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Sample records for dna microarray analysis

  1. Gene Expression Analysis Using Agilent DNA Microarrays

    DEFF Research Database (Denmark)

    Stangegaard, Michael

    2009-01-01

    Hybridization of labeled cDNA to microarrays is an intuitively simple and a vastly underestimated process. If it is not performed, optimized, and standardized with the same attention to detail as e.g., RNA amplification, information may be overlooked or even lost. Careful balancing of the amount ...

  2. Metric learning for DNA microarray data analysis

    International Nuclear Information System (INIS)

    Takeuchi, Ichiro; Nakagawa, Masao; Seto, Masao

    2009-01-01

    In many microarray studies, gene set selection is an important preliminary step for subsequent main task such as tumor classification, cancer subtype identification, etc. In this paper, we investigate the possibility of using metric learning as an alternative to gene set selection. We develop a simple metric learning algorithm aiming to use it for microarray data analysis. Exploiting a property of the algorithm, we introduce a novel approach for extending the metric learning to be adaptive. We apply the algorithm to previously studied microarray data on malignant lymphoma subtype identification.

  3. 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...

  4. DNA microarray data and contextual analysis of correlation graphs

    Directory of Open Access Journals (Sweden)

    Hingamp Pascal

    2003-04-01

    Full Text Available Abstract Background DNA microarrays are used to produce large sets of expression measurements from which specific biological information is sought. Their analysis requires efficient and reliable algorithms for dimensional reduction, classification and annotation. Results We study networks of co-expressed genes obtained from DNA microarray experiments. The mathematical concept of curvature on graphs is used to group genes or samples into clusters to which relevant gene or sample annotations are automatically assigned. Application to publicly available yeast and human lymphoma data demonstrates the reliability of the method in spite of its simplicity, especially with respect to the small number of parameters involved. Conclusions We provide a method for automatically determining relevant gene clusters among the many genes monitored with microarrays. The automatic annotations and the graphical interface improve the readability of the data. A C++ implementation, called Trixy, is available from http://tagc.univ-mrs.fr/bioinformatics/trixy.html.

  5. The application of DNA microarrays in gene expression analysis

    NARCIS (Netherlands)

    Hal, van N.L.W.; Vorst, O.; Houwelingen, van A.M.M.L.; Kok, E.J.; Peijnenburg, A.A.C.M.; Aharoni, A.; Tunen, van A.J.; Keijer, J.

    2000-01-01

    DNA microarray technology is a new and powerful technology that will substantially increase the speed of molecular biological research. This paper gives a survey of DNA microarray technology and its use in gene expression studies. The technical aspects and their potential improvements are discussed.

  6. The application of DNA microarrays in gene expression analysis.

    Science.gov (United States)

    van Hal, N L; Vorst, O; van Houwelingen, A M; Kok, E J; Peijnenburg, A; Aharoni, A; van Tunen, A J; Keijer, J

    2000-03-31

    DNA microarray technology is a new and powerful technology that will substantially increase the speed of molecular biological research. This paper gives a survey of DNA microarray technology and its use in gene expression studies. The technical aspects and their potential improvements are discussed. These comprise array manufacturing and design, array hybridisation, scanning, and data handling. Furthermore, it is discussed how DNA microarrays can be applied in the working fields of: safety, functionality and health of food and gene discovery and pathway engineering in plants.

  7. 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...... we have used DNA microarray analysis to examine the molecular events involved in response to fimbrial gene expression in E. coli K-12. Observed differential expression levels of the fim genes were in good agreement with our current knowledge of the stoichiometry of type I fimbriae. Changes in fim...

  8. 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.

  9. 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.

  10. DNA Microarray Technology

    Science.gov (United States)

    Skip to main content DNA Microarray Technology Enter Search Term(s): Español Research Funding An Overview Bioinformatics Current Grants Education and Training Funding Extramural Research News Features Funding Divisions Funding ...

  11. Xylella fastidiosa gene expression analysis by DNA microarrays

    Directory of Open Access Journals (Sweden)

    Regiane F. Travensolo

    2009-01-01

    Full Text Available Xylella fastidiosa genome sequencing has generated valuable data by identifying genes acting either on metabolic pathways or in associated pathogenicity and virulence. Based on available information on these genes, new strategies for studying their expression patterns, such as microarray technology, were employed. A total of 2,600 primer pairs were synthesized and then used to generate fragments using the PCR technique. The arrays were hybridized against cDNAs labeled during reverse transcription reactions and which were obtained from bacteria grown under two different conditions (liquid XDM2 and liquid BCYE. All data were statistically analyzed to verify which genes were differentially expressed. In addition to exploring conditions for X. fastidiosa genome-wide transcriptome analysis, the present work observed the differential expression of several classes of genes (energy, protein, amino acid and nucleotide metabolism, transport, degradation of substances, toxins and hypothetical proteins, among others. The understanding of expressed genes in these two different media will be useful in comprehending the metabolic characteristics of X. fastidiosa, and in evaluating how important certain genes are for the functioning and survival of these bacteria in plants.

  12. Xylella fastidiosa gene expression analysis by DNA microarrays

    OpenAIRE

    Travensolo,Regiane F.; Carareto-Alves,Lucia M.; Costa,Maria V.C.G.; Lopes,Tiago J.S.; Carrilho,Emanuel; Lemos,Eliana G.M.

    2009-01-01

    Xylella fastidiosa genome sequencing has generated valuable data by identifying genes acting either on metabolic pathways or in associated pathogenicity and virulence. Based on available information on these genes, new strategies for studying their expression patterns, such as microarray technology, were employed. A total of 2,600 primer pairs were synthesized and then used to generate fragments using the PCR technique. The arrays were hybridized against cDNAs labeled during reverse transcrip...

  13. Nonlinear matching measure for the analysis of on-off type DNA microarray images

    Science.gov (United States)

    Kim, Jong D.; Park, Misun; Kim, Jongwon

    2003-07-01

    In this paper, we propose a new nonlinear matching measure for automatic analysis of the on-off type DNA microarray images in which the hybridized spots are detected by the template matching method. The targeting spots of HPV DNA chips are designed for genotyping the human papilloma virus(HPV). The proposed measure is obtained by binarythresholding over the whole template region and taking the number of white pixels inside the spotted area. This measure is evaluated in terms of the accuracy of the estimated marker location to show better performance than the normalized covariance.

  14. A High Phosphorus Diet Affects Lipid Metabolism in Rat Liver: A DNA Microarray Analysis

    Science.gov (United States)

    Chun, Sunwoo; Bamba, Takeshi; Suyama, Tatsuya; Ishijima, Tomoko; Fukusaki, Eiichiro; Abe, Keiko; Nakai, Yuji

    2016-01-01

    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 acids

  15. DNA Microarray Technology; TOPICAL

    International Nuclear Information System (INIS)

    WERNER-WASHBURNE, MARGARET; DAVIDSON, GEORGE S.

    2002-01-01

    Collaboration between Sandia National Laboratories and the University of New Mexico Biology Department resulted in the capability to train students in microarray techniques and the interpretation of data from microarray experiments. These studies provide for a better understanding of the role of stationary phase and the gene regulation involved in exit from stationary phase, which may eventually have important clinical implications. Importantly, this research trained numerous students and is the basis for three new Ph.D. projects

  16. DNA microarrays : a molecular cloning manual

    National Research Council Canada - National Science Library

    Sambrook, Joseph; Bowtell, David

    2002-01-01

    .... DNA Microarrays provides authoritative, detailed instruction on the design, construction, and applications of microarrays, as well as comprehensive descriptions of the software tools and strategies...

  17. 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

  18. A High Phosphorus Diet Affects Lipid Metabolism in Rat Liver: A DNA Microarray Analysis.

    Directory of Open Access Journals (Sweden)

    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

  19. 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.

  20. Incorporation of gene-specific variability improves expression analysis using high-density DNA microarrays

    Directory of Open Access Journals (Sweden)

    Spitznagel Edward

    2003-11-01

    Full Text Available Abstract Background The assessment of data reproducibility is essential for application of microarray technology to exploration of biological pathways and disease states. Technical variability in data analysis largely depends on signal intensity. Within that context, the reproducibility of individual probe sets has not been hitherto addressed. Results We used an extraordinarily large replicate data set derived from human placental trophoblast to analyze probe-specific contribution to variability of gene expression. We found that signal variability, in addition to being signal-intensity dependant, is probe set-specific. Importantly, we developed a novel method to quantify the contribution of this probe set-specific variability. Furthermore, we devised a formula that incorporates a priori-computed, replicate-based information on probe set- and intensity-specific variability in determination of expression changes even without technical replicates. Conclusion The strategy of incorporating probe set-specific variability is superior to analysis based on arbitrary fold-change thresholds. We recommend its incorporation to any computation of gene expression changes using high-density DNA microarrays. A Java application implementing our T-score is available at http://www.sadovsky.wustl.edu/tscore.html.

  1. Radioactive cDNA microarray in neurospsychiatry

    International Nuclear Information System (INIS)

    Choe, Jae Gol; Shin, Kyung Ho; Lee, Min Soo; Kim, Meyoung Kon

    2003-01-01

    Microarray technology allows the simultaneous analysis of gene expression patterns of thousands of genes, in a systematic fashion, under a similar set of experimental conditions, thus making the data highly comparable. In some cases arrays are used simply as a primary screen leading to downstream molecular characterization of individual gene candidates. In other cases, the goal of expression profiling is to begin to identify complex regulatory networks underlying developmental processes and disease states. Microarrays were originally used with cell lines or other simple model systems. More recently, microarrays have been used in the analysis of more complex biological tissues including neural systems and the brain. The application of cDNA arrays in neuropsychiatry has lagged behind other fields for a number of reasons. These include a requirement for a large amount of input probe RNA in fluorescent-glass based array systems and the cellular complexity introduced by multicellular brain and neural tissues. An additional factor that impacts the general use of microarrays in neuropsychiatry is the lack of availability of sequenced clone sets from model systems. While human cDNA clones have been widely available, high quality rat, mouse, and drosophilae, among others are just becoming widely available. A final factor in the application of cDNA microarrays in neuropsychiatry is cost of commercial arrays. As academic microarray facilitates become more commonplace custom made arrays will become more widely available at a lower cost allowing more widespread applications. In summary, microarray technology is rapidly having an impact on many areas of biomedical research. Radioisotope-nylon based microarrays offer alternatives that may in some cases be more sensitive, flexible, inexpensive, and universal as compared to other array formats, such as fluorescent-glass arrays. In some situations of limited RNA or exotic species, radioactive membrane microarrays may be the most

  2. Radioactive cDNA microarray in neurospsychiatry

    Energy Technology Data Exchange (ETDEWEB)

    Choe, Jae Gol; Shin, Kyung Ho; Lee, Min Soo; Kim, Meyoung Kon [Korea University Medical School, Seoul (Korea, Republic of)

    2003-02-01

    Microarray technology allows the simultaneous analysis of gene expression patterns of thousands of genes, in a systematic fashion, under a similar set of experimental conditions, thus making the data highly comparable. In some cases arrays are used simply as a primary screen leading to downstream molecular characterization of individual gene candidates. In other cases, the goal of expression profiling is to begin to identify complex regulatory networks underlying developmental processes and disease states. Microarrays were originally used with cell lines or other simple model systems. More recently, microarrays have been used in the analysis of more complex biological tissues including neural systems and the brain. The application of cDNA arrays in neuropsychiatry has lagged behind other fields for a number of reasons. These include a requirement for a large amount of input probe RNA in fluorescent-glass based array systems and the cellular complexity introduced by multicellular brain and neural tissues. An additional factor that impacts the general use of microarrays in neuropsychiatry is the lack of availability of sequenced clone sets from model systems. While human cDNA clones have been widely available, high quality rat, mouse, and drosophilae, among others are just becoming widely available. A final factor in the application of cDNA microarrays in neuropsychiatry is cost of commercial arrays. As academic microarray facilitates become more commonplace custom made arrays will become more widely available at a lower cost allowing more widespread applications. In summary, microarray technology is rapidly having an impact on many areas of biomedical research. Radioisotope-nylon based microarrays offer alternatives that may in some cases be more sensitive, flexible, inexpensive, and universal as compared to other array formats, such as fluorescent-glass arrays. In some situations of limited RNA or exotic species, radioactive membrane microarrays may be the most

  3. Importance of the efficiency of double-stranded DNA formation in cDNA synthesis for the imprecision of microarray expression analysis.

    Science.gov (United States)

    Thormar, Hans G; Gudmundsson, Bjarki; Eiriksdottir, Freyja; Kil, Siyoen; Gunnarsson, Gudmundur H; Magnusson, Magnus Karl; Hsu, Jason C; Jonsson, Jon J

    2013-04-01

    The causes of imprecision in microarray expression analysis are poorly understood, limiting the use of this technology in molecular diagnostics. Two-dimensional strandness-dependent electrophoresis (2D-SDE) separates nucleic acid molecules on the basis of length and strandness, i.e., double-stranded DNA (dsDNA), single-stranded DNA (ssDNA), and RNA·DNA hybrids. We used 2D-SDE to measure the efficiency of cDNA synthesis and its importance for the imprecision of an in vitro transcription-based microarray expression analysis. The relative amount of double-stranded cDNA formed in replicate experiments that used the same RNA sample template was highly variable, ranging between 0% and 72% of the total DNA. Microarray experiments showed an inverse relationship between the difference between sample pairs in probe variance and the relative amount of dsDNA. Approximately 15% of probes showed between-sample variation (P cDNA synthesized can be an important component of the imprecision in T7 RNA polymerase-based microarray expression analysis. © 2013 American Association for Clinical Chemistry

  4. Early Gene Expression in Wounded Human Keratinocytes Revealed by DNA Microarray Analysis

    Directory of Open Access Journals (Sweden)

    Pascal Barbry

    2006-04-01

    Full Text Available Wound healing involves several steps: spreading of the cells, migration and proliferation. We have profiled gene expression during the early events of wound healing in normal human keratinocytes with a home-made DNA microarray containing about 1000 relevant human probes. An original wounding machine was used, that allows the wounding of up to 40% of the surface of a confluent monolayer of cultured cells grown on a Petri dish (compared with 5% with a classical ‘scratch’ method. The two aims of the present study were: (a to validate a limited number of genes by comparing the expression levels obtained with this technique with those found in the literature; (b to combine the use of the wounding machine with DNA microarray analysis for large-scale detection of the molecular events triggered during the early stages of the wound-healing process. The time-courses of RNA expression observed at 0.5, 1.5, 3, 6 and 15 h after wounding for genes such as c-Fos, c-Jun, Egr1, the plasminogen activator PLAU (uPA and the signal transducer and transcription activator STAT3, were consistent with previously published data. This suggests that our methodologies are able to perform quantitative measurement of gene expression. Transcripts encoding two zinc finger proteins, ZFP36 and ZNF161, and the tumour necrosis factor α-induced protein TNFAIP3, were also overexpressed after wounding. The role of the p38 mitogen-activated protein kinase (p38MAPK in wound healing was shown after the inhibition of p38 by SB203580, but our results also suggest the existence of surrogate activating pathways.

  5. Transcription analysis of apple fruit development using cDNA microarrays

    NARCIS (Netherlands)

    Soglio, V.; Costa, F.; Molthoff, J.W.; Weemen-Hendriks, M.; Schouten, H.J.; Gianfranceschi, L.

    2009-01-01

    The knowledge of the molecular mechanisms underlying fruit quality traits is fundamental to devise efficient marker-assisted selection strategies and to improve apple breeding. In this study, cDNA microarray technology was used to identify genes whose expression changes during fruit development and

  6. DNA Microarrays in Comparative Genomics and Transcriptomics

    DEFF Research Database (Denmark)

    Willenbrock, Hanni

    2007-01-01

    at identifying the exact breakpoints where DNA has been gained or lost. In this thesis, three popular methods are compared and a realistic simulation model is presented for generating artificial data with known breakpoints and known DNA copy number. By using simulated data, we obtain a realistic evaluation......During the past few years, innovations in the DNA sequencing technology has led to an explosion in available DNA sequence information. This has revolutionized biological research and promoted the development of high throughput analysis methods that can take advantage of the vast amount of sequence...... data. For this, the DNA microarray technology has gained enormous popularity due to its ability to measure the presence or the activity of thousands of genes simultaneously. Microarrays for high throughput data analyses are not limited to a few organisms but may be applied to everything from bacteria...

  7. High-throughput screening of suppression subtractive hybridization cDNA libraries using DNA microarray analysis

    CSIR Research Space (South Africa)

    Van den Berg, N

    2004-11-01

    Full Text Available Efficient construction of cDNA libraries enriched for differentially expressed transcripts is an important first step in many biological investigations. We present a quantitative procedure for screening cDNA libraries constructed by suppression...

  8. DNA Microarray Workshop

    National Research Council Canada - National Science Library

    Lauro, Bernie

    1999-01-01

    .... Funding for the workshop was provided by the US Department of Defense (USAMRAA). The aim of the meeting was to discuss how to best use the data derived from the Malaria Genome Sequencing Project for the functional analysis of the genome...

  9. Production of DNA microarray and expression analysis of genes from Xylella fastidiosa in different culture media

    Directory of Open Access Journals (Sweden)

    Regiane de Fátima Travensolo

    2009-06-01

    Full Text Available DNA Microarray was developed to monitor the expression of many genes from Xylella fastidiosa, allowing the side by-side comparison of two situations in a single experiment. The experiments were performed using X. fastidiosa cells grown in two culture media: BCYE and XDM2. The primers were synthesized, spotted onto glass slides and the array was hybridized against fluorescently labeled cDNAs. The emitted signals were quantified, normalized and the data were statistically analyzed to verify the differentially expressed genes. According to the data, 104 genes were differentially expressed in XDM2 and 30 genes in BCYE media. The present study showed that DNA microarray technique efficiently differentiate the expressed genes under different conditions.DNA Microarray foi desenvolvida para monitorar a expressão de muitos genes de Xylella fastidiosa, permitindo a comparação de duas situações distintas em um único experimento. Os experimentos foram feitos utilizando células de X. fastidiosa cultivada em dois meios de cultura: BCYE e XDM2. Pares de oligonucleotídeos iniciadores foram sintetizados, depositados em lâminas de vidro e o arranjo foi hibridizado contra cDNAs marcados fluorescentemente. Os sinais emitidos foram quantificados, normalizados e os dados foram estatisticamente analisados para verificar os genes diferencialmente expressos. De acordo com nossos dados, 104 genes foram diferencialmente expressos para o meio de cultura XDM2 e 30 genes para o BCYE. No presente estudo, nós demonstramos que a técnica de DNA microarrays eficientemente diferencia genes expressos sob diferentes condições de cultivo.

  10. Single-cell multiple gene expression analysis based on single-molecule-detection microarray assay for multi-DNA determination

    Energy Technology Data Exchange (ETDEWEB)

    Li, Lu [School of Chemistry and Chemical Engineering, Shandong University, Jinan 250100 (China); Wang, Xianwei [School of Life Sciences, Shandong University, Jinan 250100 (China); Zhang, Xiaoli [School of Chemistry and Chemical Engineering, Shandong University, Jinan 250100 (China); Wang, Jinxing [School of Life Sciences, Shandong University, Jinan 250100 (China); Jin, Wenrui, E-mail: jwr@sdu.edu.cn [School of Chemistry and Chemical Engineering, Shandong University, Jinan 250100 (China)

    2015-01-07

    Highlights: • A single-molecule-detection (SMD) microarray for 10 samples is fabricated. • The based-SMD microarray assay (SMA) can determine 8 DNAs for each sample. • The limit of detection of SMA is as low as 1.3 × 10{sup −16} mol L{sup −1}. • The SMA can be applied in single-cell multiple gene expression analysis. - Abstract: We report a novel ultra-sensitive and high-selective single-molecule-detection microarray assay (SMA) for multiple DNA determination. In the SMA, a capture DNA (DNAc) microarray consisting of 10 subarrays with 9 spots for each subarray is fabricated on a silanized glass coverslip as the substrate. On the subarrays, the spot-to-spot spacing is 500 μm and each spot has a diameter of ∼300 μm. The sequence of the DNAcs on the 9 spots of a subarray is different, to determine 8 types of target DNAs (DNAts). Thus, 8 types of DNAts are captured to their complementary DNAcs at 8 spots of a subarray, respectively, and then labeled with quantum dots (QDs) attached to 8 types of detection DNAs (DNAds) with different sequences. The ninth spot is used to detect the blank value. In order to determine the same 8 types of DNAts in 10 samples, the 10 DNAc-modified subarrays on the microarray are identical. Fluorescence single-molecule images of the QD-labeled DNAts on each spot of the subarray are acquired using a home-made single-molecule microarray reader. The amounts of the DNAts are quantified by counting the bright dots from the QDs. For a microarray, 8 types of DNAts in 10 samples can be quantified in parallel. The limit of detection of the SMA for DNA determination is as low as 1.3 × 10{sup −16} mol L{sup −1}. The SMA for multi-DNA determination can also be applied in single-cell multiple gene expression analysis through quantification of complementary DNAs (cDNAs) corresponding to multiple messenger RNAs (mRNAs) in single cells. To do so, total RNA in single cells is extracted and reversely transcribed into their cDNAs. Three

  11. Bacterial identification and subtyping using DNA microarray and DNA sequencing.

    Science.gov (United States)

    Al-Khaldi, Sufian F; Mossoba, Magdi M; Allard, Marc M; Lienau, E Kurt; Brown, Eric D

    2012-01-01

    The era of fast and accurate discovery of biological sequence motifs in prokaryotic and eukaryotic cells is here. The co-evolution of direct genome sequencing and DNA microarray strategies not only will identify, isotype, and serotype pathogenic bacteria, but also it will aid in the discovery of new gene functions by detecting gene expressions in different diseases and environmental conditions. Microarray bacterial identification has made great advances in working with pure and mixed bacterial samples. The technological advances have moved beyond bacterial gene expression to include bacterial identification and isotyping. Application of new tools such as mid-infrared chemical imaging improves detection of hybridization in DNA microarrays. The research in this field is promising and future work will reveal the potential of infrared technology in bacterial identification. On the other hand, DNA sequencing by using 454 pyrosequencing is so cost effective that the promise of $1,000 per bacterial genome sequence is becoming a reality. Pyrosequencing technology is a simple to use technique that can produce accurate and quantitative analysis of DNA sequences with a great speed. The deposition of massive amounts of bacterial genomic information in databanks is creating fingerprint phylogenetic analysis that will ultimately replace several technologies such as Pulsed Field Gel Electrophoresis. In this chapter, we will review (1) the use of DNA microarray using fluorescence and infrared imaging detection for identification of pathogenic bacteria, and (2) use of pyrosequencing in DNA cluster analysis to fingerprint bacterial phylogenetic trees.

  12. BioconductorBuntu: a Linux distribution that implements a web-based DNA microarray analysis server.

    Science.gov (United States)

    Geeleher, Paul; Morris, Dermot; Hinde, John P; Golden, Aaron

    2009-06-01

    BioconductorBuntu is a custom distribution of Ubuntu Linux that automatically installs a server-side microarray processing environment, providing a user-friendly web-based GUI to many of the tools developed by the Bioconductor Project, accessible locally or across a network. System installation is via booting off a CD image or by using a Debian package provided to upgrade an existing Ubuntu installation. In its current version, several microarray analysis pipelines are supported including oligonucleotide, dual-or single-dye experiments, including post-processing with Gene Set Enrichment Analysis. BioconductorBuntu is designed to be extensible, by server-side integration of further relevant Bioconductor modules as required, facilitated by its straightforward underlying Python-based infrastructure. BioconductorBuntu offers an ideal environment for the development of processing procedures to facilitate the analysis of next-generation sequencing datasets. BioconductorBuntu is available for download under a creative commons license along with additional documentation and a tutorial from (http://bioinf.nuigalway.ie).

  13. cDNA microarray analysis of human keratinocytes cells of patients submitted to chemoradiotherapy and oral photobiomodulation therapy: pilot study.

    Science.gov (United States)

    Antunes, Heliton S; Wajnberg, Gabriel; Pinho, Marcos B; Jorge, Natasha Andressa Nogueira; de Moraes, Joyce Luana Melo; Stefanoff, Claudio Gustavo; Herchenhorn, Daniel; Araújo, Carlos M M; Viégas, Celia Maria Pais; Rampini, Mariana P; Dias, Fernando L; de Araujo-Souza, Patricia Savio; Passetti, Fabio; Ferreira, Carlos G

    2018-01-01

    Oral mucositis is an acute toxicity that occurs in patients submitted to chemoradiotherapy to treat head and neck squamous cell carcinoma. In this study, we evaluated differences in gene expression in the keratinocytes of the oral mucosa of patients treated with photobiomodulation therapy and tried to associate the molecular mechanisms with clinical findings. From June 2009 to December 2010, 27 patients were included in a randomized double-blind pilot study. Buccal smears from 13 patients were obtained at days 1 and 10 of chemoradiotherapy, and overall gene expression of samples from both dates were analyzed by complementary DNA (cDNA) microarray. In addition, samples from other 14 patients were also collected at D1 and D10 of chemoradiotherapy for subsequent validation of cDNA microarray findings by qPCR. The expression array analysis identified 105 upregulated and 60 downregulated genes in our post-treatment samples when compared with controls. Among the upregulated genes with the highest fold change, it was interesting to observe the presence of genes related to keratinocyte differentiation. Among downregulated genes were observed genes related to cytotoxicity and immune response. The results indicate that genes known to be induced during differentiation of human epidermal keratinocytes were upregulated while genes associated with cytotoxicity and immune response were downregulated in the laser group. These results support previous clinical findings indicating that the lower incidence of oral mucositis associated with photobiomodulation therapy might be correlated to the activation of genes involved in keratinocyte differentiation.

  14. cDNA Microarray Analysis of Serially Sampled Cervical Cancer Specimens From Patients Treated With Thermochemoradiotherapy

    International Nuclear Information System (INIS)

    Borkamo, Erling Dahl; Schem, Baard-Christian; Fluge, Oystein; Bruland, Ove; Dahl, Olav; Mella, Olav

    2009-01-01

    Purpose: To elucidate changes in gene expression after treatment with regional thermochemoradiotherapy in locally advanced squamous cell cervical cancer. Methods and Materials: Tru-Cut biopsy specimens were serially collected from 16 patients. Microarray gene expression levels before and 24 h after the first and second trimodality treatment sessions were compared. Pathway and network analyses were conducted by use of Ingenuity Pathways Analysis (IPA; Ingenuity Systems, Redwood City, CA). Single gene expressions were analyzed by quantitative real-time reverse transcription-polymerase chain reaction. Results: We detected 53 annotated genes that were differentially expressed after trimodality treatment. Central in the three top networks detected by IPA were interferon alfa, interferon beta, and interferon gamma receptor; nuclear factor κB; and tumor necrosis factor, respectively. These genes encode proteins that are important in regulation cell signaling, proliferation, gene expression, and immune stimulation. Biological processes over-represented among the 53 genes were fibrosis, tumorigenesis, and immune response. Conclusions: Microarrays showed minor changes in gene expression after thermochemoradiotherapy in locally advanced cervical cancer. We detected 53 differentially expressed genes, mainly involved in fibrosis, tumorigenesis, and immune response. A limitation with the use of serial biopsy specimens was low quality of ribonucleic acid from tumors that respond to highly effective therapy. Another 'key limitation' is timing of the post-treatment biopsy, because 24 h may be too late to adequately assess the impact of hyperthermia on gene expression.

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

    DEFF Research Database (Denmark)

    Skov, Vibe

    2007-01-01

    (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...... comparable to other commercial and custom made microarrays and is a cost-effective alternative especially in larger epidemiological studies....

  16. Development of a porcine skeletal muscle cDNA microarray: analysis of differential transcript expression in phenotypically distinct muscles

    Directory of Open Access Journals (Sweden)

    Stear Michael

    2003-03-01

    Full Text Available Abstract Background Microarray profiling has the potential to illuminate the molecular processes that govern the phenotypic characteristics of porcine skeletal muscles, such as hypertrophy or atrophy, and the expression of specific fibre types. This information is not only important for understanding basic muscle biology but also provides underpinning knowledge for enhancing the efficiency of livestock production. Results We report on the de novo development of a composite skeletal muscle cDNA microarray, comprising 5500 clones from two developmentally distinct cDNA libraries (longissimus dorsi of a 50-day porcine foetus and the gastrocnemius of a 3-day-old pig. Clones selected for the microarray assembly were of low to moderate abundance, as indicated by colony hybridisation. We profiled the differential expression of genes between the psoas (red muscle and the longissimus dorsi (white muscle, by co-hybridisation of Cy3 and Cy5 labelled cDNA derived from these two muscles. Results from seven microarray slides (replicates correctly identified genes that were expected to be differentially expressed, as well as a number of novel candidate regulatory genes. Quantitative real-time RT-PCR on selected genes was used to confirm the results from the microarray. Conclusion We have developed a porcine skeletal muscle cDNA microarray and have identified a number of candidate genes that could be involved in muscle phenotype determination, including several members of the casein kinase 2 signalling pathway.

  17. 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].

  18. Microarrays (DNA Chips) for the Classroom Laboratory

    Science.gov (United States)

    Barnard, Betsy; Sussman, Michael; BonDurant, Sandra Splinter; Nienhuis, James; Krysan, Patrick

    2006-01-01

    We have developed and optimized the necessary laboratory materials to make DNA microarray technology accessible to all high school students at a fraction of both cost and data size. The primary component is a DNA chip/array that students "print" by hand and then analyze using research tools that have been adapted for classroom use. The…

  19. Visual Analysis of DNA Microarray Data for Accurate Molecular Identification of Non-albicans Candida Isolates from Patients with Candidemia Episodes

    OpenAIRE

    De Luca Ferrari, Michela; Ribeiro Resende, Mariângela; Sakai, Kanae; Muraosa, Yasunori; Lyra, Luzia; Gonoi, Tohru; Mikami, Yuzuru; Tominaga, Kenichiro; Kamei, Katsuhiko; Zaninelli Schreiber, Angelica; Trabasso, Plinio; Moretti, Maria Luiza

    2013-01-01

    The performance of a visual slide-based DNA microarray for the identification of non-albicans Candida spp. was evaluated. Among 167 isolates that had previously been identified by Vitek 2, the agreement between DNA microarray and sequencing results was 97.6%. This DNA microarray platform showed excellent performance.

  20. Monitoring expression profiles of rice (Oryza sativa L.) genes under abiotic stresses using cDNA Microarray Analysis (abstract)

    International Nuclear Information System (INIS)

    Rabbani, M.A.

    2005-01-01

    Transcript regulation in response to cold, drought, high salinity and ABA application was investigated in rice (Oryza sativa L., Nipponbare) with microarray analysis including approx. 1700 independent DNA elements derived from three cDNA libraries constructed from 15-day old rice seedlings stressed with drought, cold and high salinity. A total of 141 non-redundant genes were identified, whose expression ratios were more than three-fold compared with the control genes for at least one of stress treatments in microarray analysis. However, after RNA gel blot analysis, a total of 73 genes were identified, among them the transcripts of 36, 62, 57 and 43 genes were found increased after cold, drought, high salinity and ABA application, respectively. Sixteen of these identified genes have been reported previously to be stress inducible in rice, while 57 of which are novel that have not been reported earlier as stress responsive in rice. We observed a strong association in the expression patterns of stress responsive genes and found 15 stress inducible genes that responded to all four treatments. Based on Venn diagram analysis, 56 genes were induced by both drought and high salinity, whereas 22 genes were upregulated by both cold and high salinity stress. Similarly 43 genes were induced by both drought stress and ABA application, while only 17 genes were identified as cold and ABA inducible genes. These results indicated the existence of greater cross talk between drought, ABA and high salinity stress signaling processes than those between cold and ABA, and cold and high salinity stress signaling pathways. The cold, drought, high salinity and ABA inducible genes were classified into four gene groups from their expression profiles. Analysis of data enabled us to identify a number of promoters and possible cis-acting DNA elements of several genes induced by a variety of abiotic stresses by combining expression data with genomic sequence data of rice. Comparative analysis of

  1. Microarray-based analysis of plasma cirDNA epigenetic modification profiling in xenografted mice exposed to intermittent hypoxia

    Directory of Open Access Journals (Sweden)

    Rene Cortese

    2015-09-01

    Full Text Available Intermittent hypoxia (IH during sleep is one of the major abnormalities occurring in patients suffering from obstructive sleep apnea (OSA, a highly prevalent disorder affecting 6–15% of the general population, particularly among obese people. IH has been proposed as a major determinant of oncogenetically-related processes such as tumor growth, invasion and metastasis. During the growth and expansion of tumors, fragmented DNA is released into the bloodstream and enters the circulation. Circulating tumor DNA (cirDNA conserves the genetic and epigenetic profiles from the tumor of origin and can be isolated from the plasma fraction. Here we report a microarray-based epigenetic profiling of cirDNA isolated from blood samples of mice engrafted with TC1 epithelial lung cancer cells and controls, which were exposed to IH during sleep (XenoIH group, n = 3 or control conditions, (i.e., room air (RA; XenoRA group, n = 3 conditions. To prepare the targets for microarray hybridization, we applied a previously developed method that enriches the modified fraction of the cirDNA without amplification of genomic DNA. Regions of differential cirDNA modification between the two groups were identified by hybridizing the enriched fractions for each sample to Affymetrix GeneChip Human Promoter Arrays 1.0R. Microarray raw and processed data were deposited in NCBI's Gene Expression Omnibus (GEO database (accession number: GSE61070.

  2. Identifying Fishes through DNA Barcodes and Microarrays.

    Directory of Open Access Journals (Sweden)

    Marc Kochzius

    2010-09-01

    Full Text Available International fish trade reached an import value of 62.8 billion Euro in 2006, of which 44.6% are covered by the European Union. Species identification is a key problem throughout the life cycle of fishes: from eggs and larvae to adults in fisheries research and control, as well as processed fish products in consumer protection.This study aims to evaluate the applicability of the three mitochondrial genes 16S rRNA (16S, cytochrome b (cyt b, and cytochrome oxidase subunit I (COI for the identification of 50 European marine fish species by combining techniques of "DNA barcoding" and microarrays. In a DNA barcoding approach, neighbour Joining (NJ phylogenetic trees of 369 16S, 212 cyt b, and 447 COI sequences indicated that cyt b and COI are suitable for unambiguous identification, whereas 16S failed to discriminate closely related flatfish and gurnard species. In course of probe design for DNA microarray development, each of the markers yielded a high number of potentially species-specific probes in silico, although many of them were rejected based on microarray hybridisation experiments. None of the markers provided probes to discriminate the sibling flatfish and gurnard species. However, since 16S-probes were less negatively influenced by the "position of label" effect and showed the lowest rejection rate and the highest mean signal intensity, 16S is more suitable for DNA microarray probe design than cty b and COI. The large portion of rejected COI-probes after hybridisation experiments (>90% renders the DNA barcoding marker as rather unsuitable for this high-throughput technology.Based on these data, a DNA microarray containing 64 functional oligonucleotide probes for the identification of 30 out of the 50 fish species investigated was developed. It represents the next step towards an automated and easy-to-handle method to identify fish, ichthyoplankton, and fish products.

  3. Comparing transformation methods for DNA microarray data

    NARCIS (Netherlands)

    Thygesen, Helene H.; Zwinderman, Aeilko H.

    2004-01-01

    Background: When DNA microarray data are used for gene clustering, genotype/phenotype correlation studies, or tissue classification the signal intensities are usually transformed and normalized in several steps in order to improve comparability and signal/noise ratio. These steps may include

  4. Differential gene expression in a DNA double-strand-break repair mutant XRS-5 defective in Ku80. Analysis by cDNA microarray

    Energy Technology Data Exchange (ETDEWEB)

    Chan, John Y.H.; Chen, Lung-Kun; Chang, Jui-Feng [National Yang Ming Univ., Taipei, Taiwan (China). Inst. of Radiological Sciences] (and others)

    2001-12-01

    The ability of cells to rejoin DNA double-strand breaks (DSBs) usually correlates with their radiosensitivity. This correlation has been demonstrated in radiosensitive cells, including the Chinese hamster ovary mutant XRS-5. XRS-5 is defective in a DNA end-binding protein, Ku80, which is a component of a DNA-dependent protein kinase complex used for joining strand breaks. However, Ku80-deficient cells are known to be retarded in cell proliferation and growth as well as other yet to be identified defects. Using custom-made 600-gene cDNA microarray filters, we found differential gene expressions between the wild-type and XRS-5 cells. Defective Ku80 apparently affects the expression of several repair genes, including topoisomerase-I and -IIA, ERCC5, MLH1, and ATM. In contrast, other DNA repair-associated genes, such as GADD45A, EGR1 MDM2 and p53, were not affected. In addition, for large numbers of growth-associated genes, such as cyclins and clks, the growth factors and cytokines were also affected. Down-regulated expression was also found in several categories of seemingly unrelated genes, including apoptosis, angiogenesis, kinase and signaling, phosphatase, stress protein, proto-oncogenes and tumor suppressors, transcription and translation factors. A RT-PCR analysis confirmed that the XRS-5 cells used were defective in Ku80 expression. The diversified groups of genes being affected could mean that Ku80, a multi-functional DNA-binding protein, not only affects DNA repair, but is also involved in transcription regulation. Our data, taken together, indicate that there are specific genes being modulated in Ku80- deficient cells, and that some of the DNA repair pathways and other biological functions are apparently linked, suggesting that a defect in one gene could have global effects on many other processes. (author)

  5. Differential gene expression in a DNA double-strand-break repair mutant XRS-5 defective in Ku80. Analysis by cDNA microarray

    International Nuclear Information System (INIS)

    Chan, John Y.H.; Chen, Lung-Kun; Chang, Jui-Feng

    2001-01-01

    The ability of cells to rejoin DNA double-strand breaks (DSBs) usually correlates with their radiosensitivity. This correlation has been demonstrated in radiosensitive cells, including the Chinese hamster ovary mutant XRS-5. XRS-5 is defective in a DNA end-binding protein, Ku80, which is a component of a DNA-dependent protein kinase complex used for joining strand breaks. However, Ku80-deficient cells are known to be retarded in cell proliferation and growth as well as other yet to be identified defects. Using custom-made 600-gene cDNA microarray filters, we found differential gene expressions between the wild-type and XRS-5 cells. Defective Ku80 apparently affects the expression of several repair genes, including topoisomerase-I and -IIA, ERCC5, MLH1, and ATM. In contrast, other DNA repair-associated genes, such as GADD45A, EGR1 MDM2 and p53, were not affected. In addition, for large numbers of growth-associated genes, such as cyclins and clks, the growth factors and cytokines were also affected. Down-regulated expression was also found in several categories of seemingly unrelated genes, including apoptosis, angiogenesis, kinase and signaling, phosphatase, stress protein, proto-oncogenes and tumor suppressors, transcription and translation factors. A RT-PCR analysis confirmed that the XRS-5 cells used were defective in Ku80 expression. The diversified groups of genes being affected could mean that Ku80, a multi-functional DNA-binding protein, not only affects DNA repair, but is also involved in transcription regulation. Our data, taken together, indicate that there are specific genes being modulated in Ku80- deficient cells, and that some of the DNA repair pathways and other biological functions are apparently linked, suggesting that a defect in one gene could have global effects on many other processes. (author)

  6. Development of DNA Microarrays for Metabolic Pathway and Bioprocess Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Gregory Stephanopoulos

    2004-07-31

    Transcriptional profiling experiments utilizing DNA microarrays to study the intracellular accumulation of PHB in Synechocystis has proved difficult in large part because strains that show significant differences in PHB which would justify global analysis of gene expression have not been isolated.

  7. DNA microarray technique for detecting food-borne pathogens

    Directory of Open Access Journals (Sweden)

    Xing GAO

    2012-08-01

    Full Text Available Objective To study the application of DNA microarray technique for screening and identifying multiple food-borne pathogens. Methods The oligonucleotide probes were designed by Clustal X and Oligo 6.0 at the conserved regions of specific genes of multiple food-borne pathogens, and then were validated by bioinformatic analyses. The 5' end of each probe was modified by amino-group and 10 Poly-T, and the optimized probes were synthesized and spotted on aldehyde-coated slides. The bacteria DNA template incubated with Klenow enzyme was amplified by arbitrarily primed PCR, and PCR products incorporated into Aminoallyl-dUTP were coupled with fluorescent dye. After hybridization of the purified PCR products with DNA microarray, the hybridization image and fluorescence intensity analysis was acquired by ScanArray and GenePix Pro 5.1 software. A series of detection conditions such as arbitrarily primed PCR and microarray hybridization were optimized. The specificity of this approach was evaluated by 16 different bacteria DNA, and the sensitivity and reproducibility were verified by 4 food-borne pathogens DNA. The samples of multiple bacteria DNA and simulated water samples of Shigella dysenteriae were detected. Results Nine different food-borne bacteria were successfully discriminated under the same condition. The sensitivity of genomic DNA was 102 -103pg/ μl, and the coefficient of variation (CV of the reproducibility of assay was less than 15%. The corresponding specific hybridization maps of the multiple bacteria DNA samples were obtained, and the detection limit of simulated water sample of Shigella dysenteriae was 3.54×105cfu/ml. Conclusions The DNA microarray detection system based on arbitrarily primed PCR can be employed for effective detection of multiple food-borne pathogens, and this assay may offer a new method for high-throughput platform for detecting bacteria.

  8. Phylogenetic Analysis of Shewanella Strains by DNA Relatedness Derived from Whole Genome Microarray DNA-DNA Hybridization and Comparisons with Other Methods

    International Nuclear Information System (INIS)

    Wu, Liyou; Yi, T.Y.; Van Nostrand, Joy; Zhou, Jizhong

    2010-01-01

    Phylogenetic analyses were done for the Shewanella strains isolated from Baltic Sea (38 strains), US DOE Hanford Uranium bioremediation site (Hanford Reach of the Columbia River (HRCR), 11 strains), Pacific Ocean and Hawaiian sediments (8 strains), and strains from other resources (16 strains) with three out group strains, Rhodopseudomonas palustris, Clostridium cellulolyticum, and Thermoanaerobacter ethanolicus X514, using DNA relatedness derived from WCGA-based DNA-DNA hybridizations, sequence similarities of 16S rRNA gene and gyrB gene, and sequence similarities of 6 loci of Shewanella genome selected from a shared gene list of the Shewanella strains with whole genome sequenced based on the average nucleotide identity of them (ANI). The phylogenetic trees based on 16S rRNA and gyrB gene sequences, and DNA relatedness derived from WCGA hybridizations of the tested Shewanella strains share exactly the same sub-clusters with very few exceptions, in which the strains were basically grouped by species. However, the phylogenetic analysis based on DNA relatedness derived from WCGA hybridizations dramatically increased the differentiation resolution at species and strains level within Shewanella genus. When the tree based on DNA relatedness derived from WCGA hybridizations was compared to the tree based on the combined sequences of the selected functional genes (6 loci), we found that the resolutions of both methods are similar, but the clustering of the tree based on DNA relatedness derived from WMGA hybridizations was clearer. These results indicate that WCGA-based DNA-DNA hybridization is an idea alternative of conventional DNA-DNA hybridization methods and it is superior to the phylogenetics methods based on sequence similarities of single genes. Detailed analysis is being performed for the re-classification of the strains examined.

  9. Phylogenetic Analysis of Shewanella Strains by DNA Relatedness Derived from Whole Genome Microarray DNA-DNA Hybridization and Comparison with Other Methods

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Liyou; Yi, T. Y.; Van Nostrand, Joy; Zhou, Jizhong

    2010-05-17

    Phylogenetic analyses were done for the Shewanella strains isolated from Baltic Sea (38 strains), US DOE Hanford Uranium bioremediation site [Hanford Reach of the Columbia River (HRCR), 11 strains], Pacific Ocean and Hawaiian sediments (8 strains), and strains from other resources (16 strains) with three out group strains, Rhodopseudomonas palustris, Clostridium cellulolyticum, and Thermoanaerobacter ethanolicus X514, using DNA relatedness derived from WCGA-based DNA-DNA hybridizations, sequence similarities of 16S rRNA gene and gyrB gene, and sequence similarities of 6 loci of Shewanella genome selected from a shared gene list of the Shewanella strains with whole genome sequenced based on the average nucleotide identity of them (ANI). The phylogenetic trees based on 16S rRNA and gyrB gene sequences, and DNA relatedness derived from WCGA hybridizations of the tested Shewanella strains share exactly the same sub-clusters with very few exceptions, in which the strains were basically grouped by species. However, the phylogenetic analysis based on DNA relatedness derived from WCGA hybridizations dramatically increased the differentiation resolution at species and strains level within Shewanella genus. When the tree based on DNA relatedness derived from WCGA hybridizations was compared to the tree based on the combined sequences of the selected functional genes (6 loci), we found that the resolutions of both methods are similar, but the clustering of the tree based on DNA relatedness derived from WMGA hybridizations was clearer. These results indicate that WCGA-based DNA-DNA hybridization is an idea alternative of conventional DNA-DNA hybridization methods and it is superior to the phylogenetics methods based on sequence similarities of single genes. Detailed analysis is being performed for the re-classification of the strains examined.

  10. DNA microarray analysis of the cyanotroph Pseudomonas pseudoalcaligenes CECT5344 in response to nitrogen starvation, cyanide and a jewelry wastewater.

    Science.gov (United States)

    Luque-Almagro, V M; Escribano, M P; Manso, I; Sáez, L P; Cabello, P; Moreno-Vivián, C; Roldán, M D

    2015-11-20

    Pseudomonas pseudoalcaligenes CECT5344 is an alkaliphilic bacterium that can use cyanide as nitrogen source for growth, becoming a suitable candidate to be applied in biological treatment of cyanide-containing wastewaters. The assessment of the whole genome sequence of the strain CECT5344 has allowed the generation of DNA microarrays to analyze the response to different nitrogen sources. The mRNA of P. pseudoalcaligenes CECT5344 cells grown under nitrogen limiting conditions showed considerable changes when compared against the transcripts from cells grown with ammonium; up-regulated genes were, among others, the glnK gene encoding the nitrogen regulatory protein PII, the two-component ntrBC system involved in global nitrogen regulation, and the ammonium transporter-encoding amtB gene. The protein coding transcripts of P. pseudoalcaligenes CECT5344 cells grown with sodium cyanide or an industrial jewelry wastewater that contains high concentration of cyanide and metals like iron, copper and zinc, were also compared against the transcripts of cells grown with ammonium as nitrogen source. This analysis revealed the induction by cyanide and the cyanide-rich wastewater of four nitrilase-encoding genes, including the nitC gene that is essential for cyanide assimilation, the cyanase cynS gene involved in cyanate assimilation, the cioAB genes required for the cyanide-insensitive respiration, and the ahpC gene coding for an alkyl-hydroperoxide reductase that could be related with iron homeostasis and oxidative stress. The nitC and cynS genes were also induced in cells grown under nitrogen starvation conditions. In cells grown with the jewelry wastewater, a malate quinone:oxidoreductase mqoB gene and several genes coding for metal extrusion systems were specifically induced. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

  11. Evaluation of toxicity of the mycotoxin citrinin using yeast ORF DNA microarray and Oligo DNA microarray

    Directory of Open Access Journals (Sweden)

    Nobumasa Hitoshi

    2007-04-01

    Full Text Available Abstract Background Mycotoxins are fungal secondary metabolites commonly present in feed and food, and are widely regarded as hazardous contaminants. Citrinin, one of the very well known mycotoxins that was first isolated from Penicillium citrinum, is produced by more than 10 kinds of fungi, and is possibly spread all over the world. However, the information on the action mechanism of the toxin is limited. Thus, we investigated the citrinin-induced genomic response for evaluating its toxicity. Results Citrinin inhibited growth of yeast cells at a concentration higher than 100 ppm. We monitored the citrinin-induced mRNA expression profiles in yeast using the ORF DNA microarray and Oligo DNA microarray, and the expression profiles were compared with those of the other stress-inducing agents. Results obtained from both microarray experiments clustered together, but were different from those of the mycotoxin patulin. The oxidative stress response genes – AADs, FLR1, OYE3, GRE2, and MET17 – were significantly induced. In the functional category, expression of genes involved in "metabolism", "cell rescue, defense and virulence", and "energy" were significantly activated. In the category of "metabolism", genes involved in the glutathione synthesis pathway were activated, and in the category of "cell rescue, defense and virulence", the ABC transporter genes were induced. To alleviate the induced stress, these cells might pump out the citrinin after modification with glutathione. While, the citrinin treatment did not induce the genes involved in the DNA repair. Conclusion Results from both microarray studies suggest that citrinin treatment induced oxidative stress in yeast cells. The genotoxicity was less severe than the patulin, suggesting that citrinin is less toxic than patulin. The reproducibility of the expression profiles was much better with the Oligo DNA microarray. However, the Oligo DNA microarray did not completely overcome cross

  12. Gene expression analysis in response to osmotic stimuli in the intervertebral disc with DNA microarray.

    Science.gov (United States)

    Zhang, Wenzhi; Li, Xu; Shang, Xifu; Zhao, Qichun; Hu, Yefeng; Xu, Xiang; He, Rui; Duan, Liqun; Zhang, Feng

    2013-12-27

    Intervertebral disc (IVD) cells experience a broad range of physicochemical stimuli under physiologic conditions, including alterations in their osmotic environment. At present, the molecular mechanisms underlying osmotic regulation in IVD cells are poorly understood. This study aims to screen genes affected by changes in osmotic pressure in cells of subjects aged 29 to 63 years old, with top-scoring pair (TSP) method. Gene expression data set GSE1648 was downloaded from Gene Expression Omnibus database, including four hyper-osmotic stimuli samples, four iso-osmotic stimuli samples, and three hypo-osmotic stimuli samples. A novel, simple method, referred to as the TSP, was used in this study. Through this method, there was no need to perform data normalization and transformation before data analysis. A total of five pairs of genes ((CYP2A6, FNTB), (PRPF8, TARDBP), (RPS5, OAZ1), (SLC25A3, NPM1) and (CBX3, SRSF9)) were selected based on the TSP method. We inferred that all these genes might play important roles in response to osmotic stimuli and age in IVD cells. Additionally, hyper-osmotic and iso-osmotic stimuli conditions were adverse factors for IVD cells. We anticipate that our results will provide new thoughts and methods for the study of IVD disease.

  13. A Customized DNA Microarray for Microbial Source Tracking ...

    Science.gov (United States)

    It is estimated that more than 160, 000 miles of rivers and streams in the United States are impaired due to the presence of waterborne pathogens. These pathogens typically originate from human and other animal fecal pollution sources; therefore, a rapid microbial source tracking (MST) method is needed to facilitate water quality assessment and impaired water remediation. We report a novel qualitative DNA microarray technology consisting of 453 probes for the detection of general fecal and host-associated bacteria, viruses, antibiotic resistance, and other environmentally relevant genetic indicators. A novel data normalization and reduction approach is also presented to help alleviate false positives often associated with high-density microarray applications. To evaluate the performance of the approach, DNA and cDNA was isolated from swine, cattle, duck, goose and gull fecal reference samples, as well as soiled poultry liter and raw municipal sewage. Based on nonmetric multidimensional scaling analysis of results, findings suggest that the novel microarray approach may be useful for pathogen detection and identification of fecal contamination in recreational waters. The ability to simultaneously detect a large collection of environmentally important genetic indicators in a single test has the potential to provide water quality managers with a wide range of information in a short period of time. Future research is warranted to measure microarray performance i

  14. Elucidation of the antibacterial mechanism of the Curvularia haloperoxidase system by DNA microarray profiling

    DEFF Research Database (Denmark)

    Hansen, E.H.; Schembri, Mark; Klemm, Per

    2004-01-01

    was the wild type. Our results demonstrate that DNA microarray technology cannot be used as the only technique to investigate the mechanisms of action of new antimicrobial compounds. However, by combining DNA microarray analysis with the subsequent creation of knockout mutants, we were able to pinpoint one...

  15. Increasing the specificity and function of DNA microarrays by processing arrays at different stringencies

    DEFF Research Database (Denmark)

    Dufva, Martin; Petersen, Jesper; Poulsen, Lena

    2009-01-01

    DNA microarrays have for a decade been the only platform for genome-wide analysis and have provided a wealth of information about living organisms. DNA microarrays are processed today under one condition only, which puts large demands on assay development because all probes on the array need to f...

  16. Generalization of DNA microarray dispersion properties: microarray equivalent of t-distribution

    DEFF Research Database (Denmark)

    Novak, Jaroslav P; Kim, Seon-Young; Xu, Jun

    2006-01-01

    BACKGROUND: DNA microarrays are a powerful technology that can provide a wealth of gene expression data for disease studies, drug development, and a wide scope of other investigations. Because of the large volume and inherent variability of DNA microarray data, many new statistical methods have...

  17. Spot detection and image segmentation in DNA microarray data.

    Science.gov (United States)

    Qin, Li; Rueda, Luis; Ali, Adnan; Ngom, Alioune

    2005-01-01

    Following the invention of microarrays in 1994, the development and applications of this technology have grown exponentially. The numerous applications of microarray technology include clinical diagnosis and treatment, drug design and discovery, tumour detection, and environmental health research. One of the key issues in the experimental approaches utilising microarrays is to extract quantitative information from the spots, which represent genes in a given experiment. For this process, the initial stages are important and they influence future steps in the analysis. Identifying the spots and separating the background from the foreground is a fundamental problem in DNA microarray data analysis. In this review, we present an overview of state-of-the-art methods for microarray image segmentation. We discuss the foundations of the circle-shaped approach, adaptive shape segmentation, histogram-based methods and the recently introduced clustering-based techniques. We analytically show that clustering-based techniques are equivalent to the one-dimensional, standard k-means clustering algorithm that utilises the Euclidean distance.

  18. Transcriptomic identification of candidate genes involved in sunflower responses to chilling and salt stresses based on cDNA microarray analysis

    Directory of Open Access Journals (Sweden)

    Paniego Norma

    2008-01-01

    Full Text Available Abstract Background Considering that sunflower production is expanding to arid regions, tolerance to abiotic stresses as drought, low temperatures and salinity arises as one of the main constrains nowadays. Differential organ-specific sunflower ESTs (expressed sequence tags were previously generated by a subtractive hybridization method that included a considerable number of putative abiotic stress associated sequences. The objective of this work is to analyze concerted gene expression profiles of organ-specific ESTs by fluorescence microarray assay, in response to high sodium chloride concentration and chilling treatments with the aim to identify and follow up candidate genes for early responses to abiotic stress in sunflower. Results Abiotic-related expressed genes were the target of this characterization through a gene expression analysis using an organ-specific cDNA fluorescence microarray approach in response to high salinity and low temperatures. The experiment included three independent replicates from leaf samples. We analyzed 317 unigenes previously isolated from differential organ-specific cDNA libraries from leaf, stem and flower at R1 and R4 developmental stage. A statistical analysis based on mean comparison by ANOVA and ordination by Principal Component Analysis allowed the detection of 80 candidate genes for either salinity and/or chilling stresses. Out of them, 50 genes were up or down regulated under both stresses, supporting common regulatory mechanisms and general responses to chilling and salinity. Interestingly 15 and 12 sequences were up regulated or down regulated specifically in one stress but not in the other, respectively. These genes are potentially involved in different regulatory mechanisms including transcription/translation/protein degradation/protein folding/ROS production or ROS-scavenging. Differential gene expression patterns were confirmed by qRT-PCR for 12.5% of the microarray candidate sequences. Conclusion

  19. DNA microarray technology in nutraceutical and food safety.

    Science.gov (United States)

    Liu-Stratton, Yiwen; Roy, Sashwati; Sen, Chandan K

    2004-04-15

    The quality and quantity of diet is a key determinant of health and disease. Molecular diagnostics may play a key role in food safety related to genetically modified foods, food-borne pathogens and novel nutraceuticals. Functional outcomes in biology are determined, for the most part, by net balance between sets of genes related to the specific outcome in question. The DNA microarray technology offers a new dimension of strength in molecular diagnostics by permitting the simultaneous analysis of large sets of genes. Automation of assay and novel bioinformatics tools make DNA microarrays a robust technology for diagnostics. Since its development a few years ago, this technology has been used for the applications of toxicogenomics, pharmacogenomics, cell biology, and clinical investigations addressing the prevention and intervention of diseases. Optimization of this technology to specifically address food safety is a vast resource that remains to be mined. Efforts to develop diagnostic custom arrays and simplified bioinformatics tools for field use are warranted.

  20. Comparing transformation methods for DNA microarray data

    Directory of Open Access Journals (Sweden)

    Zwinderman Aeilko H

    2004-06-01

    Full Text Available Abstract Background When DNA microarray data are used for gene clustering, genotype/phenotype correlation studies, or tissue classification the signal intensities are usually transformed and normalized in several steps in order to improve comparability and signal/noise ratio. These steps may include subtraction of an estimated background signal, subtracting the reference signal, smoothing (to account for nonlinear measurement effects, and more. Different authors use different approaches, and it is generally not clear to users which method they should prefer. Results We used the ratio between biological variance and measurement variance (which is an F-like statistic as a quality measure for transformation methods, and we demonstrate a method for maximizing that variance ratio on real data. We explore a number of transformations issues, including Box-Cox transformation, baseline shift, partial subtraction of the log-reference signal and smoothing. It appears that the optimal choice of parameters for the transformation methods depends on the data. Further, the behavior of the variance ratio, under the null hypothesis of zero biological variance, appears to depend on the choice of parameters. Conclusions The use of replicates in microarray experiments is important. Adjustment for the null-hypothesis behavior of the variance ratio is critical to the selection of transformation method.

  1. Identification of late O{sub 3}-responsive genes in Arabidopsis thaliana by cDNA microarray analysis

    Energy Technology Data Exchange (ETDEWEB)

    D' Haese, D. [Univ. of Antwerp, Dept. of Biology, Antwerp (BE) and Univ. of Newcastle, School of Biology and Psychology, Div. of Biology, Newcastle-Upon-Tyne (United Kingdom); Horemans, N.; Coen, W. De; Guisez, Y. [Univ. of Antwerp, Dept. of Biology, Antwerp (Belgium)

    2006-09-15

    To better understand the response of a plant to 0{sub 3} stress, an integrated microarray analysis was performed on Arabidopsis plants exposed during 2 days to purified air or 150 nl l{sup -1} O{sub 3}, 8 h day-l. Agilent Arabidopsis 2 Oligo Microarrays were used of which the reliability was confirmed by quantitative real-time PCR of nine randomly selected genes. We confirmed the O{sub 3} responsiveness of heat shock proteins (HSPs), glutathione-S-tranferases and genes involved in cell wall stiffening and microbial defence. Whereas, a previous study revealed that during an early stage of the O{sub 3} stress response, gene expression was strongly dependent on jasmonic acid and ethylene, we report that at a later stage (48 h) synthesis of jasrnonic acid and ethylene was downregulated. In addition, we observed the simultaneous induction of salicylic acid synthesis and genes involved in programmed cell death and senescence. Also typically, the later stage of the response to O{sub 3} appeared to be the induction of the complete pathway leading to the biosynthesis of anthocyanin diglucosides and the induction of thioredoxin-based redox control. Surprisingly absent in the list of induced genes were genes involved in ASC-dependent antioxidation, few of which were found to be induced after 12 h of 0{sub 3} exposure in another study. We discuss these and other particular results of the microarray analysis and provide a map depicting significantly affected genes and their pathways highlighting their interrelationships and subcellular localization. (au)

  2. Molecular biological identification of Babesia, Theileria, and Anaplasma species in cattle in Egypt using PCR assays, gene sequence analysis and a novel DNA microarray.

    Science.gov (United States)

    El-Ashker, Maged; Hotzel, Helmut; Gwida, Mayada; El-Beskawy, Mohamed; Silaghi, Cornelia; Tomaso, Herbert

    2015-01-30

    In this preliminary study, a novel DNA microarray system was tested for the diagnosis of bovine piroplasmosis and anaplasmosis in comparison with microscopy and PCR assay results. In the Dakahlia Governorate, Egypt, 164 cattle were investigated for the presence of piroplasms and Anaplasma species. All investigated cattle were clinically examined. Blood samples were screened for the presence of blood parasites using microscopy and PCR assays. Seventy-one animals were acutely ill, whereas 93 were apparently healthy. In acutely ill cattle, Babesia/Theileria species (n=11) and Anaplasma marginale (n=10) were detected. Mixed infections with Babesia/Theileria spp. and A. marginale were present in two further cases. A. marginale infections were also detected in apparently healthy subjects (n=23). The results of PCR assays were confirmed by DNA sequencing. All samples that were positive by PCR for Babesia/Theileria spp. gave also positive results in the microarray analysis. The microarray chips identified Babesia bovis (n=12) and Babesia bigemina (n=2). Cattle with babesiosis were likely to have hemoglobinuria and nervous signs when compared to those with anaplasmosis that frequently had bloody feces. We conclude that clinical examination in combination with microscopy are still very useful in diagnosing acute cases of babesiosis and anaplasmosis, but a combination of molecular biological diagnostic assays will detect even asymptomatic carriers. In perspective, parallel detection of Babesia/Theileria spp. and A. marginale infections using a single microarray system will be a valuable improvement. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

  3. Uses of Dendrimers for DNA Microarrays

    Directory of Open Access Journals (Sweden)

    Jean-Pierre Majoral

    2006-08-01

    Full Text Available Biosensors such as DNA microarrays and microchips are gaining an increasingimportance in medicinal, forensic, and environmental analyses. Such devices are based onthe detection of supramolecular interactions called hybridizations that occur betweencomplementary oligonucleotides, one linked to a solid surface (the probe, and the other oneto be analyzed (the target. This paper focuses on the improvements that hyperbranched andperfectly defined nanomolecules called dendrimers can provide to this methodology. Twomain uses of dendrimers for such purpose have been described up to now; either thedendrimer is used as linker between the solid surface and the probe oligonucleotide, or thedendrimer is used as a multilabeled entity linked to the target oligonucleotide. In the firstcase the dendrimer generally induces a higher loading of probes and an easier hybridization,due to moving away the solid phase. In the second case the high number of localized labels(generally fluorescent induces an increased sensitivity, allowing the detection of smallquantities of biological entities.

  4. Polyadenylation state microarray (PASTA) analysis.

    Science.gov (United States)

    Beilharz, Traude H; Preiss, Thomas

    2011-01-01

    Nearly all eukaryotic mRNAs terminate in a poly(A) tail that serves important roles in mRNA utilization. In the cytoplasm, the poly(A) tail promotes both mRNA stability and translation, and these functions are frequently regulated through changes in tail length. To identify the scope of poly(A) tail length control in a transcriptome, we developed the polyadenylation state microarray (PASTA) method. It involves the purification of mRNA based on poly(A) tail length using thermal elution from poly(U) sepharose, followed by microarray analysis of the resulting fractions. In this chapter we detail our PASTA approach and describe some methods for bulk and mRNA-specific poly(A) tail length measurements of use to monitor the procedure and independently verify the microarray data.

  5. 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.

  6. DNA microarray-based PCR ribotyping of Clostridium difficile.

    Science.gov (United States)

    Schneeberg, Alexander; Ehricht, Ralf; Slickers, Peter; Baier, Vico; Neubauer, Heinrich; Zimmermann, Stefan; Rabold, Denise; Lübke-Becker, Antina; Seyboldt, Christian

    2015-02-01

    This study presents a DNA microarray-based assay for fast and simple PCR ribotyping of Clostridium difficile strains. Hybridization probes were designed to query the modularly structured intergenic spacer region (ISR), which is also the template for conventional and PCR ribotyping with subsequent capillary gel electrophoresis (seq-PCR) ribotyping. The probes were derived from sequences available in GenBank as well as from theoretical ISR module combinations. A database of reference hybridization patterns was set up from a collection of 142 well-characterized C. difficile isolates representing 48 seq-PCR ribotypes. The reference hybridization patterns calculated by the arithmetic mean were compared using a similarity matrix analysis. The 48 investigated seq-PCR ribotypes revealed 27 array profiles that were clearly distinguishable. The most frequent human-pathogenic ribotypes 001, 014/020, 027, and 078/126 were discriminated by the microarray. C. difficile strains related to 078/126 (033, 045/FLI01, 078, 126, 126/FLI01, 413, 413/FLI01, 598, 620, 652, and 660) and 014/020 (014, 020, and 449) showed similar hybridization patterns, confirming their genetic relatedness, which was previously reported. A panel of 50 C. difficile field isolates was tested by seq-PCR ribotyping and the DNA microarray-based assay in parallel. Taking into account that the current version of the microarray does not discriminate some closely related seq-PCR ribotypes, all isolates were typed correctly. Moreover, seq-PCR ribotypes without reference profiles available in the database (ribotype 009 and 5 new types) were correctly recognized as new ribotypes, confirming the performance and expansion potential of the microarray. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

  7. Microarray of DNA probes on carboxylate functional beads surface

    Institute of Scientific and Technical Information of China (English)

    黄承志; 李原芳; 黄新华; 范美坤

    2000-01-01

    The microarray of DNA probes with 5’ -NH2 and 5’ -Tex/3’ -NH2 modified terminus on 10 um carboxylate functional beads surface in the presence of 1-ethyl-3-(3-dimethylaminopropyl)-carbodiimide (EDC) is characterized in the preseni paper. it was found that the microarray capacity of DNA probes on the beads surface depends on the pH of the aqueous solution, the concentra-tion of DNA probe and the total surface area of the beads. On optimal conditions, the minimum distance of 20 mer single-stranded DNA probe microarrayed on beads surface is about 14 nm, while that of 20 mer double-stranded DNA probes is about 27 nm. If the probe length increases from 20 mer to 35 mer, its microarray density decreases correspondingly. Mechanism study shows that the binding mode of DNA probes on the beads surface is nearly parallel to the beads surface.

  8. Microarray of DNA probes on carboxylate functional beads surface

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    The microarray of DNA probes with 5′-NH2 and 5′-Tex/3′-NH2 modified terminus on 10 m m carboxylate functional beads surface in the presence of 1-ethyl-3-(3-dimethylaminopropyl)- carbodiimide (EDC) is characterized in the present paper. It was found that the microarray capacity of DNA probes on the beads surface depends on the pH of the aqueous solution, the concentration of DNA probe and the total surface area of the beads. On optimal conditions, the minimum distance of 20 mer single-stranded DNA probe microarrayed on beads surface is about 14 nm, while that of 20 mer double-stranded DNA probes is about 27 nm. If the probe length increases from 20 mer to 35 mer, its microarray density decreases correspondingly. Mechanism study shows that the binding mode of DNA probes on the beads surface is nearly parallel to the beads surface.

  9. Gene organization in rice revealed by full-length cDNA mapping and gene expression analysis through microarray.

    Directory of Open Access Journals (Sweden)

    Kouji Satoh

    Full Text Available Rice (Oryza sativa L. is a model organism for the functional genomics of monocotyledonous plants since the genome size is considerably smaller than those of other monocotyledonous plants. Although highly accurate genome sequences of indica and japonica rice are available, additional resources such as full-length complementary DNA (FL-cDNA sequences are also indispensable for comprehensive analyses of gene structure and function. We cross-referenced 28.5K individual loci in the rice genome defined by mapping of 578K FL-cDNA clones with the 56K loci predicted in the TIGR genome assembly. Based on the annotation status and the presence of corresponding cDNA clones, genes were classified into 23K annotated expressed (AE genes, 33K annotated non-expressed (ANE genes, and 5.5K non-annotated expressed (NAE genes. We developed a 60mer oligo-array for analysis of gene expression from each locus. Analysis of gene structures and expression levels revealed that the general features of gene structure and expression of NAE and ANE genes were considerably different from those of AE genes. The results also suggested that the cloning efficiency of rice FL-cDNA is associated with the transcription activity of the corresponding genetic locus, although other factors may also have an effect. Comparison of the coverage of FL-cDNA among gene families suggested that FL-cDNA from genes encoding rice- or eukaryote-specific domains, and those involved in regulatory functions were difficult to produce in bacterial cells. Collectively, these results indicate that rice genes can be divided into distinct groups based on transcription activity and gene structure, and that the coverage bias of FL-cDNA clones exists due to the incompatibility of certain eukaryotic genes in bacteria.

  10. Principles of gene microarray data analysis.

    Science.gov (United States)

    Mocellin, Simone; Rossi, Carlo Riccardo

    2007-01-01

    The development of several gene expression profiling methods, such as comparative genomic hybridization (CGH), differential display, serial analysis of gene expression (SAGE), and gene microarray, together with the sequencing of the human genome, has provided an opportunity to monitor and investigate the complex cascade of molecular events leading to tumor development and progression. The availability of such large amounts of information has shifted the attention of scientists towards a nonreductionist approach to biological phenomena. High throughput technologies can be used to follow changing patterns of gene expression over time. Among them, gene microarray has become prominent because it is easier to use, does not require large-scale DNA sequencing, and allows for the parallel quantification of thousands of genes from multiple samples. Gene microarray technology is rapidly spreading worldwide and has the potential to drastically change the therapeutic approach to patients affected with tumor. Therefore, it is of paramount importance for both researchers and clinicians to know the principles underlying the analysis of the huge amount of data generated with microarray technology.

  11. cDNA microarray screening in food safety

    International Nuclear Information System (INIS)

    Roy, Sashwati; Sen, Chandan K.

    2006-01-01

    The cDNA microarray technology and related bioinformatics tools presents a wide range of novel application opportunities. The technology may be productively applied to address food safety. In this mini-review article, we present an update highlighting the late breaking discoveries that demonstrate the vitality of cDNA microarray technology as a tool to analyze food safety with reference to microbial pathogens and genetically modified foods. In order to bring the microarray technology to mainstream food safety, it is important to develop robust user-friendly tools that may be applied in a field setting. In addition, there needs to be a standardized process for regulatory agencies to interpret and act upon microarray-based data. The cDNA microarray approach is an emergent technology in diagnostics. Its values lie in being able to provide complimentary molecular insight when employed in addition to traditional tests for food safety, as part of a more comprehensive battery of tests

  12. Analysis of the effects of sex hormone background on the rat choroid plexus transcriptome by cDNA microarrays.

    Directory of Open Access Journals (Sweden)

    Telma Quintela

    Full Text Available The choroid plexus (CP are highly vascularized branched structures that protrude into the ventricles of the brain, and form a unique interface between the blood and the cerebrospinal fluid (CSF, the blood-CSF barrier, that are the main site of production and secretion of CSF. Sex hormones are widely recognized as neuroprotective agents against several neurodegenerative diseases, and the presence of sex hormones cognate receptors suggest that it may be a target for these hormones. In an effort to provide further insight into the neuroprotective mechanisms triggered by sex hormones we analyzed gene expression differences in the CP of female and male rats subjected to gonadectomy, using microarray technology. In gonadectomized female and male animals, 3045 genes were differentially expressed by 1.5-fold change, compared to sham controls. Analysis of the CP transcriptome showed that the top-five pathways significantly regulated by the sex hormone background are olfactory transduction, taste transduction, metabolism, steroid hormone biosynthesis and circadian rhythm pathways. These results represent the first overview of global expression changes in CP of female and male rats induced by gonadectomy and suggest that sex hormones are implicated in pathways with central roles in CP functions and CSF homeostasis.

  13. Chromosomal Localization of DNA Amplifications in Neuroblastoma Tumors Using cDNA Microarray Comparative Genomic Hybridization

    Directory of Open Access Journals (Sweden)

    Ben Beheshti

    2003-01-01

    Full Text Available Conventional comparative genomic hybridization (CGH profiling of neuroblastomas has identified many genomic aberrations, although the limited resolution has precluded a precise localization of sequences of interest within amplicons. To map high copy number genomic gains in clinically matched stage IV neuroblastomas, CGH analysis using a 19,200-feature cDNA microarray was used. A dedicated (freely available algorithm was developed for rapid in silico determination of chromosomal localizations of microarray cDNA targets, and for generation of an ideogram-type profile of copy number changes. Using these methodologies, novel gene amplifications undetectable by chromosome CGH were identified, and larger MYCN amplicon sizes (in one tumor up to 6 Mb than those previously reported in neuroblastoma were identified. The genes HPCAL1, LPIN1/KIAA0188, NAG, and NSE1/LOC151354 were found to be coamplified with MYCN. To determine whether stage IV primary tumors could be further subclassified based on their genomic copy number profiles, hierarchical clustering was performed. Cluster analysis of microarray CGH data identified three groups: 1 no amplifications evident, 2 a small MYCN amplicon as the only detectable imbalance, and 3 a large MYCN amplicon with additional gene amplifications. Application of CGH to cDNA microarray targets will help to determine both the variation of amplicon size and help better define amplification-dependent and independent pathways of progression in neuroblastoma.

  14. Bifidobacterium breve B-3 exerts metabolic syndrome-suppressing effects in the liver of diet-induced obese mice: a DNA microarray analysis.

    Science.gov (United States)

    Kondo, S; Kamei, A; Xiao, J Z; Iwatsuki, K; Abe, K

    2013-09-01

    We previously reported that supplementation with Bifidobacterium breve B-3 reduced body weight gain and accumulation of visceral fat in a dose-dependent manner, and improved serum levels of total cholesterol, glucose and insulin in a mouse model of diet-induced obesity. In this study, we investigated the expression of genes in the liver using DNA microarray analysis and q-PCR to reveal the mechanism of these anti-obesity effects in this mouse model. Administration of B. breve B-3 led to regulated gene expression of pathways involved in lipid metabolism and response to stress. The results indicate that these regulations in the liver are related to the anti-metabolic syndrome effects of B. breve B-3.

  15. An Overview of DNA Microarray Grid Alignment and Foreground Separation Approaches

    Directory of Open Access Journals (Sweden)

    Bajcsy Peter

    2006-01-01

    Full Text Available This paper overviews DNA microarray grid alignment and foreground separation approaches. Microarray grid alignment and foreground separation are the basic processing steps of DNA microarray images that affect the quality of gene expression information, and hence impact our confidence in any data-derived biological conclusions. Thus, understanding microarray data processing steps becomes critical for performing optimal microarray data analysis. In the past, the grid alignment and foreground separation steps have not been covered extensively in the survey literature. We present several classifications of existing algorithms, and describe the fundamental principles of these algorithms. Challenges related to automation and reliability of processed image data are outlined at the end of this overview paper.

  16. Eureka-DMA: an easy-to-operate graphical user interface for fast comprehensive investigation and analysis of DNA microarray data.

    Science.gov (United States)

    Abelson, Sagi

    2014-02-24

    In the past decade, the field of molecular biology has become increasingly quantitative; rapid development of new technologies enables researchers to investigate and address fundamental issues quickly and in an efficient manner which were once impossible. Among these technologies, DNA microarray provides methodology for many applications such as gene discovery, diseases diagnosis, drug development and toxicological research and it has been used increasingly since it first emerged. Multiple tools have been developed to interpret the high-throughput data produced by microarrays. However, many times, less consideration has been given to the fact that an extensive and effective interpretation requires close interplay between the bioinformaticians who analyze the data and the biologists who generate it. To bridge this gap and to simplify the usability of such tools we developed Eureka-DMA - an easy-to-operate graphical user interface that allows bioinformaticians and bench-biologists alike to initiate analyses as well as to investigate the data produced by DNA microarrays. In this paper, we describe Eureka-DMA, a user-friendly software that comprises a set of methods for the interpretation of gene expression arrays. Eureka-DMA includes methods for the identification of genes with differential expression between conditions; it searches for enriched pathways and gene ontology terms and combines them with other relevant features. It thus enables the full understanding of the data for following testing as well as generating new hypotheses. Here we show two analyses, demonstrating examples of how Eureka-DMA can be used and its capability to produce relevant and reliable results. We have integrated several elementary expression analysis tools to provide a unified interface for their implementation. Eureka-DMA's simple graphical user interface provides effective and efficient framework in which the investigator has the full set of tools for the visualization and interpretation

  17. Construction of a cDNA microarray derived from the ascidian Ciona intestinalis.

    Science.gov (United States)

    Azumi, Kaoru; Takahashi, Hiroki; Miki, Yasufumi; Fujie, Manabu; Usami, Takeshi; Ishikawa, Hisayoshi; Kitayama, Atsusi; Satou, Yutaka; Ueno, Naoto; Satoh, Nori

    2003-10-01

    A cDNA microarray was constructed from a basal chordate, the ascidian Ciona intestinalis. The draft genome of Ciona has been read and inferred to contain approximately 16,000 protein-coding genes, and cDNAs for transcripts of 13,464 genes have been characterized and compiled as the "Ciona intestinalis Gene Collection Release I". In the present study, we constructed a cDNA microarray of these 13,464 Ciona genes. A preliminary experiment with Cy3- and Cy5-labeled probes showed extensive differential gene expression between fertilized eggs and larvae. In addition, there was a good correlation between results obtained by the present microarray analysis and those from previous EST analyses. This first microarray of a large collection of Ciona intestinalis cDNA clones should facilitate the analysis of global gene expression and gene networks during the embryogenesis of basal chordates.

  18. Microarray analysis of DNA damage repair gene expression profiles in cervical cancer cells radioresistant to 252Cf neutron and X-rays

    International Nuclear Information System (INIS)

    Qing, Yi; Wang, Ge; Wang, Dong; Yang, Xue-Qin; Zhong, Zhao-Yang; Lei, Xin; Xie, Jia-Yin; Li, Meng-Xia; Xiang, De-Bing; Li, Zeng-Peng; Yang, Zhen-Zhou

    2010-01-01

    The aim of the study was to obtain stable radioresistant sub-lines from the human cervical cancer cell line HeLa by prolonged exposure to 252 Cf neutron and X-rays. Radioresistance mechanisms were investigated in the resulting cells using microarray analysis of DNA damage repair genes. HeLa cells were treated with fractionated 252 Cf neutron and X-rays, with a cumulative dose of 75 Gy each, over 8 months, yielding the sub-lines HeLaNR and HeLaXR. Radioresistant characteristics were detected by clone formation assay, ultrastructural observations, cell doubling time, cell cycle distribution, and apoptosis assay. Gene expression patterns of the radioresistant sub-lines were studied through microarray analysis and verified by Western blotting and real-time PCR. The radioresistant sub-lines HeLaNR and HeLaXR were more radioresisitant to 252 Cf neutron and X-rays than parental HeLa cells by detecting their radioresistant characteristics, respectively. Compared to HeLa cells, the expression of 24 genes was significantly altered by at least 2-fold in HeLaNR cells. Of these, 19 genes were up-regulated and 5 down-regulated. In HeLaXR cells, 41 genes were significantly altered by at least 2-fold; 38 genes were up-regulated and 3 down-regulated. Chronic exposure of cells to ionizing radiation induces adaptive responses that enhance tolerance of ionizing radiation and allow investigations of cellular radioresistance mechanisms. The insights gained into the molecular mechanisms activated by these 'radioresistance' genes will lead to new therapeutic targets for cervical cancer

  19. Mining meiosis and gametogenesis with DNA microarrays.

    Science.gov (United States)

    Schlecht, Ulrich; Primig, Michael

    2003-04-01

    Gametogenesis is a key developmental process that involves complex transcriptional regulation of numerous genes including many that are conserved between unicellular eukaryotes and mammals. Recent expression-profiling experiments using microarrays have provided insight into the co-ordinated transcription of several hundred genes during mitotic growth and meiotic development in budding and fission yeast. Furthermore, microarray-based studies have identified numerous loci that are regulated during the cell cycle or expressed in a germ-cell specific manner in eukaryotic model systems like Caenorhabditis elegans, Mus musculus as well as Homo sapiens. The unprecedented amount of information produced by post-genome biology has spawned novel approaches to organizing biological knowledge using currently available information technology. This review outlines experiments that contribute to an emerging comprehensive picture of the molecular machinery governing sexual reproduction in eukaryotes.

  20. Design issues in toxicogenomics using DNA microarray experiment

    International Nuclear Information System (INIS)

    Lee, Kyoung-Mu; Kim, Ju-Han; Kang, Daehee

    2005-01-01

    The methods of toxicogenomics might be classified into omics study (e.g., genomics, proteomics, and metabolomics) and population study focusing on risk assessment and gene-environment interaction. In omics study, microarray is the most popular approach. Genes falling into several categories (e.g., xenobiotics metabolism, cell cycle control, DNA repair etc.) can be selected up to 20,000 according to a priori hypothesis. The appropriate type of samples and species should be selected in advance. Multiple doses and varied exposure durations are suggested to identify those genes clearly linked to toxic response. Microarray experiments can be affected by numerous nuisance variables including experimental designs, sample extraction, type of scanners, etc. The number of slides might be determined from the magnitude and variance of expression change, false-positive rate, and desired power. Instead, pooling samples is an alternative. Online databases on chemicals with known exposure-disease outcomes and genetic information can aid the interpretation of the normalized results. Gene function can be inferred from microarray data analyzed by bioinformatics methods such as cluster analysis. The population study often adopts hospital-based or nested case-control design. Biases in subject selection and exposure assessment should be minimized, and confounding bias should also be controlled for in stratified or multiple regression analysis. Optimal sample sizes are dependent on the statistical test for gene-to-environment or gene-to-gene interaction. The design issues addressed in this mini-review are crucial in conducting toxicogenomics study. In addition, integrative approach of exposure assessment, epidemiology, and clinical trial is required

  1. Probe Selection for DNA Microarrays using OligoWiz

    DEFF Research Database (Denmark)

    Wernersson, Rasmus; Juncker, Agnieszka; Nielsen, Henrik Bjørn

    2007-01-01

    Nucleotide abundance measurements using DNA microarray technology are possible only if appropriate probes complementary to the target nucleotides can be identified. Here we present a protocol for selecting DNA probes for microarrays using the OligoWiz application. OligoWiz is a client-server appl......Nucleotide abundance measurements using DNA microarray technology are possible only if appropriate probes complementary to the target nucleotides can be identified. Here we present a protocol for selecting DNA probes for microarrays using the OligoWiz application. OligoWiz is a client......-server application that offers a detailed graphical interface and real-time user interaction on the client side, and massive computer power and a large collection of species databases (400, summer 2007) on the server side. Probes are selected according to five weighted scores: cross-hybridization, deltaT(m), folding...... computer skills and can be executed from any Internet-connected computer. The probe selection procedure for a standard microarray design targeting all yeast transcripts can be completed in 1 h....

  2. Analysis of cellular responses to aflatoxin B1 in yeast expressing human cytochrome P450 1A2 using cDNA microarrays

    International Nuclear Information System (INIS)

    Guo Yingying; Breeden, Linda L.; Fan, Wenhong; Zhao Lueping; Eaton, David L.; Zarbl, Helmut

    2006-01-01

    Aflatoxin B1 (AFB 1 ) is a potent human hepatotoxin and hepatocarcinogen produced by the mold Aspergillus flavus. In human, AFB 1 is bioactivated by cytochrome P450 (CYP450) enzymes, primarily CYP1A2, to the genotoxic epoxide that forms N 7 -guanine DNA adducts. To characterize the transcriptional responses to genotoxic insults from AFB 1 , a strain of Saccharomyces cerevisiae engineered to express human CYP1A2 was exposed to doses of AFB 1 that resulted in minimal lethality, but substantial genotoxicity. Flow cytometric analysis demonstrated a dose and time dependent S phase delay under the same treatment conditions, indicating a checkpoint response to DNA damage. Replicate cDNA microarray analyses of AFB 1 treated cells showed that about 200 genes were significantly affected by the exposure. The genes activated by AFB 1 -treatment included RAD51, DUN1 and other members of the DNA damage response signature reported in a previous study with methylmethane sulfonate and ionizing radiation [A.P. Gasch, M. Huang, S. Metzner, D. Botstein, S.J. Elledge, P.O. Brown, Genomic expression responses to DNA-damaging agents and the regulatory role of the yeast ATR homolog Mec1p, Mol. Biol. Cell 12 (2001) 2987-3003]. However, unlike previous studies using highly cytotoxic doses, environmental stress response genes [A.P. Gasch, P.T. Spellman, C.M. Kao, O. Carmel-Harel, M.B. Eisen, G. Storz, D. Botstein, P.O. Brown, Genomic expression programs in the response of yeast cells to environmental changes, Mol. Biol. Cell 11 (2000) 4241-4257] were largely unaffected by our dosing regimen. About half of the transcripts affected are also known to be cell cycle regulated. The most strongly repressed transcripts were those encoding the histone genes and a group of genes that are cell cycle regulated and peak in M phase and early G1. These include most of the known daughter-specific genes. The rapid and coordinated repression of histones and M/G1-specific transcripts cannot be explained by

  3. Analysis of cellular responses to aflatoxin B{sub 1} in yeast expressing human cytochrome P450 1A2 using cDNA microarrays

    Energy Technology Data Exchange (ETDEWEB)

    Guo Yingying [Departmental of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA (United States); Fred Hutchinson Cancer Research Center, Seattle, WA (United States); Breeden, Linda L. [Fred Hutchinson Cancer Research Center, Seattle, WA (United States); Fan, Wenhong [Fred Hutchinson Cancer Research Center, Seattle, WA (United States); Zhao Lueping [Fred Hutchinson Cancer Research Center, Seattle, WA (United States); Eaton, David L. [Departmental of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA (United States); Fred Hutchinson Cancer Research Center, Seattle, WA (United States); Zarbl, Helmut [Departmental of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA (United States) and Fred Hutchinson Cancer Research Center, Seattle, WA (United States)]. E-mail: hzarbl@fhcrc.org

    2006-01-29

    Aflatoxin B1 (AFB{sub 1}) is a potent human hepatotoxin and hepatocarcinogen produced by the mold Aspergillus flavus. In human, AFB{sub 1} is bioactivated by cytochrome P450 (CYP450) enzymes, primarily CYP1A2, to the genotoxic epoxide that forms N{sup 7}-guanine DNA adducts. To characterize the transcriptional responses to genotoxic insults from AFB{sub 1}, a strain of Saccharomyces cerevisiae engineered to express human CYP1A2 was exposed to doses of AFB{sub 1} that resulted in minimal lethality, but substantial genotoxicity. Flow cytometric analysis demonstrated a dose and time dependent S phase delay under the same treatment conditions, indicating a checkpoint response to DNA damage. Replicate cDNA microarray analyses of AFB{sub 1} treated cells showed that about 200 genes were significantly affected by the exposure. The genes activated by AFB{sub 1}-treatment included RAD51, DUN1 and other members of the DNA damage response signature reported in a previous study with methylmethane sulfonate and ionizing radiation [A.P. Gasch, M. Huang, S. Metzner, D. Botstein, S.J. Elledge, P.O. Brown, Genomic expression responses to DNA-damaging agents and the regulatory role of the yeast ATR homolog Mec1p, Mol. Biol. Cell 12 (2001) 2987-3003]. However, unlike previous studies using highly cytotoxic doses, environmental stress response genes [A.P. Gasch, P.T. Spellman, C.M. Kao, O. Carmel-Harel, M.B. Eisen, G. Storz, D. Botstein, P.O. Brown, Genomic expression programs in the response of yeast cells to environmental changes, Mol. Biol. Cell 11 (2000) 4241-4257] were largely unaffected by our dosing regimen. About half of the transcripts affected are also known to be cell cycle regulated. The most strongly repressed transcripts were those encoding the histone genes and a group of genes that are cell cycle regulated and peak in M phase and early G1. These include most of the known daughter-specific genes. The rapid and coordinated repression of histones and M/G1-specific

  4. 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.

  5. 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.

  6. 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...

  7. 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

  8. 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

    2017-02-03

    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

  9. Numerical analysis of DNA microarray data of Campylobacter jejuni strains correlated with survival, cytolethal distending toxin and haemolysin analyses

    DEFF Research Database (Denmark)

    On, Stephen L.W.; Dorrell, N.; Petersen, L.

    2006-01-01

    . Among the strains examined, 439 genes were polymorphic. Numerical analysis of these data by use of the squared Euclidean distance coefficient and Ward's clustering method clearly delineated strains into two clusters. CDT and haemolysin activities of cluster 1 strains were not statistically significantly...

  10. Gene expression analysis of the rat testis after treatment with di(2-ethylhexyl) phthalate using cDNA microarray and real-time RT-PCR

    International Nuclear Information System (INIS)

    Kijima, Kazuyasu; Toyosawa, Kaoru; Yasuba, Masashi; Matsuoka, Nobuo; Adachi, Tetsuya; Komiyama, Masatoshi; Mori, Chisato

    2004-01-01

    To investigate the effects of di(2-ethylhexyl) phthalate (DEHP) on gene expression in rat testis, 6-week-old male Sprague-Dawley rats were given a single oral dose of 20 or 2000 mg/kg and euthanized 3, 6, 24, or 72 h thereafter. Terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL)-positive cells were significantly increased in the testis at 24 and 72 h after the exposure to 2000 mg/kg of DEHP. On cDNA microarray analysis, in addition to apoptosis-related genes, genes associated with atrophy, APEX nuclease, MutS homologue (E. coli), testosterone-repressed-prostatic-message-2 (TRPM-2), connective tissue growth factor, collagen alpha 2 type V, and cell adhesion kinase were differentially expressed. To investigate the relationship between histopathological alteration and gene expression, we selected genes associated with apoptosis and analyzed their expression by real-time quantitative reverse transcription-polymerase chain reaction (RT-PCR). With 20 mg/kg of DEHP treatment, bcl-2, key gene related to apoptosis, was increased. Up-regulation of bcl-2, inhibitor of Apaf-1/caspase-9/caspase-2 cascade of apoptosis, may be related to the fact that no morphological apoptotic change was induced after dosing of 20 mg/kg DEHP. With 2000 mg/kg of DEHP treatment, the apoptotic activator cascade, Fas/FasL, FADD/caspase-8/caspase-3 cascade, and Apaf-1/caspase-9/caspase-2 cascade were increased and bcl-2 was decreased. Thus, these gene regulations might lead the cells into apoptosis in the case of high exposure to DEHP. In contrast, FADD/caspase-10/caspase-6 cascade and caspase-11/caspase-3 cascade were not increased. These results indicate that the cascades of FADD/caspase-10/caspase-6 and caspase-11/caspase-3 are not related to apoptosis with DEHP treatment

  11. DNA Microarray Technologies: A Novel Approach to Geonomic Research

    Energy Technology Data Exchange (ETDEWEB)

    Hinman, R.; Thrall, B.; Wong, K,

    2002-01-01

    A cDNA microarray allows biologists to examine the expression of thousands of genes simultaneously. Researchers may analyze the complete transcriptional program of an organism in response to specific physiological or developmental conditions. By design, a cDNA microarray is an experiment with many variables and few controls. One question that inevitably arises when working with a cDNA microarray is data reproducibility. How easy is it to confirm mRNA expression patterns? In this paper, a case study involving the treatment of a murine macrophage RAW 264.7 cell line with tumor necrosis factor alpha (TNF) was used to obtain a rough estimate of data reproducibility. Two trials were examined and a list of genes displaying either a > 2-fold or > 4-fold increase in gene expression was compiled. Variations in signal mean ratios between the two slides were observed. We can assume that erring in reproducibility may be compensated by greater inductive levels of similar genes. Steps taken to obtain results included serum starvation of cells before treatment, tests of mRNA for quality/consistency, and data normalization.

  12. Tissue Microarray Analysis Applied to Bone Diagenesis.

    Science.gov (United States)

    Mello, Rafael Barrios; Silva, Maria Regina Regis; Alves, Maria Teresa Seixas; Evison, Martin Paul; Guimarães, Marco Aurelio; Francisco, Rafaella Arrabaca; Astolphi, Rafael Dias; Iwamura, Edna Sadayo Miazato

    2017-01-04

    Taphonomic processes affecting bone post mortem are important in forensic, archaeological and palaeontological investigations. In this study, the application of tissue microarray (TMA) analysis to a sample of femoral bone specimens from 20 exhumed individuals of known period of burial and age at death is described. TMA allows multiplexing of subsamples, permitting standardized comparative analysis of adjacent sections in 3-D and of representative cross-sections of a large number of specimens. Standard hematoxylin and eosin, periodic acid-Schiff and silver methenamine, and picrosirius red staining, and CD31 and CD34 immunohistochemistry were applied to TMA sections. Osteocyte and osteocyte lacuna counts, percent bone matrix loss, and fungal spheroid element counts could be measured and collagen fibre bundles observed in all specimens. Decalcification with 7% nitric acid proceeded more rapidly than with 0.5 M EDTA and may offer better preservation of histological and cellular structure. No endothelial cells could be detected using CD31 and CD34 immunohistochemistry. Correlation between osteocytes per lacuna and age at death may reflect reported age-related responses to microdamage. Methodological limitations and caveats, and results of the TMA analysis of post mortem diagenesis in bone are discussed, and implications for DNA survival and recovery considered.

  13. An evaluation of two-channel ChIP-on-chip and DNA methylation microarray normalization strategies

    Science.gov (United States)

    2012-01-01

    Background The combination of chromatin immunoprecipitation with two-channel microarray technology enables genome-wide mapping of binding sites of DNA-interacting proteins (ChIP-on-chip) or sites with methylated CpG di-nucleotides (DNA methylation microarray). These powerful tools are the gateway to understanding gene transcription regulation. Since the goals of such studies, the sample preparation procedures, the microarray content and study design are all different from transcriptomics microarrays, the data pre-processing strategies traditionally applied to transcriptomics microarrays may not be appropriate. Particularly, the main challenge of the normalization of "regulation microarrays" is (i) to make the data of individual microarrays quantitatively comparable and (ii) to keep the signals of the enriched probes, representing DNA sequences from the precipitate, as distinguishable as possible from the signals of the un-enriched probes, representing DNA sequences largely absent from the precipitate. Results We compare several widely used normalization approaches (VSN, LOWESS, quantile, T-quantile, Tukey's biweight scaling, Peng's method) applied to a selection of regulation microarray datasets, ranging from DNA methylation to transcription factor binding and histone modification studies. Through comparison of the data distributions of control probes and gene promoter probes before and after normalization, and assessment of the power to identify known enriched genomic regions after normalization, we demonstrate that there are clear differences in performance between normalization procedures. Conclusion T-quantile normalization applied separately on the channels and Tukey's biweight scaling outperform other methods in terms of the conservation of enriched and un-enriched signal separation, as well as in identification of genomic regions known to be enriched. T-quantile normalization is preferable as it additionally improves comparability between microarrays. In

  14. [Preparation of the cDNA microarray on the differential expressed cDNA of senescence-accelerated mouse's hippocampus].

    Science.gov (United States)

    Cheng, Xiao-Rui; Zhou, Wen-Xia; Zhang, Yong-Xiang

    2006-05-01

    Alzheimer' s disease (AD) is the most common form of dementia in the elderly. AD is an invariably fatal neurodegenerative disorder with no effective treatment. Senescence-accelerated mouse prone 8 (SAMP8) is a model for studying age-related cognitive impairments and also is a good model to study brain aging and one of mouse model of AD. The technique of cDNA microarray can monitor the expression levels of thousands of genes simultaneously and can be used to study AD with the character of multi-mechanism, multi-targets and multi-pathway. In order to disclose the mechanism of AD and find the drug targets of AD, cDNA microarray containing 3136 cDNAs amplified from the suppression subtracted cDNA library of hippocampus of SAMP8 and SAMR1 was prepared with 16 blocks and 14 x 14 pins, the housekeeping gene beta-actin and G3PDH as inner conference. The background of this microarray was low and unanimous, and dots divided evenly. The conditions of hybridization and washing were optimized during the hybridization of probe and target molecule. After the data of hybridization analysis, the differential expressed cDNAs were sequenced and analyzed by the bioinformatics, and some of genes were quantified by the real time RT-PCR and the reliability of this cDNA microarray were validated. This cDNA microarray may be the good means to select the differential expressed genes and disclose the molecular mechanism of SAMP8's brain aging and AD.

  15. ESTs, cDNA microarrays, and gene expression profiling: tools for dissecting plant physiology and development.

    Science.gov (United States)

    Alba, Rob; Fei, Zhangjun; Payton, Paxton; Liu, Yang; Moore, Shanna L; Debbie, Paul; Cohn, Jonathan; D'Ascenzo, Mark; Gordon, Jeffrey S; Rose, Jocelyn K C; Martin, Gregory; Tanksley, Steven D; Bouzayen, Mondher; Jahn, Molly M; Giovannoni, Jim

    2004-09-01

    Gene expression profiling holds tremendous promise for dissecting the regulatory mechanisms and transcriptional networks that underlie biological processes. Here we provide details of approaches used by others and ourselves for gene expression profiling in plants with emphasis on cDNA microarrays and discussion of both experimental design and downstream analysis. We focus on methods and techniques emphasizing fabrication of cDNA microarrays, fluorescent labeling, cDNA hybridization, experimental design, and data processing. We include specific examples that demonstrate how this technology can be used to further our understanding of plant physiology and development (specifically fruit development and ripening) and for comparative genomics by comparing transcriptome activity in tomato and pepper fruit.

  16. Development and assessment of microarray-based DNA fingerprinting in Eucalyptus grandis.

    Science.gov (United States)

    Lezar, Sabine; Myburg, A A; Berger, D K; Wingfield, M J; Wingfield, B D

    2004-11-01

    Development of improved Eucalyptus genotypes involves the routine identification of breeding stock and superior clones. Currently, microsatellites and random amplified polymorphic DNA markers are the most widely used DNA-based techniques for fingerprinting of these trees. While these techniques have provided rapid and powerful fingerprinting assays, they are constrained by their reliance on gel or capillary electrophoresis, and therefore, relatively low throughput of fragment analysis. In contrast, recently developed microarray technology holds the promise of parallel analysis of thousands of markers in plant genomes. The aim of this study was to develop a DNA fingerprinting chip for Eucalyptus grandis and to investigate its usefulness for fingerprinting of eucalypt trees. A prototype chip was prepared using a partial genomic library from total genomic DNA of 23 E. grandis trees, of which 22 were full siblings. A total of 384 cloned genomic fragments were individually amplified and arrayed onto glass slides. DNA fingerprints were obtained for 17 individuals by hybridizing labeled genome representations of the individual trees to the 384-element chip. Polymorphic DNA fragments were identified by evaluating the binary distribution of their background-corrected signal intensities across full-sib individuals. Among 384 DNA fragments on the chip, 104 (27%) were found to be polymorphic. Hybridization of these polymorphic fragments was highly repeatable (R2>0.91) within the E. grandis individuals, and they allowed us to identify all 17 full-sib individuals. Our results suggest that DNA microarrays can be used to effectively fingerprint large numbers of closely related Eucalyptus trees.

  17. Autoregressive-model-based missing value estimation for DNA microarray time series data.

    Science.gov (United States)

    Choong, Miew Keen; Charbit, Maurice; Yan, Hong

    2009-01-01

    Missing value estimation is important in DNA microarray data analysis. A number of algorithms have been developed to solve this problem, but they have several limitations. Most existing algorithms are not able to deal with the situation where a particular time point (column) of the data is missing entirely. In this paper, we present an autoregressive-model-based missing value estimation method (ARLSimpute) that takes into account the dynamic property of microarray temporal data and the local similarity structures in the data. ARLSimpute is especially effective for the situation where a particular time point contains many missing values or where the entire time point is missing. Experiment results suggest that our proposed algorithm is an accurate missing value estimator in comparison with other imputation methods on simulated as well as real microarray time series datasets.

  18. A dynamic bead-based microarray for parallel DNA detection

    International Nuclear Information System (INIS)

    Sochol, R D; Lin, L; Casavant, B P; Dueck, M E; Lee, L P

    2011-01-01

    A microfluidic system has been designed and constructed by means of micromachining processes to integrate both microfluidic mixing of mobile microbeads and hydrodynamic microbead arraying capabilities on a single chip to simultaneously detect multiple bio-molecules. The prototype system has four parallel reaction chambers, which include microchannels of 18 × 50 µm 2 cross-sectional area and a microfluidic mixing section of 22 cm length. Parallel detection of multiple DNA oligonucleotide sequences was achieved via molecular beacon probes immobilized on polystyrene microbeads of 16 µm diameter. Experimental results show quantitative detection of three distinct DNA oligonucleotide sequences from the Hepatitis C viral (HCV) genome with single base-pair mismatch specificity. Our dynamic bead-based microarray offers an effective microfluidic platform to increase parallelization of reactions and improve microbead handling for various biological applications, including bio-molecule detection, medical diagnostics and drug screening

  19. Microarrays in ecological research: A case study of a cDNA microarray for plant-herbivore interactions

    Directory of Open Access Journals (Sweden)

    Gase Klaus

    2004-09-01

    Full Text Available Abstract Background Microarray technology allows researchers to simultaneously monitor changes in the expression ratios (ERs of hundreds of genes and has thereby revolutionized most of biology. Although this technique has the potential of elucidating early stages in an organism's phenotypic response to complex ecological interactions, to date, it has not been fully incorporated into ecological research. This is partially due to a lack of simple procedures of handling and analyzing the expression ratio (ER data produced from microarrays. Results We describe an analysis of the sources of variation in ERs from 73 hybridized cDNA microarrays, each with 234 herbivory-elicited genes from the model ecological expression system, Nicotiana attenuata, using procedures that are commonly used in ecologic research. Each gene is represented by two independently labeled PCR products and each product was arrayed in quadruplicate. We present a robust method of normalizing and analyzing ERs based on arbitrary thresholds and statistical criteria, and characterize a "norm of reaction" of ERs for 6 genes (4 of known function, 2 of unknown with different ERs as determined across all analyzed arrays to provide a biologically-informed alternative to the use of arbitrary expression ratios in determining significance of expression. These gene-specific ERs and their variance (gene CV were used to calculate array-based variances (array CV, which, in turn, were used to study the effects of array age, probe cDNA quantity and quality, and quality of spotted PCR products as estimates of technical variation. Cluster analysis and a Principal Component Analysis (PCA were used to reveal associations among the transcriptional "imprints" of arrays hybridized with cDNA probes derived from mRNA from N. attenuata plants variously elicited and attacked by different herbivore species and from three congeners: N. quadrivalis, N. longiflora and N. clevelandii. Additionally, the PCA

  20. Tissue Microarray Analysis Applied to Bone Diagenesis

    OpenAIRE

    Barrios Mello, Rafael; Regis Silva, Maria Regina; Seixas Alves, Maria Teresa; Evison, Martin; Guimarães, Marco Aurélio; Francisco, Rafaella Arrabaça; Dias Astolphi, Rafael; Miazato Iwamura, Edna Sadayo

    2017-01-01

    Taphonomic processes affecting bone post mortem are important in forensic, archaeological and palaeontological investigations. In this study, the application of tissue microarray (TMA) analysis to a sample of femoral bone specimens from 20 exhumed individuals of known period of burial and age at death is described. TMA allows multiplexing of subsamples, permitting standardized comparative analysis of adjacent sections in 3-D and of representative cross-sections of a large number of specimens....

  1. Sensitivity and fidelity of DNA microarray improved with integration of Amplified Differential Gene Expression (ADGE

    Directory of Open Access Journals (Sweden)

    Ile Kristina E

    2003-07-01

    Full Text Available Abstract Background The ADGE technique is a method designed to magnify the ratios of gene expression before detection. It improves the detection sensitivity to small change of gene expression and requires small amount of starting material. However, the throughput of ADGE is low. We integrated ADGE with DNA microarray (ADGE microarray and compared it with regular microarray. Results When ADGE was integrated with DNA microarray, a quantitative relationship of a power function between detected and input ratios was found. Because of ratio magnification, ADGE microarray was better able to detect small changes in gene expression in a drug resistant model cell line system. The PCR amplification of templates and efficient labeling reduced the requirement of starting material to as little as 125 ng of total RNA for one slide hybridization and enhanced the signal intensity. Integration of ratio magnification, template amplification and efficient labeling in ADGE microarray reduced artifacts in microarray data and improved detection fidelity. The results of ADGE microarray were less variable and more reproducible than those of regular microarray. A gene expression profile generated with ADGE microarray characterized the drug resistant phenotype, particularly with reference to glutathione, proliferation and kinase pathways. Conclusion ADGE microarray magnified the ratios of differential gene expression in a power function, improved the detection sensitivity and fidelity and reduced the requirement for starting material while maintaining high throughput. ADGE microarray generated a more informative expression pattern than regular microarray.

  2. DNA microarrays of baculovirus genomes: differential expression of viral genes in two susceptible insect cell lines.

    Science.gov (United States)

    Yamagishi, J; Isobe, R; Takebuchi, T; Bando, H

    2003-03-01

    We describe, for the first time, the generation of a viral DNA chip for simultaneous expression measurements of nearly all known open reading frames (ORFs) in the best-studied members of the family Baculoviridae, Autographa californica multiple nucleopolyhedrovirus (AcMNPV) and Bombyx mori nucleopolyhedrovirus (BmNPV). In this study, a viral DNA chip (Ac-BmNPV chip) was fabricated and used to characterize the viral gene expression profile for AcMNPV in different cell types. The viral chip is composed of microarrays of viral DNA prepared by robotic deposition of PCR-amplified viral DNA fragments on glass for ORFs in the NPV genome. Viral gene expression was monitored by hybridization to the DNA fragment microarrays with fluorescently labeled cDNAs prepared from infected Spodoptera frugiperda, Sf9 cells and Trichoplusia ni, TnHigh-Five cells, the latter a major producer of baculovirus and recombinant proteins. A comparison of expression profiles of known ORFs in AcMNPV elucidated six genes (ORF150, p10, pk2, and three late gene expression factor genes lef-3, p35 and lef- 6) the expression of each of which was regulated differently in the two cell lines. Most of these genes are known to be closely involved in the viral life cycle such as in DNA replication, late gene expression and the release of polyhedra from infected cells. These results imply that the differential expression of these viral genes accounts for the differences in viral replication between these two cell lines. Thus, these fabricated microarrays of NPV DNA which allow a rapid analysis of gene expression at the viral genome level should greatly speed the functional analysis of large genomes of NPV.

  3. A DNA Microarray Analysis of Chemokine and Receptor Genes in the Rat Dental Follicle – Role of Secreted Frizzled-Related Protein-1 in Osteoclastogenesis

    Science.gov (United States)

    Liu, Dawen; Wise, Gary E.

    2007-01-01

    The dental follicle, a loose connective tissue sac that surrounds the unerupted tooth, appears to regulate the osteoclastogenesis needed for eruption; i.e., bone resorption to form an eruption pathway. Thus, DNA microarray studies were conducted to determine which chemokines and their receptors were expressed chronologically in the dental follicle, chemokines that might attract osteoclast precursors. In the rat first mandibular molar, a major burst of osteoclastogenesis occurs at day 3 with a minor burst at day 10. The results of the microarray confirmed our previous studies showing the gene expression of molecules such as CSF-1 and MCP-1 in the dental follicle cells. Other new genes also were detected, including secreted frizzled-related protein-1 (SFRP-1), which was found to be down-regulated at days 3 and 9. Using rat bone marrow cultures to conduct in vitro osteoclastogenic assays, it was demonstrated that SFRP-1 inhibited osteoclast formation in a concentration-dependent fashion. However, with increasing concentrations of SFRP-1, the number of TRAP-positive mononuclear cells increased suggesting that SFRP-1 inhibits osteoclast formation by inhibiting the fusion of mononuclear cells (osteoclast precursors). Co-culturing bone marrow mononuclear cells and dental follicle cells demonstrated that the dental follicle cells were secreting a product(s) that inhibited osteoclastogenesis, as measured by counting of TRAP-positive osteoclasts. Adding an antibody either to SFRP-1 or OPG partially restored osteoclastogenesis. Adding both anti-SFRP-1 and anti-OPG fully negated the inhibitory effect of the follicle cells upon osteoclastogenesis. These results strongly suggest that SFRP-1 and OPG, both secreted by the dental follicle cells, use different pathways to exert their inhibitory effect on osteoclastogenesis. Based on these in vitro studies of osteoclastogenesis, it is likely that the down-regulation of SFRP-1 gene expression in the dental follicle at days 3 and 9 is

  4. 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

  5. The Development of Protein Microarrays and Their Applications in DNA-Protein and Protein-Protein Interaction Analyses of Arabidopsis Transcription Factors

    Science.gov (United States)

    Gong, Wei; He, Kun; Covington, Mike; Dinesh-Kumar, S. P.; Snyder, Michael; Harmer, Stacey L.; Zhu, Yu-Xian; Deng, Xing Wang

    2009-01-01

    We used our collection of Arabidopsis transcription factor (TF) ORFeome clones to construct protein microarrays containing as many as 802 TF proteins. These protein microarrays were used for both protein-DNA and protein-protein interaction analyses. For protein-DNA interaction studies, we examined AP2/ERF family TFs and their cognate cis-elements. By careful comparison of the DNA-binding specificity of 13 TFs on the protein microarray with previous non-microarray data, we showed that protein microarrays provide an efficient and high throughput tool for genome-wide analysis of TF-DNA interactions. This microarray protein-DNA interaction analysis allowed us to derive a comprehensive view of DNA-binding profiles of AP2/ERF family proteins in Arabidopsis. It also revealed four TFs that bound the EE (evening element) and had the expected phased gene expression under clock-regulation, thus providing a basis for further functional analysis of their roles in clock regulation of gene expression. We also developed procedures for detecting protein interactions using this TF protein microarray and discovered four novel partners that interact with HY5, which can be validated by yeast two-hybrid assays. Thus, plant TF protein microarrays offer an attractive high-throughput alternative to traditional techniques for TF functional characterization on a global scale. PMID:19802365

  6. Complete gene expression profiling of Saccharopolyspora erythraea using GeneChip DNA microarrays

    Directory of Open Access Journals (Sweden)

    Bordoni Roberta

    2007-11-01

    Full Text Available Abstract Background The Saccharopolyspora erythraea genome sequence, recently published, presents considerable divergence from those of streptomycetes in gene organization and function, confirming the remarkable potential of S. erythraea for producing many other secondary metabolites in addition to erythromycin. In order to investigate, at whole transcriptome level, how S. erythraea genes are modulated, a DNA microarray was specifically designed and constructed on the S. erythraea strain NRRL 2338 genome sequence, and the expression profiles of 6494 ORFs were monitored during growth in complex liquid medium. Results The transcriptional analysis identified a set of 404 genes, whose transcriptional signals vary during growth and characterize three distinct phases: a rapid growth until 32 h (Phase A; a growth slowdown until 52 h (Phase B; and another rapid growth phase from 56 h to 72 h (Phase C before the cells enter the stationary phase. A non-parametric statistical method, that identifies chromosomal regions with transcriptional imbalances, determined regional organization of transcription along the chromosome, highlighting differences between core and non-core regions, and strand specific patterns of expression. Microarray data were used to characterize the temporal behaviour of major functional classes and of all the gene clusters for secondary metabolism. The results confirmed that the ery cluster is up-regulated during Phase A and identified six additional clusters (for terpenes and non-ribosomal peptides that are clearly regulated in later phases. Conclusion The use of a S. erythraea DNA microarray improved specificity and sensitivity of gene expression analysis, allowing a global and at the same time detailed picture of how S. erythraea genes are modulated. This work underlines the importance of using DNA microarrays, coupled with an exhaustive statistical and bioinformatic analysis of the results, to understand the transcriptional

  7. Radioactive cDNA microarray (II): Gene expression profiling of antidepressant treatment by human cDNA microarray

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Ji Hye; Kang, Rhee Hun; Ham, Byung Joo; Lee, Min Su; Shin, Kyung Ho; Choe, Jae Gol; Kim, Meyoung Kon [College of Medicine, Univ. of Korea, Seoul (Korea, Republic of)

    2003-07-01

    Major depressive disorder is a prevalent psychiatric disorder in primary care, associated with impaired patient functioning and well-being. Fluoxetine is a selective serotonin-reuptake inhibitors (SSRIs) and is a commonly prescribed antidepressant compound. Its action is primarily attributed to selective inhibition of the reuptake of serotonin (5-hydroxytryptamine) in the central nervous system. Objectives ; the aims of this study were two-fold: (1) to determine the usefulness for investigation of the transcription profiles in depression patients, and (2) to assess the differences in gene expression profiles between positive response group and negative response groups by fluoxetine treatment. This study included 53 patients with major depression (26 in positive response group with antidepressant treatment, 27 in negative response group with antidepressant treatment), and 53 healthy controls. To examine the difference of gene expression profile in depression patients, radioactive complementary DNA microarrays were used to evaluate changes in the expression of 1,152 genes in total. Using 33p-labeled probes, this method provided highly sensitive gene expression profiles including brain receptors, drug metabolism, and cellular signaling. Gene transcription profiles were classified into several categories in accordance with the antidepressant gene-regulation. The gene profiles were significantly up-(22 genes) and down-(16 genes) regulated in the positive response group when compared to the control group. Also, in the negative response group, 35 genes were up-regulated and 8 genes were down-regulated when compared to the control group. Consequently, we demonstrated that radioactive human cDNA microarray is highly likely to be an efficient technology for evaluating the gene regulation of antidepressants, such as selective serotonin-reuptake inhibitors (SSRIs), by using high-throughput biotechnology.

  8. Radioactive cDNA microarray (II): Gene expression profiling of antidepressant treatment by human cDNA microarray

    International Nuclear Information System (INIS)

    Lee, Ji Hye; Kang, Rhee Hun; Ham, Byung Joo; Lee, Min Su; Shin, Kyung Ho; Choe, Jae Gol; Kim, Meyoung Kon

    2003-01-01

    Major depressive disorder is a prevalent psychiatric disorder in primary care, associated with impaired patient functioning and well-being. Fluoxetine is a selective serotonin-reuptake inhibitors (SSRIs) and is a commonly prescribed antidepressant compound. Its action is primarily attributed to selective inhibition of the reuptake of serotonin (5-hydroxytryptamine) in the central nervous system. Objectives ; the aims of this study were two-fold: (1) to determine the usefulness for investigation of the transcription profiles in depression patients, and (2) to assess the differences in gene expression profiles between positive response group and negative response groups by fluoxetine treatment. This study included 53 patients with major depression (26 in positive response group with antidepressant treatment, 27 in negative response group with antidepressant treatment), and 53 healthy controls. To examine the difference of gene expression profile in depression patients, radioactive complementary DNA microarrays were used to evaluate changes in the expression of 1,152 genes in total. Using 33p-labeled probes, this method provided highly sensitive gene expression profiles including brain receptors, drug metabolism, and cellular signaling. Gene transcription profiles were classified into several categories in accordance with the antidepressant gene-regulation. The gene profiles were significantly up-(22 genes) and down-(16 genes) regulated in the positive response group when compared to the control group. Also, in the negative response group, 35 genes were up-regulated and 8 genes were down-regulated when compared to the control group. Consequently, we demonstrated that radioactive human cDNA microarray is highly likely to be an efficient technology for evaluating the gene regulation of antidepressants, such as selective serotonin-reuptake inhibitors (SSRIs), by using high-throughput biotechnology

  9. 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.

    Science.gov (United States)

    Dai, Yilin; Guo, Ling; Li, Meng; Chen, Yi-Bu

    2012-06-08

    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. 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. 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.

  10. Clustering approaches to identifying gene expression patterns from DNA microarray data.

    Science.gov (United States)

    Do, Jin Hwan; Choi, Dong-Kug

    2008-04-30

    The analysis of microarray data is essential for large amounts of gene expression data. In this review we focus on clustering techniques. The biological rationale for this approach is the fact that many co-expressed genes are co-regulated, and identifying co-expressed genes could aid in functional annotation of novel genes, de novo identification of transcription factor binding sites and elucidation of complex biological pathways. Co-expressed genes are usually identified in microarray experiments by clustering techniques. There are many such methods, and the results obtained even for the same datasets may vary considerably depending on the algorithms and metrics for dissimilarity measures used, as well as on user-selectable parameters such as desired number of clusters and initial values. Therefore, biologists who want to interpret microarray data should be aware of the weakness and strengths of the clustering methods used. In this review, we survey the basic principles of clustering of DNA microarray data from crisp clustering algorithms such as hierarchical clustering, K-means and self-organizing maps, to complex clustering algorithms like fuzzy clustering.

  11. Examination of gene expression in mice exposed to low dose radiation using affymetrix cDNA microarrays

    Energy Technology Data Exchange (ETDEWEB)

    Morris, D.; Knox, D.; Lavoie, J.; Lemon, J.; Boreham, D. [McMaster Univ., Hamilton, Ontario (Canada)

    2005-07-01

    'Full text:' Gamma radiation acts via the indirect effect to damage cells by producing reactive oxygen species (ROS). These ROS are capable damaging macromolecules and, altering signal pathways and gene transcription. Cells have evolved enzymes and mechanisms to scavenge ROS and repair oxidative damage. Microarrays allow the survey of the gene transcription activity of thousands of genes simultaneously. Messenger RNA is extracted from cells, hybridized with the complementary DNA (cDNA) of a microarray chip, and examined with a chip reader. Affymetrix microarray chips have been produced by the CSCHAH in Winnipeg containing 26000 murine genes. Groups of female mice have been exposed to low dose whole body chronic gamma radiation exposures of 0,50,100, and 120 mGy, corresponding to 15,30,60, and 75 weeks, respectively. MRNA from mice brain tissue has been extracted, isolated, converted to cDNA and labeled. Gene expression in each irradiated mouse was compared to the pooled expression of the control mice. Analysis of gene expression levels are performed with microarray analytical software, Array Pro by Media Cybernetics, and powerful statistical software, BRB microarray tools. Differences in gene expressions, focusing on genes for cytokines, DNA repair mechanisms, immuno-modulators, apoptosis pathways, and enzymatic anti-oxidant systems, are being examined and will be reported. (author)

  12. Robust multi-scale clustering of large DNA microarray datasets with the consensus algorithm

    DEFF Research Database (Denmark)

    Grotkjær, Thomas; Winther, Ole; Regenberg, Birgitte

    2006-01-01

    Motivation: Hierarchical and relocation clustering (e.g. K-means and self-organizing maps) have been successful tools in the display and analysis of whole genome DNA microarray expression data. However, the results of hierarchical clustering are sensitive to outliers, and most relocation methods...... analysis by collecting re-occurring clustering patterns in a co-occurrence matrix. The results show that consensus clustering obtained from clustering multiple times with Variational Bayes Mixtures of Gaussians or K-means significantly reduces the classification error rate for a simulated dataset...

  13. Uropathogenic Escherichia coli virulence genes: invaluable approaches for designing DNA microarray probes.

    Science.gov (United States)

    Jahandeh, Nadia; Ranjbar, Reza; Behzadi, Payam; Behzadi, Elham

    2015-01-01

    The pathotypes of uropathogenic Escherichia coli (UPEC) cause different types of urinary tract infections (UTIs). The presence of a wide range of virulence genes in UPEC enables us to design appropriate DNA microarray probes. These probes, which are used in DNA microarray technology, provide us with an accurate and rapid diagnosis and definitive treatment in association with UTIs caused by UPEC pathotypes. The main goal of this article is to introduce the UPEC virulence genes as invaluable approaches for designing DNA microarray probes. Main search engines such as Google Scholar and databases like NCBI were searched to find and study several original pieces of literature, review articles, and DNA gene sequences. In parallel with in silico studies, the experiences of the authors were helpful for selecting appropriate sources and writing this review article. There is a significant variety of virulence genes among UPEC strains. The DNA sequences of virulence genes are fabulous patterns for designing microarray probes. The location of virulence genes and their sequence lengths influence the quality of probes. The use of selected virulence genes for designing microarray probes gives us a wide range of choices from which the best probe candidates can be chosen. DNA microarray technology provides us with an accurate, rapid, cost-effective, sensitive, and specific molecular diagnostic method which is facilitated by designing microarray probes. Via these tools, we are able to have an accurate diagnosis and a definitive treatment regarding UTIs caused by UPEC pathotypes.

  14. The intraclass correlation coefficient applied for evaluation of data correction, labeling methods and rectal biopsy sampling in DNA microarray experiments

    NARCIS (Netherlands)

    Pellis, E.P.M.; Franssen-Hal, van N.L.W.; Burema, J.; Keijer, J.

    2003-01-01

    We show that the intraclass correlation coefficient (ICC) can be used as a relatively simple statistical measure to assess methodological and biological variation in DNA microarray analysis. The ICC is a measure that determines the reproducibility of a variable, which can easily be calculated from

  15. Microarray MAPH: accurate array-based detection of relative copy number in genomic DNA.

    Science.gov (United States)

    Gibbons, Brian; Datta, Parikkhit; Wu, Ying; Chan, Alan; Al Armour, John

    2006-06-30

    Current methods for measurement of copy number do not combine all the desirable qualities of convenience, throughput, economy, accuracy and resolution. In this study, to improve the throughput associated with Multiplex Amplifiable Probe Hybridisation (MAPH) we aimed to develop a modification based on the 3-Dimensional, Flow-Through Microarray Platform from PamGene International. In this new method, electrophoretic analysis of amplified products is replaced with photometric analysis of a probed oligonucleotide array. Copy number analysis of hybridised probes is based on a dual-label approach by comparing the intensity of Cy3-labelled MAPH probes amplified from test samples co-hybridised with similarly amplified Cy5-labelled reference MAPH probes. The key feature of using a hybridisation-based end point with MAPH is that discrimination of amplified probes is based on sequence and not fragment length. In this study we showed that microarray MAPH measurement of PMP22 gene dosage correlates well with PMP22 gene dosage determined by capillary MAPH and that copy number was accurately reported in analyses of DNA from 38 individuals, 12 of which were known to have Charcot-Marie-Tooth disease type 1A (CMT1A). Measurement of microarray-based endpoints for MAPH appears to be of comparable accuracy to electrophoretic methods, and holds the prospect of fully exploiting the potential multiplicity of MAPH. The technology has the potential to simplify copy number assays for genes with a large number of exons, or of expanded sets of probes from dispersed genomic locations.

  16. SiPM as miniaturised optical biosensor for DNA-microarray applications

    Directory of Open Access Journals (Sweden)

    M.F. Santangelo

    2015-12-01

    Full Text Available A miniaturized optical biosensor for low-level fluorescence emitted by DNA strands labelled with CY5 is showed. Aim of this work is to demonstrate that a Si-based photodetector, having a low noise and a high sensitivity, can replace traditional detection systems in DNA-microarray applications. The photodetector used is a photomultiplier (SiPM, with 25 pixels. It exhibits a higher sensitivity than commercial optical readers and we experimentally found a detection limit for spotted dried samples of ∼1 nM. We measured the fluorescence signal in different operating conditions (angle of analysis, fluorophores concentrations, solution volumes and support. Once fixed the angle of analysis, for samples spotted on Al-TEOS slide dried, the system is proportional to the concentration of the analyte in the sample and is linear in the range 1 nM–1 μM. For solutions, the range of linearity ranges from 100 fM to 10 nM. The system potentialities and the device low costs suggest it as basic component for the design and fabrication of a cheap, easy and portable optical system. Keywords: Optical Biosensor, SiPM, DNA microarray, Fluorophore detection

  17. Microarray-based DNA methylation study of Ewing's sarcoma of the bone.

    Science.gov (United States)

    Park, Hye-Rim; Jung, Woon-Won; Kim, Hyun-Sook; Park, Yong-Koo

    2014-10-01

    Alterations in DNA methylation patterns are a hallmark of malignancy. However, the majority of epigenetic studies of Ewing's sarcoma have focused on the analysis of only a few candidate genes. Comprehensive studies are thus lacking and are required. The aim of the present study was to identify novel methylation markers in Ewing's sarcoma using microarray analysis. The current study reports the microarray-based DNA methylation study of 1,505 CpG sites of 807 cancer-related genes from 69 Ewing's sarcoma samples. The Illumina GoldenGate Methylation Cancer Panel I microarray was used, and with the appropriate controls (n=14), a total of 92 hypermethylated genes were identified in the Ewing's sarcoma samples. The majority of the hypermethylated genes were associated with cell adhesion, cell regulation, development and signal transduction. The overall methylation mean values were compared between patients who survived and those that did not. The overall methylation mean was significantly higher in the patients who did not survive (0.25±0.03) than in those who did (0.22±0.05) (P=0.0322). However, the overall methylation mean was not found to significantly correlate with age, gender or tumor location. GDF10 , OSM , APC and HOXA11 were the most significant differentially-methylated genes, however, their methylation levels were not found to significantly correlate with the survival rate. The DNA methylation profile of Ewing's sarcoma was characterized and 92 genes that were significantly hypermethylated were detected. A trend towards a more aggressive behavior was identified in the methylated group. The results of this study indicated that methylation may be significant in the development of Ewing's sarcoma.

  18. Isolation of Microarray-Grade Total RNA, MicroRNA, and DNA from a Single PAXgene Blood RNA Tube

    DEFF Research Database (Denmark)

    Kruhøffer, Mogens; Andersen, Lars Dyrskjøt; Voss, Thorsten

    2007-01-01

    We have developed a procedure for isolation of microRNA and genomic DNA in addition to total RNA from whole blood stabilized in PAXgene Blood RNA tubes. The procedure is based on automatic extraction on a BioRobot MDx and includes isolation of DNA from a fraction of the stabilized blood...... and recovery of small RNA species that are otherwise lost. The procedure presented here is suitable for large-scale experiments and is amenable to further automation. Procured total RNA and DNA was tested using Affymetrix Expression and single-nucleotide polymorphism GeneChips, respectively, and isolated micro......RNA was tested using spotted locked nucleic acid-based microarrays. We conclude that the yield and quality of total RNA, microRNA, and DNA from a single PAXgene blood RNA tube is sufficient for downstream microarray analysis....

  19. 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.

  20. On the statistical assessment of classifiers using DNA microarray data

    Directory of Open Access Journals (Sweden)

    Carella M

    2006-08-01

    Full Text Available Abstract Background In this paper we present a method for the statistical assessment of cancer predictors which make use of gene expression profiles. The methodology is applied to a new data set of microarray gene expression data collected in Casa Sollievo della Sofferenza Hospital, Foggia – Italy. The data set is made up of normal (22 and tumor (25 specimens extracted from 25 patients affected by colon cancer. We propose to give answers to some questions which are relevant for the automatic diagnosis of cancer such as: Is the size of the available data set sufficient to build accurate classifiers? What is the statistical significance of the associated error rates? In what ways can accuracy be considered dependant on the adopted classification scheme? How many genes are correlated with the pathology and how many are sufficient for an accurate colon cancer classification? The method we propose answers these questions whilst avoiding the potential pitfalls hidden in the analysis and interpretation of microarray data. Results We estimate the generalization error, evaluated through the Leave-K-Out Cross Validation error, for three different classification schemes by varying the number of training examples and the number of the genes used. The statistical significance of the error rate is measured by using a permutation test. We provide a statistical analysis in terms of the frequencies of the genes involved in the classification. Using the whole set of genes, we found that the Weighted Voting Algorithm (WVA classifier learns the distinction between normal and tumor specimens with 25 training examples, providing e = 21% (p = 0.045 as an error rate. This remains constant even when the number of examples increases. Moreover, Regularized Least Squares (RLS and Support Vector Machines (SVM classifiers can learn with only 15 training examples, with an error rate of e = 19% (p = 0.035 and e = 18% (p = 0.037 respectively. Moreover, the error rate

  1. Methods for interpreting lists of affected genes obtained in a DNA microarray experiment

    Directory of Open Access Journals (Sweden)

    Hedegaard Jakob

    2009-07-01

    Full Text Available Abstract Background The aim of this paper was to describe and compare the methods used and the results obtained by the participants in a joint EADGENE (European Animal Disease Genomic Network of Excellence and SABRE (Cutting Edge Genomics for Sustainable Animal Breeding workshop focusing on post analysis of microarray data. The participating groups were provided with identical lists of microarray probes, including test statistics for three different contrasts, and the normalised log-ratios for each array, to be used as the starting point for interpreting the affected probes. The data originated from a microarray experiment conducted to study the host reactions in broilers occurring shortly after a secondary challenge with either a homologous or heterologous species of Eimeria. Results Several conceptually different analytical approaches, using both commercial and public available software, were applied by the participating groups. The following tools were used: Ingenuity Pathway Analysis, MAPPFinder, LIMMA, GOstats, GOEAST, GOTM, Globaltest, TopGO, ArrayUnlock, Pathway Studio, GIST and AnnotationDbi. The main focus of the approaches was to utilise the relation between probes/genes and their gene ontology and pathways to interpret the affected probes/genes. The lack of a well-annotated chicken genome did though limit the possibilities to fully explore the tools. The main results from these analyses showed that the biological interpretation is highly dependent on the statistical method used but that some common biological conclusions could be reached. Conclusion It is highly recommended to test different analytical methods on the same data set and compare the results to obtain a reliable biological interpretation of the affected genes in a DNA microarray experiment.

  2. Improvement in the amine glass platform by bubbling method for a DNA microarray.

    Science.gov (United States)

    Jee, Seung Hyun; Kim, Jong Won; Lee, Ji Hyeong; Yoon, Young Soo

    2015-01-01

    A glass platform with high sensitivity for sexually transmitted diseases microarray is described here. An amino-silane-based self-assembled monolayer was coated on the surface of a glass platform using a novel bubbling method. The optimized surface of the glass platform had highly uniform surface modifications using this method, as well as improved hybridization properties with capture probes in the DNA microarray. On the basis of these results, the improved glass platform serves as a highly reliable and optimal material for the DNA microarray. Moreover, in this study, we demonstrated that our glass platform, manufactured by utilizing the bubbling method, had higher uniformity, shorter processing time, lower background signal, and higher spot signal than the platforms manufactured by the general dipping method. The DNA microarray manufactured with a glass platform prepared using bubbling method can be used as a clinical diagnostic tool.

  3. CDNA Microarray Based Comparative Gene Expression Analysis of Primary Breast Tumors Versus In Vitro Transformed Neoplastic Breast Epithelium

    National Research Council Canada - National Science Library

    Szallasi, Zoltan

    2001-01-01

    .... The first group of clones is being sorted by their ability to form tumors. We are currently performing cDNA microarray analysis quantifying the expression level of about 15,000 genes in these cell lines...

  4. Detection of Alicyclobacillus species in fruit juice using a random genomic DNA microarray chip.

    Science.gov (United States)

    Jang, Jun Hyeong; Kim, Sun-Joong; Yoon, Bo Hyun; Ryu, Jee-Hoon; Gu, Man Bock; Chang, Hyo-Ihl

    2011-06-01

    This study describes a method using a DNA microarray chip to rapidly and simultaneously detect Alicyclobacillus species in orange juice based on the hybridization of genomic DNA with random probes. Three food spoilage bacteria were used in this study: Alicyclobacillus acidocaldarius, Alicyclobacillus acidoterrestris, and Alicyclobacillus cycloheptanicus. The three Alicyclobacillus species were adjusted to 2 × 10(3) CFU/ml and inoculated into pasteurized 100% pure orange juice. Cy5-dCTP labeling was used for reference signals, and Cy3-dCTP was labeled for target genomic DNA. The molar ratio of 1:1 of Cy3-dCTP and Cy5-dCTP was used. DNA microarray chips were fabricated using randomly fragmented DNA of Alicyclobacillus spp. and were hybridized with genomic DNA extracted from Bacillus spp. Genomic DNA extracted from Alicyclobacillus spp. showed a significantly higher hybridization rate compared with DNA of Bacillus spp., thereby distinguishing Alicyclobacillus spp. from Bacillus spp. The results showed that the microarray DNA chip containing randomly fragmented genomic DNA was specific and clearly identified specific food spoilage bacteria. This microarray system is a good tool for rapid and specific detection of thermophilic spoilage bacteria, mainly Alicyclobacillus spp., and is useful and applicable to the fruit juice industry.

  5. 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.

  6. Parallel characterization of anaerobic toluene- and ethylbenzene-degrading microbial consortia by PCR-denaturing gradient gel electrophoresis, RNA-DNA membrane hybridization, and DNA microarray technology

    Science.gov (United States)

    Koizumi, Yoshikazu; Kelly, John J.; Nakagawa, Tatsunori; Urakawa, Hidetoshi; El-Fantroussi, Said; Al-Muzaini, Saleh; Fukui, Manabu; Urushigawa, Yoshikuni; Stahl, David A.

    2002-01-01

    A mesophilic toluene-degrading consortium (TDC) and an ethylbenzene-degrading consortium (EDC) were established under sulfate-reducing conditions. These consortia were first characterized by denaturing gradient gel electrophoresis (DGGE) fingerprinting of PCR-amplified 16S rRNA gene fragments, followed by sequencing. The sequences of the major bands (T-1 and E-2) belonging to TDC and EDC, respectively, were affiliated with the family Desulfobacteriaceae. Another major band from EDC (E-1) was related to an uncultured non-sulfate-reducing soil bacterium. Oligonucleotide probes specific for the 16S rRNAs of target organisms corresponding to T-1, E-1, and E-2 were designed, and hybridization conditions were optimized for two analytical formats, membrane and DNA microarray hybridization. Both formats were used to characterize the TDC and EDC, and the results of both were consistent with DGGE analysis. In order to assess the utility of the microarray format for analysis of environmental samples, oil-contaminated sediments from the coast of Kuwait were analyzed. The DNA microarray successfully detected bacterial nucleic acids from these samples, but probes targeting specific groups of sulfate-reducing bacteria did not give positive signals. The results of this study demonstrate the limitations and the potential utility of DNA microarrays for microbial community analysis.

  7. Hybridization chain reaction amplification for highly sensitive fluorescence detection of DNA with dextran coated microarrays.

    Science.gov (United States)

    Chao, Jie; Li, Zhenhua; Li, Jing; Peng, Hongzhen; Su, Shao; Li, Qian; Zhu, Changfeng; Zuo, Xiaolei; Song, Shiping; Wang, Lianhui; Wang, Lihua

    2016-07-15

    Microarrays of biomolecules hold great promise in the fields of genomics, proteomics, and clinical assays on account of their remarkably parallel and high-throughput assay capability. However, the fluorescence detection used in most conventional DNA microarrays is still limited by sensitivity. In this study, we have demonstrated a novel universal and highly sensitive platform for fluorescent detection of sequence specific DNA at the femtomolar level by combining dextran-coated microarrays with hybridization chain reaction (HCR) signal amplification. Three-dimensional dextran matrix was covalently coated on glass surface as the scaffold to immobilize DNA recognition probes to increase the surface binding capacity and accessibility. DNA nanowire tentacles were formed on the matrix surface for efficient signal amplification by capturing multiple fluorescent molecules in a highly ordered way. By quantifying microscopic fluorescent signals, the synergetic effects of dextran and HCR greatly improved sensitivity of DNA microarrays, with a detection limit of 10fM (1×10(5) molecules). This detection assay could recognize one-base mismatch with fluorescence signals dropped down to ~20%. This cost-effective microarray platform also worked well with samples in serum and thus shows great potential for clinical diagnosis. Copyright © 2016 Elsevier B.V. All rights reserved.

  8. Microarray MAPH: accurate array-based detection of relative copy number in genomic DNA

    Directory of Open Access Journals (Sweden)

    Chan Alan

    2006-06-01

    Full Text Available Abstract Background Current methods for measurement of copy number do not combine all the desirable qualities of convenience, throughput, economy, accuracy and resolution. In this study, to improve the throughput associated with Multiplex Amplifiable Probe Hybridisation (MAPH we aimed to develop a modification based on the 3-Dimensional, Flow-Through Microarray Platform from PamGene International. In this new method, electrophoretic analysis of amplified products is replaced with photometric analysis of a probed oligonucleotide array. Copy number analysis of hybridised probes is based on a dual-label approach by comparing the intensity of Cy3-labelled MAPH probes amplified from test samples co-hybridised with similarly amplified Cy5-labelled reference MAPH probes. The key feature of using a hybridisation-based end point with MAPH is that discrimination of amplified probes is based on sequence and not fragment length. Results In this study we showed that microarray MAPH measurement of PMP22 gene dosage correlates well with PMP22 gene dosage determined by capillary MAPH and that copy number was accurately reported in analyses of DNA from 38 individuals, 12 of which were known to have Charcot-Marie-Tooth disease type 1A (CMT1A. Conclusion Measurement of microarray-based endpoints for MAPH appears to be of comparable accuracy to electrophoretic methods, and holds the prospect of fully exploiting the potential multiplicity of MAPH. The technology has the potential to simplify copy number assays for genes with a large number of exons, or of expanded sets of probes from dispersed genomic locations.

  9. PMA-PhyloChip DNA Microarray to Elucidate Viable Microbial Community Structure

    Science.gov (United States)

    Venkateswaran, Kasthuri J.; Stam, Christina N.; Andersen, Gary L.; DeSantis, Todd

    2011-01-01

    in the dark. Thereafter, the sample is exposed to visible light for five minutes, so that the DNA from dead cells will be cross-linked. Following this PMA treatment step, the sample is concentrated by centrifugation and washed (to remove excessive PMA) before DNA is extracted. The 16S rRNA gene fragments will be amplified by PCR to screen the total microbial community using PhyloChip DNA microarray analysis. This approach will detect only the viable microbial community since the PMA intercalated DNA from dead cells would be unavailable for PCR amplification. The total detection time including PCR reaction for low biomass samples will be a few hours. Numerous markets may use this technology. The food industry uses spore detection to validate new alternative food processing technologies, sterility, and quality. Pharmaceutical and medical equipment companies also detect spores as a marker for sterility. This system can be used for validating sterilization processes, water treatment systems, and in various public health and homeland security applications.

  10. 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…

  11. Improvement in the amine glass platform by bubbling method for a DNA microarray

    Directory of Open Access Journals (Sweden)

    Jee SH

    2015-10-01

    Full Text Available Seung Hyun Jee,1 Jong Won Kim,2 Ji Hyeong Lee,2 Young Soo Yoon11Department of Chemical and Biological Engineering, Gachon University, Seongnam, Gyeonggi, Republic of Korea; 2Genomics Clinical Research Institute, LabGenomics Co., Ltd., Bundang-gu, Seongnam-si, Gyeonggi-do, Republic of KoreaAbstract: A glass platform with high sensitivity for sexually transmitted diseases microarray is described here. An amino-silane-based self-assembled monolayer was coated on the surface of a glass platform using a novel bubbling method. The optimized surface of the glass platform had highly uniform surface modifications using this method, as well as improved hybridization properties with capture probes in the DNA microarray. On the basis of these results, the improved glass platform serves as a highly reliable and optimal material for the DNA microarray. Moreover, in this study, we demonstrated that our glass platform, manufactured by utilizing the bubbling method, had higher uniformity, shorter processing time, lower background signal, and higher spot signal than the platforms manufactured by the general dipping method. The DNA microarray manufactured with a glass platform prepared using bubbling method can be used as a clinical diagnostic tool. Keywords: DNA microarray, glass platform, bubbling method, self-assambled monolayer

  12. eSensor: an electrochemical detection-based DNA microarray technology enabling sample-to-answer molecular diagnostics

    Science.gov (United States)

    Liu, Robin H.; Longiaru, Mathew

    2009-05-01

    DNA microarrays are becoming a widespread tool used in life science and drug screening due to its many benefits of miniaturization and integration. Microarrays permit a highly multiplexed DNA analysis. Recently, the development of new detection methods and simplified methodologies has rapidly expanded the use of microarray technologies from predominantly gene expression analysis into the arena of diagnostics. Osmetech's eSensor® is an electrochemical detection platform based on a low-to- medium density DNA hybridization array on a cost-effective printed circuit board substrate. eSensor® has been cleared by FDA for Warfarin sensitivity test and Cystic Fibrosis Carrier Detection. Other genetic-based diagnostic and infectious disease detection tests are under development. The eSensor® platform eliminates the need for an expensive laser-based optical system and fluorescent reagents. It allows one to perform hybridization and detection in a single and small instrument without any fluidic processing and handling. Furthermore, the eSensor® platform is readily adaptable to on-chip sample-to-answer genetic analyses using microfluidics technology. The eSensor® platform provides a cost-effective solution to direct sample-to-answer genetic analysis, and thus have a potential impact in the fields of point-of-care genetic analysis, environmental testing, and biological warfare agent detection.

  13. Detecting variants with Metabolic Design, a new software tool to design probes for explorative functional DNA microarray development

    Directory of Open Access Journals (Sweden)

    Gravelat Fabrice

    2010-09-01

    Full Text Available Abstract Background Microorganisms display vast diversity, and each one has its own set of genes, cell components and metabolic reactions. To assess their huge unexploited metabolic potential in different ecosystems, we need high throughput tools, such as functional microarrays, that allow the simultaneous analysis of thousands of genes. However, most classical functional microarrays use specific probes that monitor only known sequences, and so fail to cover the full microbial gene diversity present in complex environments. We have thus developed an algorithm, implemented in the user-friendly program Metabolic Design, to design efficient explorative probes. Results First we have validated our approach by studying eight enzymes involved in the degradation of polycyclic aromatic hydrocarbons from the model strain Sphingomonas paucimobilis sp. EPA505 using a designed microarray of 8,048 probes. As expected, microarray assays identified the targeted set of genes induced during biodegradation kinetics experiments with various pollutants. We have then confirmed the identity of these new genes by sequencing, and corroborated the quantitative discrimination of our microarray by quantitative real-time PCR. Finally, we have assessed metabolic capacities of microbial communities in soil contaminated with aromatic hydrocarbons. Results show that our probe design (sensitivity and explorative quality can be used to study a complex environment efficiently. Conclusions We successfully use our microarray to detect gene expression encoding enzymes involved in polycyclic aromatic hydrocarbon degradation for the model strain. In addition, DNA microarray experiments performed on soil polluted by organic pollutants without prior sequence assumptions demonstrate high specificity and sensitivity for gene detection. Metabolic Design is thus a powerful, efficient tool that can be used to design explorative probes and monitor metabolic pathways in complex environments

  14. DNA microarray unravels rapid changes in transcriptome of MK-801 treated rat brain

    Science.gov (United States)

    Kobayashi, Yuka; Kulikova, Sofya P; Shibato, Junko; Rakwal, Randeep; Satoh, Hiroyuki; Pinault, Didier; Masuo, Yoshinori

    2015-01-01

    AIM: To investigate the impact of MK-801 on gene expression patterns genome wide in rat brain regions. METHODS: Rats were treated with an intraperitoneal injection of MK-801 [0.08 (low-dose) and 0.16 (high-dose) mg/kg] or NaCl (vehicle control). In a first series of experiment, the frontoparietal electrocorticogram was recorded 15 min before and 60 min after injection. In a second series of experiments, the whole brain of each animal was rapidly removed at 40 min post-injection, and different regions were separated: amygdala, cerebral cortex, hippocampus, hypothalamus, midbrain and ventral striatum on ice followed by DNA microarray (4 × 44 K whole rat genome chip) analysis. RESULTS: Spectral analysis revealed that a single systemic injection of MK-801 significantly and selectively augmented the power of baseline gamma frequency (30-80 Hz) oscillations in the frontoparietal electroencephalogram. DNA microarray analysis showed the largest number (up- and down- regulations) of gene expressions in the cerebral cortex (378), midbrain (376), hippocampus (375), ventral striatum (353), amygdala (301), and hypothalamus (201) under low-dose (0.08 mg/kg) of MK-801. Under high-dose (0.16 mg/kg), ventral striatum (811) showed the largest number of gene expression changes. Gene expression changes were functionally categorized to reveal expression of genes and function varies with each brain region. CONCLUSION: Acute MK-801 treatment increases synchrony of baseline gamma oscillations, and causes very early changes in gene expressions in six individual rat brain regions, a first report. PMID:26629322

  15. Normal uniform mixture differential gene expression detection for cDNA microarrays

    Directory of Open Access Journals (Sweden)

    Raftery Adrian E

    2005-07-01

    Full Text Available Abstract Background One of the primary tasks in analysing gene expression data is finding genes that are differentially expressed in different samples. Multiple testing issues due to the thousands of tests run make some of the more popular methods for doing this problematic. Results We propose a simple method, Normal Uniform Differential Gene Expression (NUDGE detection for finding differentially expressed genes in cDNA microarrays. The method uses a simple univariate normal-uniform mixture model, in combination with new normalization methods for spread as well as mean that extend the lowess normalization of Dudoit, Yang, Callow and Speed (2002 1. It takes account of multiple testing, and gives probabilities of differential expression as part of its output. It can be applied to either single-slide or replicated experiments, and it is very fast. Three datasets are analyzed using NUDGE, and the results are compared to those given by other popular methods: unadjusted and Bonferroni-adjusted t tests, Significance Analysis of Microarrays (SAM, and Empirical Bayes for microarrays (EBarrays with both Gamma-Gamma and Lognormal-Normal models. Conclusion The method gives a high probability of differential expression to genes known/suspected a priori to be differentially expressed and a low probability to the others. In terms of known false positives and false negatives, the method outperforms all multiple-replicate methods except for the Gamma-Gamma EBarrays method to which it offers comparable results with the added advantages of greater simplicity, speed, fewer assumptions and applicability to the single replicate case. An R package called nudge to implement the methods in this paper will be made available soon at http://www.bioconductor.org.

  16. High-throughput DNA microarray detection of pathogenic bacteria in shallow well groundwater in the Kathmandu Valley, Nepal.

    Science.gov (United States)

    Inoue, Daisuke; Hinoura, Takuji; Suzuki, Noriko; Pang, Junqin; Malla, Rabin; Shrestha, Sadhana; Chapagain, Saroj Kumar; Matsuzawa, Hiroaki; Nakamura, Takashi; Tanaka, Yasuhiro; Ike, Michihiko; Nishida, Kei; Sei, Kazunari

    2015-01-01

    Because of heavy dependence on groundwater for drinking water and other domestic use, microbial contamination of groundwater is a serious problem in the Kathmandu Valley, Nepal. This study investigated comprehensively the occurrence of pathogenic bacteria in shallow well groundwater in the Kathmandu Valley by applying DNA microarray analysis targeting 941 pathogenic bacterial species/groups. Water quality measurements found significant coliform (fecal) contamination in 10 of the 11 investigated groundwater samples and significant nitrogen contamination in some samples. The results of DNA microarray analysis revealed the presence of 1-37 pathogen species/groups, including 1-27 biosafety level 2 ones, in 9 of the 11 groundwater samples. While the detected pathogens included several feces- and animal-related ones, those belonging to Legionella and Arthrobacter, which were considered not to be directly associated with feces, were detected prevalently. This study could provide a rough picture of overall pathogenic bacterial contamination in the Kathmandu Valley, and demonstrated the usefulness of DNA microarray analysis as a comprehensive screening tool of a wide variety of pathogenic bacteria.

  17. A comparison of parametric and nonparametric methods for normalising cDNA microarray data.

    Science.gov (United States)

    Khondoker, Mizanur R; Glasbey, Chris A; Worton, Bruce J

    2007-12-01

    Normalisation is an essential first step in the analysis of most cDNA microarray data, to correct for effects arising from imperfections in the technology. Loess smoothing is commonly used to correct for trends in log-ratio data. However, parametric models, such as the additive plus multiplicative variance model, have been preferred for scale normalisation, though the variance structure of microarray data may be of a more complex nature than can be accommodated by a parametric model. We propose a new nonparametric approach that incorporates location and scale normalisation simultaneously using a Generalised Additive Model for Location, Scale and Shape (GAMLSS, Rigby and Stasinopoulos, 2005, Applied Statistics, 54, 507-554). We compare its performance in inferring differential expression with Huber et al.'s (2002, Bioinformatics, 18, 96-104) arsinh variance stabilising transformation (AVST) using real and simulated data. We show GAMLSS to be as powerful as AVST when the parametric model is correct, and more powerful when the model is wrong. (c) 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

  18. Integration of Multiplexed Microfluidic Electrokinetic Concentrators with a Morpholino Microarray via Reversible Surface Bonding for Enhanced DNA Hybridization.

    Science.gov (United States)

    Martins, Diogo; Wei, Xi; Levicky, Rastislav; Song, Yong-Ak

    2016-04-05

    We describe a microfluidic concentration device to accelerate the surface hybridization reaction between DNA and morpholinos (MOs) for enhanced detection. The microfluidic concentrator comprises a single polydimethylsiloxane (PDMS) microchannel onto which an ion-selective layer of conductive polymer poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) ( PSS) was directly printed and then reversibly surface bonded onto a morpholino microarray for hybridization. Using this electrokinetic trapping concentrator, we could achieve a maximum concentration factor of ∼800 for DNA and a limit of detection of 10 nM within 15 min. In terms of the detection speed, it enabled faster hybridization by around 10-fold when compared to conventional diffusion-based hybridization. A significant advantage of our approach is that the fabrication of the microfluidic concentrator is completely decoupled from the microarray; by eliminating the need to deposit an ion-selective layer on the microarray surface prior to device integration, interfacing between both modules, the PDMS chip for electrokinetic concentration and the substrate for DNA sensing are easier and applicable to any microarray platform. Furthermore, this fabrication strategy facilitates a multiplexing of concentrators. We have demonstrated the proof-of-concept for multiplexing by building a device with 5 parallel concentrators connected to a single inlet/outlet and applying it to parallel concentration and hybridization. Such device yielded similar concentration and hybridization efficiency compared to that of a single-channel device without adding any complexity to the fabrication and setup. These results demonstrate that our concentrator concept can be applied to the development of a highly multiplexed concentrator-enhanced microarray detection system for either genetic analysis or other diagnostic assays.

  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. An efficient algorithm for the stochastic simulation of the hybridization of DNA to microarrays

    Directory of Open Access Journals (Sweden)

    Laurenzi Ian J

    2009-12-01

    Full Text Available Abstract Background Although oligonucleotide microarray technology is ubiquitous in genomic research, reproducibility and standardization of expression measurements still concern many researchers. Cross-hybridization between microarray probes and non-target ssDNA has been implicated as a primary factor in sensitivity and selectivity loss. Since hybridization is a chemical process, it may be modeled at a population-level using a combination of material balance equations and thermodynamics. However, the hybridization reaction network may be exceptionally large for commercial arrays, which often possess at least one reporter per transcript. Quantification of the kinetics and equilibrium of exceptionally large chemical systems of this type is numerically infeasible with customary approaches. Results In this paper, we present a robust and computationally efficient algorithm for the simulation of hybridization processes underlying microarray assays. Our method may be utilized to identify the extent to which nucleic acid targets (e.g. cDNA will cross-hybridize with probes, and by extension, characterize probe robustnessusing the information specified by MAGE-TAB. Using this algorithm, we characterize cross-hybridization in a modified commercial microarray assay. Conclusions By integrating stochastic simulation with thermodynamic prediction tools for DNA hybridization, one may robustly and rapidly characterize of the selectivity of a proposed microarray design at the probe and "system" levels. Our code is available at http://www.laurenzi.net.

  1. A DNA Microarray-Based Assay to Detect Dual Infection with Two Dengue Virus Serotypes

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    Alvaro Díaz-Badillo

    2014-04-01

    Full Text Available Here; we have described and tested a microarray based-method for the screening of dengue virus (DENV serotypes. This DNA microarray assay is specific and sensitive and can detect dual infections with two dengue virus serotypes and single-serotype infections. Other methodologies may underestimate samples containing more than one serotype. This technology can be used to discriminate between the four DENV serotypes. Single-stranded DNA targets were covalently attached to glass slides and hybridised with specific labelled probes. DENV isolates and dengue samples were used to evaluate microarray performance. Our results demonstrate that the probes hybridized specifically to DENV serotypes; with no detection of unspecific signals. This finding provides evidence that specific probes can effectively identify single and double infections in DENV samples.

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

    Directory of Open Access Journals (Sweden)

    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

  3. Microfluidic DNA microarrays in PMMA chips: streamlined fabrication via simultaneous DNA immobilization and bonding activation by brief UV exposure

    DEFF Research Database (Denmark)

    Sabourin, David; Petersen, J; Snakenborg, Detlef

    2010-01-01

    This report presents and describes a simple and scalable method for producing functional DNA microarrays within enclosed polymeric, PMMA, microfluidic devices. Brief (30 s) exposure to UV simultaneously immobilized poly(T)poly(C)-tagged DNA probes to the surface of unmodified PMMA and activated...... the surface for bonding below the glass transition temperature of the bulk PMMA. Functionality and validation of the enclosed PMMA microarrays was demonstrated as 18 patients were correctly genotyped for all eight mutation sites in the HBB gene interrogated. The fabrication process therefore produced probes...... with desired hybridization properties and sufficient bonding between PMMA layers to allow construction of microfluidic devices. The streamlined fabrication method is suited to the production of low-cost microfluidic microarray-based diagnostic devices and, as such, is equally applicable to the development...

  4. FibroChip, a Functional DNA Microarray to Monitor Cellulolytic and Hemicellulolytic Activities of Rumen Microbiota

    Directory of Open Access Journals (Sweden)

    Sophie Comtet-Marre

    2018-02-01

    Full Text Available Ruminants fulfill their energy needs for growth primarily through microbial breakdown of plant biomass in the rumen. Several biotic and abiotic factors influence the efficiency of fiber degradation, which can ultimately impact animal productivity and health. To provide more insight into mechanisms involved in the modulation of fibrolytic activity, a functional DNA microarray targeting genes encoding key enzymes involved in cellulose and hemicellulose degradation by rumen microbiota was designed. Eight carbohydrate-active enzyme (CAZyme families (GH5, GH9, GH10, GH11, GH43, GH48, CE1, and CE6 were selected which represented 392 genes from bacteria, protozoa, and fungi. The DNA microarray, designated as FibroChip, was validated using targets of increasing complexity and demonstrated sensitivity and specificity. In addition, FibroChip was evaluated for its explorative and semi-quantitative potential. Differential expression of CAZyme genes was evidenced in the rumen bacterium Fibrobacter succinogenes S85 grown on wheat straw or cellobiose. FibroChip was used to identify the expressed CAZyme genes from the targeted families in the rumen of a cow fed a mixed diet based on grass silage. Among expressed genes, those encoding GH43, GH5, and GH10 families were the most represented. Most of the F. succinogenes genes detected by the FibroChip were also detected following RNA-seq analysis of RNA transcripts obtained from the rumen fluid sample. Use of the FibroChip also indicated that transcripts of fiber degrading enzymes derived from eukaryotes (protozoa and anaerobic fungi represented a significant proportion of the total microbial mRNA pool. FibroChip represents a reliable and high-throughput tool that enables researchers to monitor active members of fiber degradation in the rumen.

  5. FibroChip, a Functional DNA Microarray to Monitor Cellulolytic and Hemicellulolytic Activities of Rumen Microbiota.

    Science.gov (United States)

    Comtet-Marre, Sophie; Chaucheyras-Durand, Frédérique; Bouzid, Ourdia; Mosoni, Pascale; Bayat, Ali R; Peyret, Pierre; Forano, Evelyne

    2018-01-01

    Ruminants fulfill their energy needs for growth primarily through microbial breakdown of plant biomass in the rumen. Several biotic and abiotic factors influence the efficiency of fiber degradation, which can ultimately impact animal productivity and health. To provide more insight into mechanisms involved in the modulation of fibrolytic activity, a functional DNA microarray targeting genes encoding key enzymes involved in cellulose and hemicellulose degradation by rumen microbiota was designed. Eight carbohydrate-active enzyme (CAZyme) families (GH5, GH9, GH10, GH11, GH43, GH48, CE1, and CE6) were selected which represented 392 genes from bacteria, protozoa, and fungi. The DNA microarray, designated as FibroChip, was validated using targets of increasing complexity and demonstrated sensitivity and specificity. In addition, FibroChip was evaluated for its explorative and semi-quantitative potential. Differential expression of CAZyme genes was evidenced in the rumen bacterium Fibrobacter succinogenes S85 grown on wheat straw or cellobiose. FibroChip was used to identify the expressed CAZyme genes from the targeted families in the rumen of a cow fed a mixed diet based on grass silage. Among expressed genes, those encoding GH43, GH5, and GH10 families were the most represented. Most of the F. succinogenes genes detected by the FibroChip were also detected following RNA-seq analysis of RNA transcripts obtained from the rumen fluid sample. Use of the FibroChip also indicated that transcripts of fiber degrading enzymes derived from eukaryotes (protozoa and anaerobic fungi) represented a significant proportion of the total microbial mRNA pool. FibroChip represents a reliable and high-throughput tool that enables researchers to monitor active members of fiber degradation in the rumen.

  6. Observation of intermittency in gene expression on cDNA microarrays

    CERN Document Server

    Peterson, L E

    2002-01-01

    We used scaled factorial moments to search for intermittency in the log expression ratios (LERs) for thousands of genes spotted on cDNA microarrays (gene chips). Results indicate varying levels of intermittency in gene expression. The observation of intermittency in the data analyzed provides a complimentary handle on moderately expressed genes, generally not tackled by conventional techniques.

  7. Use of the cDNA microarray technology in thesafety assessment of GM food plants

    DEFF Research Database (Denmark)

    Pedersen, Jan W.; Knudsen, Ib; Eriksen, Folmer Damsted

    This report focuses on new analytical approaches that might give more insight into possible changes in a genetically modified plant. Primarily the focus is on the new DNA microarray technique but also proteomics and metabolomics are discussed.The report describes the new techniques and evaluates ...

  8. Use of the cDNA microarray technology in the safety assessment of GM food plants

    NARCIS (Netherlands)

    Kok, E.J.; Kleter, G.A.; Dijk, van J.P.

    2003-01-01

    This report focuses on new analytical approaches that might give more insight into possible changes in a genetically modified plant. Primarily the focus is on the new DNA microarray technique but also proteomics and metabolomics are discussed.The report describes the new techniques and evaluates the

  9. Use of Low-Density DNA Microarrays and Photopolymerization for Genotyping Foodborne-Associated Noroviruses

    Science.gov (United States)

    Human noroviruses cause up to 21 million cases of foodborne disease in the United States annually and are the most common cause of acute gastroenteritis in industrialized countries. To reduce the burden of foodborne disease associated with viruses, the use of low density DNA microarrays in conjunct...

  10. 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.

  11. Robust embryo identification using first polar body single nucleotide polymorphism microarray-based DNA fingerprinting.

    Science.gov (United States)

    Treff, Nathan R; Su, Jing; Kasabwala, Natasha; Tao, Xin; Miller, Kathleen A; Scott, Richard T

    2010-05-01

    This study sought to validate a novel, minimally invasive system for embryo tracking by single nucleotide polymorphism microarray-based DNA fingerprinting of the first polar body. First polar body-based assignments of which embryos implanted and were delivered after multiple ET were 100% consistent with previously validated embryo DNA fingerprinting-based assignments. Copyright 2010 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

  12. 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. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

  13. The Use of Atomic Force Microscopy for 3D Analysis of Nucleic Acid Hybridization on Microarrays.

    Science.gov (United States)

    Dubrovin, E V; Presnova, G V; Rubtsova, M Yu; Egorov, A M; Grigorenko, V G; Yaminsky, I V

    2015-01-01

    Oligonucleotide microarrays are considered today to be one of the most efficient methods of gene diagnostics. The capability of atomic force microscopy (AFM) to characterize the three-dimensional morphology of single molecules on a surface allows one to use it as an effective tool for the 3D analysis of a microarray for the detection of nucleic acids. The high resolution of AFM offers ways to decrease the detection threshold of target DNA and increase the signal-to-noise ratio. In this work, we suggest an approach to the evaluation of the results of hybridization of gold nanoparticle-labeled nucleic acids on silicon microarrays based on an AFM analysis of the surface both in air and in liquid which takes into account of their three-dimensional structure. We suggest a quantitative measure of the hybridization results which is based on the fraction of the surface area occupied by the nanoparticles.

  14. 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.

  15. Comparative DNA microarray analysis of human monocyte derived dendritic cells and MUTZ-3 cells exposed to the moderate skin sensitizer cinnamaldehyde

    International Nuclear Information System (INIS)

    Python, Francois; Goebel, Carsten; Aeby, Pierre

    2009-01-01

    The number of studies involved in the development of in vitro skin sensitization tests has increased since the adoption of the EU 7th amendment to the cosmetics directive proposing to ban animal testing for cosmetic ingredients by 2013. Several studies have recently demonstrated that sensitizers induce a relevant up-regulation of activation markers such as CD86, CD54, IL-8 or IL-1β in human myeloid cell lines (e.g., U937, MUTZ-3, THP-1) or in human peripheral blood monocyte-derived dendritic cells (PBMDCs). The present study aimed at the identification of new dendritic cell activation markers in order to further improve the in vitro evaluation of the sensitizing potential of chemicals. We have compared the gene expression profiles of PBMDCs and the human cell line MUTZ-3 after a 24-h exposure to the moderate sensitizer cinnamaldehyde. A list of 80 genes modulated in both cell types was obtained and a set of candidate marker genes was selected for further analysis. Cells were exposed to selected sensitizers and non-sensitizers for 24 h and gene expression was analyzed by quantitative real-time reverse transcriptase-polymerase chain reaction. Results indicated that PIR, TRIM16 and two Nrf2-regulated genes, CES1 and NQO1, are modulated by most sensitizers. Up-regulation of these genes could also be observed in our recently published DC-activation test with U937 cells. Due to their role in DC activation, these new genes may help to further refine the in vitro approaches for the screening of the sensitizing properties of a chemical.

  16. An automated microfluidic DNA microarray platform for genetic variant detection in inherited arrhythmic diseases.

    Science.gov (United States)

    Huang, Shu-Hong; Chang, Yu-Shin; Juang, Jyh-Ming Jimmy; Chang, Kai-Wei; Tsai, Mong-Hsun; Lu, Tzu-Pin; Lai, Liang-Chuan; Chuang, Eric Y; Huang, Nien-Tsu

    2018-03-12

    In this study, we developed an automated microfluidic DNA microarray (AMDM) platform for point mutation detection of genetic variants in inherited arrhythmic diseases. The platform allows for automated and programmable reagent sequencing under precise conditions of hybridization flow and temperature control. It is composed of a commercial microfluidic control system, a microfluidic microarray device, and a temperature control unit. The automated and rapid hybridization process can be performed in the AMDM platform using Cy3 labeled oligonucleotide exons of SCN5A genetic DNA, which produces proteins associated with sodium channels abundant in the heart (cardiac) muscle cells. We then introduce a graphene oxide (GO)-assisted DNA microarray hybridization protocol to enable point mutation detection. In this protocol, a GO solution is added after the staining step to quench dyes bound to single-stranded DNA or non-perfectly matched DNA, which can improve point mutation specificity. As proof-of-concept we extracted the wild-type and mutant of exon 12 and exon 17 of SCN5A genetic DNA from patients with long QT syndrome or Brugada syndrome by touchdown PCR and performed a successful point mutation discrimination in the AMDM platform. Overall, the AMDM platform can greatly reduce laborious and time-consuming hybridization steps and prevent potential contamination. Furthermore, by introducing the reciprocating flow into the microchannel during the hybridization process, the total assay time can be reduced to 3 hours, which is 6 times faster than the conventional DNA microarray. Given the automatic assay operation, shorter assay time, and high point mutation discrimination, we believe that the AMDM platform has potential for low-cost, rapid and sensitive genetic testing in a simple and user-friendly manner, which may benefit gene screening in medical practice.

  17. Meta-analysis of archived DNA microarrays identifies genes regulated by hypoxia and involved in a metastatic phenotype in cancer cells

    International Nuclear Information System (INIS)

    Pierre, Michael; DeHertogh, Benoît; Gaigneaux, Anthoula; DeMeulder, Bertrand; Berger, Fabrice; Bareke, Eric; Michiels, Carine; Depiereux, Eric

    2010-01-01

    Metastasis is a major cancer-related cause of death. Recent studies have described metastasis pathways. However, the exact contribution of each pathway remains unclear. Another key feature of a tumor is the presence of hypoxic areas caused by a lack of oxygen at the center of the tumor. Hypoxia leads to the expression of pro-metastatic genes as well as the repression of anti-metastatic genes. As many Affymetrix datasets about metastasis and hypoxia are publicly available and not fully exploited, this study proposes to re-analyze these datasets to extract new information about the metastatic phenotype induced by hypoxia in different cancer cell lines. Affymetrix datasets about metastasis and/or hypoxia were downloaded from GEO and ArrayExpress. AffyProbeMiner and GCRMA packages were used for pre-processing and the Window Welch t test was used for processing. Three approaches of meta-analysis were eventually used for the selection of genes of interest. Three complementary approaches were used, that eventually selected 183 genes of interest. Out of these 183 genes, 99, among which the well known JUNB, FOS and TP63, have already been described in the literature to be involved in cancer. Moreover, 39 genes of those, such as SERPINE1 and MMP7, are known to regulate metastasis. Twenty-one genes including VEGFA and ID2 have also been described to be involved in the response to hypoxia. Lastly, DAVID classified those 183 genes in 24 different pathways, among which 8 are directly related to cancer while 5 others are related to proliferation and cell motility. A negative control composed of 183 random genes failed to provide such results. Interestingly, 6 pathways retrieved by DAVID with the 183 genes of interest concern pathogen recognition and phagocytosis. The proposed methodology was able to find genes actually known to be involved in cancer, metastasis and hypoxia and, thus, we propose that the other genes selected based on the same methodology are of prime interest in

  18. Preparation of fluorescent-dye-labeled cDNA from RNA for microarray hybridization.

    Science.gov (United States)

    Ares, Manuel

    2014-01-01

    This protocol describes how to prepare fluorescently labeled cDNA for hybridization to microarrays. It consists of two steps: first, a mixture of anchored oligo(dT) and random hexamers is used to prime amine-modified cDNA synthesis by reverse transcriptase using a modified deoxynucleotide with a reactive amine group (aminoallyl-dUTP) and an RNA sample as a template. Second, the cDNA is purified and exchanged into bicarbonate buffer so that the amine groups in the cDNA react with the dye N-hydroxysuccinimide (NHS) esters, covalently joining the dye to the cDNA. The dye-coupled cDNA is purified again, and the amount of dye incorporated per microgram of cDNA is determined.

  19. AMDA: an R package for the automated microarray data analysis

    Directory of Open Access Journals (Sweden)

    Foti Maria

    2006-07-01

    Full Text Available Abstract Background Microarrays are routinely used to assess mRNA transcript levels on a genome-wide scale. Large amount of microarray datasets are now available in several databases, and new experiments are constantly being performed. In spite of this fact, few and limited tools exist for quickly and easily analyzing the results. Microarray analysis can be challenging for researchers without the necessary training and it can be time-consuming for service providers with many users. Results To address these problems we have developed an automated microarray data analysis (AMDA software, which provides scientists with an easy and integrated system for the analysis of Affymetrix microarray experiments. AMDA is free and it is available as an R package. It is based on the Bioconductor project that provides a number of powerful bioinformatics and microarray analysis tools. This automated pipeline integrates different functions available in the R and Bioconductor projects with newly developed functions. AMDA covers all of the steps, performing a full data analysis, including image analysis, quality controls, normalization, selection of differentially expressed genes, clustering, correspondence analysis and functional evaluation. Finally a LaTEX document is dynamically generated depending on the performed analysis steps. The generated report contains comments and analysis results as well as the references to several files for a deeper investigation. Conclusion AMDA is freely available as an R package under the GPL license. The package as well as an example analysis report can be downloaded in the Services/Bioinformatics section of the Genopolis http://www.genopolis.it/

  20. A statistical model for investigating binding probabilities of DNA nucleotide sequences using microarrays.

    Science.gov (United States)

    Lee, Mei-Ling Ting; Bulyk, Martha L; Whitmore, G A; Church, George M

    2002-12-01

    There is considerable scientific interest in knowing the probability that a site-specific transcription factor will bind to a given DNA sequence. Microarray methods provide an effective means for assessing the binding affinities of a large number of DNA sequences as demonstrated by Bulyk et al. (2001, Proceedings of the National Academy of Sciences, USA 98, 7158-7163) in their study of the DNA-binding specificities of Zif268 zinc fingers using microarray technology. In a follow-up investigation, Bulyk, Johnson, and Church (2002, Nucleic Acid Research 30, 1255-1261) studied the interdependence of nucleotides on the binding affinities of transcription proteins. Our article is motivated by this pair of studies. We present a general statistical methodology for analyzing microarray intensity measurements reflecting DNA-protein interactions. The log probability of a protein binding to a DNA sequence on an array is modeled using a linear ANOVA model. This model is convenient because it employs familiar statistical concepts and procedures and also because it is effective for investigating the probability structure of the binding mechanism.

  1. Gene expression profiling in gill tissues of White spot syndrome virus infected black tiger shrimp Penaeus monodon by DNA microarray.

    Science.gov (United States)

    Shekhar, M S; Gomathi, A; Gopikrishna, G; Ponniah, A G

    2015-06-01

    White spot syndrome virus (WSSV) continues to be the most devastating viral pathogen infecting penaeid shrimp the world over. The genome of WSSV has been deciphered and characterized from three geographical isolates and significant progress has been made in developing various molecular diagnostic methods to detect the virus. However, the information on host immune gene response to WSSV pathogenesis is limited. Microarray analysis was carried out as an approach to analyse the gene expression in black tiger shrimp Penaeus monodon in response to WSSV infection. Gill tissues collected from the WSSV infected shrimp at 6, 24, 48 h and moribund stage were analysed for differential gene expression. Shrimp cDNAs of 40,059 unique sequences were considered for designing the microarray chip. The Cy3-labeled cRNA derived from healthy and WSSV-infected shrimp was subjected to hybridization with all the DNA spots in the microarray which revealed 8,633 and 11,147 as up- and down-regulated genes respectively at different time intervals post infection. The altered expression of these numerous genes represented diverse functions such as immune response, osmoregulation, apoptosis, nucleic acid binding, energy and metabolism, signal transduction, stress response and molting. The changes in gene expression profiles observed by microarray analysis provides molecular insights and framework of genes which are up- and down-regulated at different time intervals during WSSV infection in shrimp. The microarray data was validated by Real Time analysis of four differentially expressed genes involved in apoptosis (translationally controlled tumor protein, inhibitor of apoptosis protein, ubiquitin conjugated enzyme E2 and caspase) for gene expression levels. The role of apoptosis related genes in WSSV infected shrimp is discussed herein.

  2. Study of hepatitis B virus gene mutations with enzymatic colorimetry-based DNA microarray.

    Science.gov (United States)

    Mao, Hailei; Wang, Huimin; Zhang, Donglei; Mao, Hongju; Zhao, Jianlong; Shi, Jian; Cui, Zhichu

    2006-01-01

    To establish a modified microarray method for detecting HBV gene mutations in the clinic. Site-specific oligonucleotide probes were immobilized to microarray slides and hybridized to biotin-labeled HBV gene fragments amplified from two-step PCR. Hybridized targets were transferred to nitrocellulose membranes, followed by intensity measurement using BCIP/NBT colorimetry. HBV genes from 99 Hepatitis B patients and 40 healthy blood donors were analyzed. Mutation frequencies of HBV pre-core/core and basic core promoter (BCP) regions were found to be significantly higher in the patient group (42%, 40% versus 2.5%, 5%, P colorimetry method exhibited the same level of sensitivity and reproducibility. An enzymatic colorimetry-based DNA microarray assay was successfully established to monitor HBV mutations. Pre-core/core and BCP mutations of HBV genes could be major causes of HBV infection in HBeAg-negative patients and could also be relevant to chronicity and aggravation of hepatitis B.

  3. Bystander effect: Biological endpoints and microarray analysis

    Energy Technology Data Exchange (ETDEWEB)

    Chaudhry, M. Ahmad [Department of Medical Laboratory and Radiation Sciences, College of Nursing and Health Sciences, University of Vermont, 302 Rowell Building, Burlington, VT 05405 (United States) and DNA Microarray Facility, University of Vermont, Burlington, VT 05405 (United States)]. E-mail: mchaudhr@uvm.edu

    2006-05-11

    In cell populations exposed to ionizing radiation, the biological effects occur in a much larger proportion of cells than are estimated to be traversed by radiation. It has been suggested that irradiated cells are capable of providing signals to the neighboring unirradiated cells resulting in damage to these cells. This phenomenon is termed the bystander effect. The bystander effect induces persistent, long-term, transmissible changes that result in delayed death and neoplastic transformation. Because the bystander effect is relevant to carcinogenesis, it could have significant implications for risk estimation for radiation exposure. The nature of the bystander effect signal and how it impacts the unirradiated cells remains to be elucidated. Examination of the changes in gene expression could provide clues to understanding the bystander effect and could define the signaling pathways involved in sustaining damage to these cells. The microarray technology serves as a tool to gain insight into the molecular pathways leading to bystander effect. Using medium from irradiated normal human diploid lung fibroblasts as a model system we examined gene expression alterations in bystander cells. The microarray data revealed that the radiation-induced gene expression profile in irradiated cells is different from unirradiated bystander cells suggesting that the pathways leading to biological effects in the bystander cells are different from the directly irradiated cells. The genes known to be responsive to ionizing radiation were observed in irradiated cells. Several genes were upregulated in cells receiving media from irradiated cells. Surprisingly no genes were found to be downregulated in these cells. A number of genes belonging to extracellular signaling, growth factors and several receptors were identified in bystander cells. Interestingly 15 genes involved in the cell communication processes were found to be upregulated. The induction of receptors and the cell

  4. Bystander effect: Biological endpoints and microarray analysis

    International Nuclear Information System (INIS)

    Chaudhry, M. Ahmad

    2006-01-01

    In cell populations exposed to ionizing radiation, the biological effects occur in a much larger proportion of cells than are estimated to be traversed by radiation. It has been suggested that irradiated cells are capable of providing signals to the neighboring unirradiated cells resulting in damage to these cells. This phenomenon is termed the bystander effect. The bystander effect induces persistent, long-term, transmissible changes that result in delayed death and neoplastic transformation. Because the bystander effect is relevant to carcinogenesis, it could have significant implications for risk estimation for radiation exposure. The nature of the bystander effect signal and how it impacts the unirradiated cells remains to be elucidated. Examination of the changes in gene expression could provide clues to understanding the bystander effect and could define the signaling pathways involved in sustaining damage to these cells. The microarray technology serves as a tool to gain insight into the molecular pathways leading to bystander effect. Using medium from irradiated normal human diploid lung fibroblasts as a model system we examined gene expression alterations in bystander cells. The microarray data revealed that the radiation-induced gene expression profile in irradiated cells is different from unirradiated bystander cells suggesting that the pathways leading to biological effects in the bystander cells are different from the directly irradiated cells. The genes known to be responsive to ionizing radiation were observed in irradiated cells. Several genes were upregulated in cells receiving media from irradiated cells. Surprisingly no genes were found to be downregulated in these cells. A number of genes belonging to extracellular signaling, growth factors and several receptors were identified in bystander cells. Interestingly 15 genes involved in the cell communication processes were found to be upregulated. The induction of receptors and the cell

  5. Effects of ingested turmeric oleoresin on glucose and lipid metabolisms in obese diabetic mice: a DNA microarray study.

    Science.gov (United States)

    Honda, Shinichi; Aoki, Fumiki; Tanaka, Hozumi; Kishida, Hideyuki; Nishiyama, Tozo; Okada, Shinji; Matsumoto, Ichiro; Abe, Keiko; Mae, Tatsumasa

    2006-11-29

    Turmeric, the rhizome of Curcuma longa L., has a wide range of effects on human health. Turmeric oleoresin, an extract of turmeric, is often used for flavoring and coloring. Curcuminoids and turmeric essential oil are both contained in turmeric oleoresin, and both of these fractions have hypoglycemic effects. In the present study, we comprehensively assessed the effect of turmeric oleoresin on hepatic gene expression in obese diabetic KK-Ay mice using DNA microarray analysis and quantitative real-time polymerase chain reaction (PCR). Female KK-Ay mice aged 6 weeks (n = 6/group) were fed a high-fat diet containing turmeric oleoresin, curcuminoids, and essential oil for 5 weeks. The same diet without any of these fractions was used as a control diet. Ingestion of turmeric oleoresin and essential oil inhibited the development of increased blood glucose and abdominal fat mass, while curcuminoids only inhibited the increase in blood glucose. DNA microarray analysis indicated that turmeric oleoresin ingestion up-regulated the expression of genes related to glycolysis, beta-oxidation, and cholesterol metabolism in the liver of KK-Ay mice, while expression of gluconeogenesis-related genes was down-regulated. Real-time PCR analysis was conducted to assess the contribution of the curcuminoids and essential oil in turmeric oleoresin to the changes in expression of representative genes selected by DNA microarray analysis. This analysis suggested that curcuminoids regulated turmeric oleoresin ingestion-induced expression of glycolysis-related genes and also that curcuminoids and turmeric essential oil acted synergistically to regulate the peroxisomal beta-oxidation-related gene expression induced by turmeric oleoresin ingestion. These changes in gene expression were considered to be the mechanism by which the turmeric oleoresin affected the control of both blood glucose levels and abdominal adipose tissue masses. All of these results suggest that the use of whole turmeric

  6. Establishment and Application of a Visual DNA Microarray for the Detection of Food-borne Pathogens.

    Science.gov (United States)

    Li, Yongjin

    2016-01-01

    The accurate detection and identification of food-borne pathogenic microorganisms is critical for food safety nowadays. In the present work, a visual DNA microarray was established and applied to detect pathogens commonly found in food, including Salmonella enterica, Shigella flexneri, E. coli O157:H7 and Listeria monocytogenes in food samples. Multiplex PCR (mPCR) was employed to simultaneously amplify specific gene fragments, fimY for Salmonella, ipaH for Shigella, iap for L. monocytogenes and ECs2841 for E. coli O157:H7, respectively. Biotinylated PCR amplicons annealed to the microarray probes were then reacted with a streptavidin-alkaline phosphatase conjugate and nitro blue tetrazolium/5-bromo-4-chloro-3'-indolylphosphate, p-toluidine salt (NBT/BCIP); the positive results were easily visualized as blue dots formatted on the microarray surface. The performance of a DNA microarray was tested against 14 representative collection strains and mock-contamination food samples. The combination of mPCR and a visual micro-plate chip specifically and sensitively detected Salmonella enterica, Shigella flexneri, E. coli O157:H7 and Listeria monocytogenes in standard strains and food matrices with a sensitivity of ∼10(2) CFU/mL of bacterial culture. Thus, the developed method is advantageous because of its high throughput, cost-effectiveness and ease of use.

  7. Position dependent mismatch discrimination on DNA microarrays – experiments and model

    Directory of Open Access Journals (Sweden)

    Michel Wolfgang

    2008-12-01

    Full Text Available Abstract Background The propensity of oligonucleotide strands to form stable duplexes with complementary sequences is fundamental to a variety of biological and biotechnological processes as various as microRNA signalling, microarray hybridization and PCR. Yet our understanding of oligonucleotide hybridization, in particular in presence of surfaces, is rather limited. Here we use oligonucleotide microarrays made in-house by optically controlled DNA synthesis to produce probe sets comprising all possible single base mismatches and base bulges for each of 20 sequence motifs under study. Results We observe that mismatch discrimination is mostly determined by the defect position (relative to the duplex ends as well as by the sequence context. We investigate the thermodynamics of the oligonucleotide duplexes on the basis of double-ended molecular zipper. Theoretical predictions of defect positional influence as well as long range sequence influence agree well with the experimental results. Conclusion Molecular zipping at thermodynamic equilibrium explains the binding affinity of mismatched DNA duplexes on microarrays well. The position dependent nearest neighbor model (PDNN can be inferred from it. Quantitative understanding of microarray experiments from first principles is in reach.

  8. Analysis of Chromothripsis by Combined FISH and Microarray Analysis.

    Science.gov (United States)

    MacKinnon, Ruth N

    2018-01-01

    Fluorescence in situ hybridization (FISH) to metaphase chromosomes, in conjunction with SNP array, array CGH, or whole genome sequencing, can help determine the organization of abnormal genomes after chromothripsis and other types of complex genome rearrangement. DNA microarrays can identify the changes in copy number, but they do not give information on the organization of the abnormal chromosomes, balanced rearrangements, or abnormalities of the centromeres and other regions comprised of highly repetitive DNA. Many of these details can be determined by the strategic use of metaphase FISH. FISH is a single-cell technique, so it can identify low-frequency chromosome abnormalities, and it can determine which chromosome abnormalities occur in the same or different clonal populations. These are important considerations in cancer. Metaphase chromosomes are intact, so information about abnormalities of the chromosome homologues is preserved. Here we describe strategies for working out the organization of highly rearranged genomes by combining SNP array data with various metaphase FISH methods. This approach can also be used to address some of the uncertainties arising from whole genome or mate-pair sequencing data.

  9. 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.

  10. An MCMC Algorithm for Target Estimation in Real-Time DNA Microarrays

    Directory of Open Access Journals (Sweden)

    Vikalo Haris

    2010-01-01

    Full Text Available DNA microarrays detect the presence and quantify the amounts of nucleic acid molecules of interest. They rely on a chemical attraction between the target molecules and their Watson-Crick complements, which serve as biological sensing elements (probes. The attraction between these biomolecules leads to binding, in which probes capture target analytes. Recently developed real-time DNA microarrays are capable of observing kinetics of the binding process. They collect noisy measurements of the amount of captured molecules at discrete points in time. Molecular binding is a random process which, in this paper, is modeled by a stochastic differential equation. The target analyte quantification is posed as a parameter estimation problem, and solved using a Markov Chain Monte Carlo technique. In simulation studies where we test the robustness with respect to the measurement noise, the proposed technique significantly outperforms previously proposed methods. Moreover, the proposed approach is tested and verified on experimental data.

  11. DNA microarray genotyping and virulence and antimicrobial resistance gene profiling of methicillin-resistant Staphylococcus aureus bloodstream isolates from renal patients.

    LENUS (Irish Health Repository)

    McNicholas, Sinead

    2012-02-01

    Thirty-six methicillin-resistant Staphylococcus aureus (MRSA) bloodstream isolates from renal patients were genetically characterized by DNA microarray analysis and spa typing. The isolates were highly clonal, belonging mainly to ST22-MRSA-IV. The immune evasion and enterotoxin gene clusters were found in 29\\/36 (80%) and 33\\/36 (92%) isolates, respectively.

  12. DNA microarray genotyping and virulence and antimicrobial resistance gene profiling of methicillin-resistant Staphylococcus aureus bloodstream isolates from renal patients.

    LENUS (Irish Health Repository)

    McNicholas, Sinead

    2011-12-01

    Thirty-six methicillin-resistant Staphylococcus aureus (MRSA) bloodstream isolates from renal patients were genetically characterized by DNA microarray analysis and spa typing. The isolates were highly clonal, belonging mainly to ST22-MRSA-IV. The immune evasion and enterotoxin gene clusters were found in 29\\/36 (80%) and 33\\/36 (92%) isolates, respectively.

  13. The effects of radiation on p53-mutated glioma cells using cDNA microarray technique

    International Nuclear Information System (INIS)

    Ngo, F.Q.H.; Hsiao, Y.-Y.H.

    2003-01-01

    Full text: In this study, we investigated the effects of 10-Gy irradiation on cell-cycle arrest, apoptosis and clonogenic death in the p53-mutated human U138MG (malignant glioblastoma) cell line. In order to evaluate time-dependent events in cellular responses to radiation, we did a time course study by incubating cells ranging from 0.5 to 48 hours after irradiation. Cell-cycle distribution and apoptosis were evaluated by flow cytometry using propidium iodide (PI) and annexin-V plus PI staining. Cell viability and proliferative capacity were studied by colony formation assay. Dual fluorescence cDNA microarray technique was used to examine the differential expression patterns of the irradiated cells. The cDNA microarray chips used contained DNA sequences corresponding to 12,814 human genes. From the flow cytometry data, it can be observed that radiation induced G2/M phase arrest and that late apoptosis was more evident following G2/M arrest. After 36 hours, some cells underwent senescence and the remains continued on with the cell cycle. Microarray analyses revealed changes in the expression of a small number of cell-cycle-related genes (p21, cyclin B1, etc.) and cell-death genes (tumor necrosis factors, DDB2, etc.) suggesting their involvement in radiation-induced cell-cycle arrest and apoptosis. In silico interpretations of the molecular mechanisms responsible for these radiation effects are in progress

  14. Microarray analysis of the gene expression profile in triethylene ...

    African Journals Online (AJOL)

    Microarray analysis of the gene expression profile in triethylene glycol dimethacrylate-treated human dental pulp cells. ... Conclusions: Our results suggest that TEGDMA can change the many functions of hDPCs through large changes in gene expression levels and complex interactions with different signaling pathways.

  15. Gene targeting associated with the radiation sensitivity in squamous cell carcinoma by using microarray analysis

    International Nuclear Information System (INIS)

    Nimura, Yoshinori; Kumagai, Ken; Kouzu, Yoshinao; Higo, Morihiro; Kato, Yoshikuni; Seki, Naohiko; Yamada, Shigeru

    2005-01-01

    In order to identify a set of genes related to radiation sensitivity of squamous cell carcinoma (SCC) and establish a predictive method, we compared expression profiles of radio-sensitive/radio-resistant SCC cell lines, using the in-house cDNA microarray consisting of 2,201 human genes derived from full-length enriched SCC cDNA libraries and the Human oligo chip 30 K (Hitachi Software Engineering). Surviving fractions (SF) after irradiation of heavy iron were calculated by colony formation assay. Three pairs (TE2-TE13, YES5-YES6, and HSC3-HSC2), sensitive (SF1 0.6), were selected for the microarray analysis. The results of cDNA microarray analysis showed that 20 genes in resistant cell lines and 5 genes in sensitive cell lines were up regulated more than 1.5-fold compared with sensitive and resistant cell lines respectively. Fourteen out of 25 genes were confirmed the gene expression profiles by real-time polymerase chain reaction (PCR). Twenty-seven genes identified by Human oligo chip 30 K are candidate for the markers to distinguish radio-sensitive from radio-resistant. These results suggest that the isolated 27 genes are the candidates that might be used as specific molecular markers to predict radiation sensitivity. (author)

  16. 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

  17. Fiber optic chemical sensors: The evolution of high- density fiber-optic DNA microarrays

    Science.gov (United States)

    Ferguson, Jane A.

    2001-06-01

    Sensors were developed for multianalyte monitoring, fermentation monitoring, lactate analysis, remote oxygen detection for use in bioremediation monitoring and in a fuel spill clean-up project, heavy metal analysis, and high density DNA microarrays. The major focus of this thesis involved creating and improving high-density DNA gene arrays. Fiber optic sensors are created using fluorescent indicators, polymeric supports, and optical fiber substrates. The fluorescent indicator is entrapped in a polymer layer and attached to the tip of the optical fiber. The tip of the fiber bearing the sensing layer (the distal end) is placed in the sample of interest while the other end of the fiber (the proximal end) is connected to an analysis system. Any length of fiber can be used without compromising the integrity or sensitivity of the system. A fiber optic oxygen sensor was designed incorporating an oxygen sensitive fluorescent dye and a gas permeable polymer attached to an optical fiber. The construction simplicity and ruggedness of the sensor enabled its deployment for in situ chemical oxidation and bioremediation studies. Optical fibers were also used as the substrate to detect biomolecules in solution. To monitor bioprocesses, the production of the analyte of interest must be coupled with a species that is optically measurable. For example, oxygen is consumed in many metabolic functions. The fiber optic oxygen sensor is equipped with an additional sensing layer. Upon contact with a specific biochemical in the sample, a reaction occurs in the additional sensing layer that either consumes or produces oxygen. This dual layer system was used to monitor the presence of lactate, an important metabolite for clinical and bioprocess analysis. In many biological and environmental systems, the generation of one species occurs coincidentally with the generation or consumption of another species. A multianalyte sensor was prepared that can monitor the simultaneous activity of pH, CO2

  18. 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.

  19. Verification of animal species in ham and salami by dna microarray and real time pcr methods

    Directory of Open Access Journals (Sweden)

    Zuzana Drdolová

    2017-01-01

    Full Text Available Consumer protection and detecting of adulteration is very important and has a wide societal impact in the economic sphere. Detection of animal species in meat products and the use of combining different methods is one of the means to achieve relevant product status. The aim of this study was to reveal whether or not the products label clearly meets the content declared by producer. In our study, 29 samples of meat products such as salami and ham obtained from stores and supermarkets in Slovakia were analyzed to detect the existing animal species according to the product label the use of Chipron LCD Array Analysis System, Meat 5.0. Products in which the presence of non-declared animal species has been detected were subjected to testing by the innuDETECT PCR Real-Time Kit, repeatedly. The results showed that 20 (68.96% samples were improperly labeled. From in total 14 tested ham samples 11 (78.57% products exhibited non-conformity with declared composition. Tested salami samples (15 revealed 9 (60% incorrectly labelled products. The results obtained by DNA Microarray and Real Time PCR methods were identical, and both methods should be extensively promoted for the detection of animal species in the meat and meat products. Normal 0 21 false false false EN-GB X-NONE X-NONE

  20. Integrating Biological Perspectives:. a Quantum Leap for Microarray Expression Analysis

    Science.gov (United States)

    Wanke, Dierk; Kilian, Joachim; Bloss, Ulrich; Mangelsen, Elke; Supper, Jochen; Harter, Klaus; Berendzen, Kenneth W.

    2009-02-01

    Biologists and bioinformatic scientists cope with the analysis of transcript abundance and the extraction of meaningful information from microarray expression data. By exploiting biological information accessible in public databases, we try to extend our current knowledge over the plant model organism Arabidopsis thaliana. Here, we give two examples of increasing the quality of information gained from large scale expression experiments by the integration of microarray-unrelated biological information: First, we utilize Arabidopsis microarray data to demonstrate that expression profiles are usually conserved between orthologous genes of different organisms. In an initial step of the analysis, orthology has to be inferred unambiguously, which then allows comparison of expression profiles between orthologs. We make use of the publicly available microarray expression data of Arabidopsis and barley, Hordeum vulgare. We found a generally positive correlation in expression trajectories between true orthologs although both organisms are only distantly related in evolutionary time scale. Second, extracting clusters of co-regulated genes implies similarities in transcriptional regulation via similar cis-regulatory elements (CREs). Vice versa approaches, where co-regulated gene clusters are found by investigating on CREs were not successful in general. Nonetheless, in some cases the presence of CREs in a defined position, orientation or CRE-combinations is positively correlated with co-regulated gene clusters. Here, we make use of genes involved in the phenylpropanoid biosynthetic pathway, to give one positive example for this approach.

  1. Novel insights into the unfolded protein response using Pichia pastoris specific DNA microarrays

    Directory of Open Access Journals (Sweden)

    Kreil David P

    2008-08-01

    Full Text Available Abstract Background DNA Microarrays are regarded as a valuable tool for basic and applied research in microbiology. However, for many industrially important microorganisms the lack of commercially available microarrays still hampers physiological research. Exemplarily, our understanding of protein folding and secretion in the yeast Pichia pastoris is presently widely dependent on conclusions drawn from analogies to Saccharomyces cerevisiae. To close this gap for a yeast species employed for its high capacity to produce heterologous proteins, we developed full genome DNA microarrays for P. pastoris and analyzed the unfolded protein response (UPR in this yeast species, as compared to S. cerevisiae. Results By combining the partially annotated gene list of P. pastoris with de novo gene finding a list of putative open reading frames was generated for which an oligonucleotide probe set was designed using the probe design tool TherMODO (a thermodynamic model-based oligoset design optimizer. To evaluate the performance of the novel array design, microarrays carrying the oligo set were hybridized with samples from treatments with dithiothreitol (DTT or a strain overexpressing the UPR transcription factor HAC1, both compared with a wild type strain in normal medium as untreated control. DTT treatment was compared with literature data for S. cerevisiae, and revealed similarities, but also important differences between the two yeast species. Overexpression of HAC1, the most direct control for UPR genes, resulted in significant new understanding of this important regulatory pathway in P. pastoris, and generally in yeasts. Conclusion The differences observed between P. pastoris and S. cerevisiae underline the importance of DNA microarrays for industrial production strains. P. pastoris reacts to DTT treatment mainly by the regulation of genes related to chemical stimulus, electron transport and respiration, while the overexpression of HAC1 induced many genes

  2. Bioinformatics and Microarray Data Analysis on the Cloud.

    Science.gov (United States)

    Calabrese, Barbara; Cannataro, Mario

    2016-01-01

    High-throughput platforms such as microarray, mass spectrometry, and next-generation sequencing are producing an increasing volume of omics data that needs large data storage and computing power. Cloud computing offers massive scalable computing and storage, data sharing, on-demand anytime and anywhere access to resources and applications, and thus, it may represent the key technology for facing those issues. In fact, in the recent years it has been adopted for the deployment of different bioinformatics solutions and services both in academia and in the industry. Although this, cloud computing presents several issues regarding the security and privacy of data, that are particularly important when analyzing patients data, such as in personalized medicine. This chapter reviews main academic and industrial cloud-based bioinformatics solutions; with a special focus on microarray data analysis solutions and underlines main issues and problems related to the use of such platforms for the storage and analysis of patients data.

  3. Rational design of DNA sequences for nanotechnology, microarrays and molecular computers using Eulerian graphs.

    Science.gov (United States)

    Pancoska, Petr; Moravek, Zdenek; Moll, Ute M

    2004-01-01

    Nucleic acids are molecules of choice for both established and emerging nanoscale technologies. These technologies benefit from large functional densities of 'DNA processing elements' that can be readily manufactured. To achieve the desired functionality, polynucleotide sequences are currently designed by a process that involves tedious and laborious filtering of potential candidates against a series of requirements and parameters. Here, we present a complete novel methodology for the rapid rational design of large sets of DNA sequences. This method allows for the direct implementation of very complex and detailed requirements for the generated sequences, thus avoiding 'brute force' filtering. At the same time, these sequences have narrow distributions of melting temperatures. The molecular part of the design process can be done without computer assistance, using an efficient 'human engineering' approach by drawing a single blueprint graph that represents all generated sequences. Moreover, the method eliminates the necessity for extensive thermodynamic calculations. Melting temperature can be calculated only once (or not at all). In addition, the isostability of the sequences is independent of the selection of a particular set of thermodynamic parameters. Applications are presented for DNA sequence designs for microarrays, universal microarray zip sequences and electron transfer experiments.

  4. 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.

  5. cDNA microarrays as a tool for identification of biomineralization proteins in the coccolithophorid Emiliania huxleyi (Haptophyta).

    Science.gov (United States)

    Quinn, Patrick; Bowers, Robert M; Zhang, Xiaoyu; Wahlund, Thomas M; Fanelli, Michael A; Olszova, Daniela; Read, Betsy A

    2006-08-01

    Marine unicellular coccolithophore algae produce species-specific calcite scales otherwise known as coccoliths. While the coccoliths and their elaborate architecture have attracted the attention of investigators from various scientific disciplines, our knowledge of the underpinnings of the process of biomineralization in this alga is still in its infancy. The processes of calcification and coccolithogenesis are highly regulated and likely to be complex, requiring coordinated expression of many genes and pathways. In this study, we have employed cDNA microarrays to investigate changes in gene expression associated with biomineralization in the most abundant coccolithophorid, Emiliania huxleyi. Expression profiling of cultures grown under calcifying and noncalcifying conditions has been carried out using cDNA microarrays corresponding to approximately 2,300 expressed sequence tags. A total of 127 significantly up- or down-regulated transcripts were identified using a P value of 0.01 and a change of >2.0-fold. Real-time reverse transcriptase PCR was used to test the overall validity of the microarray data, as well as the relevance of many of the proteins predicted to be associated with biomineralization, including a novel gamma-class carbonic anhydrase (A. R. Soto, H. Zheng, D. Shoemaker, J. Rodriguez, B. A. Read, and T. M. Wahlund, Appl. Environ. Microbiol. 72:5500-5511, 2006). Differentially regulated genes include those related to cellular metabolism, ion channels, transport proteins, vesicular trafficking, and cell signaling. The putative function of the vast majority of candidate transcripts could not be defined. Nonetheless, the data described herein represent profiles of the transcription changes associated with biomineralization-related pathways in E. huxleyi and have identified novel and potentially useful targets for more detailed analysis.

  6. 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

  7. Microarray mRNA expression analysis of Fanconi anemia fibroblasts.

    Science.gov (United States)

    Galetzka, D; Weis, E; Rittner, G; Schindler, D; Haaf, T

    2008-01-01

    Fanconi anemia (FA) cells are generally hypersensitive to DNA cross-linking agents, implying that mutations in the different FANC genes cause a similar DNA repair defect(s). By using a customized cDNA microarray chip for DNA repair- and cell cycle-associated genes, we identified three genes, cathepsin B (CTSB), glutaredoxin (GLRX), and polo-like kinase 2 (PLK2), that were misregulated in untreated primary fibroblasts from three unrelated FA-D2 patients, compared to six controls. Quantitative real-time RT PCR was used to validate these results and to study possible molecular links between FA-D2 and other FA subtypes. GLRX was misregulated to opposite directions in a variety of different FA subtypes. Increased CTSB and decreased PLK2 expression was found in all or almost all of the analyzed complementation groups and, therefore, may be related to the defective FA pathway. Transcriptional upregulation of the CTSB proteinase appears to be a secondary phenomenon due to proliferation differences between FA and normal fibroblast cultures. In contrast, PLK2 is known to play a pivotal role in processes that are linked to FA defects and may contribute in multiple ways to the FA phenotype: PLK2 is a target gene for TP53, is likely to function as a tumor suppressor gene in hematologic neoplasia, and Plk2(-/-) mice are small because of defective embryonal development. (c) 2008 S. Karger AG, Basel.

  8. Microarray analysis of gene expression profiles in ripening pineapple fruits.

    Science.gov (United States)

    Koia, Jonni H; Moyle, Richard L; Botella, Jose R

    2012-12-18

    Pineapple (Ananas comosus) is a tropical fruit crop of significant commercial importance. Although the physiological changes that occur during pineapple fruit development have been well characterized, little is known about the molecular events that occur during the fruit ripening process. Understanding the molecular basis of pineapple fruit ripening will aid the development of new varieties via molecular breeding or genetic modification. In this study we developed a 9277 element pineapple microarray and used it to profile gene expression changes that occur during pineapple fruit ripening. Microarray analyses identified 271 unique cDNAs differentially expressed at least 1.5-fold between the mature green and mature yellow stages of pineapple fruit ripening. Among these 271 sequences, 184 share significant homology with genes encoding proteins of known function, 53 share homology with genes encoding proteins of unknown function and 34 share no significant homology with any database accession. Of the 237 pineapple sequences with homologs, 160 were up-regulated and 77 were down-regulated during pineapple fruit ripening. DAVID Functional Annotation Cluster (FAC) analysis of all 237 sequences with homologs revealed confident enrichment scores for redox activity, organic acid metabolism, metalloenzyme activity, glycolysis, vitamin C biosynthesis, antioxidant activity and cysteine peptidase activity, indicating the functional significance and importance of these processes and pathways during pineapple fruit development. Quantitative real-time PCR analysis validated the microarray expression results for nine out of ten genes tested. This is the first report of a microarray based gene expression study undertaken in pineapple. Our bioinformatic analyses of the transcript profiles have identified a number of genes, processes and pathways with putative involvement in the pineapple fruit ripening process. This study extends our knowledge of the molecular basis of pineapple fruit

  9. Massively multiplexed microbial identification using resequencing DNA microarrays for outbreak investigation

    Science.gov (United States)

    Leski, T. A.; Ansumana, R.; Jimmy, D. H.; Bangura, U.; Malanoski, A. P.; Lin, B.; Stenger, D. A.

    2011-06-01

    Multiplexed microbial diagnostic assays are a promising method for detection and identification of pathogens causing syndromes characterized by nonspecific symptoms in which traditional differential diagnosis is difficult. Also such assays can play an important role in outbreak investigations and environmental screening for intentional or accidental release of biothreat agents, which requires simultaneous testing for hundreds of potential pathogens. The resequencing pathogen microarray (RPM) is an emerging technological platform, relying on a combination of massively multiplex PCR and high-density DNA microarrays for rapid detection and high-resolution identification of hundreds of infectious agents simultaneously. The RPM diagnostic system was deployed in Sierra Leone, West Africa in collaboration with Njala University and Mercy Hospital Research Laboratory located in Bo. We used the RPM-Flu microarray designed for broad-range detection of human respiratory pathogens, to investigate a suspected outbreak of avian influenza in a number of poultry farms in which significant mortality of chickens was observed. The microarray results were additionally confirmed by influenza specific real-time PCR. The results of the study excluded the possibility that the outbreak was caused by influenza, but implicated Klebsiella pneumoniae as a possible pathogen. The outcome of this feasibility study confirms that application of broad-spectrum detection platforms for outbreak investigation in low-resource locations is possible and allows for rapid discovery of the responsible agents, even in cases when different agents are suspected. This strategy enables quick and cost effective detection of low probability events such as outbreak of a rare disease or intentional release of a biothreat agent.

  10. DNA-microarrays identification of Streptococcus mutans genes associated with biofilm thickness

    Directory of Open Access Journals (Sweden)

    Feldman Mark

    2008-12-01

    Full Text Available Abstract Background A biofilm is a complex community of microorganisms that develop on surfaces in diverse environments. The thickness of the biofilm plays a crucial role in the physiology of the immobilized bacteria. The most cariogenic bacteria, mutans streptococci, are common inhabitants of a dental biofilm community. In this study, DNA-microarray analysis was used to identify differentially expressed genes associated with the thickness of S. mutans biofilms. Results Comparative transcriptome analyses indicated that expression of 29 genes was differentially altered in 400- vs. 100-microns depth and 39 genes in 200- vs. 100-microns biofilms. Only 10 S. mutans genes showed differential expression in both 400- vs. 100-microns and 200- vs. 100-microns biofilms. All of these genes were upregulated. As sucrose is a predominant factor in oral biofilm development, its influence was evaluated on selected genes expression in the various depths of biofilms. The presence of sucrose did not noticeably change the regulation of these genes in 400- vs. 100-microns and/or 200- vs. 100-microns biofilms tested by real-time RT-PCR. Furthermore, we analyzed the expression profile of selected biofilm thickness associated genes in the luxS- mutant strain. The expression of those genes was not radically changed in the mutant strain compared to wild-type bacteria in planktonic condition. Only slight downregulation was recorded in SMU.2146c, SMU.574, SMU.609, and SMU.987 genes expression in luxS- bacteria in biofilm vs. planktonic environments. Conclusion These findings reveal genes associated with the thickness of biofilms of S. mutans. Expression of these genes is apparently not regulated directly by luxS and is not necessarily influenced by the presence of sucrose in the growth media.

  11. A DNA microarray-based methylation-sensitive (MS)-AFLP hybridization method for genetic and epigenetic analyses.

    Science.gov (United States)

    Yamamoto, F; Yamamoto, M

    2004-07-01

    We previously developed a PCR-based DNA fingerprinting technique named the Methylation Sensitive (MS)-AFLP method, which permits comparative genome-wide scanning of methylation status with a manageable number of fingerprinting experiments. The technique uses the methylation sensitive restriction enzyme NotI in the context of the existing Amplified Fragment Length Polymorphism (AFLP) method. Here we report the successful conversion of this gel electrophoresis-based DNA fingerprinting technique into a DNA microarray hybridization technique (DNA Microarray MS-AFLP). By performing a total of 30 (15 x 2 reciprocal labeling) DNA Microarray MS-AFLP hybridization experiments on genomic DNA from two breast and three prostate cancer cell lines in all pairwise combinations, and Southern hybridization experiments using more than 100 different probes, we have demonstrated that the DNA Microarray MS-AFLP is a reliable method for genetic and epigenetic analyses. No statistically significant differences were observed in the number of differences between the breast-prostate hybridization experiments and the breast-breast or prostate-prostate comparisons.

  12. PNA-PEG modified silicon platforms as functional bio-interfaces for applications in DNA microarrays and biosensors.

    Science.gov (United States)

    Cattani-Scholz, Anna; Pedone, Daniel; Blobner, Florian; Abstreiter, Gerhard; Schwartz, Jeffrey; Tornow, Marc; Andruzzi, Luisa

    2009-03-09

    The synthesis and characterization of two types of silicon-based biofunctional interfaces are reported; each interface bonds a dense layer of poly(ethylene glycol) (PEG(n)) and peptide nucleic acid (PNA) probes. Phosphonate self-assembled monolayers were derivatized with PNA using a maleimido-terminated PEG(45). Similarly, siloxane monolayers were functionalized with PNA using a maleimido-terminated PEG(45) spacer and were subsequently modified with a shorter methoxy-terminated PEG(12) ("back-filling"). The long PEG(45) spacer was used to distance the PNA probe from the surface and to minimize undesirable nonspecific adsorption of DNA analyte. The short PEG(12) "back-filler" was used to provide additional passivation of the surface against nonspecific DNA adsorption. X-ray photoelectron spectroscopic (XPS) analysis near the C 1s and N 1s ionization edges was done to characterize chemical groups formed in the near-surface region, which confirmed binding of PEG and PNA to the phosphonate and silane films. XPS also indicated that additional PEG chains were tethered to the surface during the back-filling process. Fluorescence hybridization experiments were carried out with complementary and noncDNA strands; both phosphonate and siloxane biofunctional surfaces were effective for hybridization of cDNA strands and significantly reduced nonspecific adsorption of the analyte. Spatial patterns were prepared by polydimethylsiloxane (PDMS) micromolding on the PNA-functionalized surfaces; selective hybridization of fluorescently labeled DNA was shown at the PNA functionalized regions, and physisorption at the probe-less PEG-functionalized regions was dramatically reduced. These results show that PNA-PEG derivatized phosphonate monolayers hold promise for the smooth integration of device surface chemistry with semiconductor technology for the fabrication of DNA biosensors. In addition, our results confirm that PNA-PEG derivatized self-assembled carboxyalkylsiloxane films are

  13. Methods for interpreting lists of affected genes obtained in a DNA microarray experiment

    DEFF Research Database (Denmark)

    Hedegaard, Jakob; Arce, Christina; Bicciato, Silvio

    2009-01-01

    The aim of this paper was to describe and compare the methods used and the results obtained by the participants in a joint EADGENE (European Animal Disease Genomic Network of Excellence) and SABRE (Cutting Edge Genomics for Sustainable Animal Breeding) workshop focusing on post analysis of microa...... a microarray experiment conducted to study the host reactions in broilers occurring shortly after a secondary challenge with either a homologous or heterologous species of Eimeria...

  14. Selective recognition of DNA from olive leaves and olive oil by PNA and modified-PNA microarrays

    Science.gov (United States)

    Rossi, Stefano; Calabretta, Alessandro; Tedeschi, Tullia; Sforza, Stefano; Arcioni, Sergio; Baldoni, Luciana; Corradini, Roberto; Marchelli, Rosangela

    2012-01-01

    PNA probes for the specific detection of DNA from olive oil samples by microarray technology were developed. The presence of as low as 5% refined hazelnut (Corylus avellana) oil in extra-virgin olive oil (Olea europaea L.) could be detected by using a PNA microarray. A set of two single nucleotide polymorphisms (SNPs) from the Actin gene of Olive was chosen as a model for evaluating the ability of PNA probes for discriminating olive cultivars. Both unmodified and C2-modified PNAs bearing an arginine side-chain were used, the latter showing higher sequence specificity. DNA extracted from leaves of three different cultivars (Ogliarola leccese, Canino and Frantoio) could be easily discriminated using a microarray with unmodified PNA probes, whereas discrimination of DNA from oil samples was more challenging, and could be obtained only by using chiral PNA probes. PMID:22772038

  15. 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/.

  16. Dissection of the inflammatory bowel disease transcriptome using genome-wide cDNA microarrays.

    Directory of Open Access Journals (Sweden)

    Christine M Costello

    2005-08-01

    Full Text Available BACKGROUND: The differential pathophysiologic mechanisms that trigger and maintain the two forms of inflammatory bowel disease (IBD, Crohn disease (CD, and ulcerative colitis (UC are only partially understood. cDNA microarrays can be used to decipher gene regulation events at a genome-wide level and to identify novel unknown genes that might be involved in perpetuating inflammatory disease progression. METHODS AND FINDINGS: High-density cDNA microarrays representing 33,792 UniGene clusters were prepared. Biopsies were taken from the sigmoid colon of normal controls (n = 11, CD patients (n = 10 and UC patients (n = 10. 33P-radiolabeled cDNA from purified poly(A+ RNA extracted from biopsies (unpooled was hybridized to the arrays. We identified 500 and 272 transcripts differentially regulated in CD and UC, respectively. Interesting hits were independently verified by real-time PCR in a second sample of 100 individuals, and immunohistochemistry was used for exemplary localization. The main findings point to novel molecules important in abnormal immune regulation and the highly disturbed cell biology of colonic epithelial cells in IBD pathogenesis, e.g., CYLD (cylindromatosis, turban tumor syndrome and CDH11 (cadherin 11, type 2. By the nature of the array setup, many of the genes identified were to our knowledge previously uncharacterized, and prediction of the putative function of a subsection of these genes indicate that some could be involved in early events in disease pathophysiology. CONCLUSION: A comprehensive set of candidate genes not previously associated with IBD was revealed, which underlines the polygenic and complex nature of the disease. It points out substantial differences in pathophysiology between CD and UC. The multiple unknown genes identified may stimulate new research in the fields of barrier mechanisms and cell signalling in the context of IBD, and ultimately new therapeutic approaches.

  17. A Comparison Study for DNA Motif Modeling on Protein Binding Microarray

    KAUST Repository

    Wong, Ka-Chun; Li, Yue; Peng, Chengbin; Wong, Hau-San

    2015-01-01

    Transcription Factor Binding Sites (TFBSs) are relatively short (5-15 bp) and degenerate. Identifying them is a computationally challenging task. In particular, Protein Binding Microarray (PBM) is a high-throughput platform that can measure the DNA binding preference of a protein in a comprehensive and unbiased manner; for instance, a typical PBM experiment can measure binding signal intensities of a protein to all possible DNA k-mers (k=810). Since proteins can often bind to DNA with different binding intensities, one of the major challenges is to build motif models which can fully capture the quantitative binding affinity data. To learn DNA motif models from the non-convex objective function landscape, several optimization methods are compared and applied to the PBM motif model building problem. In particular, representative methods from different optimization paradigms have been chosen for modeling performance comparison on hundreds of PBM datasets. The results suggest that the multimodal optimization methods are very effective for capturing the binding preference information from PBM data. In particular, we observe a general performance improvement using di-nucleotide modeling over mono-nucleotide modeling. In addition, the models learned by the best-performing method are applied to two independent applications: PBM probe rotation testing and ChIP-Seq peak sequence prediction, demonstrating its biological applicability.

  18. A Comparison Study for DNA Motif Modeling on Protein Binding Microarray

    KAUST Repository

    Wong, Ka-Chun

    2015-06-11

    Transcription Factor Binding Sites (TFBSs) are relatively short (5-15 bp) and degenerate. Identifying them is a computationally challenging task. In particular, Protein Binding Microarray (PBM) is a high-throughput platform that can measure the DNA binding preference of a protein in a comprehensive and unbiased manner; for instance, a typical PBM experiment can measure binding signal intensities of a protein to all possible DNA k-mers (k=810). Since proteins can often bind to DNA with different binding intensities, one of the major challenges is to build motif models which can fully capture the quantitative binding affinity data. To learn DNA motif models from the non-convex objective function landscape, several optimization methods are compared and applied to the PBM motif model building problem. In particular, representative methods from different optimization paradigms have been chosen for modeling performance comparison on hundreds of PBM datasets. The results suggest that the multimodal optimization methods are very effective for capturing the binding preference information from PBM data. In particular, we observe a general performance improvement using di-nucleotide modeling over mono-nucleotide modeling. In addition, the models learned by the best-performing method are applied to two independent applications: PBM probe rotation testing and ChIP-Seq peak sequence prediction, demonstrating its biological applicability.

  19. Systematic spatial bias in DNA microarray hybridization is caused by probe spot position-dependent variability in lateral diffusion.

    Science.gov (United States)

    Steger, Doris; Berry, David; Haider, Susanne; Horn, Matthias; Wagner, Michael; Stocker, Roman; Loy, Alexander

    2011-01-01

    The hybridization of nucleic acid targets with surface-immobilized probes is a widely used assay for the parallel detection of multiple targets in medical and biological research. Despite its widespread application, DNA microarray technology still suffers from several biases and lack of reproducibility, stemming in part from an incomplete understanding of the processes governing surface hybridization. In particular, non-random spatial variations within individual microarray hybridizations are often observed, but the mechanisms underpinning this positional bias remain incompletely explained. This study identifies and rationalizes a systematic spatial bias in the intensity of surface hybridization, characterized by markedly increased signal intensity of spots located at the boundaries of the spotted areas of the microarray slide. Combining observations from a simplified single-probe block array format with predictions from a mathematical model, the mechanism responsible for this bias is found to be a position-dependent variation in lateral diffusion of target molecules. Numerical simulations reveal a strong influence of microarray well geometry on the spatial bias. Reciprocal adjustment of the size of the microarray hybridization chamber to the area of surface-bound probes is a simple and effective measure to minimize or eliminate the diffusion-based bias, resulting in increased uniformity and accuracy of quantitative DNA microarray hybridization.

  20. Development of a microarray-based assay for efficient testing of new HSP70/DnaK inhibitors.

    Science.gov (United States)

    Mohammadi-Ostad-Kalayeh, Sona; Hrupins, Vjaceslavs; Helmsen, Sabine; Ahlbrecht, Christin; Stahl, Frank; Scheper, Thomas; Preller, Matthias; Surup, Frank; Stadler, Marc; Kirschning, Andreas; Zeilinger, Carsten

    2017-12-15

    A facile method for testing ATP binding in a highly miniaturized microarray environment using human HSP70 and DnaK from Mycobacterium tuberculosis as biological targets is reported. Supported by molecular modelling studies we demonstrate that the position of the fluorescence label on ATP has a strong influence on the binding to human HSP70. Importantly, the label has to be positioned on the adenine ring and not to the terminal phosphate group. Unlabelled ATP displaced bound Cy5-ATP from HSP70 in the micromolar range. The affinity of a well-known HSP70 inhibitor VER155008 for the ATP binding site in HSP70 was determined, with a EC 50 in the micromolar range, whereas reblastin, a HSP90-inhibitor, did not compete for ATP in the presence of HSP70. The applicability of the method was demonstrated by screening a small compound library of natural products. This unraveled that terphenyls rickenyl A and D, recently isolated from cultures of the fungus Hypoxylon rickii, are inhibitors of HSP70. They compete with ATP for the chaperone in the range of 29 µM (Rickenyl D) and 49 µM (Rickenyl A). Furthermore, the microarray-based test system enabled protein-protein interaction analysis using full-length HSP70 and HSP90 proteins. The labelled full-length human HSP90 binds with a half-maximal affinity of 5.5 µg/ml (∼40 µM) to HSP70. The data also demonstrate that the microarray test has potency for many applications from inhibitor screening to target-oriented interaction studies. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Enhancing the Sensitivity of DNA Microarray Using Dye-Doped Silica Nanoparticles: Detection of Human Papilloma Virus

    Science.gov (United States)

    Enrichi, F.; Riccò, R.; Meneghello, A.; Pierobon, R.; Canton, G.; Cretaio, E.

    2010-10-01

    DNA microarray is a high-throughput technology used for detection and quantification of nucleic acid molecules and others of biological interest. The analysis is based on the specific hybridization between probe sequences deposited in array and a target ss-DNA amplified by PCR and functionalized by a fluorescent dye. Organic labels have well known disadvantages like photobleaching and low signal intensities, which put a limitation to the lower amount of DNA material that can be detected. Therefore for trace analysis the development of more efficient biomarkers is required. With this aim we present in this paper the synthesis and application of alternative hybrid nanosystems obtained by incorporating standard fluorescent molecules into monodisperse silica nanoparticles. Efficient application to the detection of Human Papilloma Virus is demonstrated. This virus is associated to the formation of cervical cancer, a leading cause of death by cancer for women worldwide. It is shown that the use of the novel biomarkers increases the optical signal of about one order of magnitude with respect to the free dyes or quantum dots in conventional instruments. This is due to the high number of molecules that can be accommodated into each nanoparticle, to the reduced photobleaching and to the improved environmental protection of the dyes when encapsulated in the silica matrix. The cheap and easy synthesis of these luminescent particles, the stability in water, the surface functionalizability and bio-compatibility make them very promising for present and future bio-labeling and bio-imaging applications.

  2. Evaluation of normalization methods for cDNA microarray data by k-NN classification

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Wei; Xing, Eric P; Myers, Connie; Mian, Saira; Bissell, Mina J

    2004-12-17

    Non-biological factors give rise to unwanted variations in cDNA microarray data. There are many normalization methods designed to remove such variations. However, to date there have been few published systematic evaluations of these techniques for removing variations arising from dye biases in the context of downstream, higher-order analytical tasks such as classification. Ten location normalization methods that adjust spatial- and/or intensity-dependent dye biases, and three scale methods that adjust scale differences were applied, individually and in combination, to five distinct, published, cancer biology-related cDNA microarray data sets. Leave-one-out cross-validation (LOOCV) classification error was employed as the quantitative end-point for assessing the effectiveness of a normalization method. In particular, a known classifier, k-nearest neighbor (k-NN), was estimated from data normalized using a given technique, and the LOOCV error rate of the ensuing model was computed. We found that k-NN classifiers are sensitive to dye biases in the data. Using NONRM and GMEDIAN as baseline methods, our results show that single-bias-removal techniques which remove either spatial-dependent dye bias (referred later as spatial effect) or intensity-dependent dye bias (referred later as intensity effect) moderately reduce LOOCV classification errors; whereas double-bias-removal techniques which remove both spatial- and intensity effect reduce LOOCV classification errors even further. Of the 41 different strategies examined, three two-step processes, IGLOESS-SLFILTERW7, ISTSPLINE-SLLOESS and IGLOESS-SLLOESS, all of which removed intensity effect globally and spatial effect locally, appear to reduce LOOCV classification errors most consistently and effectively across all data sets. We also found that the investigated scale normalization methods do not reduce LOOCV classification error. Using LOOCV error of k-NNs as the evaluation criterion, three double

  3. Identification of Differentially Expressed IGFBP5-Related Genes in Breast Cancer Tumor Tissues Using cDNA Microarray Experiments.

    Science.gov (United States)

    Akkiprik, Mustafa; Peker, İrem; Özmen, Tolga; Amuran, Gökçe Güllü; Güllüoğlu, Bahadır M; Kaya, Handan; Özer, Ayşe

    2015-11-10

    IGFBP5 is an important regulatory protein in breast cancer progression. We tried to identify differentially expressed genes (DEGs) between breast tumor tissues with IGFBP5 overexpression and their adjacent normal tissues. In this study, thirty-eight breast cancer and adjacent normal breast tissue samples were used to determine IGFBP5 expression by qPCR. cDNA microarrays were applied to the highest IGFBP5 overexpressed tumor samples compared to their adjacent normal breast tissue. Microarray analysis revealed that a total of 186 genes were differentially expressed in breast cancer compared with normal breast tissues. Of the 186 genes, 169 genes were downregulated and 17 genes were upregulated in the tumor samples. KEGG pathway analyses showed that protein digestion and absorption, focal adhesion, salivary secretion, drug metabolism-cytochrome P450, and phenylalanine metabolism pathways are involved. Among these DEGs, the prominent top two genes (MMP11 and COL1A1) which potentially correlated with IGFBP5 were selected for validation using real time RT-qPCR. Only COL1A1 expression showed a consistent upregulation with IGFBP5 expression and COL1A1 and MMP11 were significantly positively correlated. We concluded that the discovery of coordinately expressed genes related with IGFBP5 might contribute to understanding of the molecular mechanism of the function of IGFBP5 in breast cancer. Further functional studies on DEGs and association with IGFBP5 may identify novel biomarkers for clinical applications in breast cancer.

  4. Detection of perturbation phases and developmental stages in organisms from DNA microarray time series data.

    Directory of Open Access Journals (Sweden)

    Marianne Rooman

    Full Text Available Available DNA microarray time series that record gene expression along the developmental stages of multicellular eukaryotes, or in unicellular organisms subject to external perturbations such as stress and diauxie, are analyzed. By pairwise comparison of the gene expression profiles on the basis of a translation-invariant and scale-invariant distance measure corresponding to least-rectangle regression, it is shown that peaks in the average distance values are noticeable and are localized around specific time points. These points systematically coincide with the transition points between developmental phases or just follow the external perturbations. This approach can thus be used to identify automatically, from microarray time series alone, the presence of external perturbations or the succession of developmental stages in arbitrary cell systems. Moreover, our results show that there is a striking similarity between the gene expression responses to these a priori very different phenomena. In contrast, the cell cycle does not involve a perturbation-like phase, but rather continuous gene expression remodeling. Similar analyses were conducted using three other standard distance measures, showing that the one we introduced was superior. Based on these findings, we set up an adapted clustering method that uses this distance measure and classifies the genes on the basis of their expression profiles within each developmental stage or between perturbation phases.

  5. Discovery of possible gene relationships through the application of self-organizing maps to DNA microarray databases.

    Science.gov (United States)

    Chavez-Alvarez, Rocio; Chavoya, Arturo; Mendez-Vazquez, Andres

    2014-01-01

    DNA microarrays and cell cycle synchronization experiments have made possible the study of the mechanisms of cell cycle regulation of Saccharomyces cerevisiae by simultaneously monitoring the expression levels of thousands of genes at specific time points. On the other hand, pattern recognition techniques can contribute to the analysis of such massive measurements, providing a model of gene expression level evolution through the cell cycle process. In this paper, we propose the use of one of such techniques--an unsupervised artificial neural network called a Self-Organizing Map (SOM)-which has been successfully applied to processes involving very noisy signals, classifying and organizing them, and assisting in the discovery of behavior patterns without requiring prior knowledge about the process under analysis. As a test bed for the use of SOMs in finding possible relationships among genes and their possible contribution in some biological processes, we selected 282 S. cerevisiae genes that have been shown through biological experiments to have an activity during the cell cycle. The expression level of these genes was analyzed in five of the most cited time series DNA microarray databases used in the study of the cell cycle of this organism. With the use of SOM, it was possible to find clusters of genes with similar behavior in the five databases along two cell cycles. This result suggested that some of these genes might be biologically related or might have a regulatory relationship, as was corroborated by comparing some of the clusters obtained with SOMs against a previously reported regulatory network that was generated using biological knowledge, such as protein-protein interactions, gene expression levels, metabolism dynamics, promoter binding, and modification, regulation and transport of proteins. The methodology described in this paper could be applied to the study of gene relationships of other biological processes in different organisms.

  6. Supervised group Lasso with applications to microarray data analysis

    Directory of Open Access Journals (Sweden)

    Huang Jian

    2007-02-01

    Full Text Available Abstract Background A tremendous amount of efforts have been devoted to identifying genes for diagnosis and prognosis of diseases using microarray gene expression data. It has been demonstrated that gene expression data have cluster structure, where the clusters consist of co-regulated genes which tend to have coordinated functions. However, most available statistical methods for gene selection do not take into consideration the cluster structure. Results We propose a supervised group Lasso approach that takes into account the cluster structure in gene expression data for gene selection and predictive model building. For gene expression data without biological cluster information, we first divide genes into clusters using the K-means approach and determine the optimal number of clusters using the Gap method. The supervised group Lasso consists of two steps. In the first step, we identify important genes within each cluster using the Lasso method. In the second step, we select important clusters using the group Lasso. Tuning parameters are determined using V-fold cross validation at both steps to allow for further flexibility. Prediction performance is evaluated using leave-one-out cross validation. We apply the proposed method to disease classification and survival analysis with microarray data. Conclusion We analyze four microarray data sets using the proposed approach: two cancer data sets with binary cancer occurrence as outcomes and two lymphoma data sets with survival outcomes. The results show that the proposed approach is capable of identifying a small number of influential gene clusters and important genes within those clusters, and has better prediction performance than existing methods.

  7. Microarray analysis of thioacetamide-treated type 1 diabetic rats

    International Nuclear Information System (INIS)

    Devi, Sachin S.; Mehendale, Harihara M.

    2006-01-01

    It is well known that diabetes imparts high sensitivity to numerous hepatotoxicants. Previously, we have shown that a normally non-lethal dose of thioacetamide (TA, 300 mg/kg) causes 90% mortality in type 1 diabetic (DB) rats due to inhibited tissue repair allowing progression of liver injury. On the other hand, DB rats exposed to 30 mg TA/kg exhibit delayed tissue repair and delayed recovery from injury. The objective of this study was to investigate the mechanism of impaired tissue repair and progression of liver injury in TA-treated DB rats by using cDNA microarray. Gene expression pattern was examined at 0, 6, and 12 h after TA challenge, and selected mechanistic leads from microarray experiments were confirmed by real-time RT-PCR and further investigated at protein level over the time course of 0 to 36 h after TA treatment. Diabetic condition itself increased gene expression of proteases and decreased gene expression of protease inhibitors. Administration of 300 mg TA/kg to DB rats further elevated gene expression of proteases and suppressed gene expression of protease inhibitors, explaining progression of liver injury in DB rats after TA treatment. Inhibited expression of genes involved in cell division cycle (cyclin D1, IGFBP-1, ras, E2F) was observed after exposure of DB rats to 300 mg TA/kg, explaining inhibited tissue repair in these rats. On the other hand, DB rats receiving 30 mg TA/kg exhibit delayed expression of genes involved in cell division cycle, explaining delayed tissue repair in these rats. In conclusion, impaired cyclin D1 signaling along with increased proteases and decreased protease inhibitors may explain impaired tissue repair that leads to progression of liver injury initiated by TA in DB rats

  8. A Bayesian decision procedure for testing multiple hypotheses in DNA microarray experiments.

    Science.gov (United States)

    Gómez-Villegas, Miguel A; Salazar, Isabel; Sanz, Luis

    2014-02-01

    DNA microarray experiments require the use of multiple hypothesis testing procedures because thousands of hypotheses are simultaneously tested. We deal with this problem from a Bayesian decision theory perspective. We propose a decision criterion based on an estimation of the number of false null hypotheses (FNH), taking as an error measure the proportion of the posterior expected number of false positives with respect to the estimated number of true null hypotheses. The methodology is applied to a Gaussian model when testing bilateral hypotheses. The procedure is illustrated with both simulated and real data examples and the results are compared to those obtained by the Bayes rule when an additive loss function is considered for each joint action and the generalized loss 0-1 function for each individual action. Our procedure significantly reduced the percentage of false negatives whereas the percentage of false positives remains at an acceptable level.

  9. Multivariate analysis of microarray data: differential expression and differential connection.

    Science.gov (United States)

    Kiiveri, Harri T

    2011-02-01

    Typical analysis of microarray data ignores the correlation between gene expression values. In this paper we present a model for microarray data which specifically allows for correlation between genes. As a result we combine gene network ideas with linear models and differential expression. We use sparse inverse covariance matrices and their associated graphical representation to capture the notion of gene networks. An important issue in using these models is the identification of the pattern of zeroes in the inverse covariance matrix. The limitations of existing methods for doing this are discussed and we provide a workable solution for determining the zero pattern. We then consider a method for estimating the parameters in the inverse covariance matrix which is suitable for very high dimensional matrices. We also show how to construct multivariate tests of hypotheses. These overall multivariate tests can be broken down into two components, the first one being similar to tests for differential expression and the second involving the connections between genes. The methods in this paper enable the extraction of a wealth of information concerning the relationships between genes which can be conveniently represented in graphical form. Differentially expressed genes can be placed in the context of the gene network and places in the gene network where unusual or interesting patterns have emerged can be identified, leading to the formulation of hypotheses for future experimentation.

  10. Multivariate analysis of microarray data: differential expression and differential connection

    Directory of Open Access Journals (Sweden)

    Kiiveri Harri T

    2011-02-01

    Full Text Available Abstract Background Typical analysis of microarray data ignores the correlation between gene expression values. In this paper we present a model for microarray data which specifically allows for correlation between genes. As a result we combine gene network ideas with linear models and differential expression. Results We use sparse inverse covariance matrices and their associated graphical representation to capture the notion of gene networks. An important issue in using these models is the identification of the pattern of zeroes in the inverse covariance matrix. The limitations of existing methods for doing this are discussed and we provide a workable solution for determining the zero pattern. We then consider a method for estimating the parameters in the inverse covariance matrix which is suitable for very high dimensional matrices. We also show how to construct multivariate tests of hypotheses. These overall multivariate tests can be broken down into two components, the first one being similar to tests for differential expression and the second involving the connections between genes. Conclusion The methods in this paper enable the extraction of a wealth of information concerning the relationships between genes which can be conveniently represented in graphical form. Differentially expressed genes can be placed in the context of the gene network and places in the gene network where unusual or interesting patterns have emerged can be identified, leading to the formulation of hypotheses for future experimentation.

  11. Development of a cDNA microarray for the measurement of gene expression in the sheep scab mite Psoroptes ovis

    Directory of Open Access Journals (Sweden)

    Burgess Stewart TG

    2012-02-01

    Full Text Available Abstract Background Sheep scab is caused by the ectoparasitic mite Psoroptes ovis which initiates a profound cutaneous inflammatory response, leading to the development of the skin lesions which are characteristic of the disease. Existing control strategies rely upon injectable endectocides and acaricidal dips but concerns over residues, eco-toxicity and the development of acaricide resistance limit the sustainability of this approach. In order to identify alternative means of disease control, a deeper understanding of both the parasite and its interaction with the host are required. Methods Herein we describe the development and utilisation of an annotated P. ovis cDNA microarray containing 3,456 elements for the measurement of gene expression in this economically important ectoparasite. The array consists of 981 P. ovis EST sequences printed in triplicate along with 513 control elements. Array performance was validated through the analysis of gene expression differences between fed and starved P. ovis mites. Results Sequences represented on the array include homologues of major house dust mite allergens and tick salivary proteins, along with factors potentially involved in mite reproduction and xenobiotic metabolism. In order to validate the performance of this unique resource under biological conditions we used the array to analyse gene expression differences between fed and starved P. ovis mites. These analyses identified a number of house dust mite allergen homologues up-regulated in fed mites and P. ovis transcripts involved in stress responses, autophagy and chemosensory perception up-regulated in starved mites. Conclusion The P. ovis cDNA microarray described here has been shown to be both robust and reproducible and will enable future studies to analyse gene expression in this important ectoparasite.

  12. Large-scale chromatin immunoprecipitation with promoter sequence microarray analysis of the interaction of the NSs protein of Rift Valley fever virus with regulatory DNA regions of the host genome.

    Science.gov (United States)

    Benferhat, Rima; Josse, Thibaut; Albaud, Benoit; Gentien, David; Mansuroglu, Zeyni; Marcato, Vasco; Souès, Sylvie; Le Bonniec, Bernard; Bouloy, Michèle; Bonnefoy, Eliette

    2012-10-01

    Rift Valley fever virus (RVFV) is a highly pathogenic Phlebovirus that infects humans and ruminants. Initially confined to Africa, RVFV has spread outside Africa and presently represents a high risk to other geographic regions. It is responsible for high fatality rates in sheep and cattle. In humans, RVFV can induce hepatitis, encephalitis, retinitis, or fatal hemorrhagic fever. The nonstructural NSs protein that is the major virulence factor is found in the nuclei of infected cells where it associates with cellular transcription factors and cofactors. In previous work, we have shown that NSs interacts with the promoter region of the beta interferon gene abnormally maintaining the promoter in a repressed state. In this work, we performed a genome-wide analysis of the interactions between NSs and the host genome using a genome-wide chromatin immunoprecipitation combined with promoter sequence microarray, the ChIP-on-chip technique. Several cellular promoter regions were identified as significantly interacting with NSs, and the establishment of NSs interactions with these regions was often found linked to deregulation of expression of the corresponding genes. Among annotated NSs-interacting genes were present not only genes regulating innate immunity and inflammation but also genes regulating cellular pathways that have not yet been identified as targeted by RVFV. Several of these pathways, such as cell adhesion, axonal guidance, development, and coagulation were closely related to RVFV-induced disorders. In particular, we show in this work that NSs targeted and modified the expression of genes coding for coagulation factors, demonstrating for the first time that this hemorrhagic virus impairs the host coagulation cascade at the transcriptional level.

  13. An Introduction to MAMA (Meta-Analysis of MicroArray data) System.

    Science.gov (United States)

    Zhang, Zhe; Fenstermacher, David

    2005-01-01

    Analyzing microarray data across multiple experiments has been proven advantageous. To support this kind of analysis, we are developing a software system called MAMA (Meta-Analysis of MicroArray data). MAMA utilizes a client-server architecture with a relational database on the server-side for the storage of microarray datasets collected from various resources. The client-side is an application running on the end user's computer that allows the user to manipulate microarray data and analytical results locally. MAMA implementation will integrate several analytical methods, including meta-analysis within an open-source framework offering other developers the flexibility to plug in additional statistical algorithms.

  14. PIIKA 2: an expanded, web-based platform for analysis of kinome microarray data.

    Directory of Open Access Journals (Sweden)

    Brett Trost

    Full Text Available Kinome microarrays are comprised of peptides that act as phosphorylation targets for protein kinases. This platform is growing in popularity due to its ability to measure phosphorylation-mediated cellular signaling in a high-throughput manner. While software for analyzing data from DNA microarrays has also been used for kinome arrays, differences between the two technologies and associated biologies previously led us to develop Platform for Intelligent, Integrated Kinome Analysis (PIIKA, a software tool customized for the analysis of data from kinome arrays. Here, we report the development of PIIKA 2, a significantly improved version with new features and improvements in the areas of clustering, statistical analysis, and data visualization. Among other additions to the original PIIKA, PIIKA 2 now allows the user to: evaluate statistically how well groups of samples cluster together; identify sets of peptides that have consistent phosphorylation patterns among groups of samples; perform hierarchical clustering analysis with bootstrapping; view false negative probabilities and positive and negative predictive values for t-tests between pairs of samples; easily assess experimental reproducibility; and visualize the data using volcano plots, scatterplots, and interactive three-dimensional principal component analyses. Also new in PIIKA 2 is a web-based interface, which allows users unfamiliar with command-line tools to easily provide input and download the results. Collectively, the additions and improvements described here enhance both the breadth and depth of analyses available, simplify the user interface, and make the software an even more valuable tool for the analysis of kinome microarray data. Both the web-based and stand-alone versions of PIIKA 2 can be accessed via http://saphire.usask.ca.

  15. PIIKA 2: an expanded, web-based platform for analysis of kinome microarray data.

    Science.gov (United States)

    Trost, Brett; Kindrachuk, Jason; Määttänen, Pekka; Napper, Scott; Kusalik, Anthony

    2013-01-01

    Kinome microarrays are comprised of peptides that act as phosphorylation targets for protein kinases. This platform is growing in popularity due to its ability to measure phosphorylation-mediated cellular signaling in a high-throughput manner. While software for analyzing data from DNA microarrays has also been used for kinome arrays, differences between the two technologies and associated biologies previously led us to develop Platform for Intelligent, Integrated Kinome Analysis (PIIKA), a software tool customized for the analysis of data from kinome arrays. Here, we report the development of PIIKA 2, a significantly improved version with new features and improvements in the areas of clustering, statistical analysis, and data visualization. Among other additions to the original PIIKA, PIIKA 2 now allows the user to: evaluate statistically how well groups of samples cluster together; identify sets of peptides that have consistent phosphorylation patterns among groups of samples; perform hierarchical clustering analysis with bootstrapping; view false negative probabilities and positive and negative predictive values for t-tests between pairs of samples; easily assess experimental reproducibility; and visualize the data using volcano plots, scatterplots, and interactive three-dimensional principal component analyses. Also new in PIIKA 2 is a web-based interface, which allows users unfamiliar with command-line tools to easily provide input and download the results. Collectively, the additions and improvements described here enhance both the breadth and depth of analyses available, simplify the user interface, and make the software an even more valuable tool for the analysis of kinome microarray data. Both the web-based and stand-alone versions of PIIKA 2 can be accessed via http://saphire.usask.ca.

  16. Age-Specific Gene Expression Profiles of Rhesus Monkey Ovaries Detected by Microarray Analysis

    Directory of Open Access Journals (Sweden)

    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.

  17. Evaluation of DNA microarray results in the Toxicogenomics Project (TGP) consortium in Japan.

    Science.gov (United States)

    Noriyuki, Nakatsu; Igarashi, Yoshinobu; Ono, Atsushi; Yamada, Hiroshi; Ohno, Yasuo; Urushidani, Tetsuro

    2012-01-01

    An important technology used in toxicogenomic drug discovery research is the microarray, which enables researchers to simultaneously analyze the expression of a large number of genes. To build a database and data analysis system for use in assessing the safety of drugs and drug candidates, in 2002 we conducted a 5-year collaborative study in the Toxicogenomics Project (TGP1) in Japan. Experimental data generated by such studies must be validated by different laboratories for robust and accurate analysis. For this purpose, we conducted intra- and inter-laboratory validation studies with participating companies in the second collaborative study in the Toxicogenomics Project (TGP2). Gene expression in the liver of rats treated with acetaminophen (APAP) was independently examined by the participating companies using Affymetrix GeneChip microarrays. The intra- and inter-laboratory reproducibility of the data was evaluated using hierarchical clustering analysis. The toxicogenomics results were highly reproducible, indicating that the gene expression data generated in our TGP1 project is reliable and compatible with the data generated by the participating laboratories.

  18. Use of a multi-thermal washer for DNA microarrays simplifies probe design and gives robust genotyping assays

    DEFF Research Database (Denmark)

    Petersen, J.; Poulsen, Lena; Petronis, S.

    2008-01-01

    is called a multi-thermal array washer (MTAW), and it has eight individually controlled heating zones, each of which corresponds to the location of a subarray on a slide. Allele-specific oligonucleotide probes for nine mutations in the beta-globin gene were spotted in eight identical subarrays at positions......DNA microarrays are generally operated at a single condition, which severely limits the freedom of designing probes for allele-specific hybridization assays. Here, we demonstrate a fluidic device for multi-stringency posthybridization washing of microarrays on microscope slides. This device...

  19. Factorial microarray analysis of zebra mussel (Dreissena polymorpha: Dreissenidae, Bivalvia adhesion

    Directory of Open Access Journals (Sweden)

    Faisal Mohamed

    2010-05-01

    Full Text Available Abstract Background The zebra mussel (Dreissena polymorpha has been well known for its expertise in attaching to substances under the water. Studies in past decades on this underwater adhesion focused on the adhesive protein isolated from the byssogenesis apparatus of the zebra mussel. However, the mechanism of the initiation, maintenance, and determination of the attachment process remains largely unknown. Results In this study, we used a zebra mussel cDNA microarray previously developed in our lab and a factorial analysis to identify the genes that were involved in response to the changes of four factors: temperature (Factor A, current velocity (Factor B, dissolved oxygen (Factor C, and byssogenesis status (Factor D. Twenty probes in the microarray were found to be modified by one of the factors. The transcription products of four selected genes, DPFP-BG20_A01, EGP-BG97/192_B06, EGP-BG13_G05, and NH-BG17_C09 were unique to the zebra mussel foot based on the results of quantitative reverse transcription PCR (qRT-PCR. The expression profiles of these four genes under the attachment and non-attachment were also confirmed by qRT-PCR and the result is accordant to that from microarray assay. The in situ hybridization with the RNA probes of two identified genes DPFP-BG20_A01 and EGP-BG97/192_B06 indicated that both of them were expressed by a type of exocrine gland cell located in the middle part of the zebra mussel foot. Conclusions The results of this study suggested that the changes of D. polymorpha byssogenesis status and the environmental factors can dramatically affect the expression profiles of the genes unique to the foot. It turns out that the factorial design and analysis of the microarray experiment is a reliable method to identify the influence of multiple factors on the expression profiles of the probesets in the microarray; therein it provides a powerful tool to reveal the mechanism of zebra mussel underwater attachment.

  20. Factorial microarray analysis of zebra mussel (Dreissena polymorpha: Dreissenidae, Bivalvia) adhesion.

    Science.gov (United States)

    Xu, Wei; Faisal, Mohamed

    2010-05-28

    The zebra mussel (Dreissena polymorpha) has been well known for its expertise in attaching to substances under the water. Studies in past decades on this underwater adhesion focused on the adhesive protein isolated from the byssogenesis apparatus of the zebra mussel. However, the mechanism of the initiation, maintenance, and determination of the attachment process remains largely unknown. In this study, we used a zebra mussel cDNA microarray previously developed in our lab and a factorial analysis to identify the genes that were involved in response to the changes of four factors: temperature (Factor A), current velocity (Factor B), dissolved oxygen (Factor C), and byssogenesis status (Factor D). Twenty probes in the microarray were found to be modified by one of the factors. The transcription products of four selected genes, DPFP-BG20_A01, EGP-BG97/192_B06, EGP-BG13_G05, and NH-BG17_C09 were unique to the zebra mussel foot based on the results of quantitative reverse transcription PCR (qRT-PCR). The expression profiles of these four genes under the attachment and non-attachment were also confirmed by qRT-PCR and the result is accordant to that from microarray assay. The in situ hybridization with the RNA probes of two identified genes DPFP-BG20_A01 and EGP-BG97/192_B06 indicated that both of them were expressed by a type of exocrine gland cell located in the middle part of the zebra mussel foot. The results of this study suggested that the changes of D. polymorpha byssogenesis status and the environmental factors can dramatically affect the expression profiles of the genes unique to the foot. It turns out that the factorial design and analysis of the microarray experiment is a reliable method to identify the influence of multiple factors on the expression profiles of the probesets in the microarray; therein it provides a powerful tool to reveal the mechanism of zebra mussel underwater attachment.

  1. Exon microarray analysis of human dorsolateral prefrontal cortex in alcoholism.

    Science.gov (United States)

    Manzardo, Ann M; Gunewardena, Sumedha; Wang, Kun; Butler, Merlin G

    2014-06-01

    Alcohol abuse is associated with cellular and biochemical disturbances that impact upon protein and nucleic acid synthesis, brain development, function, and behavioral responses. To further characterize the genetic influences in alcoholism and the effects of alcohol consumption on gene expression, we used a highly sensitive exon microarray to examine mRNA expression in human frontal cortex of alcoholics and control males. Messenger RNA was isolated from the dorsolateral prefrontal cortex (dlPFC; Brodmann area 9) of 7 adult alcoholic (6 males, 1 female, mean age 49 years) and 7 matched controls. Affymetrix Human Exon 1.0 ST array was performed according to standard procedures and the results analyzed at the gene level. Microarray findings were validated using quantitative reverse transcription polymerase chain reaction, and the ontology of disturbed genes characterized using Ingenuity Pathway Analysis (IPA). Decreased mRNA expression was observed for genes involved in cellular adhesion (e.g., CTNNA3, ITGA2), transport (e.g., TF, ABCA8), nervous system development (e.g., LRP2, UGT8, GLDN), and signaling (e.g., RASGRP3, LGR5) with influence over lipid and myelin synthesis (e.g., ASPA, ENPP2, KLK6). IPA identified disturbances in network functions associated with neurological disease and development including cellular assembly and organization impacting on psychological disorders. Our data in alcoholism support a reduction in expression of dlPFC mRNA for genes involved with neuronal growth, differentiation, and signaling that targets white matter of the brain. Copyright © 2014 by the Research Society on Alcoholism.

  2. A Parallel Software Pipeline for DMET Microarray Genotyping Data Analysis

    Directory of Open Access Journals (Sweden)

    Giuseppe Agapito

    2018-06-01

    Full Text Available Personalized medicine is an aspect of the P4 medicine (predictive, preventive, personalized and participatory based precisely on the customization of all medical characters of each subject. In personalized medicine, the development of medical treatments and drugs is tailored to the individual characteristics and needs of each subject, according to the study of diseases at different scales from genotype to phenotype scale. To make concrete the goal of personalized medicine, it is necessary to employ high-throughput methodologies such as Next Generation Sequencing (NGS, Genome-Wide Association Studies (GWAS, Mass Spectrometry or Microarrays, that are able to investigate a single disease from a broader perspective. A side effect of high-throughput methodologies is the massive amount of data produced for each single experiment, that poses several challenges (e.g., high execution time and required memory to bioinformatic software. Thus a main requirement of modern bioinformatic softwares, is the use of good software engineering methods and efficient programming techniques, able to face those challenges, that include the use of parallel programming and efficient and compact data structures. This paper presents the design and the experimentation of a comprehensive software pipeline, named microPipe, for the preprocessing, annotation and analysis of microarray-based Single Nucleotide Polymorphism (SNP genotyping data. A use case in pharmacogenomics is presented. The main advantages of using microPipe are: the reduction of errors that may happen when trying to make data compatible among different tools; the possibility to analyze in parallel huge datasets; the easy annotation and integration of data. microPipe is available under Creative Commons license, and is freely downloadable for academic and not-for-profit institutions.

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

    Directory of Open Access Journals (Sweden)

    Pesta David

    2003-06-01

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

  4. 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.

  5. DNA microarray analyses reveal a post-irradiation differential time-dependent gene expression profile in yeast cells exposed to X-rays and gamma-rays.

    Science.gov (United States)

    Kimura, Shinzo; Ishidou, Emi; Kurita, Sakiko; Suzuki, Yoshiteru; Shibato, Junko; Rakwal, Randeep; Iwahashi, Hitoshi

    2006-07-21

    Ionizing radiation (IR) is the most enigmatic of genotoxic stress inducers in our environment that has been around from the eons of time. IR is generally considered harmful, and has been the subject of numerous studies, mostly looking at the DNA damaging effects in cells and the repair mechanisms therein. Moreover, few studies have focused on large-scale identification of cellular responses to IR, and to this end, we describe here an initial study on the transcriptional responses of the unicellular genome model, yeast (Saccharomyces cerevisiae strain S288C), by cDNA microarray. The effect of two different IR, X-rays, and gamma (gamma)-rays, was investigated by irradiating the yeast cells cultured in YPD medium with 50 Gy doses of X- and gamma-rays, followed by resuspension of the cells in YPD for time-course experiments. The samples were collected for microarray analysis at 20, 40, and 80 min after irradiation. Microarray analysis revealed a time-course transcriptional profile of changed gene expressions. Up-regulated genes belonged to the functional categories mainly related to cell cycle and DNA processing, cell rescue defense and virulence, protein and cell fate, and metabolism (X- and gamma-rays). Similarly, for X- and gamma-rays, the down-regulated genes belonged to mostly transcription and protein synthesis, cell cycle and DNA processing, control of cellular organization, cell fate, and C-compound and carbohydrate metabolism categories, respectively. This study provides for the first time a snapshot of the genome-wide mRNA expression profiles in X- and gamma-ray post-irradiated yeast cells and comparatively interprets/discusses the changed gene functional categories as effects of these two radiations vis-à-vis their energy levels.

  6. A simple gold nanoparticle-mediated immobilization method to fabricate highly homogeneous DNA microarrays having higher capacities than those prepared by using conventional techniques

    International Nuclear Information System (INIS)

    Jung, Cheulhee; Mun, Hyo Young; Li, Taihua; Park, Hyun Gyu

    2009-01-01

    A simple, highly efficient immobilization method to fabricate DNA microarrays, that utilizes gold nanoparticles as the mediator, has been developed. The fabrication method begins with electrostatic attachment of amine-modified DNA to gold nanoparticles. The resulting gold-DNA complexes are immobilized on conventional amine or aldehyde functionalized glass slides. By employing gold nanoparticles as the immobilization mediator, implementation of this procedure yields highly homogeneous microarrays that have higher binding capacities than those produced by conventional methods. This outcome is due to the increased three-dimensional immobilization surface provided by the gold nanoparticles as well as the intrinsic effects of gold on emission properties. This novel immobilization strategy gives microarrays that produce more intense hybridization signals for the complementary DNA. Furthermore, the silver enhancement technique, made possible only in the case of immobilized gold nanoparticles on the microarrays, enables simple monitoring of the integrity of the immobilized DNA probe.

  7. Gene expression of panaxydol-treated human melanoma cells using radioactive cDNA microarrays

    Energy Technology Data Exchange (ETDEWEB)

    Cho, Joong Youn; Yu, Su Jin; Soh, Jeong Won; Kim, Meyoung Kon [College of Medicine, Korea Univ., Seoul (Korea, Republic of)

    2001-07-01

    Polyacetylenic alcohols derived from Panax ginseng have been studied to be an anticancer reagent previously. One of the Panax ginseng polyacetylenic alcohols, i.e., panaxydol, has been studied to possess an antiproliferative effect on human melanoma cell line (SK-MEL-1). In ths study, radioactive cDNA microarrays enabled an efficient approach to analyze the pattern of gene expression (3.194 genes in a total) simultaneously. The bioinformatics selection of human cDNAs, which is specifically designed for immunology, apoptosis and signal transduction, were arrayed on nylon membranes. Using with {sup 33}P labeled probes, this method provided highly sensitive gene expression profiles of our interest including apoptosis, cell proliferation, cell cycle, and signal transduction. Gene expression profiles were also classified into several categories in accordance with the duration of panaxydol treatment. Consequently, the gene profiles of our interest were significantly up (199 genes, > 2.0 of Z-ratio) or down-(196 genes, < 2.0 of Z-ratio) regulated in panaxydol-treated human melanoma cells.

  8. Gene expression of panaxydol-treated human melanoma cells using radioactive cDNA microarrays

    International Nuclear Information System (INIS)

    Cho, Joong Youn; Yu, Su Jin; Soh, Jeong Won; Kim, Meyoung Kon

    2001-01-01

    Polyacetylenic alcohols derived from Panax ginseng have been studied to be an anticancer reagent previously. One of the Panax ginseng polyacetylenic alcohols, i.e., panaxydol, has been studied to possess an antiproliferative effect on human melanoma cell line (SK-MEL-1). In ths study, radioactive cDNA microarrays enabled an efficient approach to analyze the pattern of gene expression (3.194 genes in a total) simultaneously. The bioinformatics selection of human cDNAs, which is specifically designed for immunology, apoptosis and signal transduction, were arrayed on nylon membranes. Using with 33 P labeled probes, this method provided highly sensitive gene expression profiles of our interest including apoptosis, cell proliferation, cell cycle, and signal transduction. Gene expression profiles were also classified into several categories in accordance with the duration of panaxydol treatment. Consequently, the gene profiles of our interest were significantly up (199 genes, > 2.0 of Z-ratio) or down-(196 genes, < 2.0 of Z-ratio) regulated in panaxydol-treated human melanoma cells

  9. Variance estimation in the analysis of microarray data

    KAUST Repository

    Wang, Yuedong; Ma, Yanyuan; Carroll, Raymond J.

    2009-01-01

    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

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

    Directory of Open Access Journals (Sweden)

    Roshan Ramanathan

    2011-05-01

    Full Text Available 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.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.A new DNA microarray tool for the examination of S. stercoralis biology has been developed and provides new and valuable insights regarding differences between infective and

  11. Addressable droplet microarrays for single cell protein analysis.

    Science.gov (United States)

    Salehi-Reyhani, Ali; Burgin, Edward; Ces, Oscar; Willison, Keith R; Klug, David R

    2014-11-07

    Addressable droplet microarrays are potentially attractive as a way to achieve miniaturised, reduced volume, high sensitivity analyses without the need to fabricate microfluidic devices or small volume chambers. We report a practical method for producing oil-encapsulated addressable droplet microarrays which can be used for such analyses. To demonstrate their utility, we undertake a series of single cell analyses, to determine the variation in copy number of p53 proteins in cells of a human cancer cell line.

  12. Characterization of methicillin-resistant Staphylococcus aureus isolated from healthy turkeys and broilers using DNA microarrays

    Directory of Open Access Journals (Sweden)

    Hosny El-Adawy

    2016-12-01

    Full Text Available Methicillin-resistant Staphylococcus aureus (MRSA is a major human health problem and recently, domestic animals, in particular pigs and poultry are discussed as carriers and possible reservoirs of MRSA. Twenty seven S. aureus isolates from five turkey farms (n=18 and two broiler farms (n=9 were obtained by culturing of choana and skin swabs from apparently healthy birds, identified by Taqman-based real-time duplex nuc-mecA-PCR and characterized by spa typing as well as by a DNA microarray based assay which covered, amongst others, a considerable number of antibiotic resistance genes, species controls and virulence markers. The antimicrobial susceptibility profiles were tested by agar diffusion assays and genotypically confirmed by the microarray. Five different spa types (3 in turkeys and 2 in broilers were detected. The majority of MRSA isolates (24/27 belonged to clonal complex 398-MRSA-V. The most frequently occurring spa types were accordingly t011, t034 and t899. A single CC5-MRSA-III isolated from turkey and CC398-MRSA with an unidentified/truncated SCCmec element in turkey and broiler were additionally detected. The phenotypic antimicrobial resistance profiles of S. aureus isolated from both turkeys and broilers against 14 different antimicrobials showed that all isolates were resistant to ampicillin, cefoxitin, oxacillin, doxycycline and tetracycline. Moreover, all S. aureus isolated from broilers were resistant to erythromycin and azithromycin. All isolates were susceptible to gentamicin, chloramphenicol, sulphonamides and fusidic acid. The resistance rate against ciprofloxacin was 55.6% in broiler isolates and 42.1% in turkey isolates. All tetracycline resistant isolates possessed genes tetK/M. All erythromycin-resistant broiler isolates carried ermA. Only one broiler isolate (11.1% carried genes ermA, ermB and ermC, while 55.6% of turkey isolates possessed ermA and ermB genes.Neither PVL genes (lukF/S-PV, animal-associated leukocidin

  13. Microarray technology for major chemical contaminants analysis in food: current status and prospects.

    Science.gov (United States)

    Zhang, Zhaowei; Li, Peiwu; Hu, Xiaofeng; Zhang, Qi; Ding, Xiaoxia; Zhang, Wen

    2012-01-01

    Chemical contaminants in food have caused serious health issues in both humans and animals. Microarray technology is an advanced technique suitable for the analysis of chemical contaminates. In particular, immuno-microarray approach is one of the most promising methods for chemical contaminants analysis. The use of microarrays for the analysis of chemical contaminants is the subject of this review. Fabrication strategies and detection methods for chemical contaminants are discussed in detail. Application to the analysis of mycotoxins, biotoxins, pesticide residues, and pharmaceutical residues is also described. Finally, future challenges and opportunities are discussed.

  14. 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.

  15. Construction and application of a bovine immune-endocrine cDNA microarray.

    Science.gov (United States)

    Tao, Wenjing; Mallard, Bonnie; Karrow, Niel; Bridle, Byram

    2004-09-01

    A variety of commercial DNA arrays specific for humans and rodents are widely available; however, microarrays containing well-characterized genes to study pathway-specific gene expression are not as accessible for domestic animals, such as cattle, sheep and pigs. Therefore, a small-scale application-targeted bovine immune-endocrine cDNA array was developed to evaluate genetic pathways involved in the immune-endocrine axis of cattle during periods of altered homeostasis provoked by physiological or environmental stressors, such as infection, vaccination or disease. For this purpose, 167 cDNA sequences corresponding to immune, endocrine and inflammatory response genes were collected and categorized. Positive controls included 5 housekeeping genes (glyceraldehydes-3-phosphate dehydrogenase, hypoxanthine phosphoribosyltransferase, ribosomal protein L19, beta-actin, beta2-microglobulin) and bovine genomic DNA. Negative controls were a bacterial gene (Rhodococcus equi 17-kDa virulence-associated protein) and a partial sequence of the plasmid pACYC177. In addition, RNA extracted from un-stimulated, as well as superantigen (Staphylococcus aureus enterotoxin-A, S. aureus Cowan Pansorbin Cells) and mitogen-stimulated (LPS, ConA) bovine blood leukocytes was mixed, reverse transcribed and PCR amplified using gene-specific primers. The endocrine-associated genes were amplified from cDNA derived from un-stimulated bovine hypothalamus, pituitary, adrenal and thyroid gland tissues. The array was constructed in 4 repeating grids of 180 duplicated spots by coupling the PCR amplified 213-630 bp gene fragments onto poly-l-lysine coated glass slides. The bovine immune-endocrine arrays were standardized and preliminary gene expression profiles generated using Cy3 and Cy5 labelled cDNA from un-stimulated and ConA (5 microg/ml) stimulated PBMC of 4 healthy Holstein cows (2-4 replicate arrays/cow) in a time course study. Mononuclear cell-derived cytokine and chemokine (IL-2, IL-1alpha

  16. Microarray-based method for the parallel analysis of genotypes and expression profiles of wood-forming tissues in Eucalyptus grandis

    CSIR Research Space (South Africa)

    Barros, E

    2009-05-01

    Full Text Available of Eucalyptus grandis planting stock that exhibit preferred wood qualities is thus a priority of the South African forestry industry. The researchers used microarray-based DNA-amplified fragment length polymorphism (AFLP) analysis in combination with expression...

  17. Elucidating the transcription cycle of the UV-inducible hyperthermophilic archaeal virus SSV1 by DNA microarrays

    International Nuclear Information System (INIS)

    Froels, Sabrina; Gordon, Paul M.K.; Panlilio, Mayi Arcellana; Schleper, Christa; Sensen, Christoph W.

    2007-01-01

    The spindle-shaped Sulfolobus virus SSV1 was the first of a series of unusual and uniquely shaped viruses isolated from hyperthermophilic Archaea. Using whole-genome microarrays we show here that the circular 15.5 kb DNA genome of SSV1 exhibits a chronological regulation of its transcription upon UV irradiation, reminiscent to the life cycles of bacteriophages and eukaryotic viruses. The transcriptional cycle starts with a small UV-specific transcript and continues with early transcripts on both its flanks. The late transcripts appear after the onset of viral replication and are extended to their full lengths towards the end of the approximately 8.5 h cycle. While we detected only small differences in genome-wide analysis of the host Sulfolobus solfataricus comparing infected versus uninfected strains, we found a marked difference with respect to the strength and speed of the general UV response of the host. Models for the regulation of the virus cycle, and putative functions of genes in SSV1 are presented

  18. ArrayMining: a modular web-application for microarray analysis combining ensemble and consensus methods with cross-study normalization

    Directory of Open Access Journals (Sweden)

    Krasnogor Natalio

    2009-10-01

    Full Text Available Abstract Background Statistical analysis of DNA microarray data provides a valuable diagnostic tool for the investigation of genetic components of diseases. To take advantage of the multitude of available data sets and analysis methods, it is desirable to combine both different algorithms and data from different studies. Applying ensemble learning, consensus clustering and cross-study normalization methods for this purpose in an almost fully automated process and linking different analysis modules together under a single interface would simplify many microarray analysis tasks. Results We present ArrayMining.net, a web-application for microarray analysis that provides easy access to a wide choice of feature selection, clustering, prediction, gene set analysis and cross-study normalization methods. In contrast to other microarray-related web-tools, multiple algorithms and data sets for an analysis task can be combined using ensemble feature selection, ensemble prediction, consensus clustering and cross-platform data integration. By interlinking different analysis tools in a modular fashion, new exploratory routes become available, e.g. ensemble sample classification using features obtained from a gene set analysis and data from multiple studies. The analysis is further simplified by automatic parameter selection mechanisms and linkage to web tools and databases for functional annotation and literature mining. Conclusion ArrayMining.net is a free web-application for microarray analysis combining a broad choice of algorithms based on ensemble and consensus methods, using automatic parameter selection and integration with annotation databases.

  19. Microarray analysis identified Puccinia striiformis f. sp. tritici genes involved in infection and sporulation.

    Science.gov (United States)

    Puccinia striiformis f. sp. tritici (Pst) causes stripe rust, one of the most important diseases of wheat worldwide. To identify Pst genes involved in infection and sporulation, a custom oligonucleotide Genechip was made using sequences of 442 genes selected from Pst cDNA libraries. Microarray analy...

  20. Microarray Analysis of Late Response to Boron Toxicity in Barley (Hordeum vulgare L.) Leaves

    NARCIS (Netherlands)

    Oz, M.T.; Yilmaz, R.; Eyidogan, F.; Graaff, de L.H.; Yucel, M.; Oktem, H.A.

    2009-01-01

    DNA microarrays, being high-density and high-throughput, allow quantitative analyses of thousands of genes and their expression patterns in parallel. In this study, Barley1 GereChip was used to investigate transcriptome changes associated with boron (B) toxicity in a sensitive barley cultivar

  1. DNA Microarrays: a Powerful Genomic Tool for Biomedical and Clinical Research

    OpenAIRE

    Trevino, Victor; Falciani, Francesco; Barrera-Saldaña, Hugo A

    2007-01-01

    Among the many benefits of the Human Genome Project are new and powerful tools such as the genome-wide hybridization devices referred to as microarrays. Initially designed to measure gene transcriptional levels, microarray technologies are now used for comparing other genome features among individuals and their tissues and cells. Results provide valuable information on disease subcategories, disease prognosis, and treatment outcome. Likewise, they reveal differences in genetic makeup, regulat...

  2. Network Expansion and Pathway Enrichment Analysis towards Biologically Significant Findings from Microarrays

    Directory of Open Access Journals (Sweden)

    Wu Xiaogang

    2012-06-01

    Full Text Available In many cases, crucial genes show relatively slight changes between groups of samples (e.g. normal vs. disease, and many genes selected from microarray differential analysis by measuring the expression level statistically are also poorly annotated and lack of biological significance. In this paper, we present an innovative approach - network expansion and pathway enrichment analysis (NEPEA for integrative microarray analysis. We assume that organized knowledge will help microarray data analysis in significant ways, and the organized knowledge could be represented as molecular interaction networks or biological pathways. Based on this hypothesis, we develop the NEPEA framework based on network expansion from the human annotated and predicted protein interaction (HAPPI database, and pathway enrichment from the human pathway database (HPD. We use a recently-published microarray dataset (GSE24215 related to insulin resistance and type 2 diabetes (T2D as case study, since this study provided a thorough experimental validation for both genes and pathways identified computationally from classical microarray analysis and pathway analysis. We perform our NEPEA analysis for this dataset based on the results from the classical microarray analysis to identify biologically significant genes and pathways. Our findings are not only consistent with the original findings mostly, but also obtained more supports from other literatures.

  3. Clonal diversity analysis using SNP microarray: a new prognostic tool for chronic lymphocytic leukemia.

    Science.gov (United States)

    Zhang, Linsheng; Znoyko, Iya; Costa, Luciano J; Conlin, Laura K; Daber, Robert D; Self, Sally E; Wolff, Daynna J

    2011-12-01

    Chronic lymphocytic leukemia (CLL) is a clinically heterogeneous disease. The methods currently used for monitoring CLL and determining conditions for treatment are limited in their ability to predict disease progression, patient survival, and response to therapy. Although clonal diversity and the acquisition of new chromosomal abnormalities during the disease course (clonal evolution) have been associated with disease progression, their prognostic potential has been underappreciated because cytogenetic and fluorescence in situ hybridization (FISH) studies have a restricted ability to detect genomic abnormalities and clonal evolution. We hypothesized that whole genome analysis using high resolution single nucleotide polymorphism (SNP) microarrays would be useful to detect diversity and infer clonal evolution to offer prognostic information. In this study, we used the Infinium Omni1 BeadChip (Illumina, San Diego, CA) array for the analysis of genetic variation and percent mosaicism in 25 non-selected CLL patients to explore the prognostic value of the assessment of clonal diversity in patients with CLL. We calculated the percentage of mosaicism for each abnormality by applying a mathematical algorithm to the genotype frequency data and by manual determination using the Simulated DNA Copy Number (SiDCoN) tool, which was developed from a computer model of mosaicism. At least one genetic abnormality was identified in each case, and the SNP data was 98% concordant with FISH results. Clonal diversity, defined as the presence of two or more genetic abnormalities with differing percentages of mosaicism, was observed in 12 patients (48%), and the diversity correlated with the disease stage. Clonal diversity was present in most cases of advanced disease (Rai stages III and IV) or those with previous treatment, whereas 9 of 13 patients without detected clonal diversity were asymptomatic or clinically stable. In conclusion, SNP microarray studies with simultaneous evaluation

  4. An Improved Fuzzy Based Missing Value Estimation in DNA Microarray Validated by Gene Ranking

    Directory of Open Access Journals (Sweden)

    Sujay Saha

    2016-01-01

    Full Text Available Most of the gene expression data analysis algorithms require the entire gene expression matrix without any missing values. Hence, it is necessary to devise methods which would impute missing data values accurately. There exist a number of imputation algorithms to estimate those missing values. This work starts with a microarray dataset containing multiple missing values. We first apply the modified version of the fuzzy theory based existing method LRFDVImpute to impute multiple missing values of time series gene expression data and then validate the result of imputation by genetic algorithm (GA based gene ranking methodology along with some regular statistical validation techniques, like RMSE method. Gene ranking, as far as our knowledge, has not been used yet to validate the result of missing value estimation. Firstly, the proposed method has been tested on the very popular Spellman dataset and results show that error margins have been drastically reduced compared to some previous works, which indirectly validates the statistical significance of the proposed method. Then it has been applied on four other 2-class benchmark datasets, like Colorectal Cancer tumours dataset (GDS4382, Breast Cancer dataset (GSE349-350, Prostate Cancer dataset, and DLBCL-FL (Leukaemia for both missing value estimation and ranking the genes, and the results show that the proposed method can reach 100% classification accuracy with very few dominant genes, which indirectly validates the biological significance of the proposed method.

  5. Assessment of centrifugation using for accelerated immunological microarray analysis for blood cells investigation

    Directory of Open Access Journals (Sweden)

    A. V. Shishkin

    2011-01-01

    Full Text Available Phase of incubation microarray with cell suspension is prolonged when cells are investigated. It takes from 20 to 60 min if cell sedimentation on the surface of microarray is the result of gravity . Decrease of this stage duration is possible due to centrifugation. In th is article influence of centrifugation on results of analysis is considered. Changes of morphological description of cells are estimated when they a re precipitatedwith different acceleration. Also availability of centrifugation using when it is necessary to obtain the high density of cell binding in test regions of microarray if cells concentration in sample is small is demonstrated.

  6. Analysis of human HPRT- deletion mutants by the microarray-CGH (comparative genomic hybridization)

    International Nuclear Information System (INIS)

    Kodaira, M.; Sasaki, K.; Tagawa, H.; Omine, H.; Kushiro, J.; Takahashi, N.; Katayama, H.

    2003-01-01

    We are trying to evaluate genetic effects of radiation on human using mutation frequency as an indicator. For the efficient detection of mutations, it is important to understand the mechanism and the characteristics of radiation-induced mutations. We have started the analysis of hypoxanthine-guanine phosphoribosyl transferase (HPRT) mutants induced by X-ray in order to clarify the deletion size and the mutation-distribution. We analyzed 39 human X-ray induced HPRT-deletion mutants by using the microarray-CGH. The array for this analysis contains 57 BAC clones covering as much as possible of the 4Mb of the 5' side and 10Mb of the 3' side of the HPRT gene based on the NCBI genome database. DNA from parent strain and each HPRT-mutant strain are labeled with Cy5 and Cy3 respectively, and were mixed and hybridized on the array. Fluorescent intensity ratio of the obtained spots was analyzed using software we developed to identify clones corresponding to the deletion region. The deletion in these strains ranged up to 3.5 Mb on the 5' side and 6 Mb on the 3' side of the HPRT gene. Deletions in 13 strains ended around BAC clones located at about 3 Mb on the 5' side. On the 3' side, deletions extended up to the specific clones located at 1.5 Mb in 11 strains. The mutations seem to be complex on the 3' end of deletion; some accompanied duplications with deletions and others could not be explained by one mutation event. We need to confirm these results, taking into account the experimental reproducibility and the accuracy of the published genetic map. The results of the research using the microarray-CGH help us to search the regions where deletions are easily induced and to identify the factors affecting the range of deletions

  7. Investigation of cellular signalling responses to non-ionising radiation in melanocytes by microarray analysis

    International Nuclear Information System (INIS)

    Boyle, G.M.; Pedley, J.; Martyn, A.C.; Fraser, L.M.; Banducci, K.J.; Parsons, P.G.; Breit, S.N.

    2003-01-01

    Melanoma is a highly aggressive cancer resulting from the abnormal proliferation and spread of specialised pigment cells in the skin, known as melanocytes. Extensive epidemiological and molecular evidence suggests that a major risk factor for melanoma formation is exposure to non-ionising radiation in the form of solar ultra-violet (UV) light. However, the exact role of solar UV in the development of melanoma is unclear. To elucidate the molecular events that occur in melanocytes following solar UV exposure and determine how they lead to melanoma development, cDNA microarray analysis was used to analyse the gene expression profile of normal melanocytes, melanocytes exposed to simulated solar UV and melanoma cells. The development of cDNA microarray technology has allowed gene expression profiling at the mRNA level to be conducted for many thousands of genes simultaneously by hybridising an array of known sequences with labelled cDNA reverse transcribed form the sample RNA. Gene expression analysis was performed for over 13,000 genes. More than 500 genes were identified as differentially expressed in melanocytes following a single UV exposure, although overall there was a general suppression of transcription. Genes that were up-regulated included oncogenes and cytoskeletal genes; in contrast, genes encoding protein tyrosine kinases and apoptosis effectors were down-regulated. Many of the genes identified as being differentially expressed represent novel UV-regulated targets. Repeated exposure to solar UV resulted in the elevation in expression of a novel member of the transforming growth factor-b (TGF-b) superfamily, the Macrophage Inhibitory Cytokine-1 (MIC-1). Our results have shown that MIC-1 is up-regulated by solar UV in melanocytes, and is highly expressed (>3 fold) in a number of metastatic melanoma cell lines (31/61) in comparison to primary melanocytes. Furthermore functional, dimerised MIC-1 was found to be secreted by melanocytes, and secreted levels were

  8. 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

  9. 16S rRNA based microarray analysis of ten periodontal bacteria in patients with different forms of periodontitis.

    Science.gov (United States)

    Topcuoglu, Nursen; Kulekci, Guven

    2015-10-01

    DNA microarray analysis is a computer based technology, that a reverse capture, which targets 10 periodontal bacteria (ParoCheck) is available for rapid semi-quantitative determination. The aim of this three-year retrospective study was to display the microarray analysis results for the subgingival biofilm samples taken from patient cases diagnosed with different forms of periodontitis. A total of 84 patients with generalized aggressive periodontitis (GAP,n:29), generalized chronic periodontitis (GCP, n:25), peri-implantitis (PI,n:14), localized aggressive periodontitis (LAP,n:8) and refractory chronic periodontitis (RP,n:8) were consecutively selected from the archives of the Oral Microbiological Diagnostic Laboratory. The subgingival biofilm samples were analyzed by the microarray-based identification of 10 selected species. All the tested species were detected in the samples. The red complex bacteria were the most prevalent with very high levels in all groups. Fusobacterium nucleatum was detected in all samples at high levels. The green and blue complex bacteria were less prevalent compared with red and orange complex, except Aggregatibacter actinomycetemcomitas was detected in all LAP group. Positive correlations were found within all the red complex bacteria and between red and orange complex bacteria especially in GCP and GAP groups. Parocheck enables to monitoring of periodontal pathogens in all forms of periodontal disease and can be alternative to other guiding and reliable microbiologic tests. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. 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.

  11. 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.

  12. 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.

  13. 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...... in cell development. Another part of this work focused in the development of a novel methodology for the discovery of unknown algal polysaccharides and characterization of carbohydrate binding proteins. Based on the coevolution between alga and marine saprophytic microorganisms, which use the algal...

  14. Prediction of Pectin Yield and Quality by FTIR and Carbohydrate Microarray Analysis

    DEFF Research Database (Denmark)

    Baum, Andreas; Dominiak, Malgorzata Maria; Vidal-Melgosa, Silvia

    2017-01-01

    and carbohydrate microarray analysis were performed directly on the crude lime peel extracts during the time course of the extractions. Multivariate analysis of the data was carried out to predict final pectin yields. Fourier transform infrared spectroscopy (FTIR) was found applicable for determining the optimal...... extraction time for the enzymatic and acidic extraction processes, respectively. The combined results of FTIR and carbohydrate microarray analysis suggested major differences in the crude pectin extracts obtained by enzymatic and acid extraction, respectively. Enzymatically extracted pectin, thus, showed......, and that FTIR and carbohydrate microarray analysis have potential to be developed into online process analysis tools for prediction of pectin extraction yields and pectin features from measurements on crude pectin extracts....

  15. 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.

  16. Microarray analysis reveals genetic pathways modulated by tipifarnib in acute myeloid leukemia

    International Nuclear Information System (INIS)

    Raponi, Mitch; Belly, Robert T; Karp, Judith E; Lancet, Jeffrey E; Atkins, David; Wang, Yixin

    2004-01-01

    Farnesyl protein transferase inhibitors (FTIs) were originally developed to inhibit oncogenic ras, however it is now clear that there are several other potential targets for this drug class. The FTI tipifarnib (ZARNESTRA™, R115777) has recently demonstrated clinical responses in adults with refractory and relapsed acute leukemias. This study was conducted to identify genetic markers and pathways that are regulated by tipifarnib in acute myeloid leukemia (AML). Tipifarnib-mediated gene expression changes in 3 AML cell lines and bone marrow samples from two patients with AML were analyzed on a cDNA microarray containing approximately 7000 human genes. Pathways associated with these expression changes were identified using the Ingenuity Pathway Analysis tool. The expression analysis identified a common set of genes that were regulated by tipifarnib in three leukemic cell lines and in leukemic blast cells isolated from two patients who had been treated with tipifarnib. Association of modulated genes with biological functional groups identified several pathways affected by tipifarnib including cell signaling, cytoskeletal organization, immunity, and apoptosis. Gene expression changes were verified in a subset of genes using real time RT-PCR. Additionally, regulation of apoptotic genes was found to correlate with increased Annexin V staining in the THP-1 cell line but not in the HL-60 cell line. The genetic networks derived from these studies illuminate some of the biological pathways affected by FTI treatment while providing a proof of principle for identifying candidate genes that might be used as surrogate biomarkers of drug activity

  17. 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.

  18. 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

  19. 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.

  20. Gene expression patterns during the larval development of European sea bass (dicentrarchus labrax) by microarray analysis.

    Science.gov (United States)

    Darias, M J; Zambonino-Infante, J L; Hugot, K; Cahu, C L; Mazurais, D

    2008-01-01

    During the larval period, marine teleosts undergo very fast growth and dramatic changes in morphology, metabolism, and behavior to accomplish their metamorphosis into juvenile fish. Regulation of gene expression is widely thought to be a key mechanism underlying the management of the biological processes required for harmonious development over this phase of life. To provide an overall analysis of gene expression in the whole body during sea bass larval development, we monitored the expression of 6,626 distinct genes at 10 different points in time between 7 and 43 days post-hatching (dph) by using heterologous hybridization of a rainbow trout cDNA microarray. The differentially expressed genes (n = 485) could be grouped into two categories: genes that were generally up-expressed early, between 7 and 23 dph, and genes up-expressed between 25 and 43 dph. Interestingly, among the genes regulated during the larval period, those related to organogenesis, energy pathways, biosynthesis, and digestion were over-represented compared with total set of analyzed genes. We discuss the quantitative regulation of whole-body contents of these specific transcripts with regard to the ontogenesis and maturation of essential functions that take place over larval development. Our study is the first utilization of a transcriptomic approach in sea bass and reveals dynamic changes in gene expression patterns in relation to marine finfish larval development.

  1. 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.

  2. 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.

  3. Extended analysis of benchmark datasets for Agilent two-color microarrays

    Directory of Open Access Journals (Sweden)

    Kerr Kathleen F

    2007-10-01

    Full Text Available Abstract Background As part of its broad and ambitious mission, the MicroArray Quality Control (MAQC project reported the results of experiments using External RNA Controls (ERCs on five microarray platforms. For most platforms, several different methods of data processing were considered. However, there was no similar consideration of different methods for processing the data from the Agilent two-color platform. While this omission is understandable given the scale of the project, it can create the false impression that there is consensus about the best way to process Agilent two-color data. It is also important to consider whether ERCs are representative of all the probes on a microarray. Results A comparison of different methods of processing Agilent two-color data shows substantial differences among methods for low-intensity genes. The sensitivity and specificity for detecting differentially expressed genes varies substantially for different methods. Analysis also reveals that the ERCs in the MAQC data only span the upper half of the intensity range, and therefore cannot be representative of all genes on the microarray. Conclusion Although ERCs demonstrate good agreement between observed and expected log-ratios on the Agilent two-color platform, such an analysis is incomplete. Simple loess normalization outperformed data processing with Agilent's Feature Extraction software for accurate identification of differentially expressed genes. Results from studies using ERCs should not be over-generalized when ERCs are not representative of all probes on a microarray.

  4. Support vector machine and principal component analysis for microarray data classification

    Science.gov (United States)

    Astuti, Widi; Adiwijaya

    2018-03-01

    Cancer is a leading cause of death worldwide although a significant proportion of it can be cured if it is detected early. In recent decades, technology called microarray takes an important role in the diagnosis of cancer. By using data mining technique, microarray data classification can be performed to improve the accuracy of cancer diagnosis compared to traditional techniques. The characteristic of microarray data is small sample but it has huge dimension. Since that, there is a challenge for researcher to provide solutions for microarray data classification with high performance in both accuracy and running time. This research proposed the usage of Principal Component Analysis (PCA) as a dimension reduction method along with Support Vector Method (SVM) optimized by kernel functions as a classifier for microarray data classification. The proposed scheme was applied on seven data sets using 5-fold cross validation and then evaluation and analysis conducted on term of both accuracy and running time. The result showed that the scheme can obtained 100% accuracy for Ovarian and Lung Cancer data when Linear and Cubic kernel functions are used. In term of running time, PCA greatly reduced the running time for every data sets.

  5. Prevalence, identification by a DNA microarray-based assay of human and food isolates Listeria spp. from Tunisia.

    Science.gov (United States)

    Hmaïed, F; Helel, S; Le Berre, V; François, J-M; Leclercq, A; Lecuit, M; Smaoui, H; Kechrid, A; Boudabous, A; Barkallah, I

    2014-02-01

    We aimed at evaluating the prevalence of Listeria species isolated from food samples and characterizing food and human cases isolates. Between 2005 and 2007, one hundred food samples collected in the markets of Tunis were analysed in our study. Five strains of Listeria monocytogenes responsible for human listeriosis isolated in hospital of Tunis were included. Multiplex PCR serogrouping and pulsed field gel electrophoresis (PFGE) applying the enzyme AscI and ApaI were used for the characterization of isolates of L. monocytogenes. We have developed a rapid microarray-based assay to a reliable discrimination of species within the Listeria genus. The prevalence of Listeria spp. in food samples was estimated at 14% by using classical biochemical identification. Two samples were assigned to L. monocytogenes and 12 to L. innocua. DNA microarray allowed unambiguous identification of Listeria species. Our results obtained by microarray-based assay were in accordance with the biochemical identification. The two food L. monocytogenes isolates were assigned to the PCR serogroup IIa (serovar 1/2a). Whereas human L. monocytogenes isolates were of PCR serogroup IVb, (serovars 4b). These isolates present a high similarity in PFGE. Food L. monocytogenes isolates were classified into two different pulsotypes. These pulsotypes were different from that of the five strains responsible for the human cases. We confirmed the presence of Listeria spp. in variety of food samples in Tunis. Increased food and clinical surveillance must be taken into consideration in Tunisia to identify putative infections sources. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

  6. Clinical relevance of DNA microarray analyses using archival formalin-fixed paraffin-embedded breast cancer specimens

    International Nuclear Information System (INIS)

    Sadi, Al Muktafi; Wang, Dong-Yu; Youngson, Bruce J; Miller, Naomi; Boerner, Scott; Done, Susan J; Leong, Wey L

    2011-01-01

    The ability of gene profiling to predict treatment response and prognosis in breast cancers has been demonstrated in many studies using DNA microarray analyses on RNA from fresh frozen tumor specimens. In certain clinical and research situations, performing such analyses on archival formalin fixed paraffin-embedded (FFPE) surgical specimens would be advantageous as large libraries of such specimens with long-term follow-up data are widely available. However, FFPE tissue processing can cause fragmentation and chemical modifications of the RNA. A number of recent technical advances have been reported to overcome these issues. Our current study evaluates whether or not the technology is ready for clinical applications. A modified RNA extraction method and a recent DNA microarray technique, cDNA-mediated annealing, selection, extension and ligation (DASL, Illumina Inc) were evaluated. The gene profiles generated from FFPE specimens were compared to those obtained from paired fresh fine needle aspiration biopsies (FNAB) of 25 breast cancers of different clinical subtypes (based on ER and Her2/neu status). Selected RNA levels were validated using RT-qPCR, and two public databases were used to demonstrate the prognostic significance of the gene profiles generated from FFPE specimens. Compared to FNAB, RNA isolated from FFPE samples was relatively more degraded, nonetheless, over 80% of the RNA samples were deemed suitable for subsequent DASL assay. Despite a higher noise level, a set of genes from FFPE specimens correlated very well with the gene profiles obtained from FNAB, and could differentiate breast cancer subtypes. Expression levels of these genes were validated using RT-qPCR. Finally, for the first time we correlated gene expression profiles from FFPE samples to survival using two independent microarray databases. Specifically, over-expression of ANLN and KIF2C, and under-expression of MAPT strongly correlated with poor outcomes in breast cancer patients. We

  7. Genome-Wide Screening of Genes Showing Altered Expression in Liver Metastases of Human Colorectal Cancers by cDNA Microarray

    Directory of Open Access Journals (Sweden)

    Rempei Yanagawa

    2001-01-01

    Full Text Available In spite of intensive and increasingly successful attempts to determine the multiple steps involved in colorectal carcinogenesis, the mechanisms responsible for metastasis of colorectal tumors to the liver remain to be clarified. To identify genes that are candidates for involvement in the metastatic process, we analyzed genome-wide expression profiles of 10 primary colorectal cancers and their corresponding metastatic lesions by means of a cDNA microarray consisting of 9121 human genes. This analysis identified 40 genes whose expression was commonly upregulated in metastatic lesions, and 7 that were commonly downregulated. The upregulated genes encoded proteins involved in cell adhesion, or remodeling of the actin cytoskeleton. Investigation of the functions of more of the altered genes should improve our understanding of metastasis and may identify diagnostic markers and/or novel molecular targets for prevention or therapy of metastatic lesions.

  8. 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.

  9. Identifying molecular subtypes in human colon cancer using gene expression and DNA methylation microarray data.

    Science.gov (United States)

    Ren, Zhonglu; Wang, Wenhui; Li, Jinming

    2016-02-01

    Identifying colon cancer subtypes based on molecular signatures may allow for a more rational, patient-specific approach to therapy in the future. Classifications using gene expression data have been attempted before with little concordance between the different studies carried out. In this study we aimed to uncover subtypes of colon cancer that have distinct biological characteristics and identify a set of novel biomarkers which could best reflect the clinical and/or biological characteristics of each subtype. Clustering analysis and discriminant analysis were utilized to discover the subtypes in two different molecular levels on 153 colon cancer samples from The Cancer Genome Atlas (TCGA) Data Portal. At gene expression level, we identified two major subtypes, ECL1 (expression cluster 1) and ECL2 (expression cluster 2) and a list of signature genes. Due to the heterogeneity of colon cancer, the subtype ECL1 can be further subdivided into three nested subclasses, and HOTAIR were found upregulated in subclass 2. At DNA methylation level, we uncovered three major subtypes, MCL1 (methylation cluster 1), MCL2 (methylation cluster 2) and MCL3 (methylation cluster 3). We found only three subtypes of CpG island methylator phenotype (CIMP) in colon cancer instead of the four subtypes in the previous reports, and we found no sufficient evidence to subdivide MCL3 into two distinct subgroups.

  10. Microarray analysis in clinical oncology: pre-clinical optimization using needle core biopsies from xenograft tumors

    International Nuclear Information System (INIS)

    Goley, Elizabeth M; Anderson, Soni J; Ménard, Cynthia; Chuang, Eric; Lü, Xing; Tofilon, Philip J; Camphausen, Kevin

    2004-01-01

    DNA microarray profiling performed on clinical tissue specimens can potentially provide significant information regarding human cancer biology. Biopsy cores, the typical source of human tumor tissue, however, generally provide very small amounts of RNA (0.3–15 μg). RNA amplification is a common method used to increase the amount of material available for hybridization experiments. Using human xenograft tissue, we sought to address the following three questions: 1) is amplified RNA representative of the original RNA profile? 2) what is the minimum amount of total RNA required to perform a representative amplification? 3) are the direct and indirect methods of labeling the hybridization probe equivalent? Total RNA was extracted from human xenograft tissue and amplified using a linear amplification process. RNA was labeled and hybridized, and the resulting images yielded data that was extracted into two categories using the mAdb system: 'all genes' and 'outliers'. Scatter plots were generated for each slide and Pearson Coefficients of correlation were obtained. Results show that the amplification of 5 μg of total RNA yields a Pearson Correlation Coefficient of 0.752 (N = 6,987 genes) between the amplified and total RNA samples. We subsequently determined that amplification of 0.5 μg of total RNA generated a similar Pearson Correlation Coefficient as compared to the corresponding original RNA sample. Similarly, sixty-nine percent of total RNA outliers were detected with 5 μg of amplified starting RNA, and 55% of outliers were detected with 0.5 μg of starting RNA. However, amplification of 0.05 μg of starting RNA resulted in a loss of fidelity (Pearson Coefficient 0.669 between amplified and original samples, 44% outlier concordance). In these studies the direct or indirect methods of probe labeling yielded similar results. Finally, we examined whether RNA obtained from needle core biopsies of human tumor xenografts, amplified and indirectly

  11. ATMAD: robust image analysis for Automatic Tissue MicroArray De-arraying.

    Science.gov (United States)

    Nguyen, Hoai Nam; Paveau, Vincent; Cauchois, Cyril; Kervrann, Charles

    2018-04-19

    Over the last two decades, an innovative technology called Tissue Microarray (TMA), which combines multi-tissue and DNA microarray concepts, has been widely used in the field of histology. It consists of a collection of several (up to 1000 or more) tissue samples that are assembled onto a single support - typically a glass slide - according to a design grid (array) layout, in order to allow multiplex analysis by treating numerous samples under identical and standardized conditions. However, during the TMA manufacturing process, the sample positions can be highly distorted from the design grid due to the imprecision when assembling tissue samples and the deformation of the embedding waxes. Consequently, these distortions may lead to severe errors of (histological) assay results when the sample identities are mismatched between the design and its manufactured output. The development of a robust method for de-arraying TMA, which localizes and matches TMA samples with their design grid, is therefore crucial to overcome the bottleneck of this prominent technology. In this paper, we propose an Automatic, fast and robust TMA De-arraying (ATMAD) approach dedicated to images acquired with brightfield and fluorescence microscopes (or scanners). First, tissue samples are localized in the large image by applying a locally adaptive thresholding on the isotropic wavelet transform of the input TMA image. To reduce false detections, a parametric shape model is considered for segmenting ellipse-shaped objects at each detected position. Segmented objects that do not meet the size and the roundness criteria are discarded from the list of tissue samples before being matched with the design grid. Sample matching is performed by estimating the TMA grid deformation under the thin-plate model. Finally, thanks to the estimated deformation, the true tissue samples that were preliminary rejected in the early image processing step are recognized by running a second segmentation step. We

  12. 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

  13. Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency

    Directory of Open Access Journals (Sweden)

    Yeh Cheng-Yu

    2009-12-01

    Full Text Available Abstract Background Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. Results To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2 regulated by RUNX1 and STAT3 is correlated to the pathological stage

  14. Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency.

    Science.gov (United States)

    Yeh, Hsiang-Yuan; Cheng, Shih-Wu; Lin, Yu-Chun; Yeh, Cheng-Yu; Lin, Shih-Fang; Soo, Von-Wun

    2009-12-21

    Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN) algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD) as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2) regulated by RUNX1 and STAT3 is correlated to the pathological stage. We provide a computational framework to reconstruct

  15. Immunohistochemical analysis of breast tissue microarray images using contextual classifiers

    Directory of Open Access Journals (Sweden)

    Stephen J McKenna

    2013-01-01

    Full Text Available Background: Tissue microarrays (TMAs are an important tool in translational research for examining multiple cancers for molecular and protein markers. Automatic immunohistochemical (IHC scoring of breast TMA images remains a challenging problem. Methods: A two-stage approach that involves localization of regions of invasive and in-situ carcinoma followed by ordinal IHC scoring of nuclei in these regions is proposed. The localization stage classifies locations on a grid as tumor or non-tumor based on local image features. These classifications are then refined using an auto-context algorithm called spin-context. Spin-context uses a series of classifiers to integrate image feature information with spatial context information in the form of estimated class probabilities. This is achieved in a rotationally-invariant manner. The second stage estimates ordinal IHC scores in terms of the strength of staining and the proportion of nuclei stained. These estimates take the form of posterior probabilities, enabling images with uncertain scores to be referred for pathologist review. Results: The method was validated against manual pathologist scoring on two nuclear markers, progesterone receptor (PR and estrogen receptor (ER. Errors for PR data were consistently lower than those achieved with ER data. Scoring was in terms of estimated proportion of cells that were positively stained (scored on an ordinal scale of 0-6 and perceived strength of staining (scored on an ordinal scale of 0-3. Average absolute differences between predicted scores and pathologist-assigned scores were 0.74 for proportion of cells and 0.35 for strength of staining (PR. Conclusions: The use of context information via spin-context improved the precision and recall of tumor localization. The combination of the spin-context localization method with the automated scoring method resulted in reduced IHC scoring errors.

  16. SVD identifies transcript length distribution functions from DNA microarray data and reveals evolutionary forces globally affecting GBM metabolism.

    Directory of Open Access Journals (Sweden)

    Nicolas M Bertagnolli

    Full Text Available To search for evolutionary forces that might act upon transcript length, we use the singular value decomposition (SVD to identify the length distribution functions of sets and subsets of human and yeast transcripts from profiles of mRNA abundance levels across gel electrophoresis migration distances that were previously measured by DNA microarrays. We show that the SVD identifies the transcript length distribution functions as "asymmetric generalized coherent states" from the DNA microarray data and with no a-priori assumptions. Comparing subsets of human and yeast transcripts of the same gene ontology annotations, we find that in both disparate eukaryotes, transcripts involved in protein synthesis or mitochondrial metabolism are significantly shorter than typical, and in particular, significantly shorter than those involved in glucose metabolism. Comparing the subsets of human transcripts that are overexpressed in glioblastoma multiforme (GBM or normal brain tissue samples from The Cancer Genome Atlas, we find that GBM maintains normal brain overexpression of significantly short transcripts, enriched in transcripts that are involved in protein synthesis or mitochondrial metabolism, but suppresses normal overexpression of significantly longer transcripts, enriched in transcripts that are involved in glucose metabolism and brain activity. These global relations among transcript length, cellular metabolism and tumor development suggest a previously unrecognized physical mode for tumor and normal cells to differentially regulate metabolism in a transcript length-dependent manner. The identified distribution functions support a previous hypothesis from mathematical modeling of evolutionary forces that act upon transcript length in the manner of the restoring force of the harmonic oscillator.

  17. 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

  18. 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…

  19. 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…

  20. IsoGeneGUI : Multiple approaches for dose-response analysis of microarray data using R

    NARCIS (Netherlands)

    Otava, Martin; Sengupta, Rudradev; Shkedy, Ziv; Lin, Dan; Pramana, Setia; Verbeke, Tobias; Haldermans, Philippe; Hothorn, Ludwig A.; Gerhard, Daniel; Kuiper, Rebecca M.; Klinglmueller, Florian; Kasim, Adetayo

    2017-01-01

    The analysis of transcriptomic experiments with ordered covariates, such as dose-response data, has become a central topic in bioinformatics, in particular in omics studies. Consequently, multiple R packages on CRAN and Bioconductor are designed to analyse microarray data from various perspectives

  1. Rapid extraction of genomic DNA from saliva for HLA typing on microarray based on magnetic nanobeads

    Energy Technology Data Exchange (ETDEWEB)

    Xie Xin; Zhang Xu E-mail: shinezhang@hotmail.com; Yu Bingbin; Gao Huafang; Zhang Huan; Fei Weiyang

    2004-09-01

    A series of simplified protocols are developed for extracting genomic DNA from saliva by using the magnetic nanobeads as absorbents. In these protocols, both the enrichment of the target cells and the adsorption of DNA can be achieved simultaneously by our functionally modified magnetic beads in one step, and the DNA-nanobeads complex can be used as PCR templates. HLA typing based on an oligonucleotide array was conducted by hybridization with the PCR products. The result shows that the protocols are robust and sensitive.

  2. Optimization of the BLASTN substitution matrix for prediction of non-specific DNA microarray hybridization

    DEFF Research Database (Denmark)

    Eklund, Aron Charles; Friis, Pia; Wernersson, Rasmus

    2010-01-01

    BLASTN accuracy by modifying the substitution matrix and gap penalties. We generated gene expression microarray data for samples in which 1 or 10% of the target mass was an exogenous spike of known sequence. We found that the 10% spike induced 2-fold intensity changes in 3% of the probes, two......-third of which were decreases in intensity likely caused by bulk-hybridization. These changes were correlated with similarity between the spike and probe sequences. Interestingly, even very weak similarities tended to induce a change in probe intensity with the 10% spike. Using this data, we optimized the BLASTN...... substitution matrix to more accurately identify probes susceptible to non-specific hybridization with the spike. Relative to the default substitution matrix, the optimized matrix features a decreased score for A–T base pairs relative to G–C base pairs, resulting in a 5–15% increase in area under the ROC curve...

  3. An improved K-means clustering method for cDNA microarray image segmentation.

    Science.gov (United States)

    Wang, T N; Li, T J; Shao, G F; Wu, S X

    2015-07-14

    Microarray technology is a powerful tool for human genetic research and other biomedical applications. Numerous improvements to the standard K-means algorithm have been carried out to complete the image segmentation step. However, most of the previous studies classify the image into two clusters. In this paper, we propose a novel K-means algorithm, which first classifies the image into three clusters, and then one of the three clusters is divided as the background region and the other two clusters, as the foreground region. The proposed method was evaluated on six different data sets. The analyses of accuracy, efficiency, expression values, special gene spots, and noise images demonstrate the effectiveness of our method in improving the segmentation quality.

  4. DNA microarray revealed and RNAi plants confirmed key genes conferring low Cd accumulation in barley grains

    DEFF Research Database (Denmark)

    Sun, Hongyan; Chen, Zhong-Hua; Chen, Fei

    2015-01-01

    Background Understanding the mechanism of low Cd accumulation in crops is crucial for sustainable safe food production in Cd-contaminated soils. Results Confocal microscopy, atomic absorption spectrometry, gas exchange and chlorophyll fluorescence analyses revealed a distinct difference in Cd...... with a substantial difference between the two genotypes. Cd stress led to higher expression of genes involved in transport, carbohydrate metabolism and signal transduction in the low-grain-Cd-accumulating genotype. Novel transporter genes such as zinc transporter genes were identified as being associated with low Cd...... accumulation. Quantitative RT-PCR confirmed our microarray data. Furthermore, suppression of the zinc transporter genes HvZIP3 and HvZIP8 by RNAi silencing showed increased Cd accumulation and reduced Zn and Mn concentrations in barley grains. Thus, HvZIP3 and HvZIP8 could be candidate genes related to low...

  5. Correlating gene expression to physiological parameters and environmental conditons during cold acclimation of Pinus sylvestris, identification of molecular markers using cDNA microarrays

    NARCIS (Netherlands)

    Joosen, R.V.L.; Lammers, M.; Balk, P.A.; Bronnum, P.; Konings, M.C.J.M.; Perks, M.; Stattin, E.; Wordragen, van M.F.; Geest, van der A.H.M.

    2006-01-01

    Scots pine (Pinus sylvestris L.) seedlings were grown under different conditions (three field locations, two seasons and two climate room regimes), and then analyzed for freezing tolerance of shoots and roots and for transcript abundance in apical buds based on a cDNA microarray containing about

  6. Discovery of distinctive gene expression profiles in rheumatoid synovium using cDNA microarray technology: evidence for the existence of multiple pathways of tissue destruction and repair.

    NARCIS (Netherlands)

    Kraan, TC van der Pouw; Gaalen, van FA; Huizinga, T.W.; Pieterman, E; Breedveld, F.C.; Verweij, C.L.

    2003-01-01

    Rheumatoid arthritis (RA) is a heterogeneous disease. We used cDNA microarray technology to subclassify RA patients and disclose disease pathways in rheumatoid synovium. Hierarchical clustering of gene expression data identified two main groups of tissues (RA-I and RA-II). A total of 121 genes were

  7. Comparative analysis of human conjunctival and corneal epithelial gene expression with oligonucleotide microarrays.

    Science.gov (United States)

    Turner, Helen C; Budak, Murat T; Akinci, M A Murat; Wolosin, J Mario

    2007-05-01

    To determine global mRNA expression levels in corneal and conjunctival epithelia and identify transcripts that exhibit preferential tissue expression. cDNA samples derived from human conjunctival and corneal epithelia were hybridized in three independent experiments to a commercial oligonucleotide array representing more than 22,000 transcripts. The resultant signal intensities and microarray software transcript present/absent calls were used in conjunction with the local pooled error (LPE) statistical method to identify transcripts that are preferentially or exclusively expressed in one of the two tissues at significant levels (expression >1% of the beta-actin level). EASE (Expression Analysis Systematic Explorer software) was used to identify biological systems comparatively overrepresented in either epithelium. Immuno-, and cytohistochemistry was performed to validate or expand on selected results of interest. The analysis identified 332 preferential and 93 exclusive significant corneal epithelial transcripts. The corresponding numbers of conjunctival epithelium transcripts were 592 and 211, respectively. The overrepresented biological processes in the cornea were related to cell adhesion and oxiredox equilibria and cytoprotection activities. In the conjunctiva, the biological processes that were most prominent were related to innate immunity and melanogenesis. Immunohistochemistry for antigen-presenting cells and melanocytes was consistent with these gene signatures. The transcript comparison identified a substantial number of genes that have either not been identified previously or are not known to be highly expressed in these two epithelia, including testican-1, ECM1, formin, CRTAC1, and NQO1 in the cornea and, in the conjunctiva, sPLA(2)-IIA, lipocalin 2, IGFBP3, multiple MCH class II proteins, and the Na-Pi cotransporter type IIb. Comparative gene expression profiling leads to the identification of many biological processes and previously unknown genes that

  8. 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.

  9. 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.

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

    Directory of Open Access Journals (Sweden)

    Luo Wen

    2009-03-01

    Full Text Available 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.

  11. Development and application of a microarray meter tool to optimize microarray experiments

    Directory of Open Access Journals (Sweden)

    Rouse Richard JD

    2008-07-01

    Full Text Available Abstract Background Successful microarray experimentation requires a complex interplay between the slide chemistry, the printing pins, the nucleic acid probes and targets, and the hybridization milieu. Optimization of these parameters and a careful evaluation of emerging slide chemistries are a prerequisite to any large scale array fabrication effort. We have developed a 'microarray meter' tool which assesses the inherent variations associated with microarray measurement prior to embarking on large scale projects. Findings The microarray meter consists of nucleic acid targets (reference and dynamic range control and probe components. Different plate designs containing identical probe material were formulated to accommodate different robotic and pin designs. We examined the variability in probe quality and quantity (as judged by the amount of DNA printed and remaining post-hybridization using three robots equipped with capillary printing pins. Discussion The generation of microarray data with minimal variation requires consistent quality control of the (DNA microarray manufacturing and experimental processes. Spot reproducibility is a measure primarily of the variations associated with printing. The microarray meter assesses array quality by measuring the DNA content for every feature. It provides a post-hybridization analysis of array quality by scoring probe performance using three metrics, a a measure of variability in the signal intensities, b a measure of the signal dynamic range and c a measure of variability of the spot morphologies.

  12. Improving cluster-based missing value estimation of DNA microarray data.

    Science.gov (United States)

    Brás, Lígia P; Menezes, José C

    2007-06-01

    We present a modification of the weighted K-nearest neighbours imputation method (KNNimpute) for missing values (MVs) estimation in microarray data based on the reuse of estimated data. The method was called iterative KNN imputation (IKNNimpute) as the estimation is performed iteratively using the recently estimated values. The estimation efficiency of IKNNimpute was assessed under different conditions (data type, fraction and structure of missing data) by the normalized root mean squared error (NRMSE) and the correlation coefficients between estimated and true values, and compared with that of other cluster-based estimation methods (KNNimpute and sequential KNN). We further investigated the influence of imputation on the detection of differentially expressed genes using SAM by examining the differentially expressed genes that are lost after MV estimation. The performance measures give consistent results, indicating that the iterative procedure of IKNNimpute can enhance the prediction ability of cluster-based methods in the presence of high missing rates, in non-time series experiments and in data sets comprising both time series and non-time series data, because the information of the genes having MVs is used more efficiently and the iterative procedure allows refining the MV estimates. More importantly, IKNN has a smaller detrimental effect on the detection of differentially expressed genes.

  13. 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.

  14. Comparison of DNA Microarray, Loop-Mediated Isothermal Amplification (LAMP) and Real-Time PCR with DNA Sequencing for Identification of Fusarium spp. Obtained from Patients with Hematologic Malignancies.

    Science.gov (United States)

    de Souza, Marcela; Matsuzawa, Tetsuhiro; Sakai, Kanae; Muraosa, Yasunori; Lyra, Luzia; Busso-Lopes, Ariane Fidelis; Levin, Anna Sara Shafferman; Schreiber, Angélica Zaninelli; Mikami, Yuzuru; Gonoi, Tohoru; Kamei, Katsuhiko; Moretti, Maria Luiza; Trabasso, Plínio

    2017-08-01

    The performance of three molecular biology techniques, i.e., DNA microarray, loop-mediated isothermal amplification (LAMP), and real-time PCR were compared with DNA sequencing for properly identification of 20 isolates of Fusarium spp. obtained from blood stream as etiologic agent of invasive infections in patients with hematologic malignancies. DNA microarray, LAMP and real-time PCR identified 16 (80%) out of 20 samples as Fusarium solani species complex (FSSC) and four (20%) as Fusarium spp. The agreement among the techniques was 100%. LAMP exhibited 100% specificity, while DNA microarray, LAMP and real-time PCR showed 100% sensitivity. The three techniques had 100% agreement with DNA sequencing. Sixteen isolates were identified as FSSC by sequencing, being five Fusarium keratoplasticum, nine Fusarium petroliphilum and two Fusarium solani. On the other hand, sequencing identified four isolates as Fusarium non-solani species complex (FNSSC), being three isolates as Fusarium napiforme and one isolate as Fusarium oxysporum. Finally, LAMP proved to be faster and more accessible than DNA microarray and real-time PCR, since it does not require a thermocycler. Therefore, LAMP signalizes as emerging and promising methodology to be used in routine identification of Fusarium spp. among cases of invasive fungal infections.

  15. 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.

  16. Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships.

    Science.gov (United States)

    Seok, Junhee; Kaushal, Amit; Davis, Ronald W; Xiao, Wenzhong

    2010-01-18

    The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions. In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification. High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data.

  17. 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

    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....

  18. A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability

    Directory of Open Access Journals (Sweden)

    Reinders Marcel JT

    2009-11-01

    Full Text Available Abstract 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 the observed discrepancies are the measurement error associated with each feature and the choice of preprocessing method. Microarray data are known to be subject to technical variation and the confidence intervals around individual point estimates of expression levels can be wide. Furthermore, the estimated expression values also vary depending on the selected preprocessing scheme. In microarray breast cancer classification studies, however, these two forms of feature variability are almost always ignored and hence their exact role is unclear. Results We have performed a comprehensive sensitivity analysis of microarray breast cancer classification under the two types of feature variability mentioned above. We used data from six state of the art preprocessing methods, using a compendium consisting of eight diferent datasets, involving 1131 hybridizations, containing data from both one and two-color array technology. For a wide range of classifiers, we performed a joint study on performance, concordance and stability. In the stability analysis we explicitly tested classifiers for their noise tolerance by using perturbed expression profiles that are based on uncertainty information directly related to the preprocessing methods. Our results indicate that signature composition is strongly influenced by feature variability, even if the array platform and the stratification of patient samples are identical. In addition, we show that there is often a high level of discordance between individual class assignments for signatures constructed on data coming from different preprocessing schemes, even if the actual signature composition is identical

  19. Application of a cDNA microarray for profiling the gene expression of Echinococcus granulosus protoscoleces treated with albendazole and artemisinin.

    Science.gov (United States)

    Lü, Guodong; Zhang, Wenbao; Wang, Jianhua; Xiao, Yunfeng; Zhao, Jun; Zhao, Jianqin; Sun, Yimin; Zhang, Chuanshan; Wang, Junhua; Lin, Renyong; Liu, Hui; Zhang, Fuchun; Wen, Hao

    2014-12-01

    Cystic echinoccocosis (CE) is a neglected zoonosis that is caused by the dog-tapeworm Echinococcus granulosus. The disease is endemic worldwide. There is an urgent need for searching effective drug for the treatment of the disease. In this study, we sequenced a cDNA library constructed using RNA isolated from oncospheres, protoscoleces, cyst membrane and adult worms of E. granulosus. A total of 9065 non-redundant or unique sequences were obtained and spotted on chips as uniEST probes to profile the gene expression in protoscoleces of E. granulosus treated with the anthelmintic drugs albendazole and artemisinin, respectively. The results showed that 7 genes were up-regulated and 38 genes were down-regulated in the protoscoleces treated with albendazole. Gene analysis showed that these genes are responsible for energy metabolism, cell cycle and assembly of cell structure. We also identified 100 genes up-regulated and 6 genes down-regulated in the protoscoleces treated with artemisinin. These genes play roles in the transduction of environmental signals, and metabolism. Albendazole appeared its drug efficacy in damaging cell structure, while artemisinin was observed to increase the formation of the heterochromatin in protoscolex cells. Our results highlight the utility of using cDNA microarray methods to detect gene expression profiles of E. granulosus and, in particular, to understand the pharmacologic mechanism of anti-echinococcosis drugs. Copyright © 2014 Elsevier B.V. All rights reserved.

  20. FBI's DNA analysis program

    Science.gov (United States)

    Brown, John R.

    1994-03-01

    Forensic DNA profiling technology is a significant law enforcement tool due to its superior discriminating power. Applying the principles of population genetics to the DNA profile obtained in violent crime investigations results in low frequency of occurrence estimates for the DNA profile. These estimates often range from a frequency of occurrence of 1 in 50 unrelated individuals to 1 in a million unrelated individuals or even smaller. It is this power to discriminate among individuals in the population that has propelled forensic DNA technology to the forefront of forensic testing in violent crime cases. Not only is the technology extremely powerful in including or excluding a criminal suspect as the perpetrator, but it also gives rise to the potential of identifying criminal suspects in cases where the investigators of unknown suspect cases have exhausted all other available leads.

  1. 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

  2. Transcriptome analysis in non-model species: a new method for the analysis of heterologous hybridization on microarrays

    Directory of Open Access Journals (Sweden)

    Jouventin Pierre

    2010-05-01

    Full Text Available Abstract Background Recent developments in high-throughput methods of analyzing transcriptomic profiles are promising for many areas of biology, including ecophysiology. However, although commercial microarrays are available for most common laboratory models, transcriptome analysis in non-traditional model species still remains a challenge. Indeed, the signal resulting from heterologous hybridization is low and difficult to interpret because of the weak complementarity between probe and target sequences, especially when no microarray dedicated to a genetically close species is available. Results We show here that transcriptome analysis in a species genetically distant from laboratory models is made possible by using MAXRS, a new method of analyzing heterologous hybridization on microarrays. This method takes advantage of the design of several commercial microarrays, with different probes targeting the same transcript. To illustrate and test this method, we analyzed the transcriptome of king penguin pectoralis muscle hybridized to Affymetrix chicken microarrays, two organisms separated by an evolutionary distance of approximately 100 million years. The differential gene expression observed between different physiological situations computed by MAXRS was confirmed by real-time PCR on 10 genes out of 11 tested. Conclusions MAXRS appears to be an appropriate method for gene expression analysis under heterologous hybridization conditions.

  3. Domain-enhanced analysis of microarray data using GO annotations.

    Science.gov (United States)

    Liu, Jiajun; Hughes-Oliver, Jacqueline M; Menius, J Alan

    2007-05-15

    New biological systems technologies give scientists the ability to measure thousands of bio-molecules including genes, proteins, lipids and metabolites. We use domain knowledge, e.g. the Gene Ontology, to guide analysis of such data. By focusing on domain-aggregated results at, say the molecular function level, increased interpretability is available to biological scientists beyond what is possible if results are presented at the gene level. We use a 'top-down' approach to perform domain aggregation by first combining gene expressions before testing for differentially expressed patterns. This is in contrast to the more standard 'bottom-up' approach, where genes are first tested individually then aggregated by domain knowledge. The benefits are greater sensitivity for detecting signals. Our method, domain-enhanced analysis (DEA) is assessed and compared to other methods using simulation studies and analysis of two publicly available leukemia data sets. Our DEA method uses functions available in R (http://www.r-project.org/) and SAS (http://www.sas.com/). The two experimental data sets used in our analysis are available in R as Bioconductor packages, 'ALL' and 'golubEsets' (http://www.bioconductor.org/). Supplementary data are available at Bioinformatics online.

  4. SEURAT: visual analytics for the integrated analysis of microarray data.

    Science.gov (United States)

    Gribov, Alexander; Sill, Martin; Lück, Sonja; Rücker, Frank; Döhner, Konstanze; Bullinger, Lars; Benner, Axel; Unwin, Antony

    2010-06-03

    In translational cancer research, gene expression data is collected together with clinical data and genomic data arising from other chip based high throughput technologies. Software tools for the joint analysis of such high dimensional data sets together with clinical data are required. We have developed an open source software tool which provides interactive visualization capability for the integrated analysis of high-dimensional gene expression data together with associated clinical data, array CGH data and SNP array data. The different data types are organized by a comprehensive data manager. Interactive tools are provided for all graphics: heatmaps, dendrograms, barcharts, histograms, eventcharts and a chromosome browser, which displays genetic variations along the genome. All graphics are dynamic and fully linked so that any object selected in a graphic will be highlighted in all other graphics. For exploratory data analysis the software provides unsupervised data analytics like clustering, seriation algorithms and biclustering algorithms. The SEURAT software meets the growing needs of researchers to perform joint analysis of gene expression, genomical and clinical data.

  5. SEURAT: Visual analytics for the integrated analysis of microarray data

    Directory of Open Access Journals (Sweden)

    Bullinger Lars

    2010-06-01

    Full Text Available Abstract Background In translational cancer research, gene expression data is collected together with clinical data and genomic data arising from other chip based high throughput technologies. Software tools for the joint analysis of such high dimensional data sets together with clinical data are required. Results We have developed an open source software tool which provides interactive visualization capability for the integrated analysis of high-dimensional gene expression data together with associated clinical data, array CGH data and SNP array data. The different data types are organized by a comprehensive data manager. Interactive tools are provided for all graphics: heatmaps, dendrograms, barcharts, histograms, eventcharts and a chromosome browser, which displays genetic variations along the genome. All graphics are dynamic and fully linked so that any object selected in a graphic will be highlighted in all other graphics. For exploratory data analysis the software provides unsupervised data analytics like clustering, seriation algorithms and biclustering algorithms. Conclusions The SEURAT software meets the growing needs of researchers to perform joint analysis of gene expression, genomical and clinical data.

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

    Directory of Open Access Journals (Sweden)

    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

  7. Preliminary report for analysis of genome wide mutations from four ciprofloxacin resistant B. anthracis Sterne isolates generated by Illumina, 454 sequencing and microarrays for DHS

    Energy Technology Data Exchange (ETDEWEB)

    Jaing, Crystal [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Vergez, Lisa [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Hinckley, Aubree [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Thissen, James [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Gardner, Shea [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); McLoughlin, Kevin [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Jackson, Paul [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Ellingson, Sally [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Hauser, Loren [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Brettin, Tom [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Fofanov, Viacheslav [Eureka Genomics, Hercules, CA (United States); Koshinsky, Heather [Eureka Genomics, Hercules, CA (United States); Fofanov, Yuriy [Univ. of Houston, TX (United States)

    2011-06-21

    The objective of this project is to provide DHS a comprehensive evaluation of the current genomic technologies including genotyping, Taqman PCR, multiple locus variable tandem repeat analysis (MLVA), microarray and high-throughput DNA sequencing in the analysis of biothreat agents from complex environmental samples. As the result of a different DHS project, we have selected for and isolated a large number of ciprofloxacin resistant B. anthracis Sterne isolates. These isolates vary in the concentrations of ciprofloxacin that they can tolerate, suggesting multiple mutations in the samples. In collaboration with University of Houston, Eureka Genomics and Oak Ridge National Laboratory, we analyzed the ciprofloxacin resistant B. anthracis Sterne isolates by microarray hybridization, Illumina and Roche 454 sequencing to understand the error rates and sensitivity of the different methods. The report provides an assessment of the results and a complete set of all protocols used and all data generated along with information to interpret the protocols and data sets.

  8. [Diagnosis of a case with Williams-Beuren syndrome with nephrocalcinosis using chromosome microarray analysis].

    Science.gov (United States)

    Jin, S J; Liu, M; Long, W J; Luo, X P

    2016-12-02

    Objective: To explore the clinical phenotypes and the genetic cause for a boy with unexplained growth retardation, nephrocalcinosis, auditory anomalies and multi-organ/system developmental disorders. Method: Routine G-banding and chromosome microarray analysis were applied to a child with unexplained growth retardation, nephrocalcinosis, auditory anomalies and multi-organ/system developmental disorders treated in the Department of Pediatrics of Tongji Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology in September 2015 and his parents to conduct the chromosomal karyotype analysis and the whole genome scanning. Deleted genes were searched in the Decipher and NCBI databases, and their relationships with the clinical phenotypes were analyzed. Result: A six-month-old boy was refered to us because of unexplained growth retardation and feeding intolerance.The affected child presented with abnormal manifestation such as special face, umbilical hernia, growth retardation, hypothyroidism, congenital heart disease, right ear sensorineural deafness, hypercalcemia and nephrocalcinosis. The child's karyotype was 46, XY, 16qh + , and his parents' karyotypes were normal. Chromosome microarray analysis revealed a 1 436 kb deletion on the 7q11.23(72701098_74136633) region of the child. This region included 23 protein-coding genes, which were reported to be corresponding to Williams-Beuren syndrome and its certain clinical phenotypes. His parents' results of chromosome microarray analysis were normal. Conclusion: A boy with characteristic manifestation of Williams-Beuren syndrome and rare nephrocalcinosis was diagnosed using chromosome microarray analysis. The deletion on the 7q11.23 might be related to the clinical phenotypes of Williams-Beuren syndrome, yet further studies are needed.

  9. Genes involved in immunity and apoptosis are associated with human presbycusis based on microarray analysis.

    Science.gov (United States)

    Dong, Yang; Li, Ming; Liu, Puzhao; Song, Haiyan; Zhao, Yuping; Shi, Jianrong

    2014-06-01

    Genes involved in immunity and apoptosis were associated with human presbycusis. CCR3 and GILZ played an important role in the pathogenesis of presbycusis, probably through regulating chemokine receptor, T-cell apoptosis, or T-cell activation pathways. To identify genes associated with human presbycusis and explore the molecular mechanism of presbycusis. Hearing function was tested by pure-tone audiometry. Microarray analysis was performed to identify presbycusis-correlated genes by Illumina Human-6 BeadChip using the peripheral blood samples of subjects. To identify biological process categories and pathways associated with presbycusis-correlated genes, bioinformatics analysis was carried out by Gene Ontology Tree Machine (GOTM) and database for annotation, visualization, and integrated discovery (DAVID). Quantitative RT-PCR (qRT-PCR) was used to validate the microarray data. Microarray analysis identified 469 up-regulated genes and 323 down-regulated genes. Both the dominant biological processes by Gene Ontology (GO) analysis and the enriched pathways by Kyoto encyclopedia of genes and genomes (KEGG) and BIOCARTA showed that genes involved in immunity and apoptosis were associated with presbycusis. In addition, CCR3, GILZ, CXCL10, and CX3CR1 genes showed consistent difference between groups for both the gene chip and qRT-PCR data. The differences of CCR3 and GILZ between presbycusis patients and controls were statistically significant (p < 0.05).

  10. 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...... 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....

  11. Detection of mutations using microarrays of poly(C)10-poly(T)10 modified DNA probes immobilized on agarose films

    DEFF Research Database (Denmark)

    Dufva, Hans Martin; Petersen, Jesper; Stoltenborg, M.

    2006-01-01

    Allele-specific hybridization to a DNA microarray call be a useful method for genotyping patient DNA. In this article, we demonstrate that 13- to 17-base oligonucleotides tagged with a poly(T)10-poly(C)10 tail (TC tag), but otherwise unmodified, can be crosslinked by UV light irradiation to an ag......Allele-specific hybridization to a DNA microarray call be a useful method for genotyping patient DNA. In this article, we demonstrate that 13- to 17-base oligonucleotides tagged with a poly(T)10-poly(C)10 tail (TC tag), but otherwise unmodified, can be crosslinked by UV light irradiation...... to an agarose film grafted onto unmodified glass. Microarrays of TC-tagged probes immobilized on the agarose film can be used to diagnose Mutations in the human P-globin gene, which encodes the beta-chains in hemoglobin. Although the probes differed widely regarding inciting point temperature (similar to 20...... degrees C), a single stringency wash still gave sufficiently high discrimination signals between perfect match and mismatch probes to allow robust mutation detection. In all, 270 genotypings were performed on patient materials, and no genotype was incorrectly classified. Quality control experiments...

  12. A cDNA microarray, UniShrimpChip, for identification of genes relevant to testicular development in the black tiger shrimp (Penaeus monodon

    Directory of Open Access Journals (Sweden)

    Klinbunga Sirawut

    2011-04-01

    Full Text Available Abstract Background Poor reproductive maturation in captive male broodstock of the black tiger shrimp (Penaeus monodon is one of the serious problems to the farming industries. Without genome sequence, EST libraries of P. monodon were previously constructed to identify transcripts with important biological functions. In this study, a new version of cDNA microarray, UniShrimpChip, was constructed from the Peneaus monodon EST libraries of 12 tissues, containing 5,568 non-redundant cDNA clones from 10,536 unique cDNA in the P. monodon EST database. UniShrimpChip was used to study testicular development by comparing gene expression levels of wild brooders from the West and East coasts of Thailand and domesticated brooders with different ages (10-, 14-, 18-month-old. Results The overall gene expression patterns from the microarray experiments revealed distinct transcriptomic patterns between the wild and domesticated groups. Moreover, differentially expressed genes from the microarray comparisons were identified, and the expression patterns of eight selected transcripts were subsequently confirmed by reverse-transcriptase quantitative PCR (RT-qPCR. Among these, expression levels of six subunits (CSN2, 4, 5, 6, 7a, and 8 of the COP9 signalosome (CSN gene family in wild and different ages of domesticated brooders were examined by RT-qPCR. Among the six subunits, CSN5 and CSN6 were most highly expressed in wild brooders and least expressed in the 18-month-old domesticated group; therefore, their full-length cDNA sequences were characterized. Conclusions This study is the first report to employ cDNA microarray to study testicular development in the black tiger shrimp. We show that there are obvious differences between the wild and domesticated shrimp at the transcriptomic level. Furthermore, our study is the first to investigate the feasibility that the CSN gene family might have involved in reproduction and development of this economically important

  13. A multilevel Lab on chip platform for DNA analysis.

    Science.gov (United States)

    Marasso, Simone Luigi; Giuri, Eros; Canavese, Giancarlo; Castagna, Riccardo; Quaglio, Marzia; Ferrante, Ivan; Perrone, Denis; Cocuzza, Matteo

    2011-02-01

    Lab-on-chips (LOCs) are critical systems that have been introduced to speed up and reduce the cost of traditional, laborious and extensive analyses in biological and biomedical fields. These ambitious and challenging issues ask for multi-disciplinary competences that range from engineering to biology. Starting from the aim to integrate microarray technology and microfluidic devices, a complex multilevel analysis platform has been designed, fabricated and tested (All rights reserved-IT Patent number TO2009A000915). This LOC successfully manages to interface microfluidic channels with standard DNA microarray glass slides, in order to implement a complete biological protocol. Typical Micro Electro Mechanical Systems (MEMS) materials and process technologies were employed. A silicon/glass microfluidic chip and a Polydimethylsiloxane (PDMS) reaction chamber were fabricated and interfaced with a standard microarray glass slide. In order to have a high disposable system all micro-elements were passive and an external apparatus provided fluidic driving and thermal control. The major microfluidic and handling problems were investigated and innovative solutions were found. Finally, an entirely automated DNA hybridization protocol was successfully tested with a significant reduction in analysis time and reagent consumption with respect to a conventional protocol.

  14. The pathogenesis shared between abdominal aortic aneurysms and intracranial aneurysms: a microarray analysis.

    Science.gov (United States)

    Wang, Wen; Li, Hao; Zhao, Zheng; Wang, Haoyuan; Zhang, Dong; Zhang, Yan; Lan, Qing; Wang, Jiangfei; Cao, Yong; Zhao, Jizong

    2018-04-01

    Abdominal aortic aneurysms (AAAs) and intracranial saccular aneurysms (IAs) are the most common types of aneurysms. This study was to investigate the common pathogenesis shared between these two kinds of aneurysms. We collected 12 IAs samples and 12 control arteries from the Beijing Tiantan Hospital and performed microarray analysis. In addition, we utilized the microarray datasets of IAs and AAAs from the Gene Expression Omnibus (GEO), in combination with our microarray results, to generate messenger RNA expression profiles for both AAAs and IAs in our study. Functional exploration and protein-protein interaction (PPI) analysis were performed. A total of 727 common genes were differentially expressed (404 was upregulated; 323 was downregulated) for both AAAs and IAs. The GO and pathway analyses showed that the common dysregulated genes were mainly enriched in vascular smooth muscle contraction, muscle contraction, immune response, defense response, cell activation, IL-6 signaling and chemokine signaling pathways, etc. The further protein-protein analysis identified 35 hub nodes, including TNF, IL6, MAPK13, and CCL5. These hub node genes were enriched in inflammatory response, positive regulation of IL-6 production, chemokine signaling pathway, and T/B cell receptor signaling pathway. Our study will gain new insight into the molecular mechanisms for the pathogenesis of both types of aneurysms and provide new therapeutic targets for the patients harboring AAAs and IAs.

  15. 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.

  16. 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

  17. 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

  18. A microarray analysis of the rice transcriptome and its comparison to Arabidopsis

    DEFF Research Database (Denmark)

    Ma, Ligeng; Chen, Chen; Liu, Xigang

    2005-01-01

    Arabidopsis and rice are the only two model plants whose finished phase genome sequence has been completed. Here we report the construction of an oligomer microarray based on the presently known and predicted gene models in the rice genome. This microarray was used to analyze the transcriptional...... with similar genome-wide surveys of the Arabidopsis transcriptome, our results indicate that similar proportions of the two genomes are expressed in their corresponding organ types. A large percentage of the rice gene models that lack significant Arabidopsis homologs are expressed. Furthermore, the expression...... patterns of rice and Arabidopsis best-matched homologous genes in distinct functional groups indicate dramatic differences in their degree of conservation between the two species. Thus, this initial comparative analysis reveals some basic similarities and differences between the Arabidopsis and rice...

  19. A pilot study of transcription unit analysis in rice using oligonucleotide tiling-path microarray

    DEFF Research Database (Denmark)

    Stolc, Viktor; Li, Lei; Wang, Xiangfeng

    2005-01-01

    As the international efforts to sequence the rice genome are completed, an immediate challenge and opportunity is to comprehensively and accurately define all transcription units in the rice genome. Here we describe a strategy of using high-density oligonucleotide tiling-path microarrays to map...... transcription of the japonica rice genome. In a pilot experiment to test this approach, one array representing the reverse strand of the last 11.2 Mb sequence of chromosome 10 was analyzed in detail based on a mathematical model developed in this study. Analysis of the array data detected 77% of the reference...... gene models in a mixture of four RNA populations. Moreover, significant transcriptional activities were found in many of the previously annotated intergenic regions. These preliminary results demonstrate the utility of genome tiling microarrays in evaluating annotated rice gene models...

  20. Mutation analysis of 272 Spanish families affected by autosomal recessive retinitis pigmentosa using a genotyping microarray.

    Science.gov (United States)

    Ávila-Fernández, Almudena; Cantalapiedra, Diego; Aller, Elena; Vallespín, Elena; Aguirre-Lambán, Jana; Blanco-Kelly, Fiona; Corton, M; Riveiro-Álvarez, Rosa; Allikmets, Rando; Trujillo-Tiebas, María José; Millán, José M; Cremers, Frans P M; Ayuso, Carmen

    2010-12-03

    Retinitis pigmentosa (RP) is a genetically heterogeneous disorder characterized by progressive loss of vision. The aim of this study was to identify the causative mutations in 272 Spanish families using a genotyping microarray. 272 unrelated Spanish families, 107 with autosomal recessive RP (arRP) and 165 with sporadic RP (sRP), were studied using the APEX genotyping microarray. The families were also classified by clinical criteria: 86 juveniles and 186 typical RP families. Haplotype and sequence analysis were performed to identify the second mutated allele. At least one-gene variant was found in 14% and 16% of the juvenile and typical RP groups respectively. Further study identified four new mutations, providing both causative changes in 11% of the families. Retinol Dehydrogenase 12 (RDH12) was the most frequently mutated gene in the juvenile RP group, and Usher Syndrome 2A (USH2A) and Ceramide Kinase-Like (CERKL) were the most frequently mutated genes in the typical RP group. The only variant found in CERKL was p.Arg257Stop, the most frequent mutation. The genotyping microarray combined with segregation and sequence analysis allowed us to identify the causative mutations in 11% of the families. Due to the low number of characterized families, this approach should be used in tandem with other techniques.

  1. Integration of microarray analysis into the clinical diagnosis of hematological malignancies: How much can we improve cytogenetic testing?

    Science.gov (United States)

    Peterson, Jess F.; Aggarwal, Nidhi; Smith, Clayton A.; Gollin, Susanne M.; Surti, Urvashi; Rajkovic, Aleksandar; Swerdlow, Steven H.; Yatsenko, Svetlana A.

    2015-01-01

    Purpose To evaluate the clinical utility, diagnostic yield and rationale of integrating microarray analysis in the clinical diagnosis of hematological malignancies in comparison with classical chromosome karyotyping/fluorescence in situ hybridization (FISH). Methods G-banded chromosome analysis, FISH and microarray studies using customized CGH and CGH+SNP designs were performed on 27 samples from patients with hematological malignancies. A comprehensive comparison of the results obtained by three methods was conducted to evaluate benefits and limitations of these techniques for clinical diagnosis. Results Overall, 89.7% of chromosomal abnormalities identified by karyotyping/FISH studies were also detectable by microarray. Among 183 acquired copy number alterations (CNAs) identified by microarray, 94 were additional findings revealed in 14 cases (52%), and at least 30% of CNAs were in genomic regions of diagnostic/prognostic significance. Approximately 30% of novel alterations detected by microarray were >20 Mb in size. Balanced abnormalities were not detected by microarray; however, of the 19 apparently “balanced” rearrangements, 55% (6/11) of recurrent and 13% (1/8) of non-recurrent translocations had alterations at the breakpoints discovered by microarray. Conclusion Microarray technology enables accurate, cost-effective and time-efficient whole-genome analysis at a resolution significantly higher than that of conventional karyotyping and FISH. Array-CGH showed advantage in identification of cryptic imbalances and detection of clonal aberrations in population of non-dividing cancer cells and samples with poor chromosome morphology. The integration of microarray analysis into the cytogenetic diagnosis of hematologic malignancies has the potential to improve patient management by providing clinicians with additional disease specific and potentially clinically actionable genomic alterations. PMID:26299921

  2. Temporal Gene Expression Profiling of the Wheat Leaf Rust Pathosystem Using cDNA Microarray Reveals Differences in Compatible and Incompatible Defence Pathways

    OpenAIRE

    Fofana, Bourlaye; Banks, Travis W.; McCallum, Brent; Strelkov, Stephen E.; Cloutier, Sylvie

    2007-01-01

    In this study, we detail the construction of a custom cDNA spotted microarray containing 7728 wheat ESTs and the use of the array to identify host genes that are differentially expressed upon challenges with leaf rust fungal pathogens. Wheat cultivar RL6003 (Thatcher Lr1) was inoculated with Puccinia triticina virulence phenotypes BBB (incompatible) or TJB (7-2) (compatible) and sampled at four different time points (3, 6, 12, and 24 hours) after inoculation. Transcript expression levels rela...

  3. DNA microarrays immobilized on unmodified plastics in a microfluidic biochip for rapid typing of Avian Influenza Virus

    DEFF Research Database (Denmark)

    Yi, Sun; Perch-Nielsen, Ivan R.; Dufva, Martin

    2011-01-01

    Polymers are widely used for microfluidic systems, but fabrication of microarrays on such materials often requires complicated chemical surface modifications, which hinders the integration of microarrays into microfluidic systems. In this paper, we demonstrate that UV irradiation can be used to d...

  4. Microarray Meta-Analysis of RNA-Binding Protein Functions in Alternative Polyadenylation

    Science.gov (United States)

    Hu, Wenchao; Liu, Yuting; Yan, Jun

    2014-01-01

    Alternative polyadenylation (APA) is a post-transcriptional mechanism to generate diverse mRNA transcripts with different 3′UTRs from the same gene. In this study, we systematically searched for the APA events with differential expression in public mouse microarray data. Hundreds of genes with over-represented differential APA events and the corresponding experiments were identified. We further revealed that global APA differential expression occurred prevalently in tissues such as brain comparing to peripheral tissues, and biological processes such as development, differentiation and immune responses. Interestingly, we also observed widespread differential APA events in RNA-binding protein (RBP) genes such as Rbm3, Eif4e2 and Elavl1. Given the fact that RBPs are considered as the main regulators of differential APA expression, we constructed a co-expression network between APAs and RBPs using the microarray data. Further incorporation of CLIP-seq data of selected RBPs showed that Nova2 represses and Mbnl1 promotes the polyadenylation of closest poly(A) sites respectively. Altogether, our study is the first microarray meta-analysis in a mammal on the regulation of APA by RBPs that integrated massive mRNA expression data under a wide-range of biological conditions. Finally, we present our results as a comprehensive resource in an online website for the research community. PMID:24622240

  5. 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.

  6. A Discrete Wavelet Based Feature Extraction and Hybrid Classification Technique for Microarray Data Analysis

    Directory of Open Access Journals (Sweden)

    Jaison Bennet

    2014-01-01

    Full Text Available Cancer classification by doctors and radiologists was based on morphological and clinical features and had limited diagnostic ability in olden days. The recent arrival of DNA microarray technology has led to the concurrent monitoring of thousands of gene expressions in a single chip which stimulates the progress in cancer classification. In this paper, we have proposed a hybrid approach for microarray data classification based on nearest neighbor (KNN, naive Bayes, and support vector machine (SVM. Feature selection prior to classification plays a vital role and a feature selection technique which combines discrete wavelet transform (DWT and moving window technique (MWT is used. The performance of the proposed method is compared with the conventional classifiers like support vector machine, nearest neighbor, and naive Bayes. Experiments have been conducted on both real and benchmark datasets and the results indicate that the ensemble approach produces higher classification accuracy than conventional classifiers. This paper serves as an automated system for the classification of cancer and can be applied by doctors in real cases which serve as a boon to the medical community. This work further reduces the misclassification of cancers which is highly not allowed in cancer detection.

  7. DNA microarray-based solid-phase RT-PCR for rapid detection and identification of influenza virus type A and subtypes H5 and H7

    DEFF Research Database (Denmark)

    Yi, Sun; Dhumpa, Raghuram; Bang, Dang Duong

    2011-01-01

    of RNA extract in the liquid phase with sequence-specific nested PCR on the solid phase. A simple ultraviolet cross-linking method was used to immobilize the DNA probes over an unmodified glass surface, which makes solid-phase PCR a convenient possibility for AIV screening. The testing of 33 avian fecal....... In this article, a DNA microarray-based solid-phase polymerase chain reaction (PCR) approach has been developed for rapid detection of influenza virus type A and for simultaneous identification of pathogenic virus subtypes H5 and H7. This solid-phase RT-PCR method combined reverse-transcription amplification...

  8. Methylation-Sensitive Amplification Length Polymorphism (MS-AFLP) Microarrays for Epigenetic Analysis of Human Genomes.

    Science.gov (United States)

    Alonso, Sergio; Suzuki, Koichi; Yamamoto, Fumiichiro; Perucho, Manuel

    2018-01-01

    Somatic, and in a minor scale also germ line, epigenetic aberrations are fundamental to carcinogenesis, cancer progression, and tumor phenotype. DNA methylation is the most extensively studied and arguably the best understood epigenetic mechanisms that become altered in cancer. Both somatic loss of methylation (hypomethylation) and gain of methylation (hypermethylation) are found in the genome of malignant cells. In general, the cancer cell epigenome is globally hypomethylated, while some regions-typically gene-associated CpG islands-become hypermethylated. Given the profound impact that DNA methylation exerts on the transcriptional profile and genomic stability of cancer cells, its characterization is essential to fully understand the complexity of cancer biology, improve tumor classification, and ultimately advance cancer patient management and treatment. A plethora of methods have been devised to analyze and quantify DNA methylation alterations. Several of the early-developed methods relied on the use of methylation-sensitive restriction enzymes, whose activity depends on the methylation status of their recognition sequences. Among these techniques, methylation-sensitive amplification length polymorphism (MS-AFLP) was developed in the early 2000s, and successfully adapted from its original gel electrophoresis fingerprinting format to a microarray format that notably increased its throughput and allowed the quantification of the methylation changes. This array-based platform interrogates over 9500 independent loci putatively amplified by the MS-AFLP technique, corresponding to the NotI sites mapped throughout the human genome.

  9. Gene features selection for three-class disease classification via multiple orthogonal partial least square discriminant analysis and S-plot using microarray data.

    Science.gov (United States)

    Yang, Mingxing; Li, Xiumin; Li, Zhibin; Ou, Zhimin; Liu, Ming; Liu, Suhuan; Li, Xuejun; Yang, Shuyu

    2013-01-01

    DNA microarray analysis is characterized by obtaining a large number of gene variables from a small number of observations. Cluster analysis is widely used to analyze DNA microarray data to make classification and diagnosis of disease. Because there are so many irrelevant and insignificant genes in a dataset, a feature selection approach must be employed in data analysis. The performance of cluster analysis of this high-throughput data depends on whether the feature selection approach chooses the most relevant genes associated with disease classes. Here we proposed a new method using multiple Orthogonal Partial Least Squares-Discriminant Analysis (mOPLS-DA) models and S-plots to select the most relevant genes to conduct three-class disease classification and prediction. We tested our method using Golub's leukemia microarray data. For three classes with subtypes, we proposed hierarchical orthogonal partial least squares-discriminant analysis (OPLS-DA) models and S-plots to select features for two main classes and their subtypes. For three classes in parallel, we employed three OPLS-DA models and S-plots to choose marker genes for each class. The power of feature selection to classify and predict three-class disease was evaluated using cluster analysis. Further, the general performance of our method was tested using four public datasets and compared with those of four other feature selection methods. The results revealed that our method effectively selected the most relevant features for disease classification and prediction, and its performance was better than that of the other methods.

  10. Genomic response to Wnt signalling is highly context-dependent - Evidence from DNA microarray and chromatin immunoprecipitation screens of Wnt/TCF targets

    International Nuclear Information System (INIS)

    Railo, Antti; Pajunen, Antti; Itaeranta, Petri; Naillat, Florence; Vuoristo, Jussi; Kilpelaeinen, Pekka; Vainio, Seppo

    2009-01-01

    Wnt proteins are important regulators of embryonic development, and dysregulated Wnt signalling is involved in the oncogenesis of several human cancers. Our knowledge of the downstream target genes is limited, however. We used a chromatin immunoprecipitation-based assay to isolate and characterize the actual gene segments through which Wnt-activatable transcription factors, TCFs, regulate transcription and an Affymetrix microarray analysis to study the global transcriptional response to the Wnt3a ligand. The anti-β-catenin immunoprecipitation of DNA-protein complexes from mouse NIH3T3 fibroblasts expressing a fusion protein of β-catenin and TCF7 resulted in the identification of 92 genes as putative TCF targets. GeneChip assays of gene expression performed on NIH3T3 cells and the rat pheochromocytoma cell line PC12 revealed 355 genes in NIH3T3 and 129 genes in the PC12 cells with marked changes in expression after Wnt3a stimulus. Only 2 Wnt-regulated genes were shared by both cell lines. Surprisingly, Disabled-2 was the only gene identified by the chromatin immunoprecipitation approach that displayed a marked change in expression in the GeneChip assay. Taken together, our approaches give an insight into the complex context-dependent nature of Wnt pathway transcriptional responses and identify Disabled-2 as a potential new direct target for Wnt signalling.

  11. Diagnostic and analytical applications of protein microarrays

    DEFF Research Database (Denmark)

    Dufva, Hans Martin; Christensen, C.B.V.

    2005-01-01

    DNA microarrays have changed the field of biomedical sciences over the past 10 years. For several reasons, antibody and other protein microarrays have not developed at the same rate. However, protein and antibody arrays have emerged as a powerful tool to complement DNA microarrays during the post...

  12. Missing value imputation in DNA microarrays based on conjugate gradient method.

    Science.gov (United States)

    Dorri, Fatemeh; Azmi, Paeiz; Dorri, Faezeh

    2012-02-01

    Analysis of gene expression profiles needs a complete matrix of gene array values; consequently, imputation methods have been suggested. In this paper, an algorithm that is based on conjugate gradient (CG) method is proposed to estimate missing values. k-nearest neighbors of the missed entry are first selected based on absolute values of their Pearson correlation coefficient. Then a subset of genes among the k-nearest neighbors is labeled as the best similar ones. CG algorithm with this subset as its input is then used to estimate the missing values. Our proposed CG based algorithm (CGimpute) is evaluated on different data sets. The results are compared with sequential local least squares (SLLSimpute), Bayesian principle component analysis (BPCAimpute), local least squares imputation (LLSimpute), iterated local least squares imputation (ILLSimpute) and adaptive k-nearest neighbors imputation (KNNKimpute) methods. The average of normalized root mean squares error (NRMSE) and relative NRMSE in different data sets with various missing rates shows CGimpute outperforms other methods. Copyright © 2011 Elsevier Ltd. All rights reserved.

  13. Identification of transcriptional factors and key genes in primary osteoporosis by DNA microarray.

    Science.gov (United States)

    Xie, Wengui; Ji, Lixin; Zhao, Teng; Gao, Pengfei

    2015-05-09

    A number of genes have been identified to be related with primary osteoporosis while less is known about the comprehensive interactions between regulating genes and proteins. We aimed to identify the differentially expressed genes (DEGs) and regulatory effects of transcription factors (TFs) involved in primary osteoporosis. The gene expression profile GSE35958 was obtained from Gene Expression Omnibus database, including 5 primary osteoporosis and 4 normal bone tissues. The differentially expressed genes between primary osteoporosis and normal bone tissues were identified by the same package in R language. The TFs of these DEGs were predicted with the Essaghir A method. DAVID (The Database for Annotation, Visualization and Integrated Discovery) was applied to perform the GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis of DEGs. After analyzing regulatory effects, a regulatory network was built between TFs and the related DEGs. A total of 579 DEGs was screened, including 310 up-regulated genes and 269 down-regulated genes in primary osteoporosis samples. In GO terms, more up-regulated genes were enriched in transcription regulator activity, and secondly in transcription factor activity. A total 10 significant pathways were enriched in KEGG analysis, including colorectal cancer, Wnt signaling pathway, Focal adhesion, and MAPK signaling pathway. Moreover, total 7 TFs were enriched, of which CTNNB1, SP1, and TP53 regulated most up-regulated DEGs. The discovery of the enriched TFs might contribute to the understanding of the mechanism of primary osteoporosis. Further research on genes and TFs related to the WNT signaling pathway and MAPK pathway is urgent for clinical diagnosis and directing treatment of primary osteoporosis.

  14. 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.

  15. 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

  16. 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.

  17. Automated detection of regions of interest for tissue microarray experiments: an image texture analysis

    International Nuclear Information System (INIS)

    Karaçali, Bilge; Tözeren, Aydin

    2007-01-01

    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. 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. 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. 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 (graded) by different pathologists. The region of interest

  18. Prenatal chromosomal microarray analysis in fetuses with congenital heart disease: a prospective cohort study.

    Science.gov (United States)

    Wang, Yan; Cao, Li; Liang, Dong; Meng, Lulu; Wu, Yun; Qiao, Fengchang; Ji, Xiuqing; Luo, Chunyu; Zhang, Jingjing; Xu, Tianhui; Yu, Bin; Wang, Leilei; Wang, Ting; Pan, Qiong; Ma, Dingyuan; Hu, Ping; Xu, Zhengfeng

    2018-02-01

    Currently, chromosomal microarray analysis is considered the first-tier test in pediatric care and prenatal diagnosis. However, the diagnostic yield of chromosomal microarray analysis for prenatal diagnosis of congenital heart disease has not been evaluated based on a large cohort. Our aim was to evaluate the clinical utility of chromosomal microarray as the first-tier test for chromosomal abnormalities in fetuses with congenital heart disease. In this prospective study, 602 prenatal cases of congenital heart disease were investigated using single nucleotide polymorphism array over a 5-year period. Overall, pathogenic chromosomal abnormalities were identified in 125 (20.8%) of 602 prenatal cases of congenital heart disease, with 52.0% of them being numerical chromosomal abnormalities. The detection rates of likely pathogenic copy number variations and variants of uncertain significance were 1.3% and 6.0%, respectively. The detection rate of pathogenic chromosomal abnormalities in congenital heart disease plus additional structural anomalies (48.9% vs 14.3%, P congenital heart disease group. Additionally, the detection rate in congenital heart disease with additional structural anomalies group was significantly higher than that in congenital heart disease with soft markers group (48.9% vs 19.8%, P congenital heart disease with additional structural anomalies and congenital heart disease with intrauterine growth retardation groups (48.9% vs 50.0%), congenital heart disease with soft markers and congenital heart disease with intrauterine growth retardation groups (19.8% vs 50.0%), or congenital heart disease with soft markers and isolated congenital heart disease groups (19.8% vs 14.3%). The detection rate in fetuses with congenital heart disease plus mild ventriculomegaly was significantly higher than in those with other types of soft markers (50.0% vs 15.6%, P congenital heart disease in clinical practice. Copyright © 2017 Elsevier Inc. All rights reserved.

  19. Previously unidentified changes in renal cell carcinoma gene expression identified by parametric analysis of microarray data

    International Nuclear Information System (INIS)

    Lenburg, Marc E; Liou, Louis S; Gerry, Norman P; Frampton, Garrett M; Cohen, Herbert T; Christman, Michael F

    2003-01-01

    Renal cell carcinoma is a common malignancy that often presents as a metastatic-disease for which there are no effective treatments. To gain insights into the mechanism of renal cell carcinogenesis, a number of genome-wide expression profiling studies have been performed. Surprisingly, there is very poor agreement among these studies as to which genes are differentially regulated. To better understand this lack of agreement we profiled renal cell tumor gene expression using genome-wide microarrays (45,000 probe sets) and compare our analysis to previous microarray studies. We hybridized total RNA isolated from renal cell tumors and adjacent normal tissue to Affymetrix U133A and U133B arrays. We removed samples with technical defects and removed probesets that failed to exhibit sequence-specific hybridization in any of the samples. We detected differential gene expression in the resulting dataset with parametric methods and identified keywords that are overrepresented in the differentially expressed genes with the Fisher-exact test. We identify 1,234 genes that are more than three-fold changed in renal tumors by t-test, 800 of which have not been previously reported to be altered in renal cell tumors. Of the only 37 genes that have been identified as being differentially expressed in three or more of five previous microarray studies of renal tumor gene expression, our analysis finds 33 of these genes (89%). A key to the sensitivity and power of our analysis is filtering out defective samples and genes that are not reliably detected. The widespread use of sample-wise voting schemes for detecting differential expression that do not control for false positives likely account for the poor overlap among previous studies. Among the many genes we identified using parametric methods that were not previously reported as being differentially expressed in renal cell tumors are several oncogenes and tumor suppressor genes that likely play important roles in renal cell

  20. A benchmark for statistical microarray data analysis that preserves actual biological and technical variance.

    Science.gov (United States)

    De Hertogh, Benoît; De Meulder, Bertrand; Berger, Fabrice; Pierre, Michael; Bareke, Eric; Gaigneaux, Anthoula; Depiereux, Eric

    2010-01-11

    Recent reanalysis of spike-in datasets underscored the need for new and more accurate benchmark datasets for statistical microarray analysis. We present here a fresh method using biologically-relevant data to evaluate the performance of statistical methods. Our novel method ranks the probesets from a dataset composed of publicly-available biological microarray data and extracts subset matrices with precise information/noise ratios. Our method can be used to determine the capability of different methods to better estimate variance for a given number of replicates. The mean-variance and mean-fold change relationships of the matrices revealed a closer approximation of biological reality. Performance analysis refined the results from benchmarks published previously.We show that the Shrinkage t test (close to Limma) was the best of the methods tested, except when two replicates were examined, where the Regularized t test and the Window t test performed slightly better. The R scripts used for the analysis are available at http://urbm-cluster.urbm.fundp.ac.be/~bdemeulder/.

  1. The global response of Nostoc punctiforme ATCC 29133 to UVA stress, assessed in a temporal DNA microarray study.

    Science.gov (United States)

    Soule, Tanya; Gao, Qunjie; Stout, Valerie; Garcia-Pichel, Ferran

    2013-01-01

    Cyanobacteria in nature are exposed not only to the visible spectrum of sunlight but also to its harmful ultraviolet components (UVA and UVB). We used Nostoc punctiforme ATCC 29133 as a model to study the UVA response by analyzing global gene expression patterns using genomic microarrays. UVA exposure resulted in the statistically detectable differential expression of 573 genes of the 6903 that were probed, compared with that of the control cultures. Of those genes, 473 were up-regulated, while only 100 were down-regulated. Many of the down-regulated genes were involved in photosynthetic pigment biosynthesis, indicating a significant shift in this metabolism. As expected, we detected the up-regulation of genes encoding antioxidant enzymes and the sunscreen, scytonemin. However, a majority of the up-regulated genes, 47%, were unassignable bioinformatically to known functional categories, suggesting that the UVA stress response is not well understood. Interestingly, the most dramatic up-regulation involved several contiguous genes of unassigned metabolism on plasmid A. This is the first global UVA stress response analysis of any phototrophic microorganism and the differential expression of 8% of the genes of the Nostoc genome indicates that adaptation to UVA in Nostoc has been an evolutionary force of significance. © 2012 Wiley Periodicals, Inc. Photochemistry and Photobiology © 2012 The American Society of Photobiology.

  2. Segment and fit thresholding: a new method for image analysis applied to microarray and immunofluorescence data.

    Science.gov (United States)

    Ensink, Elliot; Sinha, Jessica; Sinha, Arkadeep; Tang, Huiyuan; Calderone, Heather M; Hostetter, Galen; Winter, Jordan; Cherba, David; Brand, Randall E; Allen, Peter J; Sempere, Lorenzo F; Haab, Brian B

    2015-10-06

    Experiments involving the high-throughput quantification of image data require algorithms for automation. A challenge in the development of such algorithms is to properly interpret signals over a broad range of image characteristics, without the need for manual adjustment of parameters. Here we present a new approach for locating signals in image data, called Segment and Fit Thresholding (SFT). The method assesses statistical characteristics of small segments of the image and determines the best-fit trends between the statistics. Based on the relationships, SFT identifies segments belonging to background regions; analyzes the background to determine optimal thresholds; and analyzes all segments to identify signal pixels. We optimized the initial settings for locating background and signal in antibody microarray and immunofluorescence data and found that SFT performed well over multiple, diverse image characteristics without readjustment of settings. When used for the automated analysis of multicolor, tissue-microarray images, SFT correctly found the overlap of markers with known subcellular localization, and it performed better than a fixed threshold and Otsu's method for selected images. SFT promises to advance the goal of full automation in image analysis.

  3. Large scale aggregate microarray analysis reveals three distinct molecular subclasses of human preeclampsia.

    Science.gov (United States)

    Leavey, Katherine; Bainbridge, Shannon A; Cox, Brian J

    2015-01-01

    Preeclampsia (PE) is a life-threatening hypertensive pathology of pregnancy affecting 3-5% of all pregnancies. To date, PE has no cure, early detection markers, or effective treatments short of the removal of what is thought to be the causative organ, the placenta, which may necessitate a preterm delivery. Additionally, numerous small placental microarray studies attempting to identify "PE-specific" genes have yielded inconsistent results. We therefore hypothesize that preeclampsia is a multifactorial disease encompassing several pathology subclasses, and that large cohort placental gene expression analysis will reveal these groups. To address our hypothesis, we utilized known bioinformatic methods to aggregate 7 microarray data sets across multiple platforms in order to generate a large data set of 173 patient samples, including 77 with preeclampsia. Unsupervised clustering of these patient samples revealed three distinct molecular subclasses of PE. This included a "canonical" PE subclass demonstrating elevated expression of known PE markers and genes associated with poor oxygenation and increased secretion, as well as two other subclasses potentially representing a poor maternal response to pregnancy and an immunological presentation of preeclampsia. Our analysis sheds new light on the heterogeneity of PE patients, and offers up additional avenues for future investigation. Hopefully, our subclassification of preeclampsia based on molecular diversity will finally lead to the development of robust diagnostics and patient-based treatments for this disorder.

  4. Prognostic value of matrix metalloproteinase 9 expression in patients with juvenile nasopharyngeal angiofibroma: tissue microarray analysis.

    Science.gov (United States)

    Sun, Xicai; Guo, Limin; Wang, Jingjing; Wang, Huan; Liu, Zhuofu; Liu, Juan; Yu, Huapeng; Hu, Li; Li, Han; Wang, Dehui

    2014-08-01

    Although JNA is a benign neoplasm histopathologically, it has a propensity for locally destructive growth and remains a higher postoperative recurrence rate. The aim of this study was to analyze the expression and localization of MMP-9 in JNA using tissue microarray to elucidate its correlation with clinicopathological features and recurrence. The expression of MMP-9 was assessed by immunohistochemistry in a tissue microarray from 70 patients with JNA and 10 control subjects. Correlation between the levels of MMP-9 expression and clinicopathologic variables, as well as tumor recurrence, were analyzed. MMP-9 was detected in perivascular and extravascular less differentiated cells and stromal cells of patients with JNA but not in the matured vascular endothelial cells of these patients. The presence of MMP-9 expression in JNA was correlated with patient's age (p=0.001). Spearman correlation analysis suggested that high expression of MMP-9 in JNA had negative correlation with patient's age (r=-0.412, p<0.001). The recurrence rate in JNA patients with high MMP-9 expression was significantly higher than those with low MMP-9 expression (p=0.002). In multivariate and ROC curve analysis, MMP-9 was a good prognostic factor for tumor recurrence of JNA. Higher MMP-9 expression is a poor prognostic factor for patients with JNA who have been surgically treated. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  5. Evaluation of Different Normalization and Analysis Procedures for Illumina Gene Expression Microarray Data Involving Small Changes

    Science.gov (United States)

    Johnstone, Daniel M.; Riveros, Carlos; Heidari, Moones; Graham, Ross M.; Trinder, Debbie; Berretta, Regina; Olynyk, John K.; Scott, Rodney J.; Moscato, Pablo; Milward, Elizabeth A.

    2013-01-01

    While Illumina microarrays can be used successfully for detecting small gene expression changes due to their high degree of technical replicability, there is little information on how different normalization and differential expression analysis strategies affect outcomes. To evaluate this, we assessed concordance across gene lists generated by applying different combinations of normalization strategy and analytical approach to two Illumina datasets with modest expression changes. In addition to using traditional statistical approaches, we also tested an approach based on combinatorial optimization. We found that the choice of both normalization strategy and analytical approach considerably affected outcomes, in some cases leading to substantial differences in gene lists and subsequent pathway analysis results. Our findings suggest that important biological phenomena may be overlooked when there is a routine practice of using only one approach to investigate all microarray datasets. Analytical artefacts of this kind are likely to be especially relevant for datasets involving small fold changes, where inherent technical variation—if not adequately minimized by effective normalization—may overshadow true biological variation. This report provides some basic guidelines for optimizing outcomes when working with Illumina datasets involving small expression changes. PMID:27605185

  6. Interspecies hybridization on DNA resequencing microarrays: efficiency of sequence recovery and accuracy of SNP detection in human, ape, and codfish mitochondrial DNA genomes sequenced on a human-specific MitoChip

    Directory of Open Access Journals (Sweden)

    Carr Steven M

    2007-09-01

    Full Text Available Abstract Background Iterative DNA "resequencing" on oligonucleotide microarrays offers a high-throughput method to measure intraspecific biodiversity, one that is especially suited to SNP-dense gene regions such as vertebrate mitochondrial (mtDNA genomes. However, costs of single-species design and microarray fabrication are prohibitive. A cost-effective, multi-species strategy is to hybridize experimental DNAs from diverse species to a common microarray that is tiled with oligonucleotide sets from multiple, homologous reference genomes. Such a strategy requires that cross-hybridization between the experimental DNAs and reference oligos from the different species not interfere with the accurate recovery of species-specific data. To determine the pattern and limits of such interspecific hybridization, we compared the efficiency of sequence recovery and accuracy of SNP identification by a 15,452-base human-specific microarray challenged with human, chimpanzee, gorilla, and codfish mtDNA genomes. Results In the human genome, 99.67% of the sequence was recovered with 100.0% accuracy. Accuracy of SNP identification declines log-linearly with sequence divergence from the reference, from 0.067 to 0.247 errors per SNP in the chimpanzee and gorilla genomes, respectively. Efficiency of sequence recovery declines with the increase of the number of interspecific SNPs in the 25b interval tiled by the reference oligonucleotides. In the gorilla genome, which differs from the human reference by 10%, and in which 46% of these 25b regions contain 3 or more SNP differences from the reference, only 88% of the sequence is recoverable. In the codfish genome, which differs from the reference by > 30%, less than 4% of the sequence is recoverable, in short islands ≥ 12b that are conserved between primates and fish. Conclusion Experimental DNAs bind inefficiently to homologous reference oligonucleotide sets on a re-sequencing microarray when their sequences differ by

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

    Directory of Open Access Journals (Sweden)

    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.

  8. DATE analysis: A general theory of biological change applied to microarray data.

    Science.gov (United States)

    Rasnick, David

    2009-01-01

    In contrast to conventional data mining, which searches for specific subsets of genes (extensive variables) to correlate with specific phenotypes, DATE analysis correlates intensive state variables calculated from the same datasets. At the heart of DATE analysis are two biological equations of state not dependent on genetic pathways. This result distinguishes DATE analysis from other bioinformatics approaches. The dimensionless state variable F quantifies the relative overall cellular activity of test cells compared to well-chosen reference cells. The variable pi(i) is the fold-change in the expression of the ith gene of test cells relative to reference. It is the fraction phi of the genome undergoing differential expression-not the magnitude pi-that controls biological change. The state variable phi is equivalent to the control strength of metabolic control analysis. For tractability, DATE analysis assumes a linear system of enzyme-connected networks and exploits the small average contribution of each cellular component. This approach was validated by reproducible values of the state variables F, RNA index, and phi calculated from random subsets of transcript microarray data. Using published microarray data, F, RNA index, and phi were correlated with: (1) the blood-feeding cycle of the malaria parasite, (2) embryonic development of the fruit fly, (3) temperature adaptation of Killifish, (4) exponential growth of cultured S. pneumoniae, and (5) human cancers. DATE analysis was applied to aCGH data from the great apes. A good example of the power of DATE analysis is its application to genomically unstable cancers, which have been refractory to data mining strategies. 2009 American Institute of Chemical Engineers Biotechnol.

  9. Fractals in DNA sequence analysis

    Institute of Scientific and Technical Information of China (English)

    Yu Zu-Guo(喻祖国); Vo Anh; Gong Zhi-Min(龚志民); Long Shun-Chao(龙顺潮)

    2002-01-01

    Fractal methods have been successfully used to study many problems in physics, mathematics, engineering, finance,and even in biology. There has been an increasing interest in unravelling the mysteries of DNA; for example, how can we distinguish coding and noncoding sequences, and the problems of classification and evolution relationship of organisms are key problems in bioinformatics. Although much research has been carried out by taking into consideration the long-range correlations in DNA sequences, and the global fractal dimension has been used in these works by other people, the models and methods are somewhat rough and the results are not satisfactory. In recent years, our group has introduced a time series model (statistical point of view) and a visual representation (geometrical point of view)to DNA sequence analysis. We have also used fractal dimension, correlation dimension, the Hurst exponent and the dimension spectrum (multifractal analysis) to discuss problems in this field. In this paper, we introduce these fractal models and methods and the results of DNA sequence analysis.

  10. Performance analysis of clustering techniques over microarray data: A case study

    Science.gov (United States)

    Dash, Rasmita; Misra, Bijan Bihari

    2018-03-01

    Handling big data is one of the major issues in the field of statistical data analysis. In such investigation cluster analysis plays a vital role to deal with the large scale data. There are many clustering techniques with different cluster analysis approach. But which approach suits a particular dataset is difficult to predict. To deal with this problem a grading approach is introduced over many clustering techniques to identify a stable technique. But the grading approach depends on the characteristic of dataset as well as on the validity indices. So a two stage grading approach is implemented. In this study the grading approach is implemented over five clustering techniques like hybrid swarm based clustering (HSC), k-means, partitioning around medoids (PAM), vector quantization (VQ) and agglomerative nesting (AGNES). The experimentation is conducted over five microarray datasets with seven validity indices. The finding of grading approach that a cluster technique is significant is also established by Nemenyi post-hoc hypothetical test.

  11. Comparison of two DNA microarrays for detection of plasmid-mediated antimicrobial resistance and virulence factor genes in clinical isolates of Enterobacteriaceae and non-Enterobacteriaceae.

    LENUS (Irish Health Repository)

    Walsh, Fiona

    2010-06-01

    A DNA microarray was developed to detect plasmid-mediated antimicrobial resistance (AR) and virulence factor (VF) genes in clinical isolates of Enterobacteriaceae and non-Enterobacteriaceae. The array was validated with the following bacterial species: Escherichiacoli (n=17); Klebsiellapneumoniae (n=3); Enterobacter spp. (n=6); Acinetobacter genospecies 3 (n=1); Acinetobacterbaumannii (n=1); Pseudomonasaeruginosa (n=2); and Stenotrophomonasmaltophilia (n=2). The AR gene profiles of these isolates were identified by polymerase chain reaction (PCR). The DNA microarray consisted of 155 and 133 AR and VF gene probes, respectively. Results were compared with the commercially available Identibac AMR-ve Array Tube. Hybridisation results indicated that there was excellent correlation between PCR and array results for AR and VF genes. Genes conferring resistance to each antibiotic class were identified by the DNA array. Unusual resistance genes were also identified, such as bla(SHV-5) in a bla(OXA-23)-positive carbapenem-resistant A. baumannii. The phylogenetic group of each E. coli isolate was verified by the array. These data demonstrate that it is possible to screen simultaneously for all important classes of mobile AR and VF genes in Enterobacteriaceae and non-Enterobacteriaceae whilst also assigning a correct phylogenetic group to E. coli isolates. Therefore, it is feasible to test clinical Gram-negative bacteria for all known AR genes and to provide important information regarding pathogenicity simultaneously.

  12. Chromosomal Microarray Analysis of Consecutive Individuals with Autism Spectrum Disorders Using an Ultra-High Resolution Chromosomal Microarray Optimized for Neurodevelopmental Disorders

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    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.

  13. 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.

  14. Statistical Analysis of Microarray Data with Replicated Spots: A Case Study with Synechococcus WH8102

    Directory of Open Access Journals (Sweden)

    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.

  15.  DNA microarray-based gene expression profiling in diagnosis, assessing prognosis and predicting response to therapy in colorectal cancer

    Directory of Open Access Journals (Sweden)

    Przemysław Kwiatkowski

    2012-06-01

    Full Text Available  Colorectal cancer is the most common cancer of the gastrointestinal tract. It is considered as a biological model of a certain type of cancerogenesis process in which progression from an early to late stage adenoma and cancer is accompanied by distinct genetic alterations.Clinical and pathological parameters commonly used in clinical practice are often insufficient to determine groups of patients suitable for personalized treatment. Moreover, reliable molecular markers with high prognostic value have not yet been determined. Molecular studies using DNA-based microarrays have identified numerous genes involved in cell proliferation and differentiation during the process of cancerogenesis. Assessment of the genetic profile of colorectal cancer using the microarray technique might be a useful tool in determining the groups of patients with different clinical outcomes who would benefit from additional personalized treatment.The main objective of this study was to present the current state of knowledge on the practical application of gene profiling techniques using microarrays for determining diagnosis, prognosis and response to treatment in colorectal cancer.

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

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    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

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

    International Nuclear Information System (INIS)

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

    2011-01-01

    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.

    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

  19. 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.

  20. Adaptation of a Bioinformatics Microarray Analysis Workflow for a Toxicogenomic Study in Rainbow Trout.

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    Sophie Depiereux

    Full Text Available Sex steroids play a key role in triggering sex differentiation in fish, the use of exogenous hormone treatment leading to partial or complete sex reversal. This phenomenon has attracted attention since the discovery that even low environmental doses of exogenous steroids can adversely affect gonad morphology (ovotestis development and induce reproductive failure. Modern genomic-based technologies have enhanced opportunities to find out mechanisms of actions (MOA and identify biomarkers related to the toxic action of a compound. However, high throughput data interpretation relies on statistical analysis, species genomic resources, and bioinformatics tools. The goals of this study are to improve the knowledge of feminisation in fish, by the analysis of molecular responses in the gonads of rainbow trout fry after chronic exposure to several doses (0.01, 0.1, 1 and 10 μg/L of ethynylestradiol (EE2 and to offer target genes as potential biomarkers of ovotestis development. We successfully adapted a bioinformatics microarray analysis workflow elaborated on human data to a toxicogenomic study using rainbow trout, a fish species lacking accurate functional annotation and genomic resources. The workflow allowed to obtain lists of genes supposed to be enriched in true positive differentially expressed genes (DEGs, which were subjected to over-representation analysis methods (ORA. Several pathways and ontologies, mostly related to cell division and metabolism, sexual reproduction and steroid production, were found significantly enriched in our analyses. Moreover, two sets of potential ovotestis biomarkers were selected using several criteria. The first group displayed specific potential biomarkers belonging to pathways/ontologies highlighted in the experiment. Among them, the early ovarian differentiation gene foxl2a was overexpressed. The second group, which was highly sensitive but not specific, included the DEGs presenting the highest fold change and

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

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    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.

  2. Genomotyping of Pseudomonas putida strains using P. putida KT2440-based high-density DNA microarrays: Implications for transcriptomics studies

    NARCIS (Netherlands)

    Ballerstedt, H.; Volkers, R.J.M.; Mars, A.E.; Hallsworth, J.E.; Santos, V.A.M.D.; Puchalka, J.; Duuren, J. van; Eggink, G.; Timmis, K.N.; Bont, J.A.M. de; Wery, J.

    2007-01-01

    Pseudomonas putida KT2440 is the only fully sequenced P. putida strain. Thus, for transcriptomics and proteomics studies with other P. putida strains, the P. putida KT2440 genomic database serves as standard reference. The utility of KT2440 whole-genome, high-density oligonucleotide microarrays for

  3. PhyloChip microarray analysis reveals altered gastrointestinal microbial communities in a rat model of colonic hypersensitivity

    Energy Technology Data Exchange (ETDEWEB)

    Nelson, T.A.; Holmes, S.; Alekseyenko, A.V.; Shenoy, M.; DeSantis, T.; Wu, C.H.; Andersen, G.L.; Winston, J.; Sonnenburg, J.; Pasricha, P.J.; Spormann, A.

    2010-12-01

    Irritable bowel syndrome (IBS) is a chronic, episodic gastrointestinal disorder that is prevalent in a significant fraction of western human populations; and changes in the microbiota of the large bowel have been implicated in the pathology of the disease. Using a novel comprehensive, high-density DNA microarray (PhyloChip) we performed a phylogenetic analysis of the microbial community of the large bowel in a rat model in which intracolonic acetic acid in neonates was used to induce long lasting colonic hypersensitivity and decreased stool water content and frequency, representing the equivalent of human constipation-predominant IBS. Our results revealed a significantly increased compositional difference in the microbial communities in rats with neonatal irritation as compared with controls. Even more striking was the dramatic change in the ratio of Firmicutes relative to Bacteroidetes, where neonatally irritated rats were enriched more with Bacteroidetes and also contained a different composition of species within this phylum. Our study also revealed differences at the level of bacterial families and species. The PhyloChip is a useful and convenient method to study enteric microflora. Further, this rat model system may be a useful experimental platform to study the causes and consequences of changes in microbial community composition associated with IBS.

  4. Porous Silicon Antibody Microarrays for Quantitative Analysis: Measurement of Free and Total PSA in Clinical Plasma Samples

    Science.gov (United States)

    Tojo, Axel; Malm, Johan; Marko-Varga, György; Lilja, Hans; Laurell, Thomas

    2014-01-01

    The antibody microarrays have become widespread, but their use for quantitative analyses in clinical samples has not yet been established. We investigated an immunoassay based on nanoporous silicon antibody microarrays for quantification of total prostate-specific-antigen (PSA) in 80 clinical plasma samples, and provide quantitative data from a duplex microarray assay that simultaneously quantifies free and total PSA in plasma. To further develop the assay the porous silicon chips was placed into a standard 96-well microtiter plate for higher throughput analysis. The samples analyzed by this quantitative microarray were 80 plasma samples obtained from men undergoing clinical PSA testing (dynamic range: 0.14-44ng/ml, LOD: 0.14ng/ml). The second dataset, measuring free PSA (dynamic range: 0.40-74.9ng/ml, LOD: 0.47ng/ml) and total PSA (dynamic range: 0.87-295ng/ml, LOD: 0.76ng/ml), was also obtained from the clinical routine. The reference for the quantification was a commercially available assay, the ProStatus PSA Free/Total DELFIA. In an analysis of 80 plasma samples the microarray platform performs well across the range of total PSA levels. This assay might have the potential to substitute for the large-scale microtiter plate format in diagnostic applications. The duplex assay paves the way for a future quantitative multiplex assay, which analyses several prostate cancer biomarkers simultaneously. PMID:22921878

  5. Gametogenesis in the Pacific oyster Crassostrea gigas: a microarrays-based analysis identifies sex and stage specific genes.

    Directory of Open Access Journals (Sweden)

    Nolwenn M Dheilly

    Full Text Available BACKGROUND: The Pacific oyster Crassostrea gigas (Mollusca, Lophotrochozoa is an alternative and irregular protandrous hermaphrodite: most individuals mature first as males and then change sex several times. Little is known about genetic and phenotypic basis of sex differentiation in oysters, and little more about the molecular pathways regulating reproduction. We have recently developed and validated a microarray containing 31,918 oligomers (Dheilly et al., 2011 representing the oyster transcriptome. The application of this microarray to the study of mollusk gametogenesis should provide a better understanding of the key factors involved in sex differentiation and the regulation of oyster reproduction. METHODOLOGY/PRINCIPAL FINDINGS: Gene expression was studied in gonads of oysters cultured over a yearly reproductive cycle. Principal component analysis and hierarchical clustering showed a significant divergence in gene expression patterns of males and females coinciding with the start of gonial mitosis. ANOVA analysis of the data revealed 2,482 genes differentially expressed during the course of males and/or females gametogenesis. The expression of 434 genes could be localized in either germ cells or somatic cells of the gonad by comparing the transcriptome of female gonads to the transcriptome of stripped oocytes and somatic tissues. Analysis of the annotated genes revealed conserved molecular mechanisms between mollusks and mammals: genes involved in chromatin condensation, DNA replication and repair, mitosis and meiosis regulation, transcription, translation and apoptosis were expressed in both male and female gonads. Most interestingly, early expressed male-specific genes included bindin and a dpy-30 homolog and female-specific genes included foxL2, nanos homolog 3, a pancreatic lipase related protein, cd63 and vitellogenin. Further functional analyses are now required in order to investigate their role in sex differentiation in oysters

  6. 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

  7. 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

  8. 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.

  9. 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.

  10. PAX3 gene deletion detected by microarray analysis in a girl with hearing loss.

    Science.gov (United States)

    Drozniewska, Malgorzata; Haus, Olga

    2014-01-01

    Deletions of the PAX3 gene have been rarely reported in the literature. Mutations of this gene are a common cause of Waardenburg syndrome type 1 and 3. We report a 16 year old female presenting hearing loss and normal intellectual development, without major features of Waardenburg syndrome type 1, and without family history of the syndrome. Her phenotype, however, overlaps with features of craniofacial-deafness-hand syndrome. Microarray analysis showed ~862 kb de novo deletion at 2q36.1 including PAX3. The above findings suggest that the rearrangement found in our patient appeared de novo and with high probability is a cause of her phenotype.

  11. A new locally weighted K-means for cancer-aided microarray data analysis.

    Science.gov (United States)

    Iam-On, Natthakan; Boongoen, Tossapon

    2012-11-01

    Cancer has been identified as the leading cause of death. It is predicted that around 20-26 million people will be diagnosed with cancer by 2020. With this alarming rate, there is an urgent need for a more effective methodology to understand, prevent and cure cancer. Microarray technology provides a useful basis of achieving this goal, with cluster analysis of gene expression data leading to the discrimination of patients, identification of possible tumor subtypes and individualized treatment. Amongst clustering techniques, k-means is normally chosen for its simplicity and efficiency. However, it does not account for the different importance of data attributes. This paper presents a new locally weighted extension of k-means, which has proven more accurate across many published datasets than the original and other extensions found in the literature.

  12. Microarray meta-analysis to explore abiotic stress-specific gene expression patterns in Arabidopsis.

    Science.gov (United States)

    Shen, Po-Chih; Hour, Ai-Ling; Liu, Li-Yu Daisy

    2017-12-01

    Abiotic stresses are the major limiting factors that affect plant growth, development, yield and final quality. Deciphering the underlying mechanisms of plants' adaptations to stresses using few datasets might overlook the different aspects of stress tolerance in plants, which might be simultaneously and consequently operated in the system. Fortunately, the accumulated microarray expression data offer an opportunity to infer abiotic stress-specific gene expression patterns through meta-analysis. In this study, we propose to combine microarray gene expression data under control, cold, drought, heat, and salt conditions and determined modules (gene sets) of genes highly associated with each other according to the observed expression data. By analyzing the expression variations of the Eigen genes from different conditions, we had identified two, three, and five gene modules as cold-, heat-, and salt-specific modules, respectively. Most of the cold- or heat-specific modules were differentially expressed to a particular degree in shoot samples, while most of the salt-specific modules were differentially expressed to a particular degree in root samples. A gene ontology (GO) analysis on the stress-specific modules suggested that the gene modules exclusively enriched stress-related GO terms and that different genes under the same GO terms may be alternatively disturbed in different conditions. The gene regulatory events for two genes, DREB1A and DEAR1, in the cold-specific gene module had also been validated, as evidenced through the literature search. Our protocols study the specificity of the gene modules that were specifically activated under a particular type of abiotic stress. The biplot can also assist to visualize the stress-specific gene modules. In conclusion, our approach has the potential to further elucidate mechanisms in plants and beneficial for future experiments design under different abiotic stresses.

  13. Identification of cytokinin-responsive genes using microarray meta-analysis and RNA-Seq in Arabidopsis.

    Science.gov (United States)

    Bhargava, Apurva; Clabaugh, Ivory; To, Jenn P; Maxwell, Bridey B; Chiang, Yi-Hsuan; Schaller, G Eric; Loraine, Ann; Kieber, Joseph J

    2013-05-01

    Cytokinins are N(6)-substituted adenine derivatives that play diverse roles in plant growth and development. We sought to define a robust set of genes regulated by cytokinin as well as to query the response of genes not represented on microarrays. To this end, we performed a meta-analysis of microarray data from a variety of cytokinin-treated samples and used RNA-seq to examine cytokinin-regulated gene expression in Arabidopsis (Arabidopsis thaliana). Microarray meta-analysis using 13 microarray experiments combined with empirically defined filtering criteria identified a set of 226 genes differentially regulated by cytokinin, a subset of which has previously been validated by other methods. RNA-seq validated about 73% of the up-regulated genes identified by this meta-analysis. In silico promoter analysis indicated an overrepresentation of type-B Arabidopsis response regulator binding elements, consistent with the role of type-B Arabidopsis response regulators as primary mediators of cytokinin-responsive gene expression. RNA-seq analysis identified 73 cytokinin-regulated genes that were not represented on the ATH1 microarray. Representative genes were verified using quantitative reverse transcription-polymerase chain reaction and NanoString analysis. Analysis of the genes identified reveals a substantial effect of cytokinin on genes encoding proteins involved in secondary metabolism, particularly those acting in flavonoid and phenylpropanoid biosynthesis, as well as in the regulation of redox state of the cell, particularly a set of glutaredoxin genes. Novel splicing events were found in members of some gene families that are known to play a role in cytokinin signaling or metabolism. The genes identified in this analysis represent a robust set of cytokinin-responsive genes that are useful in the analysis of cytokinin function in plants.

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

    Directory of Open Access Journals (Sweden)

    Robert T Gaeta

    . Furthermore, our microarray analysis did not provide strong evidence that homoeologous rearrangements were a determinant of genome-wide nonadditive gene expression. In light of the inherent limitations of the Arabidopsis microarray to measure gene expression in polyploid Brassicas, further studies are warranted.

  15. Multiplexed Analysis of Serum Breast and Ovarian Cancer Markers by Means of Suspension Bead-quantum Dot Microarrays

    Science.gov (United States)

    Brazhnik, Kristina; Sokolova, Zinaida; Baryshnikova, Maria; Bilan, Regina; Nabiev, Igor; Sukhanova, Alyona

    Multiplexed analysis of cancer markers is crucial for early tumor diagnosis and screening. We have designed lab-on-a-bead microarray for quantitative detection of three breast cancer markers in human serum. Quantum dots were used as bead-bound fluorescent tags for identifying each marker by means of flow cytometry. Antigen-specific beads reliably detected CA 15-3, CEA, and CA 125 in serum samples, providing clear discrimination between the samples with respect to the antigen levels. The novel microarray is advantageous over the routine single-analyte ones due to the simultaneous detection of various markers. Therefore the developed microarray is a promising tool for serum tumor marker profiling.

  16. From microarray to biology: an integrated experimental, statistical and in silico analysis of how the extracellular matrix modulates the phenotype of cancer cells

    OpenAIRE

    Centola Michael B; Dozmorov Igor; Buethe David D; Saban Ricardo; Hauser Paul J; Kyker Kimberly D; Dozmorov Mikhail G; Culkin Daniel J; Hurst Robert E

    2008-01-01

    Abstract A statistically robust and biologically-based approach for analysis of microarray data is described that integrates independent biological knowledge and data with a global F-test for finding genes of interest that minimizes the need for replicates when used for hypothesis generation. First, each microarray is normalized to its noise level around zero. The microarray dataset is then globally adjusted by robust linear regression. Second, genes of interest that capture significant respo...

  17. 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.

  18. Global Microarray Analysis of Carbohydrate Use in Alkaliphilic Hemicellulolytic Bacterium Bacillus sp. N16-5

    Science.gov (United States)

    Song, Yajian; Xue, Yanfen; Ma, Yanhe

    2013-01-01

    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. PMID:23326578

  19. 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.

  20. Using microarray analysis as a prognostic and predictive tool in oncology: focus on breast cancer and normal tissue toxicity

    NARCIS (Netherlands)

    Nuyten, Dimitry S. A.; van de Vijver, Marc J.

    2008-01-01

    Microarray analysis makes it possible to study the expression levels of tens of thousands of genes in one single experiment and is widely available for research purposes. Gene expression profiling is currently being used in many research projects aimed at identifying gene expression signatures in

  1. Microarray Study of Pathway Analysis Expression Profile Associated with MicroRNA-29a with Regard to Murine Cholestatic Liver Injuries

    Directory of Open Access Journals (Sweden)

    Sung-Chou Li

    2016-03-01

    Full Text Available Accumulating evidence demonstrates that microRNA-29 (miR-29 expression is prominently decreased in patients with hepatic fibrosis, which consequently stimulates hepatic stellate cells’ (HSCs activation. We used a cDNA microarray study to gain a more comprehensive understanding of genome-wide gene expressions by adjusting miR-29a expression in a bile duct-ligation (BDL animal model. Methods: Using miR-29a transgenic mice and wild-type littermates and applying the BDL mouse model, we characterized the function of miR-29a with regard to cholestatic liver fibrosis. Pathway enrichment analysis and/or specific validation were performed for differentially expressed genes found within the comparisons. Results: Analysis of the microarray data identified a number of differentially expressed genes due to the miR-29a transgene, BDL, or both. Additional pathway enrichment analysis revealed that TGF-β signaling had a significantly differential activated pathway depending on the occurrence of miR-29a overexpression or the lack thereof. Furthermore, overexpression was found to elicit changes in Wnt/β-catenin after BDL. Conclusion: This study verified that an elevated miR-29a level could alleviate liver fibrosis caused by cholestasis. Furthermore, the protective effects of miR-29a correlate with the downregulation of TGF-β and associated with Wnt/β-catenin signal pathway following BDL.

  2. [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.

  3. Genomic DNA Enrichment Using Sequence Capture Microarrays: a Novel Approach to Discover Sequence Nucleotide Polymorphisms (SNP) in Brassica napus L

    Science.gov (United States)

    Clarke, Wayne E.; Parkin, Isobel A.; Gajardo, Humberto A.; Gerhardt, Daniel J.; Higgins, Erin; Sidebottom, Christine; Sharpe, Andrew G.; Snowdon, Rod J.; Federico, Maria L.; Iniguez-Luy, Federico L.

    2013-01-01

    Targeted genomic selection methodologies, or sequence capture, allow for DNA enrichment and large-scale resequencing and characterization of natural genetic variation in species with complex genomes, such as rapeseed canola (Brassica napus L., AACC, 2n=38). The main goal of this project was to combine sequence capture with next generation sequencing (NGS) to discover single nucleotide polymorphisms (SNPs) in specific areas of the B. napus genome historically associated (via quantitative trait loci –QTL– analysis) to traits of agronomical and nutritional importance. A 2.1 million feature sequence capture platform was designed to interrogate DNA sequence variation across 47 specific genomic regions, representing 51.2 Mb of the Brassica A and C genomes, in ten diverse rapeseed genotypes. All ten genotypes were sequenced using the 454 Life Sciences chemistry and to assess the effect of increased sequence depth, two genotypes were also sequenced using Illumina HiSeq chemistry. As a result, 589,367 potentially useful SNPs were identified. Analysis of sequence coverage indicated a four-fold increased representation of target regions, with 57% of the filtered SNPs falling within these regions. Sixty percent of discovered SNPs corresponded to transitions while 40% were transversions. Interestingly, fifty eight percent of the SNPs were found in genic regions while 42% were found in intergenic regions. Further, a high percentage of genic SNPs was found in exons (65% and 64% for the A and C genomes, respectively). Two different genotyping assays were used to validate the discovered SNPs. Validation rates ranged from 61.5% to 84% of tested SNPs, underpinning the effectiveness of this SNP discovery approach. Most importantly, the discovered SNPs were associated with agronomically important regions of the B. napus genome generating a novel data resource for research and breeding this crop species. PMID:24312619

  4. Microarray Expression Profile and Functional Analysis of Circular RNAs in Osteosarcoma

    Directory of Open Access Journals (Sweden)

    Weihai Liu

    2017-09-01

    Full Text Available Background/Aims: Osteosarcoma (OS is the most common primary malignant bone tumor in children and adolescents. However, the molecular mechanisms regulating osteosarcoma tumorigenesis and progression are still poorly understood. Circular RNAs (circRNAs have been identified as microRNA sponges and are involved in many important biological processes. This study aims to investigate the global changes in the expression pattern of circRNAs in osteosarcoma and provide a comprehensive understanding of differentially expressed circRNAs. Methods: Microarray based circRNA expression was determined in osteosarcoma cell lines and compared with hFOB1.19, which was used as the normal control. We confirmed the microarray data by real time-qPCR in both osteosarcoma cell lines and tissues. The circRNA/microRNA/mRNA interaction network was predicted using bioinformatics. Gene Ontology analysis and 4 annotation tools for pathway analysis (KEGG, Biocarta, PANTHER and Reactome were used to predict the functions of differentially expressed circRNAs. Results: We revealed a number of differentially expressed circRNAs and 12 of them were confirmed, which suggests a potential role of circRNAs in OS. Among these differentially expressed circRNAs, hsa_circRNA_103801 was up-regulated in both osteosarcoma cell lines and tissues, while hsa_circRNA_104980 was down-regulated. The most likely potential target miRNAs for hsa_circRNA_103801 include hsa-miR-370-3p, hsa-miR-338-3p and hsa-miR-877-3p, while the most potential target miRNAs of hsa_circRNA_104980 consist of hsa-miR-1298-3p and hsa-miR-660-3p. Functional analysis found that hsa_circRNA_103801 was involved in pathways in cancer, such as the HIF-1, VEGF and angiogenesis pathway, the Rap1 signaling pathway and the PI3K-Akt signaling pathway, while hsa_circRNA_104980 was related to some pathways such as the tight junction pathway. Conclusions: This study has identified the comprehensive expression profile of circRNAs in

  5. In Silico Analysis of Microarray-Based Gene Expression Profiles Predicts Tumor Cell Response to Withanolides

    Directory of Open Access Journals (Sweden)

    Thomas Efferth

    2012-05-01

    Full Text Available Withania somnifera (L. Dunal (Indian ginseng, winter cherry, Solanaceae is widely used in traditional medicine. Roots are either chewed or used to prepare beverages (aqueous decocts. The major secondary metabolites of Withania somnifera are the withanolides, which are C-28-steroidal lactone triterpenoids. Withania somnifera extracts exert chemopreventive and anticancer activities in vitro and in vivo. The aims of the present in silico study were, firstly, to investigate whether tumor cells develop cross-resistance between standard anticancer drugs and withanolides and, secondly, to elucidate the molecular determinants of sensitivity and resistance of tumor cells towards withanolides. Using IC50 concentrations of eight different withanolides (withaferin A, withaferin A diacetate, 3-azerininylwithaferin A, withafastuosin D diacetate, 4-B-hydroxy-withanolide E, isowithanololide E, withafastuosin E, and withaperuvin and 19 established anticancer drugs, we analyzed the cross-resistance profile of 60 tumor cell lines. The cell lines revealed cross-resistance between the eight withanolides. Consistent cross-resistance between withanolides and nitrosoureas (carmustin, lomustin, and semimustin was also observed. Then, we performed transcriptomic microarray-based COMPARE and hierarchical cluster analyses of mRNA expression to identify mRNA expression profiles predicting sensitivity or resistance towards withanolides. Genes from diverse functional groups were significantly associated with response of tumor cells to withaferin A diacetate, e.g. genes functioning in DNA damage and repair, stress response, cell growth regulation, extracellular matrix components, cell adhesion and cell migration, constituents of the ribosome, cytoskeletal organization and regulation, signal transduction, transcription factors, and others.

  6. [Application of chromosome microarray analysis for fetuses with multicystic dysplastic kidney].

    Science.gov (United States)

    Chen, Feifei; Lei, Tingying; Fu, Fang; Li, Ru; Zhang, Yongling; Jing, Xiangyi; Yang, Xin; Han, Jin; Zhen, Li; Pan, Min; Liao, Can

    2016-12-10

    To explore the genetic etiology of fetuses with multicystic dysplastic kidney (MCDK) by chromosome microarray analysis (CMA). Seventy-two fetuses with MCDK were analyzed with conventional cytogenetic technique, among which 30 fetuses with a normal karyotype were subjected to CMA analysis with Affymetrix CytoScan HD arrays by following the manufacturer's protocol. The data was analyzed with ChAS software. Conventional cytogenetic technique has revealed three fetuses (4.2%) with identifiable chromosomal aberrations. CMA analysis has detected pathogenic CNVs in 5 fetuses (16.7%), which included two well-known microdeletion or microduplication syndromes, i.e., 17q12 microdeletion syndrome and Williams-Beuren syndrome (WBS) and three submicroscopic imbalances at 4q35.2, 22q13.33, and 1p33. PEX26, FKBP6, TUBGCP6, ALG12, and CYP4A11 are likely the causative genes. CMA can identify the submicroscopic imbalances unidentifiable by conventional cytogenetic technique, and therefore has a significant role in prenatal diagnosis and genetic counseling. The detection rate of pathogenic CNVs in fetuses with MCDK was 16.7% by CMA. 17q12 microdeletion syndrome and WBS are associated with MCDK. Mutations of PEX26, FKBP6, TUBGCP6, ALG12, and CYP4A11 genes may be the causes for MCDK.

  7. Comprehensive analysis of preeclampsia-associated DNA methylation in the placenta.

    Directory of Open Access Journals (Sweden)

    Tianjiao Chu

    Full Text Available A small number of recent reports have suggested that altered placental DNA methylation may be associated with early onset preeclampsia. It is important that further studies be undertaken to confirm and develop these findings. We therefore undertook a systematic analysis of DNA methylation patterns in placental tissue from 24 women with preeclampsia and 24 with uncomplicated pregnancy outcome.We analyzed the DNA methylation status of approximately 27,000 CpG sites in placental tissues in a massively parallel fashion using an oligonucleotide microarray. Follow up analysis of DNA methylation at specific CpG loci was performed using the Epityper MassArray approach and high-throughput bisulfite sequencing.Preeclampsia-specific DNA methylation changes were identified in placental tissue samples irrespective of gestational age of delivery. In addition, we identified a group of CpG sites within specific gene sequences that were only altered in early onset-preeclampsia (EOPET although these DNA methylation changes did not correlate with altered mRNA transcription. We found evidence that fetal gender influences DNA methylation at autosomal loci but could find no clear association between DNA methylation and gestational age.Preeclampsia is associated with altered placental DNA methylation. Fetal gender should be carefully considered during the design of future studies in which placental DNA is analyzed at the level of DNA methylation. Further large-scale analyses of preeclampsia-associated DNA methylation are necessary.

  8. A Java-based tool for the design of classification microarrays.

    Science.gov (United States)

    Meng, Da; Broschat, Shira L; Call, Douglas R

    2008-08-04

    Classification microarrays are used for purposes such as identifying strains of bacteria and determining genetic relationships to understand the epidemiology of an infectious disease. For these cases, mixed microarrays, which are composed of DNA from more than one organism, are more effective than conventional microarrays composed of DNA from a single organism. Selection of probes is a key factor in designing successful mixed microarrays because redundant sequences are inefficient and limited representation of diversity can restrict application of the microarray. We have developed a Java-based software tool, called PLASMID, for use in selecting the minimum set of probe sequences needed to classify different groups of plasmids or bacteria. The software program was successfully applied to several different sets of data. The utility of PLASMID was illustrated using existing mixed-plasmid microarray data as well as data from a virtual mixed-genome microarray constructed from different strains of Streptococcus. Moreover, use of data from expression microarray experiments demonstrated the generality of PLASMID. In this paper we describe a new software tool for selecting a set of probes for a classification microarray. While the tool was developed for the design of mixed microarrays-and mixed-plasmid microarrays in particular-it can also be used to design expression arrays. The user can choose from several clustering methods (including hierarchical, non-hierarchical, and a model-based genetic algorithm), several probe ranking methods, and several different display methods. A novel approach is used for probe redundancy reduction, and probe selection is accomplished via stepwise discriminant analysis. Data can be entered in different formats (including Excel and comma-delimited text), and dendrogram, heat map, and scatter plot images can be saved in several different formats (including jpeg and tiff). Weights generated using stepwise discriminant analysis can be stored for

  9. The Immunome of Colon Cancer: Functional In Silico Analysis of Antigenic Proteins Deduced from IgG Microarray Profiling

    Directory of Open Access Journals (Sweden)

    Johana A. Luna Coronell

    2018-02-01

    Full Text Available Characterization of the colon cancer immunome and its autoantibody signature from differentially-reactive antigens (DIRAGs could provide insights into aberrant cellular mechanisms or enriched networks associated with diseases. The purpose of this study was to characterize the antibody profile of plasma samples from 32 colorectal cancer (CRC patients and 32 controls using proteins isolated from 15,417 human cDNA expression clones on microarrays. 671 unique DIRAGs were identified and 632 were more highly reactive in CRC samples. Bioinformatics analyses reveal that compared to control samples, the immunoproteomic IgG profiling of CRC samples is mainly associated with cell death, survival, and proliferation pathways, especially proteins involved in EIF2 and mTOR signaling. Ribosomal proteins (e.g., RPL7, RPL22, and RPL27A and CRC-related genes such as APC, AXIN1, E2F4, MSH2, PMS2, and TP53 were highly enriched. In addition, differential pathways were observed between the CRC and control samples. Furthermore, 103 DIRAGs were reported in the SEREX antigen database, demonstrating our ability to identify known and new reactive antigens. We also found an overlap of 7 antigens with 48 “CRC genes.” These data indicate that immunomics profiling on protein microarrays is able to reveal the complexity of immune responses in cancerous diseases and faithfully reflects the underlying pathology. Keywords: Autoantibody tumor biomarker, Cancer immunology, Colorectal cancer, Immunomics, Protein microarray

  10. The Plasmodium falciparum Sexual Development Transcriptome: A Microarray Analysis using Ontology-Based Pattern Identification

    National Research Council Canada - National Science Library

    Young, Jason A; Fivelman, Quinton L; Blair, Peter L; de la Vega, Patricia; Le Roch, Karine G; Zhou, Yingyao; Carucci, Daniel J; Baker, David A; Winzeler, Elizabeth A

    2005-01-01

    ... a full-genome high-density oligonucleotide microarray. The interpretation of this transcriptional data was aided by applying a novel knowledge-based data-mining algorithm termed ontology-based pattern identification (OPI...

  11. A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability

    NARCIS (Netherlands)

    Sontrop, H.M.J.; Moerland, P.D.; Van den Ham, R.; Reinders, M.J.T.; Verhaegh, W.F.J.

    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

  12. A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability

    NARCIS (Netherlands)

    Sontrop, Herman M. J.; Moerland, Perry D.; van den Ham, René; Reinders, Marcel J. T.; Verhaegh, Wim F. J.

    2009-01-01

    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 the

  13. Microarray Gene Expression Analysis to Evaluate Cell Type Specific Expression of Targets Relevant for Immunotherapy of Hematological Malignancies.

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    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.

  14. Hematopoietic Lineage Transcriptome Stability and Representation in PAXgeneTM Collected Peripheral Blood Utilising SPIA Single-Stranded cDNA Probes for Microarray

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    Laura Kennedy

    2008-01-01

    Full Text Available Peripheral blood as a surrogate tissue for transcriptome profiling holds great promise for the discovery of diagnostic and prognostic disease biomarkers, particularly when target tissues of disease are not readily available. To maximize the reliability of gene expression data generated from clinical blood samples, both the sample collection and the microarray probe generation methods should be optimized to provide stabilized, reproducible and representative gene expression profiles faithfully representing the transcriptional profiles of the constituent blood cell types present in the circulation. Given the increasing innovation in this field in recent years, we investigated a combination of methodological advances in both RNA stabilisation and microarray probe generation with the goal of achieving robust, reliable and representative transcriptional profiles from whole blood. To assess the whole blood profiles, the transcriptomes of purified blood cell types were measured and compared with the global transcriptomes measured in whole blood. The results demonstrate that a combination of PAXgeneTM RNA stabilising technology and single-stranded cDNA probe generation afforded by the NuGEN Ovation RNA amplification system V2TM enables an approach that yields faithful representation of specific hematopoietic cell lineage transcriptomes in whole blood without the necessity for prior sample fractionation, cell enrichment or globin reduction. Storage stability assessments of the PAXgeneTM blood samples also advocate a short, fixed room temperature storage time for all PAXgeneTM blood samples collected for the purposes of global transcriptional profiling in clinical studies.

  15. Hematopoietic Lineage Transcriptome Stability and Representation in PAXgene Collected Peripheral Blood Utilising SPIA Single-Stranded cDNA Probes for Microarray.

    Science.gov (United States)

    Kennedy, Laura; Vass, J Keith; Haggart, D Ross; Moore, Steve; Burczynski, Michael E; Crowther, Dan; Miele, Gino

    2008-08-25

    Peripheral blood as a surrogate tissue for transcriptome profiling holds great promise for the discovery of diagnostic and prognostic disease biomarkers, particularly when target tissues of disease are not readily available. To maximize the reliability of gene expression data generated from clinical blood samples, both the sample collection and the microarray probe generation methods should be optimized to provide stabilized, reproducible and representative gene expression profiles faithfully representing the transcriptional profiles of the constituent blood cell types present in the circulation. Given the increasing innovation in this field in recent years, we investigated a combination of methodological advances in both RNA stabilisation and microarray probe generation with the goal of achieving robust, reliable and representative transcriptional profiles from whole blood. To assess the whole blood profiles, the transcriptomes of purified blood cell types were measured and compared with the global transcriptomes measured in whole blood. The results demonstrate that a combination of PAXgene() RNA stabilising technology and single-stranded cDNA probe generation afforded by the NuGEN Ovation RNA amplification system V2() enables an approach that yields faithful representation of specific hematopoietic cell lineage transcriptomes in whole blood without the necessity for prior sample fractionation, cell enrichment or globin reduction. Storage stability assessments of the PAXgene() blood samples also advocate a short, fixed room temperature storage time for all PAXgene() blood samples collected for the purposes of global transcriptional profiling in clinical studies.

  16. Hematopoietic Lineage Transcriptome Stability and Representation in PAXgene™ Collected Peripheral Blood Utilising SPIA Single-Stranded cDNA Probes for Microarray

    Science.gov (United States)

    Kennedy, Laura; Vass, J. Keith; Haggart, D. Ross; Moore, Steve; Burczynski, Michael E.; Crowther, Dan; Miele, Gino

    2008-01-01

    Peripheral blood as a surrogate tissue for transcriptome profiling holds great promise for the discovery of diagnostic and prognostic disease biomarkers, particularly when target tissues of disease are not readily available. To maximize the reliability of gene expression data generated from clinical blood samples, both the sample collection and the microarray probe generation methods should be optimized to provide stabilized, reproducible and representative gene expression profiles faithfully representing the transcriptional profiles of the constituent blood cell types present in the circulation. Given the increasing innovation in this field in recent years, we investigated a combination of methodological advances in both RNA stabilisation and microarray probe generation with the goal of achieving robust, reliable and representative transcriptional profiles from whole blood. To assess the whole blood profiles, the transcriptomes of purified blood cell types were measured and compared with the global transcriptomes measured in whole blood. The results demonstrate that a combination of PAXgene™ RNA stabilising technology and single-stranded cDNA probe generation afforded by the NuGEN Ovation RNA amplification system V2™ enables an approach that yields faithful representation of specific hematopoietic cell lineage transcriptomes in whole blood without the necessity for prior sample fractionation, cell enrichment or globin reduction. Storage stability assessments of the PAXgene™ blood samples also advocate a short, fixed room temperature storage time for all PAXgene™ blood samples collected for the purposes of global transcriptional profiling in clinical studies. PMID:19578521

  17. Mutation Analysis of Consanguineous Moroccan Patients with Parkinson’s Disease Combining Microarray and Gene Panel

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    Ahmed Bouhouche

    2017-10-01

    Full Text Available During the last two decades, 15 different genes have been reported to be responsible for the monogenic form of Parkinson’s disease (PD, representing a worldwide frequency of 5–10%. Among them, 10 genes have been associated with autosomal recessive PD, with PRKN and PINK1 being the most frequent. In a cohort of 145 unrelated Moroccan PD patients enrolled since 2013, 19 patients were born from a consanguineous marriage, of which 15 were isolated cases and 4 familial. One patient was homozygous for the common LRRK2 G2019S mutation and the 18 others who did not carry this mutation were screened for exon rearrangements in the PRKN gene using Affymetrix Cytoscan HD microarray. Two patients were determined homozygous for PRKN exon-deletions, while another patient presented with compound heterozygous inheritance (3/18, 17%. Two other patients showed a region of homozygosity covering the 1p36.12 locus and were sequenced for the candidate PINK1 gene, which revealed two homozygous point mutations: the known Q456X mutation in exon 7 and a novel L539F variation in exon 8. The 13 remaining patients were subjected to next-generation sequencing (NGS that targeted a panel of 22 PD-causing genes and overlapping phenotypes. NGS data showed that two unrelated consanguineous patients with juvenile-onset PD (12 and 13 years carried the same homozygous stop mutation W258X in the ATP13A2 gene, possibly resulting from a founder effect; and one patient with late onset (76 years carried a novel heterozygous frameshift mutation in SYNJ1. Clinical analysis showed that patients with the ATP13A2 mutation developed juvenile-onset PD with a severe phenotype, whereas patients having either PRKN or PINK1 mutations displayed early-onset PD with a relatively mild phenotype. By identifying pathogenic mutations in 45% (8/18 of our consanguineous Moroccan PD series, we demonstrate that the combination of chromosomal microarray analysis and NGS is a powerful approach to

  18. Microarray Data Analysis of Space Grown Arabidopsis Leaves for Genes Important in Vascular Patterning

    Science.gov (United States)

    Weitzeal, A. J.; Wyatt, S. E.; Parsons-Wingerter, P.

    2016-01-01

    Venation patterning in leaves is a major determinant of photosynthesis efficiency because of its dependency on vascular transport of photoassimilates, water, and minerals. Arabidopsis thaliana grown in microgravity show delayed growth and leaf maturation. Gene expression data from the roots, hypocotyl, and leaves of A. thaliana grown during spaceflight vs. ground control analyzed by Affymetrix microarray are available through NASAs GeneLab (GLDS-7). We analyzed the data for differential expression of genes in leaves resulting from the effects of spaceflight on vascular patterning. Two genes were found by preliminary analysis to be upregulated during spaceflight that may be related to vascular formation. The genes are responsible for coding an ARGOS like protein (potentially affecting cell elongation in the leaves), and an F-boxkelch-repeat protein (possibly contributing to protoxylem specification). Further analysis that will focus on raw data quality assessment and a moderated t-test may further confirm upregulation of the two genes and/or identify other gene candidates. Plants defective in these genes will then be assessed for phenotype by the mapping and quantification of leaf vascular patterning by NASAs VESsel GENeration (VESGEN) software to model specific vascular differences of plants grown in spaceflight.

  19. Meta-Analysis of Multiple Sclerosis Microarray Data Reveals Dysregulation in RNA Splicing Regulatory Genes

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    Elvezia Maria Paraboschi

    2015-09-01

    Full Text Available 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.

  20. 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.

  1. Cyclin D1 and Ewing's sarcoma/PNET: A microarray analysis.

    Science.gov (United States)

    Fagone, Paolo; Nicoletti, Ferdinando; Salvatorelli, Lucia; Musumeci, Giuseppe; Magro, Gaetano

    2015-10-01

    Recent immunohistochemical analyses have showed that cyclin D1 is expressed in soft tissue Ewing's sarcoma/peripheral neuroectodermal tumor (PNET) of childhood and adolescents, while it is undetectable in both embryonal and alveolar rhabdomyosarcoma. In the present paper, microarray analysis provided evidence of a significant upregulation of cyclin D1 in Ewing's sarcoma as compared to normal tissues. In addition, we confirmed our previous findings of a significant over-expression of cyclin D1 in Ewing sarcoma as compared to rhabdomyosarcoma. Bioinformatic analysis also allowed to identify some other genes, strongly correlated to cyclin D1, which, although not previously studied in pediatric tumors, could represent novel markers for the diagnosis and prognosis of Ewing's sarcoma/PNET. The data herein provided support not only the use of cyclin D1 as a diagnostic marker of Ewing sarcoma/PNET but also the possibility of using drugs targeting cyclin D1 as potential therapeutic strategies. Copyright © 2015 Elsevier GmbH. All rights reserved.

  2. Theory and Application of DNA Histogram Analysis.

    Science.gov (United States)

    Bagwell, Charles Bruce

    The underlying principles and assumptions associated with DNA histograms are discussed along with the characteristics of fluorescent probes. Information theory was described and used to calculate the information content of a DNA histogram. Two major types of DNA histogram analyses are proposed: parametric and nonparametric analysis. Three levels…

  3. Comparative Microarray Analysis of Intestinal Lymphocytes following Eimeria acervulina, E. maxima, or E. tenella Infection in the Chicken

    Science.gov (United States)

    Kim, Duk Kyung; Lillehoj, Hyun; Min, Wongi; Kim, Chul Hong; Park, Myeong Seon; Hong, Yeong Ho; Lillehoj, Erik P.

    2011-01-01

    Relative expression levels of immune- and non-immune-related mRNAs in chicken intestinal intraepithelial lymphocytes experimentally infected with Eimeria acervulina, E. maxima, or E. tenella were measured using a 10K cDNA microarray. Based on a cutoff of >2.0-fold differential expression compared with uninfected controls, relatively equal numbers of transcripts were altered by the three Eimeria infections at 1, 2, and 3 days post-primary infection. By contrast, E. tenella elicited the greatest number of altered transcripts at 4, 5, and 6 days post-primary infection, and at all time points following secondary infection. When analyzed on the basis of up- or down-regulated transcript levels over the entire 6 day infection periods, approximately equal numbers of up-regulated transcripts were detected following E. tenella primary (1,469) and secondary (1,459) infections, with a greater number of down-regulated mRNAs following secondary (1,063) vs. primary (890) infection. On the contrary, relatively few mRNA were modulated following primary infection with E. acervulina (35 up, 160 down) or E. maxima (65 up, 148 down) compared with secondary infection (E. acervulina, 1,142 up, 1,289 down; E. maxima, 368 up, 1,349 down). With all three coccidia, biological pathway analysis identified the altered transcripts as belonging to the categories of “Disease and Disorder” and “Physiological System Development and Function”. Sixteen intracellular signaling pathways were identified from the differentially expressed transcripts following Eimeria infection, with the greatest significance observed following E. acervulina infection. Taken together, this new information will expand our understanding of host-pathogen interactions in avian coccidiosis and contribute to the development of novel disease control strategies. PMID:22140460

  4. Analysis of gene expression profile microarray data in complex regional pain syndrome.

    Science.gov (United States)

    Tan, Wulin; Song, Yiyan; Mo, Chengqiang; Jiang, Shuangjian; Wang, Zhongxing

    2017-09-01

    The aim of the present study was to predict key genes and proteins associated with complex regional pain syndrome (CRPS) using bioinformatics analysis. The gene expression profiling microarray data, GSE47603, which included peripheral blood samples from 4 patients with CRPS and 5 healthy controls, was obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) in CRPS patients compared with healthy controls were identified using the GEO2R online tool. Functional enrichment analysis was then performed using The Database for Annotation Visualization and Integrated Discovery online tool. Protein‑protein interaction (PPI) network analysis was subsequently performed using Search Tool for the Retrieval of Interaction Genes database and analyzed with Cytoscape software. A total of 257 DEGs were identified, including 243 upregulated genes and 14 downregulated ones. Genes in the human leukocyte antigen (HLA) family were most significantly differentially expressed. Enrichment analysis demonstrated that signaling pathways, including immune response, cell motion, adhesion and angiogenesis were associated with CRPS. PPI network analysis revealed that key genes, including early region 1A binding protein p300 (EP300), CREB‑binding protein (CREBBP), signal transducer and activator of transcription (STAT)3, STAT5A and integrin α M were associated with CRPS. The results suggest that the immune response may therefore serve an important role in CRPS development. In addition, genes in the HLA family, such as HLA‑DQB1 and HLA‑DRB1, may present potential biomarkers for the diagnosis of CRPS. Furthermore, EP300, its paralog CREBBP, and the STAT family genes, STAT3 and STAT5 may be important in the development of CRPS.

  5. Advanced microarray technologies for clinical diagnostics

    NARCIS (Netherlands)

    Pierik, Anke

    2011-01-01

    DNA microarrays become increasingly important in the field of clinical diagnostics. These microarrays, also called DNA chips, are small solid substrates, typically having a maximum surface area of a few cm2, onto which many spots are arrayed in a pre-determined pattern. Each of these spots contains

  6. Meta-analysis of Drosophila circadian microarray studies identifies a novel set of rhythmically expressed genes.

    Directory of Open Access Journals (Sweden)

    Kevin P Keegan

    2007-11-01

    Full Text Available Five independent groups have reported microarray studies that identify dozens of rhythmically expressed genes in the fruit fly Drosophila melanogaster. Limited overlap among the lists of discovered genes makes it difficult to determine which, if any, exhibit truly rhythmic patterns of expression. We reanalyzed data from all five reports and found two sources for the observed discrepancies, the use of different expression pattern detection algorithms and underlying variation among the datasets. To improve upon the methods originally employed, we developed a new analysis that involves compilation of all existing data, application of identical transformation and standardization procedures followed by ANOVA-based statistical prescreening, and three separate classes of post hoc analysis: cross-correlation to various cycling waveforms, autocorrelation, and a previously described fast Fourier transform-based technique. Permutation-based statistical tests were used to derive significance measures for all post hoc tests. We find application of our method, most significantly the ANOVA prescreening procedure, significantly reduces the false discovery rate relative to that observed among the results of the original five reports while maintaining desirable statistical power. We identify a set of 81 cycling transcripts previously found in one or more of the original reports as well as a novel set of 133 transcripts not found in any of the original studies. We introduce a novel analysis method that compensates for variability observed among the original five Drosophila circadian array reports. Based on the statistical fidelity of our meta-analysis results, and the results of our initial validation experiments (quantitative RT-PCR, we predict many of our newly found genes to be bona fide cyclers, and suggest that they may lead to new insights into the pathways through which clock mechanisms regulate behavioral rhythms.

  7. Identification of Cell Surface Targets through Meta-analysis of Microarray Data

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    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.

  8. 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.

  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. Hormonal receptors and vascular endothelial growth factor in juvenile nasopharyngeal angiofibroma: immunohistochemical and tissue microarray analysis.

    Science.gov (United States)

    Liu, Zhuofu; Wang, Jingjing; Wang, Huan; Wang, Dehui; Hu, Li; Liu, Quan; Sun, Xicai

    2015-01-01

    This work demonstrated that juvenile nasopharyngeal angiofibromas (JNAs) express high levels of hormone receptors and vascular endothelial growth factor (VEGF) compared with normal nasal mucosa. The interaction between hormone receptors and VEGF may be involved in the initiation and growth of JNA. JNA is a rare benign tumor that occurs almost exclusively in male adolescents. Although generally regarded as a hormone-dependent tumor, this has not been proven in previous studies. The aim of this study was to investigate the role of hormone receptors in JNA and the relationship with clinical characteristics. Standard immunohistochemical microarray analysis was performed on 70 JNA samples and 10 turbinate tissue samples. Specific antibodies for androgen receptor (AR), estrogen receptor-α (ER-α), estrogen receptor-β (ER-β), progesterone receptor (PR), and VEGF were examined, and the relationships of receptor expression with age, tumor stage, and bleeding were evaluated. RESULTS showed that JNA expressed ER-α (92.9%), ER-β (91.4%), AR (65.7%), PR (12.8%), and VEGF (95.7%) at different levels. High level of VEGF was linked to elevated ER-α and ER-β. There was no significant relationship between hormonal receptors and age at diagnosis, tumor stage or bleeding. However, overexpression of ER-α was found to be an indicator of poor prognosis (p = 0.031).

  11. Microarray-Based Identification of Transcription Factor Target Genes

    NARCIS (Netherlands)

    Gorte, M.; Horstman, A.; Page, R.B.; Heidstra, R.; Stromberg, A.; Boutilier, K.A.

    2011-01-01

    Microarray analysis is widely used to identify transcriptional changes associated with genetic perturbation or signaling events. Here we describe its application in the identification of plant transcription factor target genes with emphasis on the design of suitable DNA constructs for controlling TF

  12. A DNA methylation microarray-based study identifies ERG as a gene commonly methylated in prostate cancer.

    Science.gov (United States)

    Schwartzman, Jacob; Mongoue-Tchokote, Solange; Gibbs, Angela; Gao, Lina; Corless, Christopher L; Jin, Jennifer; Zarour, Luai; Higano, Celestia; True, Lawrence D; Vessella, Robert L; Wilmot, Beth; Bottomly, Daniel; McWeeney, Shannon K; Bova, G Steven; Partin, Alan W; Mori, Motomi; Alumkal, Joshi

    2011-10-01

    DNA methylation of promoter regions is a common event in prostate cancer, one of the most common cancers in men worldwide. Because prior reports demonstrating that DNA methylation is important in prostate cancer studied a limited number of genes, we systematically quantified the DNA methylation status of 1505 CpG dinucleotides for 807 genes in 78 paraffin-embedded prostate cancer samples and three normal prostate samples. The ERG gene, commonly repressed in prostate cells in the absence of an oncogenic fusion to the TMPRSS2 gene, was one of the most commonly methylated genes, occurring in 74% of prostate cancer specimens. In an independent group of patient samples, we confirmed that ERG DNA methylation was common, occurring in 57% of specimens, and cancer-specific. The ERG promoter is marked by repressive chromatin marks mediated by polycomb proteins in both normal prostate cells and prostate cancer cells, which may explain ERG's predisposition to DNA methylation and the fact that tumors with ERG DNA methylation were more methylated, in general. These results demonstrate that bead arrays offer a high-throughput method to discover novel genes with promoter DNA methylation such as ERG, whose measurement may improve our ability to more accurately detect prostate cancer.

  13. Single-Nucleotide Polymorphism-Microarray Ploidy Analysis of Paraffin-Embedded Products of Conception in Recurrent Pregnancy Loss Evaluations.

    Science.gov (United States)

    Maslow, Bat-Sheva L; Budinetz, Tara; Sueldo, Carolina; Anspach, Erica; Engmann, Lawrence; Benadiva, Claudio; Nulsen, John C

    2015-07-01

    To compare the analysis of chromosome number from paraffin-embedded products of conception using single-nucleotide polymorphism (SNP) microarray with the recommended screening for the evaluation of couples presenting with recurrent pregnancy loss who do not have previous fetal cytogenetic data. We performed a retrospective cohort study including all women who presented for a new evaluation of recurrent pregnancy loss over a 2-year period (January 1, 2012, to December 31, 2013). All participants had at least two documented first-trimester losses and both the recommended screening tests and SNP microarray performed on at least one paraffin-embedded products of conception sample. Single-nucleotide polymorphism microarray identifies all 24 chromosomes (22 autosomes, X, and Y). Forty-two women with a total of 178 losses were included in the study. Paraffin-embedded products of conception from 62 losses were sent for SNP microarray. Single-nucleotide polymorphism microarray successfully diagnosed fetal chromosome number in 71% (44/62) of samples, of which 43% (19/44) were euploid and 57% (25/44) were noneuploid. Seven of 42 (17%) participants had abnormalities on recurrent pregnancy loss screening. The per-person detection rate for a cause of pregnancy loss was significantly higher in the SNP microarray (0.50; 95% confidence interval [CI] 0.36-0.64) compared with recurrent pregnancy loss evaluation (0.17; 95% CI 0.08-0.31) (P=.002). Participants with one or more euploid loss identified on paraffin-embedded products of conception were significantly more likely to have an abnormality on recurrent pregnancy loss screening than those with only noneuploid results (P=.028). The significance remained when controlling for age, number of losses, number of samples, and total pregnancies. These results suggest that SNP microarray testing of paraffin-embedded products of conception is a valuable tool for the evaluation of recurrent pregnancy loss in patients without prior fetal

  14. Molecular characterisation of the early response in pigs to experimental infection with Actinobacillus pleuropneumoniae using cDNA microarrays

    DEFF Research Database (Denmark)

    Hedegaard, Jakob; Skovgaard, Kerstin; Mortensen, Shila

    2007-01-01

    Background: The bacterium Actinobacillus pleuropneumoniae is responsible for porcine pleuropneumonia, a widespread, highly contagious and often fatal respiratory disease of pigs. The general porcine innate immune response after A. pleuropneumoniae infection is still not clarified. The objective...... lymph node tissue were hybridised to an expanded version of the porcine microarray with 26879 unique PCR products. Results: A total of 357 genes differed significantly in expression between infected and non-infected lung tissue, 713 genes differed in expression in liver tissue from infected versus non-infected...... animals and 130 genes differed in expression in tracheobronchial lymph node tissue from infected versus non-infected animals. Among these genes, several have previously been described to be part of a general host response to infections encoding immune response related proteins. In inflamed lung tissue...

  15. Meta-Analysis of Microarray Data of Rainbow Trout Fry Gonad Differentiation Modulated by Ethynylestradiol.

    Directory of Open Access Journals (Sweden)

    Sophie Depiereux

    Full Text Available Sex differentiation in fish is a highly labile process easily reversed by the use of exogenous hormonal treatment and has led to environmental concerns since low doses of estrogenic molecules can adversely impact fish reproduction. The goal of this study was to identify pathways altered by treatment with ethynylestradiol (EE2 in developing fish and to find new target genes to be tested further for their possible role in male-to-female sex transdifferentiation. To this end, we have successfully adapted a previously developed bioinformatics workflow to a meta-analysis of two datasets studying sex reversal following exposure to EE2 in juvenile rainbow trout. The meta-analysis consisted of retrieving the intersection of the top gene lists generated for both datasets, performed at different levels of stringency. The intersecting gene lists, enriched in true positive differentially expressed genes (DEGs, were subjected to over-representation analysis (ORA which allowed identifying several statistically significant enriched pathways altered by EE2 treatment and several new candidate pathways, such as progesterone-mediated oocyte maturation and PPAR signalling. Moreover, several relevant key genes potentially implicated in the early transdifferentiation process were selected. Altogether, the results show that EE2 has a great effect on gene expression in juvenile rainbow trout. The feminization process seems to result from the altered transcription of genes implicated in normal female gonad differentiation, resulting in expression similar to that observed in normal females (i.e. the repression of key testicular markers cyp17a1, cyp11b, tbx1, as well as from other genes (including transcription factors that respond specifically to the EE2 treatment. The results also showed that the bioinformatics workflow can be applied to different types of microarray platforms and could be generalized to (ecotoxicogenomics studies for environmental risk assessment

  16. Senescent vs. non-senescent cells in the human annulus in vivo: Cell harvest with laser capture microdissection and gene expression studies with microarray analysis

    Directory of Open Access Journals (Sweden)

    Ingram Jane A

    2010-01-01

    Full Text Available Abstract Background Senescent cells are well-recognized in the aging/degenerating human disc. Senescent cells are viable, cannot divide, remain metabolically active and accumulate within the disc over time. Molecular analysis of senescent cells in tissue offers a special challenge since there are no cell surface markers for senescence which would let one use fluorescence-activated cell sorting as a method for separating out senescent cells. Methods We employed a novel laser capture microdissection (LCM design to selectively harvest senescent and non-senescent annulus cells in paraffin-embedded tissue, and compared their gene expression with microarray analysis. LCM was used to separately harvest senescent and non-senescent cells from 11 human annulus specimens. Results Microarray analysis revealed significant differences in expression levels in senescent cells vs non-senescent cells: 292 genes were upregulated, and 321 downregulated. Genes with established relationships to senescence were found to be significantly upregulated in senescent cells vs. non-senescent cells: p38 (MPAK14, RB-Associated KRAB zinc finger, Discoidin, CUB and LCCL domain, growth arrest and DNA-damage inducible beta, p28ING5, sphingosine-1-phosphate receptor 2 and somatostatin receptor 3; cyclin-dependent kinase 8 showed significant downregulation in senescent cells. Nitric oxidase synthase 1, and heat shock 70 kDa protein 6, both of which were significantly down-regulated in senescent cells, also showed significant changes. Additional genes related to cytokines, cell proliferation, and other processes were also identified. Conclusions Our LCM-microarray analyses identified a set of genes associated with senescence which were significantly upregulated in senescent vs non-senescent cells in the human annulus. These genes include p38 MAP kinase, discoidin, inhibitor of growth family member 5, and growth arrest and DNA-damage-inducible beta. Other genes, including genes

  17. A tiling microarray for global analysis of chloroplast genome expression in cucumber and other plants

    Directory of Open Access Journals (Sweden)

    Pląder Wojciech

    2011-09-01

    Full Text Available Abstract Plastids are small organelles equipped with their own genomes (plastomes. Although these organelles are involved in numerous plant metabolic pathways, current knowledge about the transcriptional activity of plastomes is limited. To solve this problem, we constructed a plastid tiling microarray (PlasTi-microarray consisting of 1629 oligonucleotide probes. The oligonucleotides were designed based on the cucumber chloroplast genomic sequence and targeted both strands of the plastome in a non-contiguous arrangement. Up to 4 specific probes were designed for each gene/exon, and the intergenic regions were covered regularly, with 70-nt intervals. We also developed a protocol for direct chemical labeling and hybridization of as little as 2 micrograms of chloroplast RNA. We used this protocol for profiling the expression of the cucumber chloroplast plastome on the PlasTi-microarray. Owing to the high sequence similarity of plant plastomes, the newly constructed microarray can be used to study plants other than cucumber. Comparative hybridization of chloroplast transcriptomes from cucumber, Arabidopsis, tomato and spinach showed that the PlasTi-microarray is highly versatile.

  18. Comparative RNA-Seq and microarray analysis of gene expression changes in B-cell lymphomas of Canis familiaris.

    Directory of Open Access Journals (Sweden)

    Marie Mooney

    Full Text Available Comparative oncology is a developing research discipline that is being used to assist our understanding of human neoplastic diseases. Companion canines are a preferred animal oncology model due to spontaneous tumor development and similarity to human disease at the pathophysiological level. We use a paired RNA sequencing (RNA-Seq/microarray analysis of a set of four normal canine lymph nodes and ten canine lymphoma fine needle aspirates to identify technical biases and variation between the technologies and convergence on biological disease pathways. Surrogate Variable Analysis (SVA provides a formal multivariate analysis of the combined RNA-Seq/microarray data set. Applying SVA to the data allows us to decompose variation into contributions associated with transcript abundance, differences between the technology, and latent variation within each technology. A substantial and highly statistically significant component of the variation reflects transcript abundance, and RNA-Seq appeared more sensitive for detection of transcripts expressed at low levels. Latent random variation among RNA-Seq samples is also distinct in character from that impacting microarray samples. In particular, we observed variation between RNA-Seq samples that reflects transcript GC content. Platform-independent variable decomposition without a priori knowledge of the sources of variation using SVA represents a generalizable method for accomplishing cross-platform data analysis. We identified genes differentially expressed between normal lymph nodes of disease free dogs and a subset of the diseased dogs diagnosed with B-cell lymphoma using each technology. There is statistically significant overlap between the RNA-Seq and microarray sets of differentially expressed genes. Analysis of overlapping genes in the context of biological systems suggests elevated expression and activity of PI3K signaling in B-cell lymphoma biopsies compared with normal biopsies, consistent with

  19. Quantitative miRNA expression analysis: comparing microarrays with next-generation sequencing

    DEFF Research Database (Denmark)

    Willenbrock, Hanni; Salomon, Jesper; Søkilde, Rolf

    2009-01-01

    Recently, next-generation sequencing has been introduced as a promising, new platform for assessing the copy number of transcripts, while the existing microarray technology is considered less reliable for absolute, quantitative expression measurements. Nonetheless, so far, results from the two...... technologies have only been compared based on biological data, leading to the conclusion that, although they are somewhat correlated, expression values differ significantly. Here, we use synthetic RNA samples, resembling human microRNA samples, to find that microarray expression measures actually correlate...... better with sample RNA content than expression measures obtained from sequencing data. In addition, microarrays appear highly sensitive and perform equivalently to next-generation sequencing in terms of reproducibility and relative ratio quantification....

  20. Microarray analysis reveals key genes and pathways in Tetralogy of Fallot

    Science.gov (United States)

    He, Yue-E; Qiu, Hui-Xian; Jiang, Jian-Bing; Wu, Rong-Zhou; Xiang, Ru-Lian; Zhang, Yuan-Hai

    2017-01-01

    The aim of the present study was to identify key genes that may be involved in the pathogenesis of Tetralogy of Fallot (TOF) using bioinformatics methods. The GSE26125 microarray dataset, which includes cardiovascular tissue samples derived from 16 children with TOF and five healthy age-matched control infants, was downloaded from the Gene Expression Omnibus database. Differential expression analysis was performed between TOF and control samples to identify differentially expressed genes (DEGs) using Student's t-test, and the R/limma package, with a log2 fold-change of >2 and a false discovery rate of <0.01 set as thresholds. The biological functions of DEGs were analyzed using the ToppGene database. The ReactomeFIViz application was used to construct functional interaction (FI) networks, and the genes in each module were subjected to pathway enrichment analysis. The iRegulon plugin was used to identify transcription factors predicted to regulate the DEGs in the FI network, and the gene-transcription factor pairs were then visualized using Cytoscape software. A total of 878 DEGs were identified, including 848 upregulated genes and 30 downregulated genes. The gene FI network contained seven function modules, which were all comprised of upregulated genes. Genes enriched in Module 1 were enriched in the following three neurological disorder-associated signaling pathways: Parkinson's disease, Alzheimer's disease and Huntington's disease. Genes in Modules 0, 3 and 5 were dominantly enriched in pathways associated with ribosomes and protein translation. The Xbox binding protein 1 transcription factor was demonstrated to be involved in the regulation of genes encoding the subunits of cytoplasmic and mitochondrial ribosomes, as well as genes involved in neurodegenerative disorders. Therefore, dysfunction of genes involved in signaling pathways associated with neurodegenerative disorders, ribosome function and protein translation may contribute to the pathogenesis of TOF

  1. Microarray analysis of toxicogenomic effects of Ortho-phenylphenol in Staphylococcus aureus

    Directory of Open Access Journals (Sweden)

    Toghrol Freshteh

    2008-09-01

    Full Text Available Abstract Background Staphylococcus aureus (S. aureus, is responsible for many infectious diseases, ranging from benign skin infections to life-threatening endocarditis and toxic shock syndrome. Ortho-phenylphenol (OPP is an antimicrobial agent and an active ingredient of EPA-registered disinfectants with wide human exposure in various agricultural, hospital and veterinary disinfectant products. Despite many uses, an understanding of a cellular response to OPP and it's mechanism of action, targeted genes, and the connectivity between targeted genes and the rest of cell metabolism remains obscure. Results Herein, we performed a genome-wide transcriptome analysis of the cellular responses of S. aureus when exposed to 0.82 mM of OPP for 20 and 60 min. Our data indicated that OPP downregulated the biosynthesis of many amino acids, which are required for protein synthesis. In particular, the genes encoding the enzymes of the diaminopimelate (DAP pathway which results in lysine biosynthesis were significantly downregualted. Intriguingly, we revealed that the transcription of genes encoding ribosomal proteins was upregulated by OPP and at the same time, the genes encoding iron acquisition and transport were downregulated. The genes encoding virulence factors were upregulated and genes encoding phospholipids were downregulated upon 20 min exposure to OPP. Conclusion By using microarray analysis that enables us to simultaneously and globally examine the complete transcriptome during cellular responses, we have revealed novel information regarding the mode of action of OPP on Staphylococcus: OPP inhibits anabolism of many amino acids and highly downregulates the genes that encode the enzymes involved in the DAP pathway. Lysine and DAP are essential for building up the peptidoglycan cell wall. It was concluded that the mode of action of OPP is similar to the mechanism of action of some antibiotics. The discovery of this phenomenon provides useful

  2. Microarray expression analysis of meiosis and microsporogenesis in hexaploid bread wheat

    Directory of Open Access Journals (Sweden)

    Langridge Peter

    2006-10-01

    Full Text Available Abstract Background Our understanding of the mechanisms that govern the cellular process of meiosis is limited in higher plants with polyploid genomes. Bread wheat is an allohexaploid that behaves as a diploid during meiosis. Chromosome pairing is restricted to homologous chromosomes despite the presence of homoeologues in the nucleus. The importance of wheat as a crop and the extensive use of wild wheat relatives in breeding programs has prompted many years of cytogenetic and genetic research to develop an understanding of the control of chromosome pairing and recombination. The rapid advance of biochemical and molecular information on meiosis in model organisms such as yeast provides new opportunities to investigate the molecular basis of chromosome pairing control in wheat. However, building the link between the model and wheat requires points of data contact. Results We report here a large-scale transcriptomics study using the Affymetrix wheat GeneChip® aimed at providing this link between wheat and model systems and at identifying early meiotic genes. Analysis of the microarray data identified 1,350 transcripts temporally-regulated during the early stages of meiosis. Expression profiles with annotated transcript functions including chromatin condensation, synaptonemal complex formation, recombination and fertility were identified. From the 1,350 transcripts, 30 displayed at least an eight-fold expression change between and including pre-meiosis and telophase II, with more than 50% of these having no similarities to known sequences in NCBI and TIGR databases. Conclusion This resource is now available to support research into the molecular basis of pairing and recombination control in the complex polyploid, wheat.

  3. Aligning ontologies and integrating textual evidence for pathway analysis of microarray data

    Energy Technology Data Exchange (ETDEWEB)

    Gopalan, Banu; Posse, Christian; Sanfilippo, Antonio P.; Stenzel-Poore, Mary; Stevens, S.L.; Castano, Jose; Beagley, Nathaniel; Riensche, Roderick M.; Baddeley, Bob; Simon, R.P.; Pustejovsky, James

    2006-10-08

    Expression arrays are introducing a paradigmatic change in biology by shifting experimental approaches from single gene studies to genome-level analysis, monitoring the ex-pression levels of several thousands of genes in parallel. The massive amounts of data obtained from the microarray data needs to be integrated and interpreted to infer biological meaning within the context of information-rich pathways. In this paper, we present a methodology that integrates textual information with annotations from cross-referenced ontolo-gies to map genes to pathways in a semi-automated way. We illustrate this approach and compare it favorably to other tools by analyzing the gene expression changes underlying the biological phenomena related to stroke. Stroke is the third leading cause of death and a major disabler in the United States. Through years of study, researchers have amassed a significant knowledge base about stroke, and this knowledge, coupled with new technologies, is providing a wealth of new scientific opportunities. The potential for neu-roprotective stroke therapy is enormous. However, the roles of neurogenesis, angiogenesis, and other proliferative re-sponses in the recovery process following ischemia and the molecular mechanisms that lead to these processes still need to be uncovered. Improved annotation of genomic and pro-teomic data, including annotation of pathways in which genes and proteins are involved, is required to facilitate their interpretation and clinical application. While our approach is not aimed at replacing existing curated pathway databases, it reveals multiple hidden relationships that are not evident with the way these databases analyze functional groupings of genes from the Gene Ontology.

  4. Crowdsourcing for translational research: analysis of biomarker expression using cancer microarrays.

    Science.gov (United States)

    Lawson, Jonathan; Robinson-Vyas, Rupesh J; McQuillan, Janette P; Paterson, Andy; Christie, Sarah; Kidza-Griffiths, Matthew; McDuffus, Leigh-Anne; Moutasim, Karwan A; Shaw, Emily C; Kiltie, Anne E; Howat, William J; Hanby, Andrew M; Thomas, Gareth J; Smittenaar, Peter

    2017-01-17

    Academic pathology suffers from an acute and growing lack of workforce resource. This especially impacts on translational elements of clinical trials, which can require detailed analysis of thousands of tissue samples. We tested whether crowdsourcing - enlisting help from the public - is a sufficiently accurate method to score such samples. We developed a novel online interface to train and test lay participants on cancer detection and immunohistochemistry scoring in tissue microarrays. Lay participants initially performed cancer detection on lung cancer images stained for CD8, and we measured how extending a basic tutorial by annotated example images and feedback-based training affected cancer detection accuracy. We then applied this tutorial to additional cancer types and immunohistochemistry markers - bladder/ki67, lung/EGFR, and oesophageal/CD8 - to establish accuracy compared with experts. Using this optimised tutorial, we then tested lay participants' accuracy on immunohistochemistry scoring of lung/EGFR and bladder/p53 samples. We observed that for cancer detection, annotated example images and feedback-based training both improved accuracy compared with a basic tutorial only. Using this optimised tutorial, we demonstrate highly accurate (>0.90 area under curve) detection of cancer in samples stained with nuclear, cytoplasmic and membrane cell markers. We also observed high Spearman correlations between lay participants and experts for immunohistochemistry scoring (0.91 (0.78, 0.96) and 0.97 (0.91, 0.99) for lung/EGFR and bladder/p53 samples, respectively). These results establish crowdsourcing as a promising method to screen large data sets for biomarkers in cancer pathology research across a range of cancers and immunohistochemical stains.

  5. Grating coupled SPR microarray analysis of proteins and cells in blood from mice with breast cancer.

    Science.gov (United States)

    Mendoza, A; Torrisi, D M; Sell, S; Cady, N C; Lawrence, D A

    2016-01-21

    Biomarker discovery for early disease diagnosis is highly important. Of late, much effort has been made to analyze complex biological fluids in an effort to develop new markers specific for different cancer types. Recent advancements in label-free technologies such as surface plasmon resonance (SPR)-based biosensors have shown promise as a diagnostic tool since there is no need for labeling or separation of cells. Furthermore, SPR can provide rapid, real-time detection of antigens from biological samples since SPR is highly sensitive to changes in surface-associated molecular and cellular interactions. Herein, we report a lab-on-a-chip microarray biosensor that utilizes grating-coupled surface plasmon resonance (GCSPR) and grating-coupled surface plasmon coupled fluorescence (GCSPCF) imaging to detect circulating tumor cells (CTCs) from a mouse model (FVB-MMTV-PyVT). GCSPR and GCSPCF analysis was accomplished by spotting antibodies to surface cell markers, cytokines and stress proteins on a nanofabricated GCSPR microchip and screening blood samples from FVB control mice or FVB-MMTV-PyVT mice with developing mammary carcinomas. A transgenic MMTV-PyVT mouse derived cancer cell line was also analyzed. The analyses indicated that CD24, CD44, CD326, CD133 and CD49b were expressed in both cell lines and in blood from MMTV-PyVT mice. Furthermore, cytokines such as IL-6, IL-10 and TNF-α, along with heat shock proteins HSP60, HSP27, HSc70(HSP73), HSP90 total, HSP70/HSc70, HSP90, HSP70, HSP90 alpha, phosphotyrosine and HSF-1 were overexpressed in MMTV-PyVT mice.

  6. Microarray analysis of gene expression alteration in human middle ear epithelial cells induced by micro particle.

    Science.gov (United States)

    Song, Jae-Jun; Kwon, Jee Young; Park, Moo Kyun; Seo, Young Rok

    2013-10-01

    The primary aim of this study is to reveal the effect of particulate matter (PM) on the human middle ear epithelial cell (HMEEC). The HMEEC was treated with PM (300 μg/ml) for 24 h. Total RNA was extracted and used for microarray analysis. Molecular pathways among differentially expressed genes were further analyzed by using Pathway Studio 9.0 software. For selected genes, the changes in gene expression were confirmed by real-time PCR. A total of 611 genes were regulated by PM. Among them, 366 genes were up-regulated, whereas 245 genes were down-regulated. Up-regulated genes were mainly involved in cellular processes, including reactive oxygen species generation, cell proliferation, apoptosis, cell differentiation, inflammatory response and immune response. Down-regulated genes affected several cellular processes, including cell differentiation, cell cycle, proliferation, apoptosis and cell migration. A total of 21 genes were discovered as crucial components in potential signaling networks containing 2-fold up regulated genes. Four genes, VEGFA, IL1B, CSF2 and HMOX1 were revealed as key mediator genes among the up-regulated genes. A total of 25 genes were revealed as key modulators in the signaling pathway associated with 2-fold down regulated genes. Four genes, including IGF1R, TIMP1, IL6 and FN1, were identified as the main modulator genes. We identified the differentially expressed genes in PM-treated HMEEC, whose expression profile may provide a useful clue for the understanding of environmental pathophysiology of otitis media. Our work indicates that air pollution, like PM, plays an important role in the pathogenesis of otitis media. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  7. Microarray Cluster Analysis of Irradiated Growth Plate Zones Following Laser Microdissection

    International Nuclear Information System (INIS)

    Damron, Timothy A.; Zhang Mingliang; Pritchard, Meredith R.; Middleton, Frank A.; Horton, Jason A.; Margulies, Bryan M.; Strauss, Judith A.; Farnum, Cornelia E.; Spadaro, Joseph A.

    2009-01-01

    Purpose: Genes and pathways involved in early growth plate chondrocyte recovery after fractionated irradiation were sought as potential targets for selective radiorecovery modulation. Materials and Methods: Three groups of six 5-week male Sprague-Dawley rats underwent fractionated irradiation to the right tibiae over 5 days, totaling 17.5 Gy, and then were killed at 7, 11, and 16 days after the first radiotherapy fraction. The growth plates were collected from the proximal tibiae bilaterally and subsequently underwent laser microdissection to separate reserve, perichondral, proliferative, and hypertrophic zones. Differential gene expression was analyzed between irradiated right and nonirradiated left tibia using RAE230 2.0 GeneChip microarray, compared between zones and time points and subjected to functional pathway cluster analysis with real-time polymerase chain reaction to confirm selected results. Results: Each zone had a number of pathways showing enrichment after the pattern of hypothesized importance to growth plate recovery, yet few met the strictest criteria. The proliferative and hypertrophic zones showed both the greatest number of genes with a 10-fold right/left change at 7 days after initiation of irradiation and enrichment of the most functional pathways involved in bone, cartilage, matrix, or skeletal development. Six genes confirmed by real-time polymerase chain reaction to have early upregulation included insulin-like growth factor 2, procollagen type I alpha 2, matrix metallopeptidase 9, parathyroid hormone receptor 1, fibromodulin, and aggrecan 1. Conclusions: Nine overlapping pathways in the proliferative and hypertrophic zones (skeletal development, ossification, bone remodeling, cartilage development, extracellular matrix structural constituent, proteinaceous extracellular matrix, collagen, extracellular matrix, and extracellular matrix part) may play key roles in early growth plate radiorecovery.

  8. Molecular sub-classification of renal epithelial tumors using meta-analysis of gene expression microarrays.

    Directory of Open Access Journals (Sweden)

    Thomas Sanford

    Full Text Available To evaluate the accuracy of the sub-classification of renal cortical neoplasms using molecular signatures.A search of publicly available databases was performed to identify microarray datasets with multiple histologic sub-types of renal cortical neoplasms. Meta-analytic techniques were utilized to identify differentially expressed genes for each histologic subtype. The lists of genes obtained from the meta-analysis were used to create predictive signatures through the use of a pair-based method. These signatures were organized into an algorithm to sub-classify renal neoplasms. The use of these signatures according to our algorithm was validated on several independent datasets.We identified three Gene Expression Omnibus datasets that fit our criteria to develop a training set. All of the datasets in our study utilized the Affymetrix platform. The final training dataset included 149 samples represented by the four most common histologic subtypes of renal cortical neoplasms: 69 clear cell, 41 papillary, 16 chromophobe, and 23 oncocytomas. When validation of our signatures was performed on external datasets, we were able to correctly classify 68 of the 72 samples (94%. The correct classification by subtype was 19/20 (95% for clear cell, 14/14 (100% for papillary, 17/19 (89% for chromophobe, 18/19 (95% for oncocytomas.Through the use of meta-analytic techniques, we were able to create an algorithm that sub-classified renal neoplasms on a molecular level with 94% accuracy across multiple independent datasets. This algorithm may aid in selecting molecular therapies and may improve the accuracy of subtyping of renal cortical tumors.

  9. Toxicity of Doxorubicin on Pig Liver After Chemoembolization with Doxorubicin-loaded Microspheres: A Pilot DNA-microarrays and Histology Study

    Energy Technology Data Exchange (ETDEWEB)

    Verret, Valentin, E-mail: valentin.verret@archimmed.com; Namur, Julien; Ghegediban, Saieda Homayra [ArchimMed (France); Wassef, Michel [University of Paris 7-Denis Diderot, Department of Pathology, Faculty of Medicine, AP-HP Hopital Lariboisiere (France); Moine, Laurence [Universite Paris Sud, Faculte de Pharmacie, UMR CNRS 8612, IFR 141-ITFM (France); Bonneau, Michel [AP-HP/INRA, Centre de Recherche En Imagerie Interventionnelle (France); Pelage, Jean-Pierre [AP-HP Hopital Ambroise Pare, Department of Interventional Radiology (France); Laurent, Alexandre [AP-HP/INRA, Centre de Recherche En Imagerie Interventionnelle (France)

    2013-02-15

    The potential mechanisms accounting for the hepatotoxicity of doxorubicin-loaded microspheres in chemoembolization were examined by combining histology and DNA-microarray techniques.The left hepatic arteries of two pigs were embolized with 1 mL of doxorubicin-loaded (25 mg; (DoxMS)) or non-loaded (BlandMS) microspheres. The histopathological effects of the embolization were analyzed at 1 week. RNAs extracted from both the embolized and control liver areas were hybridized onto Agilent porcine microarrays. Genes showing significantly different expression (p < 0.01; fold-change > 2) between two groups were classified by biological process. At 1 week after embolization, DoxMS caused arterial and parenchymal necrosis in 51 and 38 % of embolized vessels, respectively. By contrast, BlandMS did not cause any tissue damage. Up-regulated genes following embolization with DoxMS (vs. BlandMS, n = 353) were mainly involved in cell death, apoptosis, and metabolism of doxorubicin. Down-regulated genes (n = 120) were mainly related to hepatic functions, including enzymes of lipid and carbohydrate metabolisms. Up-regulated genes included genes related to cell proliferation (growth factors and transcription factors), tissue remodeling (MMPs and several collagen types), inflammatory reaction (interleukins and chemokines), and angiogenesis (angiogenic factors and HIF1a pathway), all of which play an important role in liver healing and regeneration. DoxMS caused lesions to the liver, provoked cell death, and disturbed liver metabolism. An inflammatory repair process with cell proliferation, tissue remodeling, and angiogenesis was rapidly initiated during the first week after chemoembolization. This pilot study provides a comprehensive method to compare different types of DoxMS in healthy animals or tumor models.

  10. Extending the scope of diagnostic chromosome analysis: detection of single gene defects using high-resolution SNP microarrays.

    Science.gov (United States)

    Bruno, Damien L; Stark, Zornitza; Amor, David J; Burgess, Trent; Butler, Kathy; Corrie, Sylvea; Francis, David; Ganesamoorthy, Devika; Hills, Louise; James, Paul A; O'Rielly, Darren; Oertel, Ralph; Savarirayan, Ravi; Prabhakara, Krishnamurthy; Salce, Nicholas; Slater, Howard R

    2011-12-01

    Microarray analysis has provided significant advances in the diagnosis of conditions resulting from submicroscopic chromosome abnormalities. It has been recommended that array testing should be a "first tier" test in the evaluation of individuals with intellectual disability, developmental delay, congenital anomalies, and autism. The availability of arrays with increasingly high probe coverage and resolution has increased the detection of decreasingly small copy number changes (CNCs) down to the intragenic or even exon level. Importantly, arrays that genotype SNPs also detect extended regions of homozygosity. We describe 14 examples of single gene disorders caused by intragenic changes from a consecutive set of 6,500 tests using high-resolution SNP microarrays. These cases illustrate the increased scope of cytogenetic testing beyond dominant chromosome rearrangements that typically contain many genes. Nine of the cases confirmed the clinical diagnosis, that is, followed a "phenotype to genotype" approach. Five were diagnosed by the laboratory analysis in the absence of a specific clinical diagnosis, that is, followed a "genotype to phenotype" approach. Two were clinically significant, incidental findings. The importance of astute clinical assessment and laboratory-clinician consultation is emphasized to optimize the value of microarrays in the diagnosis of disorders caused by single gene copy number and sequence mutations. © 2011 Wiley-Liss, Inc.

  11. A new modified histogram matching normalization for time series microarray analysis

    NARCIS (Netherlands)

    Astola, L.J.; Molenaar, J.

    2014-01-01

    Microarray data is often utilized in inferring regulatory networks. Quantile normalization (QN) is a popular method to reduce array-to-array variation. We show that in the context of time series measurements QN may not be the best choice for this task, especially not if the inference is based on

  12. Mutation analysis of 272 Spanish families affected by autosomal recessive retinitis pigmentosa using a genotyping microarray.

    NARCIS (Netherlands)

    Avila-Fernandez, A.; Cantalapiedra, D.; Aller, E.; Vallespin, E.; Aguirre-Lamban, J.; Blanco-Kelly, F.; Corton, M.; Riveiro-Alvarez, R.; Allikmets, R.; Trujillo-Tiebas, M.J.; Millan, J.M.; Cremers, F.P.M.; Ayuso, C.

    2010-01-01

    PURPOSE: Retinitis pigmentosa (RP) is a genetically heterogeneous disorder characterized by progressive loss of vision. The aim of this study was to identify the causative mutations in 272 Spanish families using a genotyping microarray. METHODS: 272 unrelated Spanish families, 107 with autosomal

  13. Functional microarray analysis of nitrogen and carbon cycling genes across an Antarctic latitudinal transect.

    NARCIS (Netherlands)

    Yergeau, E.; Kang, S.; He, Z.; Zhou, J.; Kowalchuk, G.A.

    2007-01-01

    Soil-borne microbial communities were examined via a functional gene microarray approach across a southern polar latitudinal gradient to gain insight into the environmental factors steering soil N- and C-cycling in terrestrial Antarctic ecosystems. The abundance and diversity of functional gene

  14. Emerging use of gene expression microarrays in plant physiology.

    Science.gov (United States)

    Wullschleger, Stan D; Difazio, Stephen P

    2003-01-01

    Microarrays have become an important technology for the global analysis of gene expression in humans, animals, plants, and microbes. Implemented in the context of a well-designed experiment, cDNA and oligonucleotide arrays can provide highthroughput, simultaneous analysis of transcript abundance for hundreds, if not thousands, of genes. However, despite widespread acceptance, the use of microarrays as a tool to better understand processes of interest to the plant physiologist is still being explored. To help illustrate current uses of microarrays in the plant sciences, several case studies that we believe demonstrate the emerging application of gene expression arrays in plant physiology were selected from among the many posters and presentations at the 2003 Plant and Animal Genome XI Conference. Based on this survey, microarrays are being used to assess gene expression in plants exposed to the experimental manipulation of air temperature, soil water content and aluminium concentration in the root zone. Analysis often includes characterizing transcript profiles for multiple post-treatment sampling periods and categorizing genes with common patterns of response using hierarchical clustering techniques. In addition, microarrays are also providing insights into developmental changes in gene expression associated with fibre and root elongation in cotton and maize, respectively. Technical and analytical limitations of microarrays are discussed and projects attempting to advance areas of microarray design and data analysis are highlighted. Finally, although much work remains, we conclude that microarrays are a valuable tool for the plant physiologist interested in the characterization and identification of individual genes and gene families with potential application in the fields of agriculture, horticulture and forestry.

  15. Emerging Use of Gene Expression Microarrays in Plant Physiology

    Directory of Open Access Journals (Sweden)

    Stephen P. Difazio

    2006-04-01

    Full Text Available Microarrays have become an important technology for the global analysis of gene expression in humans, animals, plants, and microbes. Implemented in the context of a well-designed experiment, cDNA and oligonucleotide arrays can provide highthroughput, simultaneous analysis of transcript abundance for hundreds, if not thousands, of genes. However, despite widespread acceptance, the use of microarrays as a tool to better understand processes of interest to the plant physiologist is still being explored. To help illustrate current uses of microarrays in the plant sciences, several case studies that we believe demonstrate the emerging application of gene expression arrays in plant physiology were selected from among the many posters and presentations at the 2003 Plant and Animal Genome XI Conference. Based on this survey, microarrays are being used to assess gene expression in plants exposed to the experimental manipulation of air temperature, soil water content and aluminium concentration in the root zone. Analysis often includes characterizing transcript profiles for multiple post-treatment sampling periods and categorizing genes with common patterns of response using hierarchical clustering techniques. In addition, microarrays are also providing insights into developmental changes in gene expression associated with fibre and root elongation in cotton and maize, respectively. Technical and analytical limitations of microarrays are discussed and projects attempting to advance areas of microarray design and data analysis are highlighted. Finally, although much work remains, we conclude that microarrays are a valuable tool for the plant physiologist interested in the characterization and identification of individual genes and gene families with potential application in the fields of agriculture, horticulture and forestry.

  16. Microarray analysis of serum mRNA in patients with head and neck squamous cell carcinoma at whole-genome scale

    Czech Academy of Sciences Publication Activity Database

    Čapková, M.; Šáchová, Jana; Strnad, Hynek; Kolář, Michal; Hroudová, Miluše; Chovanec, M.; Čada, Z.; Štefl, M.; Valach, J.; Kastner, J.; Smetana, K. Jr.; Plzák, J.

    -, April 23 (2014) ISSN 2314-6141 R&D Projects: GA MZd(CZ) NT13488 Institutional support: RVO:68378050 Keywords : Microarray Analysis * Head and Neck Squamous Cell Carcinoma * whole-genome scale Subject RIV: EB - Genetics ; Molecular Biology

  17. ValWorkBench: an open source Java library for cluster validation, with applications to microarray data analysis.

    Science.gov (United States)

    Giancarlo, R; Scaturro, D; Utro, F

    2015-02-01

    The prediction of the number of clusters in a dataset, in particular microarrays, is a fundamental task in biological data analysis, usually performed via validation measures. Unfortunately, it has received very little attention and in fact there is a growing need for software tools/libraries dedicated to it. Here we present ValWorkBench, a software library consisting of eleven well known validation measures, together with novel heuristic approximations for some of them. The main objective of this paper is to provide the interested researcher with the full software documentation of an open source cluster validation platform having the main features of being easily extendible in a homogeneous way and of offering software components that can be readily re-used. Consequently, the focus of the presentation is on the architecture of the library, since it provides an essential map that can be used to access the full software documentation, which is available at the supplementary material website [1]. The mentioned main features of ValWorkBench are also discussed and exemplified, with emphasis on software abstraction design and re-usability. A comparison with existing cluster validation software libraries, mainly in terms of the mentioned features, is also offered. It suggests that ValWorkBench is a much needed contribution to the microarray software development/algorithm engineering community. For completeness, it is important to mention that previous accurate algorithmic experimental analysis of the relative merits of each of the implemented measures [19,23,25], carried out specifically on microarray data, gives useful insights on the effectiveness of ValWorkBench for cluster validation to researchers in the microarray community interested in its use for the mentioned task. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  18. Direct calibration of PICKY-designed microarrays

    Directory of Open Access Journals (Sweden)

    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.

  19. Microarray analysis of a salamander hopeful monster reveals transcriptional signatures of paedomorphic brain development

    Science.gov (United States)

    2010-01-01

    Background The Mexican axolotl (Ambystoma mexicanum) is considered a hopeful monster because it exhibits an adaptive and derived mode of development - paedomorphosis - that has evolved rapidly and independently among tiger salamanders. Unlike related tiger salamanders that undergo metamorphosis, axolotls retain larval morphological traits into adulthood and thus present an adult body plan that differs dramatically from the ancestral (metamorphic) form. The basis of paedomorphic development was investigated by comparing temporal patterns of gene transcription between axolotl and tiger salamander larvae (Ambystoma tigrinum tigrinum) that typically undergo a metamorphosis. Results Transcript abundances from whole brain and pituitary were estimated via microarray analysis on four different days post hatching (42, 56, 70, 84 dph) and regression modeling was used to independently identify genes that were differentially expressed as a function of time in both species. Collectively, more differentially expressed genes (DEGs) were identified as unique to the axolotl (n = 76) and tiger salamander (n = 292) than were identified as shared (n = 108). All but two of the shared DEGs exhibited the same temporal pattern of expression and the unique genes tended to show greater changes later in the larval period when tiger salamander larvae were undergoing anatomical metamorphosis. A second, complementary analysis that directly compared the expression of 1320 genes between the species identified 409 genes that differed as a function of species or the interaction between time and species. Of these 409 DEGs, 84% exhibited higher abundances in tiger salamander larvae at all sampling times. Conclusions Many of the unique tiger salamander transcriptional responses are probably associated with metamorphic biological processes. However, the axolotl also showed unique patterns of transcription early in development. In particular, the axolotl showed a genome-wide reduction in mRNA abundance

  20. Microarray analysis of a salamander hopeful monster reveals transcriptional signatures of paedomorphic brain development

    Directory of Open Access Journals (Sweden)

    Putta Srikrishna

    2010-06-01

    Full Text Available Abstract Background The Mexican axolotl (Ambystoma mexicanum is considered a hopeful monster because it exhibits an adaptive and derived mode of development - paedomorphosis - that has evolved rapidly and independently among tiger salamanders. Unlike related tiger salamanders that undergo metamorphosis, axolotls retain larval morphological traits into adulthood and thus present an adult body plan that differs dramatically from the ancestral (metamorphic form. The basis of paedomorphic development was investigated by comparing temporal patterns of gene transcription between axolotl and tiger salamander larvae (Ambystoma tigrinum tigrinum that typically undergo a metamorphosis. Results Transcript abundances from whole brain and pituitary were estimated via microarray analysis on four different days post hatching (42, 56, 70, 84 dph and regression modeling was used to independently identify genes that were differentially expressed as a function of time in both species. Collectively, more differentially expressed genes (DEGs were identified as unique to the axolotl (n = 76 and tiger salamander (n = 292 than were identified as shared (n = 108. All but two of the shared DEGs exhibited the same temporal pattern of expression and the unique genes tended to show greater changes later in the larval period when tiger salamander larvae were undergoing anatomical metamorphosis. A second, complementary analysis that directly compared the expression of 1320 genes between the species identified 409 genes that differed as a function of species or the interaction between time and species. Of these 409 DEGs, 84% exhibited higher abundances in tiger salamander larvae at all sampling times. Conclusions Many of the unique tiger salamander transcriptional responses are probably associated with metamorphic biological processes. However, the axolotl also showed unique patterns of transcription early in development. In particular, the axolotl showed a genome

  1. DNA microarray-based assessment of virulence potential of Shiga toxin gene-carrying Escherichia coli O104:H7 isolated from feedlot cattle feces.

    Directory of Open Access Journals (Sweden)

    Pragathi B Shridhar

    Full Text Available Escherichia coli O104:H4, a hybrid pathotype reported in a large 2011 foodborne outbreak in Germany, has not been detected in cattle feces. However, cattle harbor and shed in the feces other O104 serotypes, particularly O104:H7, which has been associated with sporadic cases of diarrhea in humans. The objective of our study was to assess the virulence potential of Shiga toxin-producing E. coli (STEC O104:H7 isolated from feces of feedlot cattle using DNA microarray. Six strains of STEC O104:H7 isolated from cattle feces were analyzed using FDA-E. coli Identification (ECID DNA microarray to determine their virulence profiles and compare them to the human strains (clinical of O104:H7, STEC O104:H4 (German outbreak strain, and O104:H21 (milk-associated Montana outbreak strain. Scatter plots were generated from the array data to visualize the gene-level differences between bovine and human O104 strains, and Pearson correlation coefficients (r were determined. Splits tree was generated to analyze relatedness between the strains. All O104:H7 strains, both bovine and human, similar to O104:H4 and O104:H21 outbreak strains were negative for intimin (eae. The bovine strains were positive for Shiga toxin 1 subtype c (stx1c, enterohemolysin (ehxA, tellurite resistance gene (terD, IrgA homolog protein (iha, type 1 fimbriae (fimH, and negative for genes that code for effector proteins of type III secretory system. The six cattle O104 strains were closely related (r = 0.86-0.98 to each other, except for a few differences in phage related and non-annotated genes. One of the human clinical O104:H7 strains (2011C-3665 was more closely related to the bovine O104:H7 strains (r = 0.81-0.85 than the other four human clinical O104:H7 strains (r = 0.75-0.79. Montana outbreak strain (O104:H21 was more closely related to four of the human clinical O104:H7 strains than the bovine O104:H7 strains. None of the bovine E. coli O104 strains carried genes characteristic of E

  2. LINKAGE ANALYSIS BY 2-DIMENSIONAL DNA TYPING

    NARCIS (Netherlands)

    MEERMAN, GJT; MULLAART, E; VANDERMEULEN, MA; DENDAAS, JHG; MOROLLI, B; UITTERLINDEN, AG; VIJG, J

    1993-01-01

    In two-dimensional (2-D) DNA typing, genomic DNA fragments are separated, first according to size by electrophoresis in a neutral polyacrylamide gel and second according to sequence by denaturing gradient gel electrophoresis, followed by hybridization analysis using micro- and minisatellite core

  3. Bovine and equine forensic DNA analysis

    NARCIS (Netherlands)

    van de Goor, L.H.P.

    2011-01-01

    Animal forensic DNA analysis is being used for human criminal investigations (e.g traces from cats and dogs), wildlife management, breeding and food safety. The most common DNA markers used for such forensic casework are short tandem repeats (STR). Rules and guidelines concerning quality assurance

  4. Short-term arginine deprivation results in large-scale modulation of hepatic gene expression in both normal and tumor cells: microarray bioinformatic analysis

    Directory of Open Access Journals (Sweden)

    Sabo Edmond

    2006-09-01

    Full Text Available Abstract Background We have reported arginine-sensitive regulation of LAT1 amino acid transporter (SLC 7A5 in normal rodent hepatic cells with loss of arginine sensitivity and high level constitutive expression in tumor cells. We hypothesized that liver cell gene expression is highly sensitive to alterations in the amino acid microenvironment and that tumor cells may differ substantially in gene sets sensitive to amino acid availability. To assess the potential number and classes of hepatic genes sensitive to arginine availability at the RNA level and compare these between normal and tumor cells, we used an Affymetrix microarray approach, a paired in vitro model of normal rat hepatic cells and a tumorigenic derivative with triplicate independent replicates. Cells were exposed to arginine-deficient or control conditions for 18 hours in medium formulated to maintain differentiated function. Results Initial two-way analysis with a p-value of 0.05 identified 1419 genes in normal cells versus 2175 in tumor cells whose expression was altered in arginine-deficient conditions relative to controls, representing 9–14% of the rat genome. More stringent bioinformatic analysis with 9-way comparisons and a minimum of 2-fold variation narrowed this set to 56 arginine-responsive genes in normal liver cells and 162 in tumor cells. Approximately half the arginine-responsive genes in normal cells overlap with those in tumor cells. Of these, the majority was increased in expression and included multiple growth, survival, and stress-related genes. GADD45, TA1/LAT1, and caspases 11 and 12 were among this group. Previously known amino acid regulated genes were among the pool in both cell types. Available cDNA probes allowed independent validation of microarray data for multiple genes. Among genes downregulated under arginine-deficient conditions were multiple genes involved in cholesterol and fatty acid metabolism. Expression of low-density lipoprotein receptor was

  5. Integrating Multiple Microarray Data for Cancer Pathway Analysis Using Bootstrapping K-S Test

    Directory of Open Access Journals (Sweden)

    Bing Han

    2009-01-01

    Full Text Available Previous applications of microarray technology for cancer research have mostly focused on identifying genes that are differentially expressed between a particular cancer and normal cells. In a biological system, genes perform different molecular functions and regulate various biological processes via interactions with other genes thus forming a variety of complex networks. Therefore, it is critical to understand the relationship (e.g., interactions between genes across different types of cancer in order to gain insights into the molecular mechanisms of cancer. Here we propose an integrative method based on the bootstrapping Kolmogorov-Smirnov test and a large set of microarray data produced with various types of cancer to discover common molecular changes in cells from normal state to cancerous state. We evaluate our method using three key pathways related to cancer and demonstrate that it is capable of finding meaningful alterations in gene relations.

  6. USE OF cDNA MICROARRAY TECHNOLOGY FOR IDENTIFICATION OF NOVEL GENES RESPONDING TO ABSCISIC ACID PHYTOHORMONE

    OpenAIRE

    D. Cabezas; Sandra Pérez; R. Huelva; Dong Haitao; Li Debao

    2005-01-01

    Se utilizó el cDNA microarreglo con 4370 unigenes, provenientes de la biblioteca del endospermo del arroz y de los tejidos de las hojas, para detectar los niveles de expresión del mRNA de los tejidos del tallo del arroz tratados con agua y con la hormona ácido abscísico (ABA). Los resultados mostraron que los niveles de expresión de cinco genes fueron reprimidos por la fitohormona ABA. El Reverse Northern confirmó que uno de los cinco genes (H024g06) fue realmente reprimido por el ABA. Los an...

  7. A New Modified Histogram Matching Normalization for Time Series Microarray Analysis.

    Science.gov (United States)

    Astola, Laura; Molenaar, Jaap

    2014-07-01

    Microarray data is often utilized in inferring regulatory networks. Quantile normalization (QN) is a popular method to reduce array-to-array variation. We show that in the context of time series measurements QN may not be the best choice for this task, especially not if the inference is based on continuous time ODE model. We propose an alternative normalization method that is better suited for network inference from time series data.

  8. A New Modified Histogram Matching Normalization for Time Series Microarray Analysis

    Directory of Open Access Journals (Sweden)

    Laura Astola

    2014-07-01

    Full Text Available Microarray data is often utilized in inferring regulatory networks. Quantile normalization (QN is a popular method to reduce array-to-array variation. We show that in the context of time series measurements QN may not be the best choice for this task, especially not if the inference is based on continuous time ODE model. We propose an alternative normalization method that is better suited for network inference from time series data.

  9. Nanopore sensors for DNA analysis

    DEFF Research Database (Denmark)

    Solovyeva, Vita; Venkatesan, B.M.; Shim, Jeong

    2012-01-01

    Solid-state nanopore sensors are promising devices for single DNA molecule detection and sequencing. This paper presents a review of our work on solid-state nanopores performed over the last decade. In particular, here we discuss atomic-layer-deposited (ALD)-based, graphene-based, and functionali......Solid-state nanopore sensors are promising devices for single DNA molecule detection and sequencing. This paper presents a review of our work on solid-state nanopores performed over the last decade. In particular, here we discuss atomic-layer-deposited (ALD)-based, graphene...

  10. Evaluation of chronic lymphocytic leukemia by BAC-based microarray analysis

    Directory of Open Access Journals (Sweden)

    McDaniel Lisa D

    2011-02-01

    Full Text Available Abstract Background Chronic lymphocytic leukemia (CLL is a highly variable disease with life expectancies ranging from months to decades. Cytogenetic findings play an integral role in defining the prognostic significance and treatment for individual patients. Results We have evaluated 25 clinical cases from a tertiary cancer center that have an established diagnosis of CLL and for which there was prior cytogenetic and/or fluorescence in situ hybridization (FISH data. We performed microarray-based comparative genomic hybridization (aCGH using a bacterial artificial chromosome (BAC-based microarray designed for the detection of known constitutional genetic syndromes. In 15 of the 25 cases, aCGH detected all copy number imbalances identified by prior cytogenetic and/or FISH studies. For the majority of those not detected, the aberrations were present at low levels of mosaicism. Furthermore, for 15 of the 25 cases, additional abnormalities were detected. Four of those cases had deletions that mapped to intervals implicated in inherited predisposition to CLL. For most cases, aCGH was able to detect abnormalities present in as few as 10% of cells. Although changes in ploidy are not easily discernable by aCGH, results for two cases illustrate the detection of additional copy gains and losses present within a mosaic tetraploid cell population. Conclusions Our results illustrate the successful evaluation of CLL using a microarray optimized for the interrogation of inherited disorders and the identification of alterations with possible relevance to CLL susceptibility.

  11. Multiplexed fluorescent microarray for human salivary protein analysis using polymer microspheres and fiber-optic bundles.

    Science.gov (United States)

    Nie, Shuai; Benito-Peña, Elena; Zhang, Huaibin; Wu, Yue; Walt, David R

    2013-10-10

    Herein, we describe a protocol for simultaneously measuring six proteins in saliva using a fiber-optic microsphere-based antibody array. The immuno-array technology employed combines the advantages of microsphere-based suspension array fabrication with the use of fluorescence microscopy. As described in the video protocol, commercially available 4.5 μm polymer microspheres were encoded into seven different types, differentiated by the concentration of two fluorescent dyes physically trapped inside the microspheres. The encoded microspheres containing surface carboxyl groups were modified with monoclonal capture antibodies through EDC/NHS coupling chemistry. To assemble the protein microarray, the different types of encoded and functionalized microspheres were mixed and randomly deposited in 4.5 μm microwells, which were chemically etched at the proximal end of a fiber-optic bundle. The fiber-optic bundle was used as both a carrier and for imaging the microspheres. Once assembled, the microarray was used to capture proteins in the saliva supernatant collected from the clinic. The detection was based on a sandwich immunoassay using a mixture of biotinylated detection antibodies for different analytes with a streptavidin-conjugated fluorescent probe, R-phycoerythrin. The