) methods use previously accumulated biological knowledge to group genes into sets and then aim to rank these gene sets in a way that reflects their relative importance in the experimental situation in question. We suspect that the presence of paralogs affects the ability of GSA methods to accurately identify the most important sets of genes for subsequent research. Results We show that paralogs, which typically have high sequence identity and similar molecular functions, also exhibit high correlation in their expression patterns. We investigate this correlation as a potential confounding factor common to current GSA methods using Indygene http:\\/\\/www.cbio.uct.ac.za\\/indygene, a web tool that reduces a supplied list of genes so that it includes no pairwise paralogy relationships above a specified sequence similarity threshold. We use the tool to reanalyse previously published microarray datasets and determine the potential utility of accounting for the presence of paralogs. Conclusions The Indygene tool efficiently removes paralogy relationships from a given dataset and we found that such a reduction, performed prior to GSA, has the ability to generate significantly different results that often represent novel and plausible biological hypotheses. This was demonstrated for three different GSA approaches when applied to the reanalysis of previously published microarray datasets and suggests that the redundancy and non-independence of paralogs is an important consideration when dealing with GSA methodologies.

  14. Assessing the Detection Capacity of Microarrays as Bio/Nanosensing Platforms

    Directory of Open Access Journals (Sweden)

    Ju Seok Lee

    2013-01-01

    Full Text Available Microarray is one of the most powerful detection systems with multiplexing and high throughput capability. It has significant potential as a versatile biosensing platform for environmental monitoring, pathogen detection, medical therapeutics, and drug screening to name a few. To date, however, microarray applications are still limited to preliminary screening of genome-scale transcription profiling or gene ontology analysis. Expanding the utility of microarrays as a detection tool for various biological and biomedical applications requires information about performance such as the limits of detection and quantification, which are considered as an essential information to decide the detection sensitivity of sensing devices. Here we present a calibration design that integrates detection limit theory and linear dynamic range to obtain a performance index of microarray detection platform using oligonucleotide arrays as a model system. Two different types of limits of detection and quantification are proposed by the prediction or tolerance interval for two common cyanine fluorescence dyes, Cy3 and Cy5. Besides oligonucleotide, the proposed method can be generalized to other microarray formats with various biomolecules such as complementary DNA, protein, peptide, carbohydrate, tissue, or other small biomolecules. Also, it can be easily applied to other fluorescence dyes for further dye chemistry improvement.

  15. Application of DNA fingerprinting with digoxigenated oligonucleotide probe (CAC)5 to analysis of the genetic variation within Taenia taeniaeformis.

    Science.gov (United States)

    Okamoto, M; Ueda, H; Hayashi, M; Oku, Y; Kurosawa, T; Kamiya, M

    1995-04-01

    DNA from T. taeniaeformis digested with the restriction endonuclease was hybridized with digoxigenated oligonucleotide probe (CAC)5. Metacestode and adult showed same clear multibanding patterns, which were characteristic of multilocus DNA fingerprinting. The fingerprinting patterns were quite different from those of the rodent hosts. Genetic variations in 4 laboratory-reared isolates of T. taeniaeformis, including 3 isolates which have been reported to be indistinguishable by infectivity, morphology and protein composition of metacestode, were investigated using this technique. Each of the 4 isolates exhibited isolate-specific fingerprinting patterns and were easily distinguished from one another, thus it was considered that (CAC)5 was a highly resolvable and informative probe for cestodes. However, it was also indicated that (CAC)5 was so sensitive that applying fingerprinting with (CAC)5 to taxonomical or phylogenetic analysis was limited where habitat of the host was restricted to the small area. In comparison to fingerprinting with 32P-labeled (CAC)5, fingerprinting with digoxigenated (CAC)5 represented more and sharper bands. It was considered that a digoxigenated probe was more useful for genetic analysis of cestodes.

  16. Brain response to traumatic brain injury in wild-type and interleukin-6 knockout mice: a microarray analysis.

    Science.gov (United States)

    Poulsen, Christian Bjørn; Penkowa, Milena; Borup, Rehannah; Nielsen, Finn Cilius; Cáceres, Mario; Quintana, Albert; Molinero, Amalia; Carrasco, Javier; Giralt, Mercedes; Hidalgo, Juan

    2005-01-01

    Traumatic injury to the brain is one of the leading causes of injury-related death or disability. Brain response to injury is orchestrated by cytokines, such as interleukin (IL)-6, but the full repertoire of responses involved is not well known. We here report the results obtained with microarrays in wild-type and IL-6 knockout mice subjected to a cryolesion of the somatosensorial cortex and killed at 0, 1, 4, 8 and 16 days post-lesion. Overall gene expression was analyzed by using Affymetrix genechips/oligonucleotide arrays with approximately 12,400 probe sets corresponding to approximately 10,000 different murine genes (MG_U74Av2). A robust, conventional statistical method (two-way anova) was employed to select the genes significantly affected. An orderly pattern of gene responses was clearly detected, with genes being up- or down-regulated at specific timings consistent with the processes involved in the initial tissue injury and later regeneration of the parenchyma. IL-6 deficiency showed a dramatic effect in the expression of many genes, especially in the 1 day post-lesion timing, which presumably underlies the poor capacity of IL-6 knockout mice to cope with brain damage. The results highlight the importance of IL-6 controlling the response of the brain to injury as well as the suitability of microarrays for identifying specific targets worthy of further study.

  17. Microarray analysis of differentially expressed genes regulating lipid metabolism during melanoma progression.

    Science.gov (United States)

    Sumantran, Venil N; Mishra, Pratik; Sudhakar, N

    2015-04-01

    A new hallmark of cancer involves acquisition of a lipogenic phenotype which promotes tumorigenesis. Little is known about lipid metabolism in melanomas. Therefore, we used BRB (Biometrics Research Branch) class comparison tool with multivariate analysis to identify differentially expressed genes in human cutaneous melanomas, compared with benign nevi and normal skin derived from the microarray dataset (GDS1375). The methods were validated by identifying known melanoma biomarkers (CITED1, FGFR2, PTPRF, LICAM, SPP1 and PHACTR1) in our results. Eighteen genes regulating metabolism of fatty acids, lipid second messengers and gangliosides were 2-9 fold upregulated in melanomas of GDS-1375. Out of the 18 genes, 13 were confirmed by KEGG pathway analysis and 10 were also significantly upregulated in human melanoma cell lines of NCI-60 Cell Miner database. Results showed that melanomas upregulated PPARGC1A transcription factor and its target genes regulating synthesis of fatty acids (SCD) and complex lipids (FABP3 and ACSL3). Melanoma also upregulated genes which prevented lipotoxicity (CPT2 and ACOT7) and regulated lipid second messengers, such as phosphatidic acid (AGPAT-4, PLD3) and inositol triphosphate (ITPKB, ITPR3). Genes for synthesis of pro-tumorigenic GM3 and GD3 gangliosides (UGCG, HEXA, ST3GAL5 and ST8SIA1) were also upregulated in melanoma. Overall, the microarray analysis of GDS-1375 dataset indicated that melanomas can become lipogenic by upregulating genes, leading to increase in fatty acid metabolism, metabolism of specific lipid second messengers, and ganglioside synthesis.

  18. Synthesis of 3'-, or 5'-, or internal methacrylamido-modified oligonucleotides

    Science.gov (United States)

    Golova, Julia B.; Chernov, Boris K.

    2010-04-27

    New modifiers were synthesized for incorporation of a methacrylic function in 3'-, 5'- and internal positions of oligonucleotides during solid phase synthesis. A modifier was used for synthesis of 5'-methacrylated oligonucleotides for preparation of microarrays by a co-polymerization method.

  19. Direct calibration of PICKY-designed microarrays

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    Ronald Pamela C

    2009-10-01

    Full Text Available Abstract Background Few microarrays have been quantitatively calibrated to identify optimal hybridization conditions because it is difficult to precisely determine the hybridization characteristics of a microarray using biologically variable cDNA samples. Results Using synthesized samples with known concentrations of specific oligonucleotides, a series of microarray experiments was conducted to evaluate microarrays designed by PICKY, an oligo microarray design software tool, and to test a direct microarray calibration method based on the PICKY-predicted, thermodynamically closest nontarget information. The complete set of microarray experiment results is archived in the GEO database with series accession number GSE14717. Additional data files and Perl programs described in this paper can be obtained from the website http://www.complex.iastate.edu under the PICKY Download area. Conclusion PICKY-designed microarray probes are highly reliable over a wide range of hybridization temperatures and sample concentrations. The microarray calibration method reported here allows researchers to experimentally optimize their hybridization conditions. Because this method is straightforward, uses existing microarrays and relatively inexpensive synthesized samples, it can be used by any lab that uses microarrays designed by PICKY. In addition, other microarrays can be reanalyzed by PICKY to obtain the thermodynamically closest nontarget information for calibration.

  20. k-Nearest neighbor models for microarray gene expression analysis and clinical outcome prediction.

    Science.gov (United States)

    Parry, R M; Jones, W; Stokes, T H; Phan, J H; Moffitt, R A; Fang, H; Shi, L; Oberthuer, A; Fischer, M; Tong, W; Wang, M D

    2010-08-01

    In the clinical application of genomic data analysis and modeling, a number of factors contribute to the performance of disease classification and clinical outcome prediction. This study focuses on the k-nearest neighbor (KNN) modeling strategy and its clinical use. Although KNN is simple and clinically appealing, large performance variations were found among experienced data analysis teams in the MicroArray Quality Control Phase II (MAQC-II) project. For clinical end points and controls from breast cancer, neuroblastoma and multiple myeloma, we systematically generated 463,320 KNN models by varying feature ranking method, number of features, distance metric, number of neighbors, vote weighting and decision threshold. We identified factors that contribute to the MAQC-II project performance variation, and validated a KNN data analysis protocol using a newly generated clinical data set with 478 neuroblastoma patients. We interpreted the biological and practical significance of the derived KNN models, and compared their performance with existing clinical factors.

  1. Statistical methodology for the analysis of dye-switch microarray experiments

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    Mansouri-Attia Nadera

    2008-02-01

    Full Text Available Abstract Background In individually dye-balanced microarray designs, each biological sample is hybridized on two different slides, once with Cy3 and once with Cy5. While this strategy ensures an automatic correction of the gene-specific labelling bias, it also induces dependencies between log-ratio measurements that must be taken into account in the statistical analysis. Results We present two original statistical procedures for the statistical analysis of individually balanced designs. These procedures are compared with the usual ML and REML mixed model procedures proposed in most statistical toolboxes, on both simulated and real data. Conclusion The UP procedure we propose as an alternative to usual mixed model procedures is more efficient and significantly faster to compute. This result provides some useful guidelines for the analysis of complex designs.

  2. Microarray based gene expression analysis of murine brown and subcutaneous adipose tissue: significance with human.

    Science.gov (United States)

    Baboota, Ritesh K; Sarma, Siddhartha M; Boparai, Ravneet K; Kondepudi, Kanthi Kiran; Mantri, Shrikant; Bishnoi, Mahendra

    2015-01-01

    Two types of adipose tissues, white (WAT) and brown (BAT) are found in mammals. Increasingly novel strategies are being proposed for the treatment of obesity and its associated complications by altering amount and/or activity of BAT using mouse models. The present study was designed to: (a) investigate the differential expression of genes in LACA mice subcutaneous WAT (sWAT) and BAT using mouse DNA microarray, (b) to compare mouse differential gene expression with previously published human data; to understand any inter- species differences between the two and (c) to make a comparative assessment with C57BL/6 mouse strain. In mouse microarray studies, over 7003, 1176 and 401 probe sets showed more than two-fold, five-fold and ten-fold change respectively in differential expression between murine BAT and WAT. Microarray data was validated using quantitative RT-PCR of key genes showing high expression in BAT (Fabp3, Ucp1, Slc27a1) and sWAT (Ms4a1, H2-Ob, Bank1) or showing relatively low expression in BAT (Pgk1, Cox6b1) and sWAT (Slc20a1, Cd74). Multi-omic pathway analysis was employed to understand possible links between the organisms. When murine two fold data was compared with published human BAT and sWAT data, 90 genes showed parallel differential expression in both mouse and human. Out of these 90 genes, 46 showed same pattern of differential expression whereas the pattern was opposite for the remaining 44 genes. Based on our microarray results and its comparison with human data, we were able to identify genes (targets) (a) which can be studied in mouse model systems to extrapolate results to human (b) where caution should be exercised before extrapolation of murine data to human. Our study provides evidence for inter species (mouse vs human) differences in differential gene expression between sWAT and BAT. Critical understanding of this data may help in development of novel ways to engineer one form of adipose tissue to another using murine model with focus on

  3. Microarray comparative genomic hybridisation analysis incorporating genomic organisation, and application to enterobacterial plant pathogens.

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    Leighton Pritchard

    2009-08-01

    Full Text Available Microarray comparative genomic hybridisation (aCGH provides an estimate of the relative abundance of genomic DNA (gDNA taken from comparator and reference organisms by hybridisation to a microarray containing probes that represent sequences from the reference organism. The experimental method is used in a number of biological applications, including the detection of human chromosomal aberrations, and in comparative genomic analysis of bacterial strains, but optimisation of the analysis is desirable in each problem domain.We present a method for analysis of bacterial aCGH data that encodes spatial information from the reference genome in a hidden Markov model. This technique is the first such method to be validated in comparisons of sequenced bacteria that diverge at the strain and at the genus level: Pectobacterium atrosepticum SCRI1043 (Pba1043 and Dickeya dadantii 3937 (Dda3937; and Lactococcus lactis subsp. lactis IL1403 and L. lactis subsp. cremoris MG1363. In all cases our method is found to outperform common and widely used aCGH analysis methods that do not incorporate spatial information. This analysis is applied to comparisons between commercially important plant pathogenic soft-rotting enterobacteria (SRE Pba1043, P. atrosepticum SCRI1039, P. carotovorum 193, and Dda3937.Our analysis indicates that it should not be assumed that hybridisation strength is a reliable proxy for sequence identity in aCGH experiments, and robustly extends the applicability of aCGH to bacterial comparisons at the genus level. Our results in the SRE further provide evidence for a dynamic, plastic 'accessory' genome, revealing major genomic islands encoding gene products that provide insight into, and may play a direct role in determining, variation amongst the SRE in terms of their environmental survival, host range and aetiology, such as phytotoxin synthesis, multidrug resistance, and nitrogen fixation.

  4. SegMine workflows for semantic microarray data analysis in Orange4WS

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    Kulovesi Kimmo

    2011-10-01

    Full Text Available Abstract Background In experimental data analysis, bioinformatics researchers increasingly rely on tools that enable the composition and reuse of scientific workflows. The utility of current bioinformatics workflow environments can be significantly increased by offering advanced data mining services as workflow components. Such services can support, for instance, knowledge discovery from diverse distributed data and knowledge sources (such as GO, KEGG, PubMed, and experimental databases. Specifically, cutting-edge data analysis approaches, such as semantic data mining, link discovery, and visualization, have not yet been made available to researchers investigating complex biological datasets. Results We present a new methodology, SegMine, for semantic analysis of microarray data by exploiting general biological knowledge, and a new workflow environment, Orange4WS, with integrated support for web services in which the SegMine methodology is implemented. The SegMine methodology consists of two main steps. First, the semantic subgroup discovery algorithm is used to construct elaborate rules that identify enriched gene sets. Then, a link discovery service is used for the creation and visualization of new biological hypotheses. The utility of SegMine, implemented as a set of workflows in Orange4WS, is demonstrated in two microarray data analysis applications. In the analysis of senescence in human stem cells, the use of SegMine resulted in three novel research hypotheses that could improve understanding of the underlying mechanisms of senescence and identification of candidate marker genes. Conclusions Compared to the available data analysis systems, SegMine offers improved hypothesis generation and data interpretation for bioinformatics in an easy-to-use integrated workflow environment.

  5. SegMine workflows for semantic microarray data analysis in Orange4WS.

    Science.gov (United States)

    Podpečan, Vid; Lavrač, Nada; Mozetič, Igor; Novak, Petra Kralj; Trajkovski, Igor; Langohr, Laura; Kulovesi, Kimmo; Toivonen, Hannu; Petek, Marko; Motaln, Helena; Gruden, Kristina

    2011-10-26

    In experimental data analysis, bioinformatics researchers increasingly rely on tools that enable the composition and reuse of scientific workflows. The utility of current bioinformatics workflow environments can be significantly increased by offering advanced data mining services as workflow components. Such services can support, for instance, knowledge discovery from diverse distributed data and knowledge sources (such as GO, KEGG, PubMed, and experimental databases). Specifically, cutting-edge data analysis approaches, such as semantic data mining, link discovery, and visualization, have not yet been made available to researchers investigating complex biological datasets. We present a new methodology, SegMine, for semantic analysis of microarray data by exploiting general biological knowledge, and a new workflow environment, Orange4WS, with integrated support for web services in which the SegMine methodology is implemented. The SegMine methodology consists of two main steps. First, the semantic subgroup discovery algorithm is used to construct elaborate rules that identify enriched gene sets. Then, a link discovery service is used for the creation and visualization of new biological hypotheses. The utility of SegMine, implemented as a set of workflows in Orange4WS, is demonstrated in two microarray data analysis applications. In the analysis of senescence in human stem cells, the use of SegMine resulted in three novel research hypotheses that could improve understanding of the underlying mechanisms of senescence and identification of candidate marker genes. Compared to the available data analysis systems, SegMine offers improved hypothesis generation and data interpretation for bioinformatics in an easy-to-use integrated workflow environment.

  6. A High Phosphorus Diet Affects Lipid Metabolism in Rat Liver: A DNA Microarray Analysis.

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    Sunwoo Chun

    Full Text Available A high phosphorus (HP diet causes disorders of renal function, bone metabolism, and vascular function. We previously demonstrated that DNA microarray analysis is an appropriate method to comprehensively evaluate the effects of a HP diet on kidney dysfunction such as calcification, fibrillization, and inflammation. We reported that type IIb sodium-dependent phosphate transporter is significantly up-regulated in this context. In the present study, we performed DNA microarray analysis to investigate the effects of a HP diet on the liver, which plays a pivotal role in energy metabolism. DNA microarray analysis was performed with total RNA isolated from the livers of rats fed a control diet (containing 0.3% phosphorus or a HP diet (containing 1.2% phosphorus. Gene Ontology analysis of differentially expressed genes (DEGs revealed that the HP diet induced down-regulation of genes involved in hepatic amino acid catabolism and lipogenesis, while genes related to fatty acid β-oxidation process were up-regulated. Although genes related to fatty acid biosynthesis were down-regulated in HP diet-fed rats, genes important for the elongation and desaturation reactions of omega-3 and -6 fatty acids were up-regulated. Concentrations of hepatic arachidonic acid and eicosapentaenoic acid were increased in HP diet-fed rats. These essential fatty acids activate peroxisome proliferator-activated receptor alpha (PPARα, a transcription factor for fatty acid β-oxidation. Evaluation of the upstream regulators of DEGs using Ingenuity Pathway Analysis indicated that PPARα was activated in the livers of HP diet-fed rats. Furthermore, the serum concentration of fibroblast growth factor 21, a hormone secreted from the liver that promotes fatty acid utilization in adipose tissue as a PPARα target gene, was higher (p = 0.054 in HP diet-fed rats than in control diet-fed rats. These data suggest that a HP diet enhances energy expenditure through the utilization of free fatty

  7. Derivation of Tissue-specific Functional Gene Sets to Aid Transcriptomic Analysis of Chemical Impacts on the Teleost Reproductive Axis.

    Science.gov (United States)

    Oligonucleotide microarrays are a powerful tool for unsupervised analysis of chemical impacts on biological systems. However, the lack of well annotated biological pathways for many aquatic organisms, including fish, and the poor power of microarray-based analyses to detect diffe...

  8. MICROARRAY ANALYSIS OF DIFFERENT GENE EXPRESSION OF HUMAN CERVICAL CANCER SUBCLONE CELL LINES

    Institute of Scientific and Technical Information of China (English)

    Chen Wei; Li Xu; Wang Xiang

    2006-01-01

    Objective To examine the differentially expressed invasion-related genes in two anchorage-independent uterine cervical carcinoma cell lines derived from the same patient using a cDNA array. Methods Two human uterine cervical carcinoma subclonal cell lines CS03 and CS07 derived from a single donor line CS1213 were established by limited dilution procedure. The two cDNA samples retro-transcribed from total RNA derived from CS03 and CS07 cells were screened by a cDNA microarray carrying 234 human cell-cycle related genes and 1011 human signal transduction and membrane receptor -associated genes, scanned with a ScanArray 3000 laser scanner. Results The cDNA microarray analysis showed that 12 genes in CS03 were up-regulated compared to CS07, and 24 genes in CS07 were up-regulated. The function of a number of differentially expressed genes was consistently associated with cell-cycle, cell proliferation, migration, apoptosis, signal transduction and tumor metastasis, including p34cdc2, TSC22, plasminogen activator inhibitor I (PAI-1)and desmosome associated protein(Pinin). Conclusion Multiple genes are differentially expressed in uterine cervical carcinoma cell lines even came from the same patient. It is suggested that these genes are involved in the different phenotypic characteristics and development of cervical carcinoma.

  9. Analysis of ripening-related gene expression in papaya using an Arabidopsis-based microarray

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    Fabi João Paulo

    2012-12-01

    Full Text Available Abstract Background Papaya (Carica papaya L. is a commercially important crop that produces climacteric fruits with a soft and sweet pulp that contain a wide range of health promoting phytochemicals. Despite its importance, little is known about transcriptional modifications during papaya fruit ripening and their control. In this study we report the analysis of ripe papaya transcriptome by using a cross-species (XSpecies microarray technique based on the phylogenetic proximity between papaya and Arabidopsis thaliana. Results Papaya transcriptome analyses resulted in the identification of 414 ripening-related genes with some having their expression validated by qPCR. The transcription profile was compared with that from ripening tomato and grape. There were many similarities between papaya and tomato especially with respect to the expression of genes encoding proteins involved in primary metabolism, regulation of transcription, biotic and abiotic stress and cell wall metabolism. XSpecies microarray data indicated that transcription factors (TFs of the MADS-box, NAC and AP2/ERF gene families were involved in the control of papaya ripening and revealed that cell wall-related gene expression in papaya had similarities to the expression profiles seen in Arabidopsis during hypocotyl development. Conclusion The cross-species array experiment identified a ripening-related set of genes in papaya allowing the comparison of transcription control between papaya and other fruit bearing taxa during the ripening process.

  10. ParaSAM: a parallelized version of the significance analysis of microarrays algorithm.

    Science.gov (United States)

    Sharma, Ashok; Zhao, Jieping; Podolsky, Robert; McIndoe, Richard A

    2010-06-01

    Significance analysis of microarrays (SAM) is a widely used permutation-based approach to identifying differentially expressed genes in microarray datasets. While SAM is freely available as an Excel plug-in and as an R-package, analyses are often limited for large datasets due to very high memory requirements. We have developed a parallelized version of the SAM algorithm called ParaSAM to overcome the memory limitations. This high performance multithreaded application provides the scientific community with an easy and manageable client-server Windows application with graphical user interface and does not require programming experience to run. The parallel nature of the application comes from the use of web services to perform the permutations. Our results indicate that ParaSAM is not only faster than the serial version, but also can analyze extremely large datasets that cannot be performed using existing implementations. A web version open to the public is available at http://bioanalysis.genomics.mcg.edu/parasam. For local installations, both the windows and web implementations of ParaSAM are available for free at http://www.amdcc.org/bioinformatics/software/parasam.aspx.

  11. Statistical Analysis of Microarray Data with Replicated Spots: A Case Study with Synechococcus WH8102

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    E. V. Thomas

    2009-01-01

    Full Text Available Until recently microarray experiments often involved relatively few arrays with only a single representation of each gene on each array. A complete genome microarray with multiple spots per gene (spread out spatially across the array was developed in order to compare the gene expression of a marine cyanobacterium and a knockout mutant strain in a defined artificial seawater medium. Statistical methods were developed for analysis in the special situation of this case study where there is gene replication within an array and where relatively few arrays are used, which can be the case with current array technology. Due in part to the replication within an array, it was possible to detect very small changes in the levels of expression between the wild type and mutant strains. One interesting biological outcome of this experiment is the indication of the extent to which the phosphorus regulatory system of this cyanobacterium affects the expression of multiple genes beyond those strictly involved in phosphorus acquisition.

  12. Microarray analysis of differentially expressed genes in preeclamptic and normal placental tissues.

    Science.gov (United States)

    Ma, K; Lian, Y; Zhou, S; Hu, R; Xiong, Y; Ting, P; Xiong, Y; Li, X; Wang, X

    2014-01-01

    To detect the candidate genes for preeclampsia (PE). The gene expression profiles in preeclamptic and normal placental tissues were analyzed using cDNA microarray approach and the altered expression of important genes were further confirmed by real-time RT-PCR (reverse transcription polymerase chain reaction) technique. Total RNA was extracted from placental tissues of three cases with severe PE and from three cases with normal pregnancy. After scanning, differentially expressed genes were detected by software. In two experiments (the fluorescent labels were exchanged), a total of 111 differentially expressed genes were detected. In placental tissue ofpreeclamptic pregnancy, 68 differentially expressed genes were up-regulated, and 44 differentially expressed genes were down-regulated. Of these genes, 16 highly differentially expressed genes were confirmed by real-time fluorescent quantitative RT-PCR, and the result showed that the ratio of gene expression differences was comparable to that detected by cDNA microarray. The results of bioinformatic analysis showed that encoding products of differentially expressed genes were correlated to infiltration of placenta trophoblastic cells, immunomodulatory factors, pregnancy-associated plasma protein, signal transduction pathway, and cell adhesion. Further studies on the biological function and regulating mechanism of these genes will provide new clues for better understanding of etiology and pathogenesis of PE.

  13. Transcriptional Profiling of Hydrogen Production Metabolism of Rhodobacter capsulatus under Temperature Stress by Microarray Analysis

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    Muazzez Gürgan

    2015-06-01

    Full Text Available Biohydrogen is a clean and renewable form of hydrogen, which can be produced by photosynthetic bacteria in outdoor large-scale photobioreactors using sunlight. In this study, the transcriptional response of Rhodobacter capsulatus to cold (4 °C and heat (42 °C stress was studied using microarrays. Bacteria were grown in 30/2 acetate/glutamate medium at 30 °C for 48 h under continuous illumination. Then, cold and heat stresses were applied for two and six hours. Growth and hydrogen production were impaired under both stress conditions. Microarray chips for R. capsulatus were custom designed by Affymetrix (GeneChip®. TR_RCH2a520699F. The numbers of significantly changed genes were 328 and 293 out of 3685 genes under cold and heat stress, respectively. Our results indicate that temperature stress greatly affects the hydrogen production metabolisms of R. capsulatus. Specifically, the expression of genes that participate in nitrogen metabolism, photosynthesis and the electron transport system were induced by cold stress, while decreased by heat stress. Heat stress also resulted in down regulation of genes related to cell envelope, transporter and binding proteins. Transcriptome analysis and physiological results were consistent with each other. The results presented here may aid clarification of the genetic mechanisms for hydrogen production in purple non-sulfur (PNS bacteria under temperature stress.

  14. Age-Specific Gene Expression Profiles of Rhesus Monkey Ovaries Detected by Microarray Analysis

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    Hengxi Wei

    2015-01-01

    Full Text Available The biological function of human ovaries declines with age. To identify the potential molecular changes in ovarian aging, we performed genome-wide gene expression analysis by microarray of ovaries from young, middle-aged, and old rhesus monkeys. Microarray data was validated by quantitative real-time PCR. Results showed that a total of 503 (60 upregulated, 443 downregulated and 84 (downregulated genes were differentially expressed in old ovaries compared to young and middle-aged groups, respectively. No difference in gene expression was found between middle-aged and young groups. Differentially expressed genes were mainly enriched in cell and organelle, cellular and physiological process, binding, and catalytic activity. These genes were primarily associated with KEGG pathways of cell cycle, DNA replication and repair, oocyte meiosis and maturation, MAPK, TGF-beta, and p53 signaling pathway. Genes upregulated were involved in aging, defense response, oxidation reduction, and negative regulation of cellular process; genes downregulated have functions in reproduction, cell cycle, DNA and RNA process, macromolecular complex assembly, and positive regulation of macromolecule metabolic process. These findings show that monkey ovary undergoes substantial change in global transcription with age. Gene expression profiles are useful in understanding the mechanisms underlying ovarian aging and age-associated infertility in primates.

  15. The microarray analysis for gene expression in haploids and diploids derived from twin-seedling rice

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    In this study, microarray technique was employed to analyze the gene expression at the RNA level between haploids and corresponding diploids derived from a rice twin-seedling line SARII-628. Differ- ent degrees of expression variations were observed in the plant after haploidization. The main results are as follows: (1) after haploidization, the ratio of the sensitive loci was 2.47% of the total loci designed on chip. Those loci were randomly distributed on the 12 pairs of rice chromosomes and the activated loci were more than the silenced ones. (2) Gene clusters on chromosome were observed for 33 se- quences. (3) GoPipe function classification for 575 sensitive loci revealed an involvement in the bio- logical process, cell component and molecular function. (4) RT-PCR generally validated the result from microarray with a coincidence rate of 83.78%. And for the randomly-selected activated or silenced loci in chip analysis, the coincidence rate was up to 91.86%.

  16. Analysing breast cancer microarrays from African Americans using shrinkage-based discriminant analysis

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    Pang Herbert

    2010-10-01

    Full Text Available Abstract Breast cancer tumours among African Americans are usually more aggressive than those found in Caucasian populations. African-American patients with breast cancer also have higher mortality rates than Caucasian women. A better understanding of the disease aetiology of these breast cancers can help to improve and develop new methods for cancer prevention, diagnosis and treatment. The main goal of this project was to identify genes that help differentiate between oestrogen receptor-positive and -negative samples among a small group of African-American patients with breast cancer. Breast cancer microarrays from one of the largest genomic consortiums were analysed using 13 African-American and 201 Caucasian samples with oestrogen receptor status. We used a shrinkage-based classification method to identify genes that were informative in discriminating between oestrogen receptor-positive and -negative samples. Subset analysis and permutation were performed to obtain a set of genes unique to the African-American population. We identified a set of 156 probe sets, which gave a misclassification rate of 0.16 in distinguishing between oestrogen receptor-positive and -negative patients. The biological relevance of our findings was explored through literature-mining techniques and pathway mapping. An independent dataset was used to validate our findings and we found that the top ten genes mapped onto this dataset gave a misclassification rate of 0.15. The described method allows us best to utilise the information available from small sample size microarray data in the context of ethnic minorities.

  17. Microarray analysis of human monocytes infected with Francisella tularensis identifies new targets of host response subversion.

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    Jonathan P Butchar

    Full Text Available Francisella tularensis is a gram-negative facultative bacterium that causes the disease tularemia, even upon exposure to low numbers of bacteria. One critical characteristic of Francisella is its ability to dampen or subvert the host immune response. In order to help understand the mechanisms by which this occurs, we performed Affymetrix microarray analysis on transcripts from blood monocytes infected with the virulent Type A Schu S4 strain. Results showed that expression of several host response genes were reduced such as those associated with interferon signaling, Toll-like receptor signaling, autophagy and phagocytosis. When compared to microarrays from monocytes infected with the less virulent F. tularensis subsp. novicida, we found qualitative differences and also a general pattern of quantitatively reduced pro-inflammatory signaling pathway genes in the Schu S4 strain. Notably, the PI3K/Akt1 pathway appeared specifically down-regulated following Schu S4 infection and a concomitantly lower cytokine response was observed. This study identifies several new factors potentially important in host cell subversion by the virulent Type A F. tularensis that may serve as novel targets for drug discovery.

  18. Microarray-bioinformatics analysis of altered genomic expression profiles between human fetal and infant myocardium

    Institute of Scientific and Technical Information of China (English)

    KONG Bo; LIU Ying-long; L(U) Xiao-dong

    2008-01-01

    Background The physiological differences between fetal and postnatal heart have been well characterized at the cellular level. However, the genetic mechanisms governing and regulating these differences have only been partially elucidated. Elucidation of the differentially expressed genes profile before and after birth has never been systematically proposed and analyzed.Methods The human oligonuclectide microarray and bioinformatics analysis approaches were applied to isolate and classify the differentially expressed genes between fetal and infant cardiac tissue samples. Quantitative real-time PCR was used to confirm the results from the microarray.Results Two hundred and forty-two differentially expressed genes were discovered and classified into 13 categories, including genes related to energy metabolism, myocyte hyperplasia, development, muscle contraction, protein synthesis and degradation, extraceUular matrix components, transcription factors, apoptosis, signal pathway molecules, organelle organization and several other biological processes. Moreover, 95 genes were identified which had not previously been reported to be expressed in the heart.Conclusions The study systematically analyzed the alteration of the gene expression profile between the human fetal and infant myocardium. A number of genes were discovered which had not been reported to be expressed in the heart. The data provided insight into the physical development mechanisms of the heart before and after birth.KONG Bo and LU Xiao-dong contributed equally to this study.

  19. Analysis of factorial time-course microarrays with application to a clinical study of burn injury.

    Science.gov (United States)

    Zhou, Baiyu; Xu, Weihong; Herndon, David; Tompkins, Ronald; Davis, Ronald; Xiao, Wenzhong; Wong, Wing Hung; Toner, Mehmet; Warren, H Shaw; Schoenfeld, David A; Rahme, Laurence; McDonald-Smith, Grace P; Hayden, Douglas; Mason, Philip; Fagan, Shawn; Yu, Yong-Ming; Cobb, J Perren; Remick, Daniel G; Mannick, John A; Lederer, James A; Gamelli, Richard L; Silver, Geoffrey M; West, Michael A; Shapiro, Michael B; Smith, Richard; Camp, David G; Qian, Weijun; Storey, John; Mindrinos, Michael; Tibshirani, Rob; Lowry, Stephen; Calvano, Steven; Chaudry, Irshad; West, Michael A; Cohen, Mitchell; Moore, Ernest E; Johnson, Jeffrey; Moldawer, Lyle L; Baker, Henry V; Efron, Philip A; Balis, Ulysses G J; Billiar, Timothy R; Ochoa, Juan B; Sperry, Jason L; Miller-Graziano, Carol L; De, Asit K; Bankey, Paul E; Finnerty, Celeste C; Jeschke, Marc G; Minei, Joseph P; Arnoldo, Brett D; Hunt, John L; Horton, Jureta; Cobb, J Perren; Brownstein, Bernard; Freeman, Bradley; Maier, Ronald V; Nathens, Avery B; Cuschieri, Joseph; Gibran, Nicole; Klein, Matthew; O'Keefe, Grant

    2010-06-01

    Time-course microarray experiments are capable of capturing dynamic gene expression profiles. It is important to study how these dynamic profiles depend on the multiple factors that characterize the experimental condition under which the time course is observed. Analytic methods are needed to simultaneously handle the time course and factorial structure in the data. We developed a method to evaluate factor effects by pooling information across the time course while accounting for multiple testing and nonnormality of the microarray data. The method effectively extracts gene-specific response features and models their dependency on the experimental factors. Both longitudinal and cross-sectional time-course data can be handled by our approach. The method was used to analyze the impact of age on the temporal gene response to burn injury in a large-scale clinical study. Our analysis reveals that 21% of the genes responsive to burn are age-specific, among which expressions of mitochondria and immunoglobulin genes are differentially perturbed in pediatric and adult patients by burn injury. These new findings in the body's response to burn injury between children and adults support further investigations of therapeutic options targeting specific age groups. The methodology proposed here has been implemented in R package "TANOVA" and submitted to the Comprehensive R Archive Network at http://www.r-project.org/. It is also available for download at http://gluegrant1.stanford.edu/TANOVA/.

  20. A Latent Variable Approach for Meta-Analysis of Gene Expression Data from Multiple Microarray Experiments

    Directory of Open Access Journals (Sweden)

    Chinnaiyan Arul M

    2007-09-01

    Full Text Available Abstract Background With the explosion in data generated using microarray technology by different investigators working on similar experiments, it is of interest to combine results across multiple studies. Results In this article, we describe a general probabilistic framework for combining high-throughput genomic data from several related microarray experiments using mixture models. A key feature of the model is the use of latent variables that represent quantities that can be combined across diverse platforms. We consider two methods for estimation of an index termed the probability of expression (POE. The first, reported in previous work by the authors, involves Markov Chain Monte Carlo (MCMC techniques. The second method is a faster algorithm based on the expectation-maximization (EM algorithm. The methods are illustrated with application to a meta-analysis of datasets for metastatic cancer. Conclusion The statistical methods described in the paper are available as an R package, metaArray 1.8.1, which is at Bioconductor, whose URL is http://www.bioconductor.org/.

  1. [Microarray analytic system for multiplex analysis by real-time polymerase chain reaction with reagents immobilized in microreactors].

    Science.gov (United States)

    Navolotskiĭ, D V; Perchik, A V; Mark'ianov, I A; Ganeev, A A; Sliadnev, M N

    2011-01-01

    A microarray analytic system that uses a silicon chip with immobilized in microreactor test-system for multiplex analysis of DNA by real-time polymerase chain reaction (RT-PCR) was developed and optimized. We suggested the method of immobilization of PCR-components of a test-system, chose the stabilizer, and conducted the optimization of the composition of reaction mixture to achieve permanent stability of a microarray. We conducted optimization of preparation of samples using magnetic sorbent and indicated that, with 2.6 x 10(4) copies/ml, 60 min are necessary to obtain positive identification including time for preparation of model probes. The abilities of the created system were demonstrated on the example of microarray analysis of samples with different content of DNA, low absolute limits of identification (20 DNA copies in microreactor), and high reproducibility of the analysis.

  2. Chromosomal Microarray Analysis of Consecutive Individuals with Autism Spectrum Disorders Using an Ultra-High Resolution Chromosomal Microarray Optimized for Neurodevelopmental Disorders

    Directory of Open Access Journals (Sweden)

    Karen S. Ho

    2016-12-01

    Full Text Available Copy number variants (CNVs detected by chromosomal microarray analysis (CMA significantly contribute to understanding the etiology of autism spectrum disorder (ASD and other related conditions. In recognition of the value of CMA testing and its impact on medical management, CMA is in medical guidelines as a first-tier test in the evaluation of children with these disorders. As CMA becomes adopted into routine care for these patients, it becomes increasingly important to report these clinical findings. This study summarizes the results of over 4 years of CMA testing by a CLIA-certified clinical testing laboratory. Using a 2.8 million probe microarray optimized for the detection of CNVs associated with neurodevelopmental disorders, we report an overall CNV detection rate of 28.1% in 10,351 consecutive patients, which rises to nearly 33% in cases without ASD, with only developmental delay/intellectual disability (DD/ID and/or multiple congenital anomalies (MCA. The overall detection rate for individuals with ASD is also significant at 24.4%. The detection rate and pathogenic yield of CMA vary significantly with the indications for testing, age, and gender, as well as the specialty of the ordering doctor. We note discrete differences in the most common recurrent CNVs found in individuals with or without a diagnosis of ASD.

  3. INCLUSive: A web portal and service registry for microarray and regulatory sequence analysis.

    Science.gov (United States)

    Coessens, Bert; Thijs, Gert; Aerts, Stein; Marchal, Kathleen; De Smet, Frank; Engelen, Kristof; Glenisson, Patrick; Moreau, Yves; Mathys, Janick; De Moor, Bart

    2003-07-01

    INCLUSive is a suite of algorithms and tools for the analysis of gene expression data and the discovery of cis-regulatory sequence elements. The tools allow normalization, filtering and clustering of microarray data, functional scoring of gene clusters, sequence retrieval, and detection of known and unknown regulatory elements using probabilistic sequence models and Gibbs sampling. All tools are available via different web pages and as web services. The web pages are connected and integrated to reflect a methodology and facilitate complex analysis using different tools. The web services can be invoked using standard SOAP messaging. Example clients are available for download to invoke the services from a remote computer or to be integrated with other applications. All services are catalogued and described in a web service registry. The INCLUSive web portal is available for academic purposes at http://www.esat.kuleuven.ac.be/inclusive.

  4. Microarray analysis of Neosartorya fischeri using different carbon sources, petroleum asphaltenes and glucose-peptone

    Science.gov (United States)

    Hernández-López, Edna L.; Ramírez-Puebla, Shamayim T.; Vazquez-Duhalt, Rafael

    2015-01-01

    Asphaltenes are considered as the most recalcitrant petroleum fraction and represent a big problem for the recovery, separation and processing of heavy oils and bitumens. Neosartorya fischeri is a saprophytic fungus that is able to grow using asphaltenes as the sole carbon source [1]. We performed transcription profiling using a custom designed microarray with the complete genome from N. fischeri NRRL 181 in order to identify genes related to the transformation of asphaltenes [1]. Data analysis was performed using the genArise software. Results showed that 287 genes were up-regulated and 118 were down-regulated. Here we describe experimental procedures and methods about our dataset (NCBI GEO accession number GSE68146) and describe the data analysis to identify different expression levels in N. fischeri using this recalcitrant carbon source. PMID:26484261

  5. Phytoremediation potential of Arabidopsis with reference to acrylamide and microarray analysis of acrylamide-response genes.

    Science.gov (United States)

    Gao, Jian-Jie; Peng, Ri-He; Zhu, Bo; Wang, Bo; Wang, Li-Juan; Xu, Jing; Sun, Miao; Yao, Quan-Hong

    2015-10-01

    Acrylamide (ACR) is a widely used industrial chemical. However, it is a dangerous compound because it showed neurotoxic effects in humans and act as reproductive toxicant and carcinogen in many animal species. In the environment, acrylamide has high soil mobility and may travel via groundwater. Phytoremediation is an effective method to remove the environmental pollutants, but the mechanism of plant response to acrylamide remains unknown. With the purpose of assessing remediation potentials of plants for acrylamide, we have examined acrylamide uptake by the model plant Arabidopsis grown on contaminated substrates with high performance liquid chromatography (HPLC) analysis. The result revealed that acrylamide could be absorbed and degraded by Arabidopsis. Further microarray analysis showed that 527 transcripts were up-regulated within 2-days under acrylamide exposure condition. We have found many potential acrylamide-induced genes playing a major role in plant metabolism and phytoremediation. Copyright © 2015 Elsevier Inc. All rights reserved.

  6. TagSmart: analysis and visualization for yeast mutant fitness data measured by tag microarrays

    Directory of Open Access Journals (Sweden)

    Xie Dan

    2007-04-01

    Full Text Available Abstract Background A nearly complete collection of gene-deletion mutants (96% of annotated open reading frames of the yeast Saccharomyces cerevisiae has been systematically constructed. Tag microarrays are widely used to measure the fitness of each mutant in a mutant mixture. The tag array experiments can have a complex experimental design, such as time course measurements and drug treatment with multiple dosages. Results TagSmart is a web application for analysis and visualization of Saccharomyces cerevisiae mutant fitness data measured by tag microarrays. It implements a robust statistical approach to assess the concentration differences among S. cerevisiae mutant strains. It also provides an interactive environment for data analysis and visualization. TagSmart has the following advantages over previously described analysis procedures: 1 it is user-friendly software rather than merely a description of analytical procedure; 2 It can handle complicated experimental designs, such as multiple time points and treatment with multiple dosages; 3 it has higher sensitivity and specificity; 4 It allows users to mask out "bad" tags in the analysis. Two biological tests were performed to illustrate the performance of TagSmart. First, we generated titration mixtures of mutant strains, in which the relative concentration of each strain was controlled. We used tag microarrays to measure the numbers of tag copies in each titration mixture. The data was analyzed with TagSmart and the result showed high precision and recall. Second, TagSmart was applied to a dataset in which heterozygous deletion strain mixture pools were treated with a new drug, Cincreasin. TagSmart identified 53 mutant strains as sensitive to Cincreasin treatment. We individually tested each identified mutant, and found 52 out of the 53 predicted mutants were indeed sensitive to Cincreasin. Conclusion TagSmart is provided "as is" to analyze tag array data produced by Affymetrix and Agilent

  7. Investigation of a new core-shell particle column for ion-pair reversed-phase liquid chromatography analysis of oligonucleotides.

    Science.gov (United States)

    Biba, Mirlinda; Welch, Christopher J; Foley, Joe P

    2014-08-01

    A new core-shell particle column showed excellent performance and durability for separation of short (∼21-mer) ribonucleic acid (RNA) oligonucleotides by ion-pair reversed-phase liquid chromatography (IP-RPLC). Previously investigated core-shell C18 columns showed excellent peak shapes and separations of closely eluting impurities by IP-RPLC. However, these columns showed only modest long-term stability at the neutral pH and elevated column temperatures of ≥60°C, typically used for IP-RPLC analysis of oligonucleotides. The newly introduced SunShell C18 column provided separations comparable to the previously evaluated core-shell columns, but with significantly improved long-term column stability when operated at neutral pH and elevated column temperature.

  8. Protein microarrays for systems biology

    Institute of Scientific and Technical Information of China (English)

    Lina Yang; Shujuan Guo; Yang Li; Shumin Zhou; Shengce Tao

    2011-01-01

    Systems biology holds the key for understanding biological systems on a system level. It eventually holds the key for the treatment and cure of complex diseases such as cancer,diabetes, obesity, mental disorders, and many others. The '-omics' technologies, such as genomics, transcriptomics,proteomics, and metabonomics, are among the major driving forces of systems biology. Featured as highthroughput, miniaturized, and capable of parallel analysis,protein microarrays have already become an important technology platform for systems biology, In this review, we will focus on the system level or global analysis of biological systems using protein microarrays. Four major types of protein microarrays will be discussed: proteome microarrays, antibody microarrays, reverse-phase protein arrays,and lectin microarrays. We will also discuss the challenges and future directions of protein microarray technologies and their applications for systems biology. We strongly believe that protein microarrays will soon become an indispensable and invaluable tool for systems biology.

  9. Microarray analysis and barcoded pyrosequencing provide consistent microbial profiles depending on the source of human intestinal samples

    NARCIS (Netherlands)

    Bogert, van den B.; Vos, de W.M.; Zoetendal, E.G.; Kleerebezem, M.

    2011-01-01

    Large-scale and in-depth characterization of the intestinal microbiota necessitates application of high-throughput 16S rRNA gene-based technologies, such as barcoded pyrosequencing and phylogenetic microarray analysis. In this study, the two techniques were compared and contrasted for analysis of th

  10. Introduction on Using the FastPCR Software and the Related Java Web Tools for PCR and Oligonucleotide Assembly and Analysis.

    Science.gov (United States)

    Kalendar, Ruslan; Tselykh, Timofey V; Khassenov, Bekbolat; Ramanculov, Erlan M

    2017-01-01

    This chapter introduces the FastPCR software as an integrated tool environment for PCR primer and probe design, which predicts properties of oligonucleotides based on experimental studies of the PCR efficiency. The software provides comprehensive facilities for designing primers for most PCR applications and their combinations. These include the standard PCR as well as the multiplex, long-distance, inverse, real-time, group-specific, unique, overlap extension PCR for multi-fragments assembling cloning and loop-mediated isothermal amplification (LAMP). It also contains a built-in program to design oligonucleotide sets both for long sequence assembly by ligase chain reaction and for design of amplicons that tile across a region(s) of interest. The software calculates the melting temperature for the standard and degenerate oligonucleotides including locked nucleic acid (LNA) and other modifications. It also provides analyses for a set of primers with the prediction of oligonucleotide properties, dimer and G/C-quadruplex detection, linguistic complexity as well as a primer dilution and resuspension calculator. The program consists of various bioinformatical tools for analysis of sequences with the GC or AT skew, CG% and GA% content, and the purine-pyrimidine skew. It also analyzes the linguistic sequence complexity and performs generation of random DNA sequence as well as restriction endonucleases analysis. The program allows to find or create restriction enzyme recognition sites for coding sequences and supports the clustering of sequences. It performs efficient and complete detection of various repeat types with visual display. The FastPCR software allows the sequence file batch processing that is essential for automation. The program is available for download at http://primerdigital.com/fastpcr.html , and its online version is located at http://primerdigital.com/tools/pcr.html .

  11. Extending Immunological Profiling in the Gilthead Sea Bream, Sparus aurata, by Enriched cDNA Library Analysis, Microarray Design and Initial Studies upon the Inflammatory Response to PAMPs

    Science.gov (United States)

    Boltaña, Sebastian; Castellana, Barbara; Goetz, Giles; Tort, Lluis; Teles, Mariana; Mulero, Victor; Novoa, Beatriz; Figueras, Antonio; Goetz, Frederick W.; Gallardo-Escarate, Cristian; Planas, Josep V.; Mackenzie, Simon

    2017-01-01

    This study describes the development and validation of an enriched oligonucleotide-microarray platform for Sparus aurata (SAQ) to provide a platform for transcriptomic studies in this species. A transcriptome database was constructed by assembly of gilthead sea bream sequences derived from public repositories of mRNA together with reads from a large collection of expressed sequence tags (EST) from two extensive targeted cDNA libraries characterizing mRNA transcripts regulated by both bacterial and viral challenge. The developed microarray was further validated by analysing monocyte/macrophage activation profiles after challenge with two Gram-negative bacterial pathogen-associated molecular patterns (PAMPs; lipopolysaccharide (LPS) and peptidoglycan (PGN)). Of the approximately 10,000 EST sequenced, we obtained a total of 6837 EST longer than 100 nt, with 3778 and 3059 EST obtained from the bacterial-primed and from the viral-primed cDNA libraries, respectively. Functional classification of contigs from the bacterial- and viral-primed cDNA libraries by Gene Ontology (GO) showed that the top five represented categories were equally represented in the two libraries: metabolism (approximately 24% of the total number of contigs), carrier proteins/membrane transport (approximately 15%), effectors/modulators and cell communication (approximately 11%), nucleoside, nucleotide and nucleic acid metabolism (approximately 7.5%) and intracellular transducers/signal transduction (approximately 5%). Transcriptome analyses using this enriched oligonucleotide platform identified differential shifts in the response to PGN and LPS in macrophage-like cells, highlighting responsive gene-cassettes tightly related to PAMP host recognition. As observed in other fish species, PGN is a powerful activator of the inflammatory response in S. aurata macrophage-like cells. We have developed and validated an oligonucleotide microarray (SAQ) that provides a platform enriched for the study of gene

  12. Extending Immunological Profiling in the Gilthead Sea Bream, Sparus aurata, by Enriched cDNA Library Analysis, Microarray Design and Initial Studies upon the Inflammatory Response to PAMPs

    Directory of Open Access Journals (Sweden)

    Sebastian Boltaña

    2017-02-01

    Full Text Available This study describes the development and validation of an enriched oligonucleotide-microarray platform for Sparus aurata (SAQ to provide a platform for transcriptomic studies in this species. A transcriptome database was constructed by assembly of gilthead sea bream sequences derived from public repositories of mRNA together with reads from a large collection of expressed sequence tags (EST from two extensive targeted cDNA libraries characterizing mRNA transcripts regulated by both bacterial and viral challenge. The developed microarray was further validated by analysing monocyte/macrophage activation profiles after challenge with two Gram-negative bacterial pathogen-associated molecular patterns (PAMPs; lipopolysaccharide (LPS and peptidoglycan (PGN. Of the approximately 10,000 EST sequenced, we obtained a total of 6837 EST longer than 100 nt, with 3778 and 3059 EST obtained from the bacterial-primed and from the viral-primed cDNA libraries, respectively. Functional classification of contigs from the bacterial- and viral-primed cDNA libraries by Gene Ontology (GO showed that the top five represented categories were equally represented in the two libraries: metabolism (approximately 24% of the total number of contigs, carrier proteins/membrane transport (approximately 15%, effectors/modulators and cell communication (approximately 11%, nucleoside, nucleotide and nucleic acid metabolism (approximately 7.5% and intracellular transducers/signal transduction (approximately 5%. Transcriptome analyses using this enriched oligonucleotide platform identified differential shifts in the response to PGN and LPS in macrophage-like cells, highlighting responsive gene-cassettes tightly related to PAMP host recognition. As observed in other fish species, PGN is a powerful activator of the inflammatory response in S. aurata macrophage-like cells. We have developed and validated an oligonucleotide microarray (SAQ that provides a platform enriched for the study

  13. EDGE3: A web-based solution for management and analysis of Agilent two color microarray experiments

    Directory of Open Access Journals (Sweden)

    Craven Mark

    2009-09-01

    Full Text Available Abstract Background The ability to generate transcriptional data on the scale of entire genomes has been a boon both in the improvement of biological understanding and in the amount of data generated. The latter, the amount of data generated, has implications when it comes to effective storage, analysis and sharing of these data. A number of software tools have been developed to store, analyze, and share microarray data. However, a majority of these tools do not offer all of these features nor do they specifically target the commonly used two color Agilent DNA microarray platform. Thus, the motivating factor for the development of EDGE3 was to incorporate the storage, analysis and sharing of microarray data in a manner that would provide a means for research groups to collaborate on Agilent-based microarray experiments without a large investment in software-related expenditures or extensive training of end-users. Results EDGE3 has been developed with two major functions in mind. The first function is to provide a workflow process for the generation of microarray data by a research laboratory or a microarray facility. The second is to store, analyze, and share microarray data in a manner that doesn't require complicated software. To satisfy the first function, EDGE3 has been developed as a means to establish a well defined experimental workflow and information system for microarray generation. To satisfy the second function, the software application utilized as the user interface of EDGE3 is a web browser. Within the web browser, a user is able to access the entire functionality, including, but not limited to, the ability to perform a number of bioinformatics based analyses, collaborate between research groups through a user-based security model, and access to the raw data files and quality control files generated by the software used to extract the signals from an array image. Conclusion Here, we present EDGE3, an open-source, web

  14. Microarray analysis identifies a common set of cellular genes modulated by different HCV replicon clones

    Directory of Open Access Journals (Sweden)

    Gerosolimo Germano

    2008-06-01

    Full Text Available Abstract Background Hepatitis C virus (HCV RNA synthesis and protein expression affect cell homeostasis by modulation of gene expression. The impact of HCV replication on global cell transcription has not been fully evaluated. Thus, we analysed the expression profiles of different clones of human hepatoma-derived Huh-7 cells carrying a self-replicating HCV RNA which express all viral proteins (HCV replicon system. Results First, we compared the expression profile of HCV replicon clone 21-5 with both the Huh-7 parental cells and the 21-5 cured (21-5c cells. In these latter, the HCV RNA has been eliminated by IFN-α treatment. To confirm data, we also analyzed microarray results from both the 21-5 and two other HCV replicon clones, 22-6 and 21-7, compared to the Huh-7 cells. The study was carried out by using the Applied Biosystems (AB Human Genome Survey Microarray v1.0 which provides 31,700 probes that correspond to 27,868 human genes. Microarray analysis revealed a specific transcriptional program induced by HCV in replicon cells respect to both IFN-α-cured and Huh-7 cells. From the original datasets of differentially expressed genes, we selected by Venn diagrams a final list of 38 genes modulated by HCV in all clones. Most of the 38 genes have never been described before and showed high fold-change associated with significant p-value, strongly supporting data reliability. Classification of the 38 genes by Panther System identified functional categories that were significantly enriched in this gene set, such as histones and ribosomal proteins as well as extracellular matrix and intracellular protein traffic. The dataset also included new genes involved in lipid metabolism, extracellular matrix and cytoskeletal network, which may be critical for HCV replication and pathogenesis. Conclusion Our data provide a comprehensive analysis of alterations in gene expression induced by HCV replication and reveal modulation of new genes potentially useful

  15. Automated detection of regions of interest for tissue microarray experiments: an image texture analysis

    Directory of Open Access Journals (Sweden)

    Tözeren Aydin

    2007-03-01

    Full Text Available Abstract Background Recent research with tissue microarrays led to a rapid progress toward quantifying the expressions of large sets of biomarkers in normal and diseased tissue. However, standard procedures for sampling tissue for molecular profiling have not yet been established. Methods This study presents a high throughput analysis of texture heterogeneity on breast tissue images for the purpose of identifying regions of interest in the tissue for molecular profiling via tissue microarray technology. Image texture of breast histology slides was described in terms of three parameters: the percentage of area occupied in an image block by chromatin (B, percentage occupied by stroma-like regions (P, and a statistical heterogeneity index H commonly used in image analysis. Texture parameters were defined and computed for each of the thousands of image blocks in our dataset using both the gray scale and color segmentation. The image blocks were then classified into three categories using the texture feature parameters in a novel statistical learning algorithm. These categories are as follows: image blocks specific to normal breast tissue, blocks specific to cancerous tissue, and those image blocks that are non-specific to normal and disease states. Results Gray scale and color segmentation techniques led to identification of same regions in histology slides as cancer-specific. Moreover the image blocks identified as cancer-specific belonged to those cell crowded regions in whole section image slides that were marked by two pathologists as regions of interest for further histological studies. Conclusion These results indicate the high efficiency of our automated method for identifying pathologic regions of interest on histology slides. Automation of critical region identification will help minimize the inter-rater variability among different raters (pathologists as hundreds of tumors that are used to develop an array have typically been evaluated

  16. Formation and characterization of DNA microarrays at silicon nitride substrates.

    Science.gov (United States)

    Manning, Mary; Redmond, Gareth

    2005-01-01

    A versatile method for direct, covalent attachment of DNA microarrays at silicon nitride layers, previously deposited by chemical vapor deposition at silicon wafer substrates, is reported. Each microarray fabrication process step, from silicon nitride substrate deposition, surface cleaning, amino-silanation, and attachment of a homobifunctional cross-linking molecule to covalent immobilization of probe oligonucleotides, is defined, characterized, and optimized to yield consistent probe microarray quality, homogeneity, and probe-target hybridization performance. The developed microarray fabrication methodology provides excellent (high signal-to-background ratio) and reproducible responsivity to target oligonucleotide hybridization with a rugged chemical stability that permits exposure of arrays to stringent pre- and posthybridization wash conditions through many sustained cycles of reuse. Overall, the achieved performance features compare very favorably with those of more mature glass based microarrays. It is proposed that this DNA microarray fabrication strategy has the potential to provide a viable route toward the successful realization of future integrated DNA biochips.

  17. MmPalateMiRNA, an R package compendium illustrating analysis of miRNA microarray data.

    Science.gov (United States)

    Brock, Guy N; Mukhopadhyay, Partha; Pihur, Vasyl; Webb, Cynthia; Greene, Robert M; Pisano, M Michele

    2013-01-08

    MicroRNAs (miRNAs) constitute the largest family of noncoding RNAs involved in gene silencing and represent critical regulators of cell and tissue differentiation. Microarray expression profiling of miRNAs is an effective means of acquiring genome-level information of miRNA activation and inhibition, as well as the potential regulatory role that these genes play within a biological system. As with mRNA expression profiling arrays, miRNA microarrays come in a variety of platforms from numerous manufacturers, and there are a multitude of techniques available for reducing and analyzing these data. In this paper, we present an analysis of a typical two-color miRNA microarray experiment using publicly available packages from R and Bioconductor, the open-source software project for the analysis of genomic data. Covered topics include visualization, normalization, quality checking, differential expression, cluster analysis, miRNA target identification, and gene set enrichment analysis. Many of these tools carry-over from the analysis of mRNA microarrays, but with some notable differences that require special attention. The paper is presented as a "compendium" which, along with the accompanying R package MmPalateMiRNA, contains all of the experimental data and source code to reproduce the analyses contained in the paper. The compendium presented in this paper will provide investigators with an access point for applying the methods available in R and Bioconductor for analysis of their own miRNA array data.

  18. A survey on filter techniques for feature selection in gene expression microarray analysis.

    Science.gov (United States)

    Lazar, Cosmin; Taminau, Jonatan; Meganck, Stijn; Steenhoff, David; Coletta, Alain; Molter, Colin; de Schaetzen, Virginie; Duque, Robin; Bersini, Hugues; Nowé, Ann

    2012-01-01

    A plenitude of feature selection (FS) methods is available in the literature, most of them rising as a need to analyze data of very high dimension, usually hundreds or thousands of variables. Such data sets are now available in various application areas like combinatorial chemistry, text mining, multivariate imaging, or bioinformatics. As a general accepted rule, these methods are grouped in filters, wrappers, and embedded methods. More recently, a new group of methods has been added in the general framework of FS: ensemble techniques. The focus in this survey is on filter feature selection methods for informative feature discovery in gene expression microarray (GEM) analysis, which is also known as differentially expressed genes (DEGs) discovery, gene prioritization, or biomarker discovery. We present them in a unified framework, using standardized notations in order to reveal their technical details and to highlight their common characteristics as well as their particularities.

  19. Antimicrobial resistance determinant microarray for analysis of multi-drug resistant isolates

    Science.gov (United States)

    Taitt, Chris Rowe; Leski, Tomasz; Stenger, David; Vora, Gary J.; House, Brent; Nicklasson, Matilda; Pimentel, Guillermo; Zurawski, Daniel V.; Kirkup, Benjamin C.; Craft, David; Waterman, Paige E.; Lesho, Emil P.; Bangurae, Umaru; Ansumana, Rashid

    2012-06-01

    The prevalence of multidrug-resistant infections in personnel wounded in Iraq and Afghanistan has made it challenging for physicians to choose effective therapeutics in a timely fashion. To address the challenge of identifying the potential for drug resistance, we have developed the Antimicrobial Resistance Determinant Microarray (ARDM) to provide DNAbased analysis for over 250 resistance genes covering 12 classes of antibiotics. Over 70 drug-resistant bacteria from different geographic regions have been analyzed on ARDM, with significant differences in patterns of resistance identified: genes for resistance to sulfonamides, trimethoprim, chloramphenicol, rifampin, and macrolide-lincosamidesulfonamide drugs were more frequently identified in isolates from sources in Iraq/Afghanistan. Of particular concern was the presence of genes responsible for resistance to many of the last-resort antibiotics used to treat war traumaassociated infections.

  20. Microarray Analysis on Gene Regulation by Estrogen, Progesterone and Tamoxifen in Human Endometrial Stromal Cells

    Directory of Open Access Journals (Sweden)

    Chun-E Ren

    2015-03-01

    Full Text Available Epithelial stromal cells represent a major cellular component of human uterine endometrium that is subject to tight hormonal regulation. Through cell-cell contacts and/or paracrine mechanisms, stromal cells play a significant role in the malignant transformation of epithelial cells. We isolated stromal cells from normal human endometrium and investigated the morphological and transcriptional changes induced by estrogen, progesterone and tamoxifen. We demonstrated that stromal cells express appreciable levels of estrogen and progesterone receptors and undergo different morphological changes upon hormonal stimulation. Microarray analysis indicated that both estrogen and progesterone induced dramatic alterations in a variety of genes associated with cell structure, transcription, cell cycle, and signaling. However, divergent patterns of changes, and in some genes opposite effects, were observed for the two hormones. A large number of genes are identified as novel targets for hormonal regulation. These hormone-responsive genes may be involved in normal uterine function and the development of endometrial malignancies.

  1. Microarray Analysis on Gene Regulation by Estrogen, Progesterone and Tamoxifen in Human Endometrial Stromal Cells

    Science.gov (United States)

    Ren, Chun-E; Zhu, Xueqiong; Li, Jinping; Lyle, Christian; Dowdy, Sean; Podratz, Karl C.; Byck, David; Chen, Hai-Bin; Jiang, Shi-Wen

    2015-01-01

    Epithelial stromal cells represent a major cellular component of human uterine endometrium that is subject to tight hormonal regulation. Through cell-cell contacts and/or paracrine mechanisms, stromal cells play a significant role in the malignant transformation of epithelial cells. We isolated stromal cells from normal human endometrium and investigated the morphological and transcriptional changes induced by estrogen, progesterone and tamoxifen. We demonstrated that stromal cells express appreciable levels of estrogen and progesterone receptors and undergo different morphological changes upon hormonal stimulation. Microarray analysis indicated that both estrogen and progesterone induced dramatic alterations in a variety of genes associated with cell structure, transcription, cell cycle, and signaling. However, divergent patterns of changes, and in some genes opposite effects, were observed for the two hormones. A large number of genes are identified as novel targets for hormonal regulation. These hormone-responsive genes may be involved in normal uterine function and the development of endometrial malignancies. PMID:25782154

  2. Global pathway analysis using DNA microarrays in skeletal muscle of women with polycystic ovary syndrome

    DEFF Research Database (Denmark)

    Skov, Vibe

    2007-01-01

    , the molecular mechanisms of insulin resistance in skeletal muscle of women with PCOS are largely unknown. The aims of the Ph.D. thesis were: to identify biological pathways of importance for insulin resistance in skeletal muscle in a group of insulin resistant obese PCOS patients using global pathway analysis...... (study 1), to investigate whether pioglitazone therapy could reverse abnormalities in the transcriptional profile of muscle associated with insulin resistance in skeletal muscle of obese PCOS patients (study 2), and to develop a microarray platform for global gene expression profiling (study 3). In study...... expression of nuclear-encoded genes involved in mitochondrial oxidative phosphorylation (OXPHOS) in skeletal muscle, and q-RT-PCR showed that downregulation of OXPHOS genes may be mediated by reduced levels of PGC-1a. Treatment with pioglitazone partially restored insulin sensitivity in obese women with PCOS...

  3. Application of a cholesterol stationary phase in the analysis of phosphorothioate oligonucleotides by means of ion pair chromatography coupled with tandem mass spectrometry.

    Science.gov (United States)

    Studzińska, Sylwia; Krzemińska, Katarzyna; Szumski, Michał; Buszewski, Bogusław

    2016-07-01

    The main aim of this study was the investigation of the influence of several ion pair reagents towards both the retention and the mass spectrometry sensitivity of phosphorothioate oligonucleotides. A cholesterol stationary phase was applied for the first time in the analysis of this group of compounds. The mobile phase composition was modified by changing the concentration and the type of amines and acetates or 1,1,1,3,3,3-hexafluoroisopropanol. It has been shown that the increase of amines concentration results in the retention factor increase for each oligonucleotide, on each adsorbent. The only exception was the mobile phase composed of triethylamine and 1,1,1,3,3,3-hexafluoroisopropanol. This is a consequence of interactions taking place between a cholesterol molecule and an alcohol. This effect was convenient when the mass spectrometry detection was applied, since it allowed an increase in the sensitivity. Moreover, optimization of the mobile phase composition and its impact on the efficiency of ionization process and on the sensitivity in mass spectrometry were also presented. The optimization of this new method, based on cholesterol stationary phase coupled with mass spectrometry detection, was finally applied for the determination of phosphorothioate oligonucleotides impurity in a real sample. Copyright © 2016 Elsevier B.V. All rights reserved.

  4. Microarray and cDNA sequence analysis of transcription during nerve-dependent limb regeneration

    Directory of Open Access Journals (Sweden)

    Bryant Susan V

    2009-01-01

    Full Text Available Abstract Background Microarray analysis and 454 cDNA sequencing were used to investigate a centuries-old problem in regenerative biology: the basis of nerve-dependent limb regeneration in salamanders. Innervated (NR and denervated (DL forelimbs of Mexican axolotls were amputated and transcripts were sampled after 0, 5, and 14 days of regeneration. Results Considerable similarity was observed between NR and DL transcriptional programs at 5 and 14 days post amputation (dpa. Genes with extracellular functions that are critical to wound healing were upregulated while muscle-specific genes were downregulated. Thus, many processes that are regulated during early limb regeneration do not depend upon nerve-derived factors. The majority of the transcriptional differences between NR and DL limbs were correlated with blastema formation; cell numbers increased in NR limbs after 5 dpa and this yielded distinct transcriptional signatures of cell proliferation in NR limbs at 14 dpa. These transcriptional signatures were not observed in DL limbs. Instead, gene expression changes within DL limbs suggest more diverse and protracted wound-healing responses. 454 cDNA sequencing complemented the microarray analysis by providing deeper sampling of transcriptional programs and associated biological processes. Assembly of new 454 cDNA sequences with existing expressed sequence tag (EST contigs from the Ambystoma EST database more than doubled (3935 to 9411 the number of non-redundant human-A. mexicanum orthologous sequences. Conclusion Many new candidate gene sequences were discovered for the first time and these will greatly enable future studies of wound healing, epigenetics, genome stability, and nerve-dependent blastema formation and outgrowth using the axolotl model.

  5. High throughput phenotypic analysis of Mycobacterium tuberculosis and Mycobacterium bovis strains' metabolism using biolog phenotype microarrays.

    Directory of Open Access Journals (Sweden)

    Bhagwati Khatri

    Full Text Available Tuberculosis is a major human and animal disease of major importance worldwide. Genetically, the closely related strains within the Mycobacterium tuberculosis complex which cause disease are well-characterized but there is an urgent need better to understand their phenotypes. To search rapidly for metabolic differences, a working method using Biolog Phenotype MicroArray analysis was developed. Of 380 substrates surveyed, 71 permitted tetrazolium dye reduction, the readout over 7 days in the method. By looking for ≥5-fold differences in dye reduction, 12 substrates differentiated M. tuberculosis H37Rv and Mycobacterium bovis AF2122/97. H37Rv and a Beijing strain of M. tuberculosis could also be distinguished in this way, as could field strains of M. bovis; even pairs of strains within one spoligotype could be distinguished by 2 to 3 substrates. Cluster analysis gave three clear groups: H37Rv, Beijing, and all the M. bovis strains. The substrates used agreed well with prior knowledge, though an unexpected finding that AF2122/97 gave greater dye reduction than H37Rv with hexoses was investigated further, in culture flasks, revealing that hexoses and Tween 80 were synergistic for growth and used simultaneously rather than in a diauxic fashion. Potential new substrates for growth media were revealed, too, most promisingly N-acetyl glucosamine. Osmotic and pH arrays divided the mycobacteria into two groups with different salt tolerance, though in contrast to the substrate arrays the groups did not entirely correlate with taxonomic differences. More interestingly, these arrays suggested differences between the amines used by the M. tuberculosis complex and enteric bacteria in acid tolerance, with some hydrophobic amino acids being highly effective. In contrast, γ-aminobutyrate, used in the enteric bacteria, had no effect in the mycobacteria. This study proved principle that Phenotype MicroArrays can be used with slow-growing pathogenic mycobacteria

  6. Microarray based gene expression analysis of Sus Scrofa duodenum exposed to zearalenone: significance to human health.

    Science.gov (United States)

    Braicu, Cornelia; Cojocneanu-Petric, Roxana; Jurj, Ancuta; Gulei, Diana; Taranu, Ionelia; Gras, Alexandru Mihail; Marin, Daniela Eliza; Berindan-Neagoe, Ioana

    2016-08-17

    Zearalenone (ZEA) is a secondary metabolite produced by Fusarium species. ZEA was proved to exert a wide range of unwanted side effects, but its mechanism of action, particularly at duodenum levels, remains unclear. In our study based on the microarray technology we assessed the alteration of gene expression pattern Sus scrofa duodenum which has been previously exposed to ZEA. Gene expression data was validated by qRT-PCR and ELISA. The gene expression data were further extrapolated the results to their human orthologues and analyzed the data in the context of human health using IPA (Ingenuity Pathways Analysis). Using Agilent microarray technology, we found that gene expression pattern was significantly affected by ZEA exposure, considering a 2-fold expression difference as a cut-off level and a p-value < 0.05. In total, we found 1576 upregulated and 2446 downregulated transcripts. About 1084 genes (764 downregulated and 751 overexpressed) were extrapolated to their human orthologues. IPA analysis showed various altered key cellular and molecular pathways. As expected, we observed a significant alteration of immune response related genes, MAPK (mitogen activate protein kinases) pathways or Toll-Like Receptors (TLRs). What captured our attention was the modulation of pathways related to the activation of early carcinogenesis. Our data demonstrate that ZEA has a complex effect at duodenum level. ZEA is able to activate not only the immune response related genes, but also those relate to colorectal carcinogenesis. The effects can be more dramatic when connected with the exposure to other environmental toxic agents or co-occurrence with different microorganisms.

  7. ANALYSIS OF GENES ASSOCIATED WITH LYMPHATIC METASTASIS IN PANCREATIC CARCINOMA USING cDNA MICROARRAY

    Institute of Scientific and Technical Information of China (English)

    谭志军; 胡先贵; 曹贵松; 唐岩

    2003-01-01

    Objective: To identify new markers for prediction of lymph node metastasis. Methods: cDNA probes were prepared by labeling mRNA from samples of four pancreatic carcinoma tissues with Cy5-dUTP and mRNA from adjacent normal tissues with Cy3-dUTP respectively through reverse transcription. The mixed probes of each sample were then hybridized with 4,096 cDNA arrays (4,000 unique human cDNA sequences), and the fluorescent signals were scanned by ScanArray 3000 scanner (General Scanning, Inc.). The values of Cy5-dUTP and Cy3-dUTP on each spot were analyzed and calculated by ImaGene 3.0 software (BioDiscovery, Inc.). Genes that differentially expresses in each cancerous tissue were sought out according to the standard that the absolute value of natural logarithm of the ratio of Cy5 to Cy3 is greater than 0.69, i. e., more than 2 times change of gene expression, and the signal value of either Cy3 and Cy5 need to be greater than 600. Then, the genes differently expressed in cancer with and without lymphatic metastasis were screened out for further analysis. Results: Among 2 samples with lymphatic metastasis and 2 samples without metastasis, 56 genes, which accounted for 1.40% of genes on the microarray slides, exhibited differentially expression in cancerous tissues with lymphatic metastasis. There were 32 over-expressed genes including 11 having been registered in Genebank, and 24 under-expressed genes including 3 in Genebank. Conclusion: Microarray analysis may provide invaluable information to identify specific gene expression profile of lymphatic metastasis in pancreatic cancer.

  8. Analysis of gene expression profile of pancreatic carcinoma using CDNA microarray

    Institute of Scientific and Technical Information of China (English)

    ZhiJun Tan; Xian-Gui Hu; Gui-Song Cao; Yan Tang

    2003-01-01

    AIM: To identify new diagnostic markers and drug targets,the gene expression profiles of pancreatic cancer were compared with that of adjacent normal tissues utilizing cDNA microarray analysis.METHODS: cDNA probes were prepared by labeling mRNA from samples of six pancreatic carcinoma tissues with Cy5dUTP and mRNA from adjacent normal tissues with Cy3dUTP respectively through reverse transcription. The mixed probes of each sample were then hybridized with 12 800cDNA arrays (12 648 unique human cDNA sequences), and the fluorescent signals were scanned by ScanArray 3 000scanner (General Scanning, Inc.). The values of CyS-dUTP and Cy3-dUTP on each spot were analyzed and calculated by ImaGene 3.0 software (BioDiscovery, Inc.). Differentially expressed genes were screened according to the criterion that the absolute value of natural logarithm of the ratio of Cy5-dUTP to Cy3-dUTP was greater-than 0.69.RESETS: Among 6 samples investigated, 301 genes, which accounted for 2.38% of genes on the microarry slides,exhibited differentially expression at least in 5. There were 166 over-expressed genes including 136 having been registered in Genebank, and 135 under-expressed genes including 79 in Genebank in cancerous tissues.CONCLUSION: Microarray analysis may provide invaluable information on disease pathology, progression, resistance to treatment, and response to cellular microenvironments of pancreatic carcinoma and ultimately may lead to improving early diagnosis and discovering innovative therapeutic approaches for cancer.

  9. High throughput phenotypic analysis of Mycobacterium tuberculosis and Mycobacterium bovis strains' metabolism using biolog phenotype microarrays.

    Science.gov (United States)

    Khatri, Bhagwati; Fielder, Mark; Jones, Gareth; Newell, William; Abu-Oun, Manal; Wheeler, Paul R

    2013-01-01

    Tuberculosis is a major human and animal disease of major importance worldwide. Genetically, the closely related strains within the Mycobacterium tuberculosis complex which cause disease are well-characterized but there is an urgent need better to understand their phenotypes. To search rapidly for metabolic differences, a working method using Biolog Phenotype MicroArray analysis was developed. Of 380 substrates surveyed, 71 permitted tetrazolium dye reduction, the readout over 7 days in the method. By looking for ≥5-fold differences in dye reduction, 12 substrates differentiated M. tuberculosis H37Rv and Mycobacterium bovis AF2122/97. H37Rv and a Beijing strain of M. tuberculosis could also be distinguished in this way, as could field strains of M. bovis; even pairs of strains within one spoligotype could be distinguished by 2 to 3 substrates. Cluster analysis gave three clear groups: H37Rv, Beijing, and all the M. bovis strains. The substrates used agreed well with prior knowledge, though an unexpected finding that AF2122/97 gave greater dye reduction than H37Rv with hexoses was investigated further, in culture flasks, revealing that hexoses and Tween 80 were synergistic for growth and used simultaneously rather than in a diauxic fashion. Potential new substrates for growth media were revealed, too, most promisingly N-acetyl glucosamine. Osmotic and pH arrays divided the mycobacteria into two groups with different salt tolerance, though in contrast to the substrate arrays the groups did not entirely correlate with taxonomic differences. More interestingly, these arrays suggested differences between the amines used by the M. tuberculosis complex and enteric bacteria in acid tolerance, with some hydrophobic amino acids being highly effective. In contrast, γ-aminobutyrate, used in the enteric bacteria, had no effect in the mycobacteria. This study proved principle that Phenotype MicroArrays can be used with slow-growing pathogenic mycobacteria and already has

  10. Microarray analysis of cytoplasmic versus whole cell RNA reveals a considerable number of missed and false positive mRNAs

    OpenAIRE

    Trask, Heidi W.; Cowper-Sal-lari, Richard; Sartor, Maureen A.; Gui, Jiang; Heath, Catherine V.; Renuka, Janhavi; Higgins, Azara-Jane; Andrews,Peter; Korc, Murray; Moore, Jason H; Craig R Tomlinson

    2009-01-01

    With no known exceptions, every published microarray study to determine differential mRNA levels in eukaryotes used RNA extracted from whole cells. It is assumed that the use of whole cell RNA in microarray gene expression analysis provides a legitimate profile of steady-state mRNA. Standard labeling methods and the prevailing dogma that mRNA resides almost exclusively in the cytoplasm has led to the long-standing belief that the nuclear RNA contribution is negligible. We report that unadulte...

  11. Analysis of differences of gene expressions in keloid and normal skin with the aid of cDNA microarray

    Institute of Scientific and Technical Information of China (English)

    Chen Wei; Fu Xiaobing; Sun Xiaoqing; Sun Tongzhu; Zhao Zhili; Yang Yinhui; Sheng Zhiyong

    2003-01-01

    Background: Microarray analysis is a popular tool to investigate the function of genes that are responsible for the phenotype of the disease. Keloid is a intricate lesion which is probably modulated by interplay of many genes. We ventured to study the differences of gene expressions between keloids and normal skins with the aid of cDNA microarray in order to explore the molecular mechanism underlying keloid formation. Methods: The PCR products of 8400 human genes were spotted on a chip in array. The DNAs were then fixed on the glass plate by a series of treatments. Total RNAs was isolated from freshly excised human keloids and normal skin, and then was purified to mRNA by Oligotex. Both the mRNA from keloids and normal skin was reversely transcribed to cDNAs with the incorporations of fluorescent dUTP, for preparing the hybridization probes. The mixed probes were then hybridized to the cDNA microarray. After highly stringent washing, the cDNA microarray was scanned for the fluorescent signals to display the differences between two kinds of tissues. Results: Among 8400 human genes, there were 402 genes (4.79%) with different expression levels between the keloids and normal skins in all cases, 250were up-regulated (2.98%) and 152 down-regulated (1.81%). Analyses of collagen, fibronectin, proteoglycan,growth factors and apoptosis related molecule gene expression confirmed that our molecular data obtained by cDNA microarray were consistent with published biochemical and clinical observations of keloids. Conclusions: DNA microarray technology is an effective technique in screening for differences in gene expression between keloid and normal skin. Many genes are involved in the formation of keloids. Further analysis of the obtained genes will help understand the molecular mechanism of keloid formation.

  12. Comparative analysis of Lactobacillus plantarum WCFS1 transcriptomes by using DNA microarray and next-generation sequencing technologies.

    NARCIS (Netherlands)

    Leimena, M.M.; Wels, M.W.; Bongers, R.S.; Smid, E.J.; Zoetendal, E.G.; Kleerebezem, M.

    2012-01-01

    RNA sequencing is starting to compete with the use of DNA microarrays for transcription analysis in eukaryotes as well as in prokaryotes. The application of RNA sequencing in prokaryotes requires additional steps in the RNA preparation procedure to increase the relative abundance of mRNA and cannot

  13. A microarray-based analysis of gametogenesis in two Portuguese populations of the European clam Ruditapes decussatus.

    Directory of Open Access Journals (Sweden)

    Joana Teixeira de Sousa

    Full Text Available The European clam, Ruditapes decussatus is a species with a high commercial importance in Portugal and other Southern European countries. Its production is almost exclusively based on natural recruitment, which is subject to high annual fluctuations. Increased knowledge of the natural reproductive cycle of R. decussatus and its molecular mechanisms would be particularly important in providing new highly valuable genomic information for better understanding the regulation of reproduction in this economically important aquaculture species. In this study, the transcriptomic bases of R. decussatus reproduction have been analysed using a custom oligonucleotide microarray representing 51,678 assembled contigs. Microarray analyses were performed in four gonadal maturation stages from two different Portuguese wild populations, characterized by different responses to spawning induction when used as progenitors in hatchery. A comparison between the two populations elucidated a specific pathway involved in the recognition signals and binding between the oocyte and components of the sperm plasma membrane. We suggest that this pathway can explain part of the differences in terms of spawning induction success between the two populations. In addition, sexes and reproductive stages were compared and a correlation between mRNA levels and gonadal area was investigated. The lists of differentially expressed genes revealed that sex explains most of the variance in gonadal gene expression. Additionally, genes like Foxl2, vitellogenin, condensing 2, mitotic apparatus protein p62, Cep57, sperm associated antigens 6, 16 and 17, motile sperm domain containing protein 2, sperm surface protein Sp17, sperm flagellar proteins 1 and 2 and dpy-30, were identified as being correlated with the gonad area and therefore supposedly with the number and/or the size of the gametes produced.

  14. Microarray and Biochemical Analysis of Lovastatin-induced Apoptosis of Squamous Cell Carcinomas

    Directory of Open Access Journals (Sweden)

    Jim Dimitroulakos

    2002-01-01

    Full Text Available We recently identified 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA reductase, the rate-limiting enzyme of the mevalonate pathway, as a potential therapeutic target of the head and neck squamous cell carcinomas (HNSCC and cervical carcinomas (CC. The products of this complex biochemical pathway, including de novo cholesterol, are vital for a variety of key cellular functions affecting membrane integrity, cell signaling, protein synthesis, and cell cycle progression. Lovastatin, a specific inhibitor of HMG-CoA reductase, induces a pronounced apoptotic response in a specific subset of tumor types, including HNSCC and CC. The mediators of this response are not well established. Identification of differentially expressed genes represents a feasible approach to delineate these mediators as lovastatin has the potential to modulate transcription indirectly by perturbing levels of sterols and other mevalonate metabolites. Expression analysis following treatment of the HNSCC cell lines SCC9 or SCC25 with 10 μM lovastatin for 1 day showed that less than 2% (9 cDNAs of the 588 cDNAs on this microarray were affected in both cell lines. These included diazepam-binding inhibitor/acyl-CoA-binding protein, the activated transcription factor 4 and rhoA. Because the biosynthesis of mevalonate leads to its incorporation into more than a dozen classes of end products, their role in lovastatin-induced apoptosis was also evaluated. Addition of the metabolites of all the major branches of the mevalonate pathway indicated that only the nonsterol moiety, geranylgeranyl pyrophosphate (GGPP, significantly inhibited the apoptotic effects of lovastatin in HNSCC and CC cells. Because rhoA requires GGPP for its function, this links the microarray and biochemical data and identifies rhoA as a potential mediator of the anticancer properties of lovastatin. Our data suggest that the depletion of nonsterol mevalonate metabolites, particularly GGPP, can be potential mediators of

  15. Global microarray analysis of carbohydrate use in alkaliphilic hemicellulolytic bacterium Bacillus sp. N16-5.

    Directory of Open Access Journals (Sweden)

    Yajian Song

    Full Text Available The alkaliphilic hemicellulolytic bacterium Bacillus sp. N16-5 has a broad substrate spectrum and exhibits the capacity to utilize complex carbohydrates such as galactomannan, xylan, and pectin. In the monosaccharide mixture, sequential utilization by Bacillus sp. N16-5 was observed. Glucose appeared to be its preferential monosaccharide, followed by fructose, mannose, arabinose, xylose, and galactose. Global transcription profiles of the strain were determined separately for growth on six monosaccharides (glucose, fructose, mannose, galactose, arabinose, and xylose and four polysaccharides (galactomannan, xylan, pectin, and sodium carboxymethylcellulose using one-color microarrays. Numerous genes potentially related to polysaccharide degradation, sugar transport, and monosaccharide metabolism were found to respond to a specific substrate. Putative gene clusters for different carbohydrates were identified according to transcriptional patterns and genome annotation. Identification and analysis of these gene clusters contributed to pathway reconstruction for carbohydrate utilization in Bacillus sp. N16-5. Several genes encoding putative sugar transporters were highly expressed during growth on specific sugars, suggesting their functional roles. Two phosphoenolpyruvate-dependent phosphotransferase systems were identified as candidate transporters for mannose and fructose, and a major facilitator superfamily transporter was identified as a candidate transporter for arabinose and xylose. Five carbohydrate uptake transporter 1 family ATP-binding cassette transporters were predicted to participate in the uptake of hemicellulose and pectin degradation products. Collectively, microarray data improved the pathway reconstruction involved in carbohydrate utilization of Bacillus sp. N16-5 and revealed that the organism precisely regulates gene transcription in response to fluctuations in energy resources.

  16. Microarray Analysis of the Transcriptome for Bacterial Wilt Resistance in Pepper (Capsicum annuum L.

    Directory of Open Access Journals (Sweden)

    Jihyun HWANG

    2011-11-01

    Full Text Available Ralstonia solanacearum causes one of the most common soil-borne vascular diseases of diverse plant species, including many solanaceous crops such as tomato and pepper. The resulting disease, bacterial wilt (BW, is devastating and difficult to control using conventional approaches. The aim of this study was to investigate the differentially expressed genes in pepper root systems in response to infection by R. solanacearum. DNA microarray (Capsicum annuum 135K Microarray v3.0 Gene Expression platform analyses were performed using a susceptible genotype, ‘Chilbok’, and a resistant genotype, ‘KC350’, at 3 time points (1, 3, and 6 days post inoculation. It has been identified 115 resistance-specific genes (R-response genes and 109 susceptibility-specific genes (S-response gene, which were up-regulated in 1 genotype, but down-regulated in the other genotype. Gene Ontology (GO analysis for functional categorization indicated that many R-response genes were related to genes that function in xyloglucan biosynthesis and cell wall organization, while S-response genes were involved in the response to stress and cell death. The expression of genes encoding xyloglucan endotransglycosylase/hydrolase (XTH and β-galactosidase were verified by real-time RT-PCR at an early time point of R. solanacearum infection. The results supported the idea that rapidly induced XTH expression in ‘KC350’ may play an important role in the restructuring and reinforcement of the cell wall and restrict bacterial movement in xylem vessels. In addition, induced expression of β-galactosidase in R. solanacearum-infected ‘Chilbok’ implied that degradation of the cell wall structure in vascular tissues by β-galactosidase might be an important factor facilitating R. solanacearum invasion of and movement in susceptible host plants.

  17. Nucleic acid sequence detection using multiplexed oligonucleotide PCR

    Science.gov (United States)

    Nolan, John P.; White, P. Scott

    2006-12-26

    Methods for rapidly detecting single or multiple sequence alleles in a sample nucleic acid are described. Provided are all of the oligonucleotide pairs capable of annealing specifically to a target allele and discriminating among possible sequences thereof, and ligating to each other to form an oligonucleotide complex when a particular sequence feature is present (or, alternatively, absent) in the sample nucleic acid. The design of each oligonucleotide pair permits the subsequent high-level PCR amplification of a specific amplicon when the oligonucleotide complex is formed, but not when the oligonucleotide complex is not formed. The presence or absence of the specific amplicon is used to detect the allele. Detection of the specific amplicon may be achieved using a variety of methods well known in the art, including without limitation, oligonucleotide capture onto DNA chips or microarrays, oligonucleotide capture onto beads or microspheres, electrophoresis, and mass spectrometry. Various labels and address-capture tags may be employed in the amplicon detection step of multiplexed assays, as further described herein.

  18. TMA Navigator: Network inference, patient stratification and survival analysis with tissue microarray data.

    Science.gov (United States)

    Lubbock, Alexander L R; Katz, Elad; Harrison, David J; Overton, Ian M

    2013-07-01

    Tissue microarrays (TMAs) allow multiplexed analysis of tissue samples and are frequently used to estimate biomarker protein expression in tumour biopsies. TMA Navigator (www.tmanavigator.org) is an open access web application for analysis of TMA data and related information, accommodating categorical, semi-continuous and continuous expression scores. Non-biological variation, or batch effects, can hinder data analysis and may be mitigated using the ComBat algorithm, which is incorporated with enhancements for automated application to TMA data. Unsupervised grouping of samples (patients) is provided according to Gaussian mixture modelling of marker scores, with cardinality selected by Bayesian information criterion regularization. Kaplan-Meier survival analysis is available, including comparison of groups identified by mixture modelling using the Mantel-Cox log-rank test. TMA Navigator also supports network inference approaches useful for TMA datasets, which often constitute comparatively few markers. Tissue and cell-type specific networks derived from TMA expression data offer insights into the molecular logic underlying pathophenotypes, towards more effective and personalized medicine. Output is interactive, and results may be exported for use with external programs. Private anonymous access is available, and user accounts may be generated for easier data management.

  19. Methanotrophic bacteria associated to rice roots: the cultivar effect assessed by T-RFLP and microarray analysis.

    Science.gov (United States)

    Lüke, Claudia; Bodrossy, Levente; Lupotto, Elisabetta; Frenzel, Peter

    2011-10-01

    Rice plants play a key role in regulating methane emissions from paddy fields by affecting both underlying processes: methane production and oxidation. Specific differences were reported for methane oxidation rates; however, studies on the bacterial communities involved are rare. Here, we analysed the methanotrophic community on the roots of 18 different rice cultivars by pmoA-based terminal restriction fragment length polymorphism (T-RFLP) and microarray analysis. Both techniques showed comparable and consistent results revealing a high diversity dominated by type II and type Ib methanotrophs. pmoA microarrays have been successfully used to study methane-oxidizing bacteria in various environments. However, the microarray's full potential resolving community structure has not been exploited yet. Here, we provide an example on how to include this information into multivariate statistics. The analysis revealed a rice cultivar effect on the methanotroph community composition that could be affiliated to the plant genotype. This effect became only significant by including the specific phylogenetic resolution provided by the microarray into the statistical analysis.

  20. Tissue tablet method: an efficient tissue banking procedure applicable to both molecular analysis and frozen tissue microarray.

    Science.gov (United States)

    Torata, Nobuhiro; Ohuchida, Kenoki; Akagawa, Shin; Cui, Lin; Kozono, Shingo; Mizumoto, Kazuhiro; Aishima, Shinichi; Oda, Yoshinao; Tanaka, Masao

    2014-01-01

    Frozen human tissues are necessary for research purposes, but tissue banking methods have not changed for more than a decade. Many institutions use cryovial tubes or plastic molds with an optimal cutting temperature compound. However, these methods are associated with several problems, such as samples sticking to one another and the need for a larger storing space. We established an efficient tissue freezing and storing procedure ("tissue tablet method") applicable to both molecular analysis and frozen tissue microarray. Tissue samples were chopped into tiny fragments and embedded into tablet-shaped frozen optimal cutting temperature compound using our original tissue-freezing plate. These tablets can be sectioned and stored in cryovial tubes. We compared the tissue quality of tablet-shaped samples with that of conventional optimal cutting temperature blocks and found no significant difference between them. Tissue microarray is a key method to utilize tissue-banking specimens. However, most tissue microarrays require the coring out of cylindrically shaped tissues from formalin-fixed, paraffin-embedded tissue blocks. Antigenic changes and mRNA degradation are frequently observed with formalin-fixed, paraffin-embedded samples. Therefore, we have applied tablet-shaped samples to construct frozen tissue microarrays with our original mounting base. Constructed tissue microarray sections showed good morphology without obvious artifact and good immunohistochemistry and in situ hybridization results. These results suggest that the quality of arrayed samples was sufficiently appropriate for research purposes. In conclusion, the tissue tablet method and frozen tissue microarray procedure can save time, provides easy tissue handling and processing, and satisfies the demands of research methodologies and tissue banking. © 2013.

  1. SIGMA: A System for Integrative Genomic Microarray Analysis of Cancer Genomes

    Directory of Open Access Journals (Sweden)

    Davies Jonathan J

    2006-12-01

    Full Text Available Abstract Background The prevalence of high resolution profiling of genomes has created a need for the integrative analysis of information generated from multiple methodologies and platforms. Although the majority of data in the public domain are gene expression profiles, and expression analysis software are available, the increase of array CGH studies has enabled integration of high throughput genomic and gene expression datasets. However, tools for direct mining and analysis of array CGH data are limited. Hence, there is a great need for analytical and display software tailored to cross platform integrative analysis of cancer genomes. Results We have created a user-friendly java application to facilitate sophisticated visualization and analysis such as cross-tumor and cross-platform comparisons. To demonstrate the utility of this software, we assembled array CGH data representing Affymetrix SNP chip, Stanford cDNA arrays and whole genome tiling path array platforms for cross comparison. This cancer genome database contains 267 profiles from commonly used cancer cell lines representing 14 different tissue types. Conclusion In this study we have developed an application for the visualization and analysis of data from high resolution array CGH platforms that can be adapted for analysis of multiple types of high throughput genomic datasets. Furthermore, we invite researchers using array CGH technology to deposit both their raw and processed data, as this will be a continually expanding database of cancer genomes. This publicly available resource, the System for Integrative Genomic Microarray Analysis (SIGMA of cancer genomes, can be accessed at http://sigma.bccrc.ca.

  2. Gene expression microarray analysis of early oxygen-induced retinopathy in the rat.

    Science.gov (United States)

    Tea, Melinda; Fogarty, Rhys; Brereton, Helen M; Michael, Michael Z; Van der Hoek, Mark B; Tsykin, Anna; Coster, Douglas J; Williams, Keryn A

    2009-12-12

    Different inbred strains of rat differ in their susceptibility to oxygen-induced retinopathy (OIR), an animal model of human retinopathy of prematurity. We examined gene expression in Sprague-Dawley (susceptible) and Fischer 344 (resistant) neonatal rats after 3 days exposure to cyclic hyperoxia or room air, using Affymetrix rat Genearrays. False discovery rate analysis was used to identify differentially regulated genes. Such genes were then ranked by fold change and submitted to the online database, DAVID. The Sprague-Dawley list returned the term "response to hypoxia," absent from the Fischer 344 output. Manual analysis indicated that many genes known to be upregulated by hypoxia-inducible factor-1alpha were downregulated by cyclic hyperoxia. Quantitative real-time RT-PCR analysis of Egln3, Bnip3, Slc16a3, and Hk2 confirmed the microarray results. We conclude that combined methodologies are required for adequate dissection of the pathophysiology of strain susceptibility to OIR in the rat. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s12177-009-9041-7) contains supplementary material, which is available to authorized users.

  3. Microarray-based analysis for hepatocellular carcinoma: From gene expression profiling to new challenges

    Institute of Scientific and Technical Information of China (English)

    Yutaka Midorikawa; Masatoshi Makuuchi; Wei Tang; Hiroyuki Aburatani

    2007-01-01

    Accumulation of mutations and alterations in the expression of various genes result in carcinogenesis, and the development of microarray technology has enabled us to identify the comprehensive gene expression alterations in oncogenesis. Many studies have applied this technology for hepatocellular carcinoma (HCC), and identified a number of candidate genes useful as biomarkers in cancer staging, prediction of recurrence and prognosis, and treatment selection. Some of these target molecules have been used to develop new serum diagnostic markers and therapeutic targets against HCC to benefit patients. Previously, we compared gene expression profiling data with classification based on clinicopathological features, such as hepatitis viral infection or liver cancer progression. The next era of gene expression analysis will require systematic integration of expression profiles with other types of biological information, such as genomic locus, gene function, and sequence information. We have reported integration between expression profiles and locus information, which is effective in detecting structural genomic abnormalities, such as chromosomal gains and losses, in which we showed that gene expression profiles are subject to chromosomal bias. Furthermore, array-based comparative genomic hybridization analysis and allelic dosage analysis using genotyping arrays for HCC were also reviewed, with comparison of conventional methods.

  4. Application of genetic algorithms and constructive neural networks for the analysis of microarray cancer data.

    Science.gov (United States)

    Luque-Baena, Rafael Marcos; Urda, Daniel; Subirats, Jose Luis; Franco, Leonardo; Jerez, Jose M

    2014-05-07

    Extracting relevant information from microarray data is a very complex task due to the characteristics of the data sets, as they comprise a large number of features while few samples are generally available. In this sense, feature selection is a very important aspect of the analysis helping in the tasks of identifying relevant genes and also for maximizing predictive information. Due to its simplicity and speed, Stepwise Forward Selection (SFS) is a widely used feature selection technique. In this work, we carry a comparative study of SFS and Genetic Algorithms (GA) as general frameworks for the analysis of microarray data with the aim of identifying group of genes with high predictive capability and biological relevance. Six standard and machine learning-based techniques (Linear Discriminant Analysis (LDA), Support Vector Machines (SVM), Naive Bayes (NB), C-MANTEC Constructive Neural Network, K-Nearest Neighbors (kNN) and Multilayer perceptron (MLP)) are used within both frameworks using six free-public datasets for the task of predicting cancer outcome. Better cancer outcome prediction results were obtained using the GA framework noting that this approach, in comparison to the SFS one, leads to a larger selection set, uses a large number of comparison between genetic profiles and thus it is computationally more intensive. Also the GA framework permitted to obtain a set of genes that can be considered to be more biologically relevant. Regarding the different classifiers used standard feedforward neural networks (MLP), LDA and SVM lead to similar and best results, while C-MANTEC and k-NN followed closely but with a lower accuracy. Further, C-MANTEC, MLP and LDA permitted to obtain a more limited set of genes in comparison to SVM, NB and kNN, and in particular C-MANTEC resulted in the most robust classifier in terms of changes in the parameter settings. This study shows that if prediction accuracy is the objective, the GA-based approach lead to better results

  5. Synthesis of high-quality libraries of long (150mer) oligonucleotides by a novel depurination controlled process

    National Research Council Canada - National Science Library

    LeProust, Emily M; Peck, Bill J; Spirin, Konstantin; McCuen, Heather Brummel; Moore, Bridget; Namsaraev, Eugeni; Caruthers, Marvin H

    2010-01-01

    ...) in fmol amounts using parallel synthesis of DNA on microarrays. The sequence accuracy of the oligonucleotides in such large-scale syntheses has been limited by the yields and side reactions of the DNA synthesis process used...

  6. Comparative study of joint analysis of microarray gene expression data in survival prediction and risk assessment of breast cancer patients.

    Science.gov (United States)

    Yasrebi, Haleh

    2016-09-01

    Microarray gene expression data sets are jointly analyzed to increase statistical power. They could either be merged together or analyzed by meta-analysis. For a given ensemble of data sets, it cannot be foreseen which of these paradigms, merging or meta-analysis, works better. In this article, three joint analysis methods, Z-score normalization, ComBat and the inverse normal method (meta-analysis) were selected for survival prognosis and risk assessment of breast cancer patients. The methods were applied to eight microarray gene expression data sets, totaling 1324 patients with two clinical endpoints, overall survival and relapse-free survival. The performance derived from the joint analysis methods was evaluated using Cox regression for survival analysis and independent validation used as bias estimation. Overall, Z-score normalization had a better performance than ComBat and meta-analysis. Higher Area Under the Receiver Operating Characteristic curve and hazard ratio were also obtained when independent validation was used as bias estimation. With a lower time and memory complexity, Z-score normalization is a simple method for joint analysis of microarray gene expression data sets. The derived findings suggest further assessment of this method in future survival prediction and cancer classification applications.

  7. Microarray Gene Expression Analysis to Evaluate Cell Type Specific Expression of Targets Relevant for Immunotherapy of Hematological Malignancies.

    Directory of Open Access Journals (Sweden)

    M J Pont

    Full Text Available Cellular immunotherapy has proven to be effective in the treatment of hematological cancers by donor lymphocyte infusion after allogeneic hematopoietic stem cell transplantation and more recently by targeted therapy with chimeric antigen or T-cell receptor-engineered T cells. However, dependent on the tissue distribution of the antigens that are targeted, anti-tumor responses can be accompanied by undesired side effects. Therefore, detailed tissue distribution analysis is essential to estimate potential efficacy and toxicity of candidate targets for immunotherapy of hematological malignancies. We performed microarray gene expression analysis of hematological malignancies of different origins, healthy hematopoietic cells and various non-hematopoietic cell types from organs that are often targeted in detrimental immune responses after allogeneic stem cell transplantation leading to graft-versus-host disease. Non-hematopoietic cells were also cultured in the presence of IFN-γ to analyze gene expression under inflammatory circumstances. Gene expression was investigated by Illumina HT12.0 microarrays and quality control analysis was performed to confirm the cell-type origin and exclude contamination of non-hematopoietic cell samples with peripheral blood cells. Microarray data were validated by quantitative RT-PCR showing strong correlations between both platforms. Detailed gene expression profiles were generated for various minor histocompatibility antigens and B-cell surface antigens to illustrate the value of the microarray dataset to estimate efficacy and toxicity of candidate targets for immunotherapy. In conclusion, our microarray database provides a relevant platform to analyze and select candidate antigens with hematopoietic (lineage-restricted expression as potential targets for immunotherapy of hematological cancers.

  8. Microarray Gene Expression Analysis to Evaluate Cell Type Specific Expression of Targets Relevant for Immunotherapy of Hematological Malignancies.

    Science.gov (United States)

    Pont, M J; Honders, M W; Kremer, A N; van Kooten, C; Out, C; Hiemstra, P S; de Boer, H C; Jager, M J; Schmelzer, E; Vries, R G; Al Hinai, A S; Kroes, W G; Monajemi, R; Goeman, J J; Böhringer, S; Marijt, W A F; Falkenburg, J H F; Griffioen, M

    2016-01-01

    Cellular immunotherapy has proven to be effective in the treatment of hematological cancers by donor lymphocyte infusion after allogeneic hematopoietic stem cell transplantation and more recently by targeted therapy with chimeric antigen or T-cell receptor-engineered T cells. However, dependent on the tissue distribution of the antigens that are targeted, anti-tumor responses can be accompanied by undesired side effects. Therefore, detailed tissue distribution analysis is essential to estimate potential efficacy and toxicity of candidate targets for immunotherapy of hematological malignancies. We performed microarray gene expression analysis of hematological malignancies of different origins, healthy hematopoietic cells and various non-hematopoietic cell types from organs that are often targeted in detrimental immune responses after allogeneic stem cell transplantation leading to graft-versus-host disease. Non-hematopoietic cells were also cultured in the presence of IFN-γ to analyze gene expression under inflammatory circumstances. Gene expression was investigated by Illumina HT12.0 microarrays and quality control analysis was performed to confirm the cell-type origin and exclude contamination of non-hematopoietic cell samples with peripheral blood cells. Microarray data were validated by quantitative RT-PCR showing strong correlations between both platforms. Detailed gene expression profiles were generated for various minor histocompatibility antigens and B-cell surface antigens to illustrate the value of the microarray dataset to estimate efficacy and toxicity of candidate targets for immunotherapy. In conclusion, our microarray database provides a relevant platform to analyze and select candidate antigens with hematopoietic (lineage)-restricted expression as potential targets for immunotherapy of hematological cancers.

  9. Hyperspectral microscopic analysis of normal, benign and carcinoma microarray tissue sections

    Science.gov (United States)

    Maggioni, Mauro; Davis, Gustave L.; Warner, Frederick J.; Geshwind, Frank B.; Coppi, Andreas C.; DeVerse, Richard A.; Coifman, Ronald R.

    2006-02-01

    We apply a unique micro-optoelectromechanical tuned light source and new algorithms to the hyper-spectral microscopic analysis of human colon biopsies. The tuned light prototype (Plain Sight Systems Inc.) transmits any combination of light frequencies, range 440nm 700nm, trans-illuminating H and E stained tissue sections of normal (N), benign adenoma (B) and malignant carcinoma (M) colon biopsies, through a Nikon Biophot microscope. Hyper-spectral photomicrographs, randomly collected 400X magnication, are obtained with a CCD camera (Sensovation) from 59 different patient biopsies (20 N, 19 B, 20 M) mounted as a microarray on a single glass slide. The spectra of each pixel are normalized and analyzed to discriminate among tissue features: gland nuclei, gland cytoplasm and lamina propria/lumens. Spectral features permit the automatic extraction of 3298 nuclei with classification as N, B or M. When nuclei are extracted from each of the 59 biopsies the average classification among N, B and M nuclei is 97.1%; classification of the biopsies, based on the average nuclei classification, is 100%. However, when the nuclei are extracted from a subset of biopsies, and the prediction is made on nuclei in the remaining biopsies, there is a marked decrement in performance to 60% across the 3 classes. Similarly the biopsy classification drops to 54%. In spite of these classification differences, which we believe are due to instrument and biopsy normalization issues, hyper-spectral analysis has the potential to achieve diagnostic efficiency needed for objective microscopic diagnosis.

  10. Multi-tissue microarray analysis identifies a molecular signature of regeneration.

    Directory of Open Access Journals (Sweden)

    Sarah E Mercer

    Full Text Available The inability to functionally repair tissues that are lost as a consequence of disease or injury remains a significant challenge for regenerative medicine. The molecular and cellular processes involved in complete restoration of tissue architecture and function are expected to be complex and remain largely unknown. Unlike humans, certain salamanders can completely regenerate injured tissues and lost appendages without scar formation. A parsimonious hypothesis would predict that all of these regenerative activities are regulated, at least in part, by a common set of genes. To test this hypothesis and identify genes that might control conserved regenerative processes, we performed a comprehensive microarray analysis of the early regenerative response in five regeneration-competent tissues from the newt Notophthalmus viridescens. Consistent with this hypothesis, we established a molecular signature for regeneration that consists of common genes or gene family members that exhibit dynamic differential regulation during regeneration in multiple tissue types. These genes include members of the matrix metalloproteinase family and its regulators, extracellular matrix components, genes involved in controlling cytoskeleton dynamics, and a variety of immune response factors. Gene Ontology term enrichment analysis validated and supported their functional activities in conserved regenerative processes. Surprisingly, dendrogram clustering and RadViz classification also revealed that each regenerative tissue had its own unique temporal expression profile, pointing to an inherent tissue-specific regenerative gene program. These new findings demand a reconsideration of how we conceptualize regenerative processes and how we devise new strategies for regenerative medicine.

  11. Multi-Tissue Microarray Analysis Identifies a Molecular Signature of Regeneration

    Science.gov (United States)

    Mercer, Sarah E.; Cheng, Chia-Ho; Atkinson, Donald L.; Krcmery, Jennifer; Guzman, Claudia E.; Kent, David T.; Zukor, Katherine; Marx, Kenneth A.; Odelberg, Shannon J.; Simon, Hans-Georg

    2012-01-01

    The inability to functionally repair tissues that are lost as a consequence of disease or injury remains a significant challenge for regenerative medicine. The molecular and cellular processes involved in complete restoration of tissue architecture and function are expected to be complex and remain largely unknown. Unlike humans, certain salamanders can completely regenerate injured tissues and lost appendages without scar formation. A parsimonious hypothesis would predict that all of these regenerative activities are regulated, at least in part, by a common set of genes. To test this hypothesis and identify genes that might control conserved regenerative processes, we performed a comprehensive microarray analysis of the early regenerative response in five regeneration-competent tissues from the newt Notophthalmus viridescens. Consistent with this hypothesis, we established a molecular signature for regeneration that consists of common genes or gene family members that exhibit dynamic differential regulation during regeneration in multiple tissue types. These genes include members of the matrix metalloproteinase family and its regulators, extracellular matrix components, genes involved in controlling cytoskeleton dynamics, and a variety of immune response factors. Gene Ontology term enrichment analysis validated and supported their functional activities in conserved regenerative processes. Surprisingly, dendrogram clustering and RadViz classification also revealed that each regenerative tissue had its own unique temporal expression profile, pointing to an inherent tissue-specific regenerative gene program. These new findings demand a reconsideration of how we conceptualize regenerative processes and how we devise new strategies for regenerative medicine. PMID:23300656

  12. A meta analysis of pancreatic microarray datasets yields new targets as cancer genes and biomarkers.

    Directory of Open Access Journals (Sweden)

    Nalin C W Goonesekere

    Full Text Available The lack of specific symptoms at early tumor stages, together with a high biological aggressiveness of the tumor contribute to the high mortality rate for pancreatic cancer (PC, which has a five year survival rate of less than 5%. Improved screening for earlier diagnosis, through the detection of diagnostic and prognostic biomarkers provides the best hope of increasing the rate of curatively resectable carcinomas. Though many serum markers have been reported to be elevated in patients with PC, so far, most of these markers have not been implemented into clinical routine due to low sensitivity or specificity. In this study, we have identified genes that are significantly upregulated in PC, through a meta-analysis of large number of microarray datasets. We demonstrate that the biological functions ascribed to these genes are clearly associated with PC and metastasis, and that that these genes exhibit a strong link to pathways involved with inflammation and the immune response. This investigation has yielded new targets for cancer genes, and potential biomarkers for pancreatic cancer. The candidate list of cancer genes includes protein kinase genes, new members of gene families currently associated with PC, as well as genes not previously linked to PC. In this study, we are also able to move towards developing a signature for hypomethylated genes, which could be useful for early detection of PC. We also show that the significantly upregulated 800+ genes in our analysis can serve as an enriched pool for tissue and serum protein biomarkers in pancreatic cancer.

  13. DNA microarray global gene expression analysis of influenza virus-infected chicken and duck cells

    Directory of Open Access Journals (Sweden)

    Suresh V. Kuchipudi

    2015-06-01

    Full Text Available The data described in this article pertain to the article by Kuchipudi et al. (2014 titled “Highly Pathogenic Avian Influenza Virus Infection in Chickens But Not Ducks Is Associated with Elevated Host Immune and Pro-inflammatory Responses” [1]. While infection of chickens with highly pathogenic avian influenza (HPAI H5N1 virus subtypes often leads to 100% mortality within 1 to 2 days, infection of ducks in contrast causes mild or no clinical signs. The rapid onset of fatal disease in chickens, but with no evidence of severe clinical symptoms in ducks, suggests underlying differences in their innate immune mechanisms. We used Chicken Genechip microarrays (Affymetrix to analyse the gene expression profiles of primary chicken and duck lung cells infected with a low pathogenic avian influenza (LPAI H2N3 virus and two HPAI H5N1 virus subtypes to understand the molecular basis of host susceptibility and resistance in chickens and ducks. Here, we described the experimental design, quality control and analysis that were performed on the data set. The data are publicly available through the Gene Expression Omnibus (GEOdatabase with accession number GSE33389, and the analysis and interpretation of these data are included in Kuchipudi et al. (2014 [1].

  14. Microarray analysis of pancreatic gene expression during biotin repletion in biotin-deficient rats.

    Science.gov (United States)

    Dakshinamurti, Krishnamurti; Bagchi, Rushita A; Abrenica, Bernard; Czubryt, Michael P

    2015-12-01

    Biotin is a B vitamin involved in multiple metabolic pathways. In humans, biotin deficiency is relatively rare but can cause dermatitis, alopecia, and perosis. Low biotin levels occur in individuals with type-2 diabetes, and supplementation with biotin plus chromium may improve blood sugar control. The acute effect on pancreatic gene expression of biotin repletion following chronic deficiency is unclear, therefore we induced biotin deficiency in adult male rats by feeding them a 20% raw egg white diet for 6 weeks. Animals were then randomized into 2 groups: one group received a single biotin supplement and returned to normal chow lacking egg white, while the second group remained on the depletion diet. After 1 week, pancreata were removed from biotin-deficient (BD) and biotin-repleted (BR) animals and RNA was isolated for microarray analysis. Biotin depletion altered gene expression in a manner indicative of inflammation, fibrosis, and defective pancreatic function. Conversely, biotin repletion activated numerous repair and anti-inflammatory pathways, reduced fibrotic gene expression, and induced multiple genes involved in pancreatic endocrine and exocrine function. A subset of the results was confirmed by quantitative real-time PCR analysis, as well as by treatment of pancreatic AR42J cells with biotin. The results indicate that biotin repletion, even after lengthy deficiency, results in the rapid induction of repair processes in the pancreas.

  15. Microarray-based analysis of microRNA expression in breast cancer stem cells

    Directory of Open Access Journals (Sweden)

    Wang Zhi-xin

    2010-12-01

    Full Text Available Abstract Background This study aimed to determine the miRNA profile in breast cancer stem cells (BCSCs and to explore the functions of characteristic BCSC miRNAs. Methods We isolated ESA+CD44+CD24-/low BCSCs from MCF-7 cells using fluorescence-activated cell sorting (FACS. A human breast cancer xenograft assay was performed to validate the stem cell properties of the isolated cells, and microarray analysis was performed to screen for BCSC-related miRNAs. These BCSC-related miRNAs were selected for bioinformatic analysis and target prediction using online software programs. Results The ESA+CD44+CD24-/low cells had up to 100- to 1000-fold greater tumor-initiating capability than the MCF-7 cells. Tumors initiated from the ESA+CD44+CD24-/low cells were included of luminal epithelial and myoepithelial cells, indicating stem cell properties. We also obtained miRNA profiles of ESA+CD44+CD24-/low BCSCs. Most of the possible targets of potential tumorigenesis-related miRNAs were oncogenes, anti-oncogenes or regulatory genes. Conclusions We identified a subset of miRNAs that were differentially expressed in BCSCs, providing a starting point to explore the functions of these miRNAs. Evaluating characteristic BCSC miRNAs represents a new method for studying breast cancer-initiating cells and developing therapeutic strategies aimed at eradicating the tumorigenic subpopulation of cells in breast cancer.

  16. A Comprehensive Comparison of Different Clustering Methods for Reliability Analysis of Microarray Data

    Science.gov (United States)

    Kafieh, Rahele; Mehridehnavi, Alireza

    2013-01-01

    In this study, we considered some competitive learning methods including hard competitive learning and soft competitive learning with/without fixed network dimensionality for reliability analysis in microarrays. In order to have a more extensive view, and keeping in mind that competitive learning methods aim at error minimization or entropy maximization (different kinds of function optimization), we decided to investigate the abilities of mixture decomposition schemes. Therefore, we assert that this study covers the algorithms based on function optimization with particular insistence on different competitive learning methods. The destination is finding the most powerful method according to a pre-specified criterion determined with numerical methods and matrix similarity measures. Furthermore, we should provide an indication showing the intrinsic ability of the dataset to form clusters before we apply a clustering algorithm. Therefore, we proposed Hopkins statistic as a method for finding the intrinsic ability of a data to be clustered. The results show the remarkable ability of Rayleigh mixture model in comparison with other methods in reliability analysis task. PMID:24083134

  17. Meta-Analysis of Multiple Sclerosis Microarray Data Reveals Dysregulation in RNA Splicing Regulatory Genes.

    Science.gov (United States)

    Paraboschi, Elvezia Maria; Cardamone, Giulia; Rimoldi, Valeria; Gemmati, Donato; Spreafico, Marta; Duga, Stefano; Soldà, Giulia; Asselta, Rosanna

    2015-09-30

    Abnormalities in RNA metabolism and alternative splicing (AS) are emerging as important players in complex disease phenotypes. In particular, accumulating evidence suggests the existence of pathogenic links between multiple sclerosis (MS) and altered AS, including functional studies showing that an imbalance in alternatively-spliced isoforms may contribute to disease etiology. Here, we tested whether the altered expression of AS-related genes represents a MS-specific signature. A comprehensive comparative analysis of gene expression profiles of publicly-available microarray datasets (190 MS cases, 182 controls), followed by gene-ontology enrichment analysis, highlighted a significant enrichment for differentially-expressed genes involved in RNA metabolism/AS. In detail, a total of 17 genes were found to be differentially expressed in MS in multiple datasets, with CELF1 being dysregulated in five out of seven studies. We confirmed CELF1 downregulation in MS (p=0.0015) by real-time RT-PCRs on RNA extracted from blood cells of 30 cases and 30 controls. As a proof of concept, we experimentally verified the unbalance in alternatively-spliced isoforms in MS of the NFAT5 gene, a putative CELF1 target. In conclusion, for the first time we provide evidence of a consistent dysregulation of splicing-related genes in MS and we discuss its possible implications in modulating specific AS events in MS susceptibility genes.

  18. Chromosomal microarray analysis in a girl with mental retardation and spina bifida.

    Science.gov (United States)

    Ben Abdallah, Inesse; Hannachi, Hanene; Soyah, Najla; Saad, Ali; Elghezal, Hatem

    2011-01-01

    Chromosomal imbalances comprise a major cause of mental retardation, particularly in association with congenital malformations and dysmorphic features. Chromosomal analysis using banded karyotyping is limited by the low resolution of this technique, and cryptic chromosomal rearrangements cannot be detected. We describe a 6-year-old girl with mental retardation, mild growth, congenital malformation, and facial anomalies. Chromosomal analysis with karyotyping produced normal results. Because the phenotype suggested chromosomal abnormality, microarray comparative genomic hybridization was used to search for a possible cryptic anomaly. A subtelomeric chromosomal imbalance, consisting of partial trisomy 2q35 and partial monosomy 3p26, was detected and confirmed using fluorescence in situ hybridization. This rearrangement was inherited from an equilibrated maternal t(2;3) reciprocal translocation. Comparative genomic hybridization array in similar situations is useful in detecting cryptic chromosomal rearrangements, identifying genes contained in deleted or duplicated regions, establishing a precise phenotype-genotype correlation, and offering unambiguous genetic counseling. Copyright © 2011 Elsevier Inc. All rights reserved.

  19. A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability

    NARCIS (Netherlands)

    H.M.J. Sontrop; P.D. Moerland; R. van den Ham; M.J.T. Reinders; W.F.J. Verhaegh

    2009-01-01

    Background: Large discrepancies in signature composition and outcome concordance have been observed between different microarray breast cancer expression profiling studies. This is often ascribed to differences in array platform as well as biological variability. We conjecture that other reasons for

  20. Discovery and analysis of inflammatory disease-related genes using cDNA microarrays

    OpenAIRE

    1997-01-01

    cDNA microarray technology is used to profile complex diseases and discover novel disease-related genes. In inflammatory disease such as rheumatoid arthritis, expression patterns of diverse cell types contribute to the pathology. We have monitored gene expression in this disease state with a microarray of selected human genes of probable significance in inflammation as well as with genes expressed in peripheral human blood cells. Messenger RNA from cultured macrophages, chondrocyte cell lines...

  1. Design, construction and validation of a Plasmodium vivax microarray for the transcriptome profiling of clinical isolates.

    Science.gov (United States)

    Boopathi, Pon Arunachalam; Subudhi, Amit Kumar; Middha, Sheetal; Acharya, Jyoti; Mugasimangalam, Raja Chinnadurai; Kochar, Sanjay Kumar; Kochar, Dhanpat Kumar; Das, Ashis

    2016-12-01

    High density oligonucleotide microarrays have been used on Plasmodium vivax field isolates to estimate whole genome expression. However, no microarray platform has been experimentally optimized for studying the transcriptome of field isolates. In the present study, we adopted both bioinformatics and experimental testing approaches to select best optimized probes suitable for detecting parasite transcripts from field samples and included them in designing a custom 15K P. vivax microarray. This microarray has long oligonucleotide probes (60mer) that were in-situ synthesized onto glass slides using Agilent SurePrint technology and has been developed into an 8X15K format (8 identical arrays on a single slide). Probes in this array were experimentally validated and represents 4180 P. vivax genes in sense orientation, of which 1219 genes have also probes in antisense orientation. Validation of the 15K array by using field samples (n=14) has shown 99% of parasite transcript detection from any of the samples. Correlation analysis between duplicate probes (n=85) present in the arrays showed perfect correlation (r(2)=0.98) indicating the reproducibility. Multiple probes representing the same gene exhibited similar kind of expression pattern across the samples (positive correlation, r≥0.6). Comparison of hybridization data with the previous studies and quantitative real-time PCR experiments were performed to highlight the microarray validation procedure. This array is unique in its design, and results indicate that the array is sensitive and reproducible. Hence, this microarray could be a valuable functional genomics tool to generate reliable expression data from P. vivax field isolates.

  2. Design, construction and validation of a Plasmodium vivax microarray for the transcriptome profiling of clinical isolates

    KAUST Repository

    Boopathi, Pon Arunachalam

    2016-10-09

    High density oligonucleotide microarrays have been used on Plasmodium vivax field isolates to estimate whole genome expression. However, no microarray platform has been experimentally optimized for studying the transcriptome of field isolates. In the present study, we adopted both bioinformatics and experimental testing approaches to select best optimized probes suitable for detecting parasite transcripts from field samples and included them in designing a custom 15K P. vivax microarray. This microarray has long oligonucleotide probes (60 mer) that were in-situ synthesized onto glass slides using Agilent SurePrint technology and has been developed into an 8X15K format (8 identical arrays on a single slide). Probes in this array were experimentally validated and represents 4180 P. vivax genes in sense orientation, of which 1219 genes have also probes in antisense orientation. Validation of the 15K array by using field samples (n =14) has shown 99% of parasite transcript detection from any of the samples. Correlation analysis between duplicate probes (n = 85) present in the arrays showed perfect correlation (r(2) = 0.98) indicating the reproducibility. Multiple probes representing the same gene exhibited similar kind of expression pattern across the samples (positive correlation, r >= 0.6). Comparison of hybridization data with the previous studies and quantitative real-time PCR experiments were performed to highlight the microarray validation procedure. This array is unique in its design, and results indicate that the array is sensitive and reproducible. Hence, this microarray could be a valuable functional genomics tool to generate reliable expression data from P. vivax field isolates. (C) 2016 Published by Elsevier B.V.

  3. Use of non-amplified RNA samples for microarray analysis of gene expression.

    Directory of Open Access Journals (Sweden)

    Hiroko Sudo

    Full Text Available Demand for high quality gene expression data has driven the development of revolutionary microarray technologies. The quality of the data is affected by the performance of the microarray platform as well as how the nucleic acid targets are prepared. The most common method for target nucleic acid preparation includes in vitro transcription amplification of the sample RNA. Although this method requires a small amount of starting material and is reported to have high reproducibility, there are also technical disadvantages such as amplification bias and the long, laborious protocol. Using RNA derived from human brain, breast and colon, we demonstrate that a non-amplification method, which was previously shown to be inferior, could be transformed to a highly quantitative method with a dynamic range of five orders of magnitude. Furthermore, the correlation coefficient calculated by comparing microarray assays using non-amplified samples with qRT-PCR assays was approximately 0.9, a value much higher than when samples were prepared using amplification methods. Our results were also compared with data from various microarray platforms studied in the MicroArray Quality Control (MAQC project. In combination with micro-columnar 3D-Gene™ microarray, this non-amplification method is applicable to a variety of genetic analyses, including biomarker screening and diagnostic tests for cancer.

  4. Identification of target genes conferring ethanol stress tolerance to Saccharomyces cerevisiae based on DNA microarray data analysis.

    Science.gov (United States)

    Hirasawa, Takashi; Yoshikawa, Katsunori; Nakakura, Yuki; Nagahisa, Keisuke; Furusawa, Chikara; Katakura, Yoshio; Shimizu, Hiroshi; Shioya, Suteaki

    2007-08-01

    During industrial production process using yeast, cells are exposed to the stress due to the accumulation of ethanol, which affects the cell growth activity and productivity of target products, thus, the ethanol stress-tolerant yeast strains are highly desired. To identify the target gene(s) for constructing ethanol stress tolerant yeast strains, we obtained the gene expression profiles of two strains of Saccharomyces cerevisiae, namely, a laboratory strain and a strain used for brewing Japanese rice wine (sake), in the presence of 5% (v/v) ethanol, using DNA microarray. For the selection of target genes for breeding ethanol stress tolerant strains, clustering of DNA microarray data was performed. For further selection, the ethanol sensitivity of the knockout mutants in each of which the gene selected by DNA microarray analysis is deleted, was also investigated. The integration of the DNA microarray data and the ethanol sensitivity data of knockout strains suggests that the enhancement of expression of genes related to tryptophan biosynthesis might confer the ethanol stress tolerance to yeast cells. Indeed, the strains overexpressing tryptophan biosynthesis genes showed a stress tolerance to 5% ethanol. Moreover, the addition of tryptophan to the culture medium and overexpression of tryptophan permease gene conferred ethanol stress tolerance to yeast cells. These results indicate that overexpression of the genes for trypophan biosynthesis increases the ethanol stress tolerance. Tryptophan supplementation to culture and overexpression of the tryptophan permease gene are also effective for the increase in ethanol stress tolerance. Our methodology for the selection of target genes for constructing ethanol stress tolerant strains, based on the data of DNA microarray analysis and phenotypes of knockout mutants, was validated.

  5. SaDA: From Sampling to Data Analysis-An Extensible Open Source Infrastructure for Rapid, Robust and Automated Management and Analysis of Modern Ecological High-Throughput Microarray Data.

    Science.gov (United States)

    Singh, Kumar Saurabh; Thual, Dominique; Spurio, Roberto; Cannata, Nicola

    2015-06-03

    One of the most crucial characteristics of day-to-day laboratory information management is the collection, storage and retrieval of information about research subjects and environmental or biomedical samples. An efficient link between sample data and experimental results is absolutely important for the successful outcome of a collaborative project. Currently available software solutions are largely limited to large scale, expensive commercial Laboratory Information Management Systems (LIMS). Acquiring such LIMS indeed can bring laboratory information management to a higher level, but most of the times this requires a sufficient investment of money, time and technical efforts. There is a clear need for a light weighted open source system which can easily be managed on local servers and handled by individual researchers. Here we present a software named SaDA for storing, retrieving and analyzing data originated from microorganism monitoring experiments. SaDA is fully integrated in the management of environmental samples, oligonucleotide sequences, microarray data and the subsequent downstream analysis procedures. It is simple and generic software, and can be extended and customized for various environmental and biomedical studies.

  6. Comparative genomics in chicken and Pekin duck using FISH mapping and microarray analysis

    Directory of Open Access Journals (Sweden)

    Fowler Katie E

    2009-08-01

    Full Text Available Abstract Background The availability of the complete chicken (Gallus gallus genome sequence as well as a large number of chicken probes for fluorescent in-situ hybridization (FISH and microarray resources facilitate comparative genomic studies between chicken and other bird species. In a previous study, we provided a comprehensive cytogenetic map for the turkey (Meleagris gallopavo and the first analysis of copy number variants (CNVs in birds. Here, we extend this approach to the Pekin duck (Anas platyrhynchos, an obvious target for comparative genomic studies due to its agricultural importance and resistance to avian flu. Results We provide a detailed molecular cytogenetic map of the duck genome through FISH assignment of 155 chicken clones. We identified one inter- and six intrachromosomal rearrangements between chicken and duck macrochromosomes and demonstrated conserved synteny among all microchromosomes analysed. Array comparative genomic hybridisation revealed 32 CNVs, of which 5 overlap previously designated "hotspot" regions between chicken and turkey. Conclusion Our results suggest extensive conservation of avian genomes across 90 million years of evolution in both macro- and microchromosomes. The data on CNVs between chicken and duck extends previous analyses in chicken and turkey and supports the hypotheses that avian genomes contain fewer CNVs than mammalian genomes and that genomes of evolutionarily distant species share regions of copy number variation ("CNV hotspots". Our results will expedite duck genomics, assist marker development and highlight areas of interest for future evolutionary and functional studies.

  7. Surface ligation-based resonance light scattering analysis of methylated genomic DNA on a microarray platform.

    Science.gov (United States)

    Ma, Lan; Lei, Zhen; Liu, Xia; Liu, Dianjun; Wang, Zhenxin

    2016-05-10

    DNA methylation is a crucial epigenetic modification and is closely related to tumorigenesis. Herein, a surface ligation-based high throughput method combined with bisulfite treatment is developed for analysis of methylated genomic DNA. In this method, a DNA microarray is employed as a reaction platform, and resonance light scattering (RLS) of nanoparticles is used as the detection principle. The specificity stems from allele-specific ligation of Taq DNA ligase, which is further enhanced by improving the fidelity of Taq DNA ligase in a heterogeneous reaction. Two amplification techniques, rolling circle amplification (RCA) and silver enhancement, are employed after the ligation reaction and a gold nanoparticle (GNP) labeling procedure is used to amplify the signal. As little as 0.01% methylated DNA (i.e. 2 pmol L(-1)) can be distinguished from the cocktail of methylated and unmethylated DNA by the proposed method. More importantly, this method shows good accuracy and sensitivity in profiling the methylation level of genomic DNA of three selected colonic cancer cell lines. This strategy provides a high throughput alternative with reasonable sensitivity and resolution for cancer study and diagnosis.

  8. Expression analysis of URI/RMP gene in endometrioid adenocarcinoma by tissue microarray immunohistochemistry.

    Science.gov (United States)

    Gu, Junxia; Liang, Yuting; Qiao, Longwei; Li, Xiaoyun; Li, Xingang; Lu, Yaojuan; Zheng, Qiping

    2013-01-01

    Multiple studies have recently demonstrated the oncogenic property of URI (or RMP, a member of the prefoldin family of molecular chaperones) during progression of hepatocellular carcinoma, ovarian cancer, and possibly prostate cancer. Most recently, we have shown that URI/RMP is up-regulated in cervical cancer, another reproductive system tumor beside ovarian and prostate cancers. To investigate if URI/RMP also plays a role in other reproductive system tumors, especially in endometrioid adenocarcinoma, we analyzed URI/RMP expression in a TMA (tissue microarray) containing tissues from 30 cases of endometrioid adenocarcinoma (which covers tumor tissues from Grade I through Grade III) and adjacent endometrium by immunohistochemistry (IHC) and densitometry analysis using image-pro plus 6.0 software. Our results showed that the mean density of URI/RMP expression in cancerous tissue is slightly higher than that of the adjacent endometrial tissue, though not statistically significant (p>0.05). There is no significant difference either between the mean density of Grade III cancerous tissue and that of Grade I and II cancers. Notably, we detected significantly higher signal intensity in cancerous tissue of all 7 Grade III cases than that of their adjacent endometrial tissue (ptissues of adjacent endometrium or gland suggests a diagnostic and possibly, a prognostic value of URI/RMP in endometrioid adenocarcinoma.

  9. Microarray Analysis Reveals the Molecular Basis of Antiarthritic Activity of Huo-Luo-Xiao-Ling Dan

    Directory of Open Access Journals (Sweden)

    Hua Yu

    2013-01-01

    Full Text Available Rheumatoid arthritis (RA is a chronic inflammatory disease of autoimmune origin. Huo-luo-xiao-ling dan (HLXL is an herbal mixture that has been used in traditional Chinese medicine over several decades to treat chronic inflammatory diseases including RA. However, the mechanism of the anti-arthritic action of this herbal remedy is poorly understood at the molecular level. In this study, we determined by microarray analysis the effects of HLXL on the global gene expression profile of the draining lymph node cells (LNC in the rat adjuvant arthritis (AA model of human RA. In LNC restimulated in vitro with the disease-related antigen mycobacterial heat-shock protein 65 (Bhsp65, 84 differentially expressed genes (DEG (64 upregulated and 20 downregulated versus 120 DEG (94 upregulated and 26 downregulated were identified in HLXL-treated versus vehicle (Water-treated rats, respectively, and 62 DEG (45 upregulated and 17 downregulated were shared between the two groups. The most affected pathways in response to HLXL treatment included immune response, inflammation, cellular proliferation and apoptosis, and metabolic processes, many of which are directly relevant to arthritis pathogenesis. These results would advance our understanding of the mechanisms underlying the anti-arthritic activity of HLXL.

  10. Microarray Analysis of Transcriptional Responses to Abscisic Acid and Salt Stress in Arabidopsis thaliana

    Directory of Open Access Journals (Sweden)

    Yucheng Wang

    2013-05-01

    Full Text Available Abscisic acid (ABA plays a crucial role in plant responses to abiotic stress. To investigate differences in plant responses to salt and ABA stimulus, differences in gene expression in Arabidopsis in response to salt and ABA were compared using an Agilent oligo microarray. A total of 144 and 139 genes were significantly up- and downregulated, respectively, under NaCl stress, while 406 and 381 genes were significantly up- and downregulated, respectively, under ABA stress conditions. In addition, 31 genes were upregulated by both NaCl and ABA stresses, and 23 genes were downregulated by these stressors, suggesting that these genes may play similar roles in plant responses to salt and ABA stress. Gene ontology (GO analysis revealed four subgroups of genes, including genes in the GO categories “Molecular transducer activity”, “Growth”, “Biological adhesion” and “Pigmentation”, which were expressed in response to ABA stress but not NaCl stress. In addition, genes that play specific roles during salt or ABA stress were identified. Our results may help elucidate differences in the response of plants to salt and ABA stress.

  11. Identification of Cell Surface Targets through Meta-analysis of Microarray Data

    Directory of Open Access Journals (Sweden)

    Henry Haeberle

    2012-07-01

    Full Text Available High-resolution image guidance for resection of residual tumor cells would enable more precise and complete excision for more effective treatment of cancers, such as medulloblastoma, the most common pediatric brain cancer. Numerous studies have shown that brain tumor patient outcomes correlate with the precision of resection. To enable guided resection with molecular specificity and cellular resolution, molecular probes that effectively delineate brain tumor boundaries are essential. Therefore, we developed a bioinformatics approach to analyze micro-array datasets for the identification of transcripts that encode candidate cell surface biomarkers that are highly enriched in medulloblastoma. The results identified 380 genes with greater than a two-fold increase in the expression in the medulloblastoma compared with that in the normal cerebellum. To enrich for targets with accessibility for extracellular molecular probes, we further refined this list by filtering it with gene ontology to identify genes with protein localization on, or within, the plasma membrane. To validate this meta-analysis, the top 10 candidates were evaluated with immunohistochemistry. We identified two targets, fibrillin 2 and EphA3, which specifically stain medulloblastoma. These results demonstrate a novel bioinformatics approach that successfully identified cell surface and extracellular candidate markers enriched in medulloblastoma versus adjacent cerebellum. These two proteins are high-value targets for the development of tumor-specific probes in medulloblastoma. This bioinformatics method has broad utility for the identification of accessible molecular targets in a variety of cancers and will enable probe development for guided resection.

  12. Analysis of Protein Glycosylation and Phosphorylation Using Liquid Phase Separation, Protein Microarray Technology, and Mass Spectrometry

    Science.gov (United States)

    Zhao, Jia; Patwa, Tasneem H.; Pal, Manoj; Qiu, Weilian; Lubman, David M.

    2010-01-01

    Summary Protein glycosylation and phosphorylation are very common posttranslational modifications. The alteration of these modifications in cancer cells is closely related to the onset and progression of cancer and other disease states. In this protocol, strategies for monitoring the changes in protein glycosylation and phosphorylation in serum or tissue cells on a global scale and specifically characterizing these alterations are included. The technique is based on lectin affinity enrichment for glycoproteins, all liquid-phase two-dimensional fractionation, protein microarray, and mass spectrometry technology. Proteins are separated based on pI in the first dimension using chromatofocusing (CF) or liquid isoelectric focusing (IEF) followed by the second-dimension separation using nonporous silica RP-HPLC. Five lectins with different binding specificities to glycan structures are used for screening glycosylation patterns in human serum through a biotin–streptavidin system. Fluorescent phosphodyes and phosphospecific antibodies are employed to detect specific phosphorylated proteins in cell lines or human tissues. The purified proteins of interest are identified by peptide sequencing. Their modifications including glycosylation and phosphorylation could be further characterized by mass-spectrometry-based approaches. These strategies can be used in biological samples for large-scale glycoproteome/phosphoproteome screening as well as for individual protein modification analysis. PMID:19241043

  13. Protective Effect of Gwakhyangjeonggisan Herbal Acupuncture Solution in Glioblastoma Cells: Microarray Analysis of Gene Expression

    Directory of Open Access Journals (Sweden)

    Hong-Seok Lee

    2005-12-01

    Full Text Available Objectives : Neurological disorders have been one of main therapeutic targets of acupuncture. The present study investigated the protective effects of Gwakhyangjeonggisan herbal acupuncture solution (GHAS. Methods : We performed 3-(4,5-dimethylthiazol-2-yl-2,5-diphenyltetrazolium bromide (MTT assay in glioblastoma cells, and did microarray analysis with cells exposed to reactive oxigen species (ROS of hydrogen peroxide by 8.0 k Human cDNA, with cut-off level of 2-fold changes in gene expression. Results : MTT assay showed protective effect of GHAS on the glioblastoma cells exposed to hydrogen peroxide. When glioblastoma cells were exposed to hydrogen peroxide, 24 genes were downregulated. When the cells were pretreated with GHAS before exposure to hydrogen peroxide, 46 genes were downregulated. Many of the genes downregulated by hydrogen peroxide stimulation were decreased in the amount of downregulation or reversed to upregulation. Conclusions : The gene expression changes observed in the present study are supposed to be related to the protective molecular mechanism of GHAS in the glioblastoma cells exposed to ROS stress.

  14. Knowledge-based analysis of microarray gene expression data by using support vector machines

    Energy Technology Data Exchange (ETDEWEB)

    William Grundy; Manuel Ares, Jr.; David Haussler

    2001-06-18

    The authors introduce a method of functionally classifying genes by using gene expression data from DNA microarray hybridization experiments. The method is based on the theory of support vector machines (SVMs). SVMs are considered a supervised computer learning method because they exploit prior knowledge of gene function to identify unknown genes of similar function from expression data. SVMs avoid several problems associated with unsupervised clustering methods, such as hierarchical clustering and self-organizing maps. SVMs have many mathematical features that make them attractive for gene expression analysis, including their flexibility in choosing a similarity function, sparseness of solution when dealing with large data sets, the ability to handle large feature spaces, and the ability to identify outliers. They test several SVMs that use different similarity metrics, as well as some other supervised learning methods, and find that the SVMs best identify sets of genes with a common function using expression data. Finally, they use SVMs to predict functional roles for uncharacterized yeast ORFs based on their expression data.

  15. Protein turnover in atrophying muscle: from nutritional intervention to microarray expression analysis

    Science.gov (United States)

    Stein, T. Peter; Wade, Charles E.

    2003-01-01

    PURPOSE OF REVIEW: In response to decreased usage, skeletal muscle undergoes adaptive reductive remodeling due to the decrease in tension on the weight bearing components of the musculo-skeletal system. This response occurs with uncomplicated disuse (e.g. bed rest, space flight), as a secondary consequence of several widely prevalent chronic diseases for which activity is reduced (e.g. chronic obstructive pulmonary disease and chronic heart failure) and is part of the aging process. The problem is therefore one of considerable clinical importance. RECENT FINDINGS: The impaired function and exercise intolerance is related more to the associated muscle wasting rather than to the specific organ system primarily impacted by the disease. Progress has continued in describing the use of anabolic drugs and dietary manipulation. The major advance in the field has been: (i) the discovery of the atrogin-1 gene and (ii) the application of microarray expression analysis and proteomics with the objectives of obtaining comprehensive understanding of the pathways changed with disuse atrophy. SUMMARY: Disuse atrophy is a common clinical problem. There is a need for therapeutic interventions that do not involve exercise. A better understanding of the changes, particularly at the molecular level, could indicate hitherto unsuspected sites for nutritional and pharmacological intervention.

  16. The Impact of the Preprocessing Methods in Downstream Analysis of Agilent Microarray Data

    Directory of Open Access Journals (Sweden)

    Loredana BĂLĂCESCU

    2015-12-01

    Full Text Available Over the past decades, gene expression microarrays have been used extensively in biomedical research. However, these high-throughput experiments are affected by technical variation and biases introduced at different levels, such as mRNA processing, labeling, hybridization, scanning and/or imaging. Therefore, data preprocessing is important to minimize these systematic errors in order to identify actual biological changes. The aim of this study was to compare all possible combinations of two normalization, four summarization, and two background correction options, using two different foreground estimates. The results shows that the background correction of the raw median signal and summarization methods used here have no impact in downstream analysis. In contrast, the choice of the normalization method influences the results; the quantile normalization leading to a better biological sensitivity of the data. When Agilent processed signal was considered, regardless of the summarization and normalization options, there were consistently identified more differentially expressed genes (DEG than when raw median signal was used. Nevertheless, the greater number of DEG didn’t result in an improvement of the biological relevance.

  17. Multivariate analysis of microarray data by principal component discriminant analysis: Prioritizing relevant transcripts linked to the degradation of different carbohydrates in Pseudomonas putida S12

    NARCIS (Netherlands)

    Werf, M.J. van der; Pieterse, B.; Luijk, N. van; Schuren, F.; Werff van der - Vat, B. van der; Overkamp, K.; Jellema, R.H.

    2006-01-01

    The value of the multivariate data analysis tools principal component analysis (PCA) and principal component discriminant analysis (PCDA) for prioritizing leads generated by microarrays was evaluated. To this end, Pseudomonas putida S12 was grown in independent triplicate fermentations on four

  18. Multivariate analysis of microarray data by principal component discriminant analysis: Prioritizing relevant transcripts linked to the degradation of different carbohydrates in Pseudomonas putida S12

    NARCIS (Netherlands)

    Werf, M.J. van der; Pieterse, B.; Luijk, N. van; Schuren, F.; Werff van der - Vat, B. van der; Overkamp, K.; Jellema, R.H.

    2006-01-01

    The value of the multivariate data analysis tools principal