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Sample records for affymetrix microarray analysis

  1. Analysis of discordant Affymetrix probesets casts serious doubt on idea of microarray data reutilization

    PubMed Central

    2014-01-01

    Background Affymetrix microarray technology allows one to investigate expression of thousands of genes simultaneously upon a variety of conditions. In a popular U133A microarray platform, the expression of 37% of genes is measured by more than one probeset. The discordant expression observed for two different probesets that match the same gene is a widespread phenomenon which is usually underestimated, ignored or disregarded. Results Here we evaluate the prevalence of discordant expression in data collected using Affymetrix HG-U133A microarray platform. In U133A, about 30% of genes annotated by two different probesets demonstrate a substantial correlation between independently measured expression values. To our surprise, sorting the probesets according to the nature of the discrepancy in their expression levels allowed the classification of the respective genes according to their fundamental functional properties, including observed enrichment by tissue-specific transcripts and alternatively spliced variants. On another hand, an absence of discrepancies in probesets that simultaneously match several different genes allowed us to pinpoint non-expressed pseudogenes and gene groups with highly correlated expression patterns. Nevertheless, in many cases, the nature of discordant expression of two probesets that match the same transcript remains unexplained. It is possible that these probesets report differently regulated sets of transcripts, or, in best case scenario, two different sets of transcripts that represent the same gene. Conclusion The majority of absolute gene expression values collected using Affymetrix microarrays may not be suitable for typical interpretative downstream analysis. PMID:25563078

  2. AffyTrees: facilitating comparative analysis of Affymetrix plant microarray chips.

    PubMed

    Frickey, Tancred; Benedito, Vagner Augusto; Udvardi, Michael; Weiller, Georg

    2008-02-01

    Microarrays measure the expression of large numbers of genes simultaneously and can be used to delve into interaction networks involving many genes at a time. However, it is often difficult to decide to what extent knowledge about the expression of genes gleaned in one model organism can be transferred to other species. This can be examined either by measuring the expression of genes of interest under comparable experimental conditions in other species, or by gathering the necessary data from comparable microarray experiments. However, it is essential to know which genes to compare between the organisms. To facilitate comparison of expression data across different species, we have implemented a Web-based software tool that provides information about sequence orthologs across a range of Affymetrix microarray chips. AffyTrees provides a quick and easy way of assigning which probe sets on different Affymetrix chips measure the expression of orthologous genes. Even in cases where gene or genome duplications have complicated the assignment, groups of comparable probe sets can be identified. The phylogenetic trees provide a resource that can be used to improve sequence annotation and detect biases in the sequence complement of Affymetrix chips. Being able to identify sequence orthologs and recognize biases in the sequence complement of chips is necessary for reliable cross-species microarray comparison. As the amount of work required to generate a single phylogeny in a nonautomated manner is considerable, AffyTrees can greatly reduce the workload for scientists interested in large-scale cross-species comparisons.

  3. Affymetrix GeneChip microarray preprocessing for multivariate analyses.

    PubMed

    McCall, Matthew N; Almudevar, Anthony

    2012-09-01

    Affymetrix GeneChip microarrays are the most widely used high-throughput technology to measure gene expression, and a wide variety of preprocessing methods have been developed to transform probe intensities reported by a microarray scanner into gene expression estimates. There have been numerous comparisons of these preprocessing methods, focusing on the most common analyses-detection of differential expression and gene or sample clustering. Recently, more complex multivariate analyses, such as gene co-expression, differential co-expression, gene set analysis and network modeling, are becoming more common; however, the same preprocessing methods are typically applied. In this article, we examine the effect of preprocessing methods on some of these multivariate analyses and provide guidance to the user as to which methods are most appropriate.

  4. Micro-Analyzer: automatic preprocessing of Affymetrix microarray data.

    PubMed

    Guzzi, Pietro Hiram; Cannataro, Mario

    2013-08-01

    A current trend in genomics is the investigation of the cell mechanism using different technologies, in order to explain the relationship among genes, molecular processes and diseases. For instance, the combined use of gene-expression arrays and genomic arrays has been demonstrated as an effective instrument in clinical practice. Consequently, in a single experiment different kind of microarrays may be used, resulting in the production of different types of binary data (images and textual raw data). The analysis of microarray data requires an initial preprocessing phase, that makes raw data suitable for use on existing analysis platforms, such as the TIGR M4 (TM4) Suite. An additional challenge to be faced by emerging data analysis platforms is the ability to treat in a combined way those different microarray formats coupled with clinical data. In fact, resulting integrated data may include both numerical and symbolic data (e.g. gene expression and SNPs regarding molecular data), as well as temporal data (e.g. the response to a drug, time to progression and survival rate), regarding clinical data. Raw data preprocessing is a crucial step in analysis but is often performed in a manual and error prone way using different software tools. Thus novel, platform independent, and possibly open source tools enabling the semi-automatic preprocessing and annotation of different microarray data are needed. The paper presents Micro-Analyzer (Microarray Analyzer), a cross-platform tool for the automatic normalization, summarization and annotation of Affymetrix gene expression and SNP binary data. It represents the evolution of the μ-CS tool, extending the preprocessing to SNP arrays that were not allowed in μ-CS. The Micro-Analyzer is provided as a Java standalone tool and enables users to read, preprocess and analyse binary microarray data (gene expression and SNPs) by invoking TM4 platform. It avoids: (i) the manual invocation of external tools (e.g. the Affymetrix Power

  5. Micro-Analyzer: automatic preprocessing of Affymetrix microarray data.

    PubMed

    Guzzi, Pietro Hiram; Cannataro, Mario

    2013-08-01

    A current trend in genomics is the investigation of the cell mechanism using different technologies, in order to explain the relationship among genes, molecular processes and diseases. For instance, the combined use of gene-expression arrays and genomic arrays has been demonstrated as an effective instrument in clinical practice. Consequently, in a single experiment different kind of microarrays may be used, resulting in the production of different types of binary data (images and textual raw data). The analysis of microarray data requires an initial preprocessing phase, that makes raw data suitable for use on existing analysis platforms, such as the TIGR M4 (TM4) Suite. An additional challenge to be faced by emerging data analysis platforms is the ability to treat in a combined way those different microarray formats coupled with clinical data. In fact, resulting integrated data may include both numerical and symbolic data (e.g. gene expression and SNPs regarding molecular data), as well as temporal data (e.g. the response to a drug, time to progression and survival rate), regarding clinical data. Raw data preprocessing is a crucial step in analysis but is often performed in a manual and error prone way using different software tools. Thus novel, platform independent, and possibly open source tools enabling the semi-automatic preprocessing and annotation of different microarray data are needed. The paper presents Micro-Analyzer (Microarray Analyzer), a cross-platform tool for the automatic normalization, summarization and annotation of Affymetrix gene expression and SNP binary data. It represents the evolution of the μ-CS tool, extending the preprocessing to SNP arrays that were not allowed in μ-CS. The Micro-Analyzer is provided as a Java standalone tool and enables users to read, preprocess and analyse binary microarray data (gene expression and SNPs) by invoking TM4 platform. It avoids: (i) the manual invocation of external tools (e.g. the Affymetrix Power

  6. Methods comparison for high-resolution transcriptional analysis of archival material on Affymetrix Plus 2.0 and Exon 1.0 microarrays.

    PubMed

    Linton, Kim; Hey, Yvonne; Dibben, Sian; Miller, Crispin; Freemont, Anthony; Radford, John; Pepper, Stuart

    2009-07-01

    Microarray gene expression profiling of formalin-fixed paraffin-embedded (FFPE) tissues is a new and evolving technique. This report compares transcript detection rates on Affymetrix U133 Plus 2.0 and Human Exon 1.0 ST GeneChips across several RNA extraction and target labeling protocols, using routinely collected archival FFPE samples. All RNA extraction protocols tested (Ambion-Optimum, Ambion-RecoverAll, and Qiagen-RNeasy FFPE) provided extracts suitable for microarray hybridization. Compared with Affymetrix One-Cycle labeled extracts, NuGEN system protocols utilizing oligo(dT) and random hexamer primers, and cDNA target preparations instead of cRNA, achieved percent present rates up to 55% on Plus 2.0 arrays. Based on two paired-sample analyses, at 90% specificity this equalled an average 30 percentage-point increase (from 50% to 80%) in FFPE transcript sensitivity relative to fresh frozen tissues, which we have assumed to have 100% sensitivity and specificity. The high content of Exon arrays, with multiple probe sets per exon, improved FFPE sensitivity to 92% at 96% specificity, corresponding to an absolute increase of ~600 genes over Plus 2.0 arrays. While larger series are needed to confirm high correspondence between fresh-frozen and FFPE expression patterns, these data suggest that both Plus 2.0 and Exon arrays are suitable platforms for FFPE microarray expression analyses.

  7. MAAMD: a workflow to standardize meta-analyses and comparison of affymetrix microarray data

    PubMed Central

    2014-01-01

    Background Mandatory deposit of raw microarray data files for public access, prior to study publication, provides significant opportunities to conduct new bioinformatics analyses within and across multiple datasets. Analysis of raw microarray data files (e.g. Affymetrix CEL files) can be time consuming, complex, and requires fundamental computational and bioinformatics skills. The development of analytical workflows to automate these tasks simplifies the processing of, improves the efficiency of, and serves to standardize multiple and sequential analyses. Once installed, workflows facilitate the tedious steps required to run rapid intra- and inter-dataset comparisons. Results We developed a workflow to facilitate and standardize Meta-Analysis of Affymetrix Microarray Data analysis (MAAMD) in Kepler. Two freely available stand-alone software tools, R and AltAnalyze were embedded in MAAMD. The inputs of MAAMD are user-editable csv files, which contain sample information and parameters describing the locations of input files and required tools. MAAMD was tested by analyzing 4 different GEO datasets from mice and drosophila. MAAMD automates data downloading, data organization, data quality control assesment, differential gene expression analysis, clustering analysis, pathway visualization, gene-set enrichment analysis, and cross-species orthologous-gene comparisons. MAAMD was utilized to identify gene orthologues responding to hypoxia or hyperoxia in both mice and drosophila. The entire set of analyses for 4 datasets (34 total microarrays) finished in ~ one hour. Conclusions MAAMD saves time, minimizes the required computer skills, and offers a standardized procedure for users to analyze microarray datasets and make new intra- and inter-dataset comparisons. PMID:24621103

  8. Rawcopy: Improved copy number analysis with Affymetrix arrays

    PubMed Central

    Mayrhofer, Markus; Viklund, Björn; Isaksson, Anders

    2016-01-01

    Microarray data is subject to noise and systematic variation that negatively affects the resolution of copy number analysis. We describe Rawcopy, an R package for processing of Affymetrix CytoScan HD, CytoScan 750k and SNP 6.0 microarray raw intensities (CEL files). Noise characteristics of a large number of reference samples are used to estimate log ratio and B-allele frequency for total and allele-specific copy number analysis. Rawcopy achieves better signal-to-noise ratio and higher proportion of validated alterations than commonly used free and proprietary alternatives. In addition, Rawcopy visualizes each microarray sample for assessment of technical quality, patient identity and genome-wide absolute copy number states. Software and instructions are available at http://rawcopy.org. PMID:27796336

  9. Tiling Microarray Analysis Tools

    SciTech Connect

    Nix, Davis Austin

    2005-05-04

    TiMAT is a package of 23 command line Java applications for use in the analysis of Affymetrix tiled genomic microarray data. TiMAT enables: 1) Rebuilding the genome annotation for entire tiled arrays (repeat filtering, chromosomal coordinate assignment). 2) Post processing of oligo intensity values (quantile normalization, median scaling, PMMM transformation), 3) Significance testing (Wilcoxon rank sum and signed rank tests, intensity difference and ratio tests) and Interval refinement (filtering based on multiple statistics, overlap comparisons), 4) Data visualization (detailed thumbnail/zoomed view with Interval Plots and data export to Affymetrix's Integrated Genome Browser) and Data reports (spreadsheet summaries and detailed profiles)

  10. affyPara-a Bioconductor Package for Parallelized Preprocessing Algorithms of Affymetrix Microarray Data.

    PubMed

    Schmidberger, Markus; Vicedo, Esmeralda; Mansmann, Ulrich

    2009-07-22

    Microarray data repositories as well as large clinical applications of gene expression allow to analyse several hundreds of microarrays at one time. The preprocessing of large amounts of microarrays is still a challenge. The algorithms are limited by the available computer hardware. For example, building classification or prognostic rules from large microarray sets will be very time consuming. Here, preprocessing has to be a part of the cross-validation and resampling strategy which is necessary to estimate the rule's prediction quality honestly.This paper proposes the new Bioconductor package affyPara for parallelized preprocessing of Affymetrix microarray data. Partition of data can be applied on arrays and parallelization of algorithms is a straightforward consequence. The partition of data and distribution to several nodes solves the main memory problems and accelerates preprocessing by up to the factor 20 for 200 or more arrays.affyPara is a free and open source package, under GPL license, available form the Bioconductor project at www.bioconductor.org. A user guide and examples are provided with the package.

  11. A new method for class prediction based on signed-rank algorithms applied to Affymetrix® microarray experiments

    PubMed Central

    Rème, Thierry; Hose, Dirk; De Vos, John; Vassal, Aurélien; Poulain, Pierre-Olivier; Pantesco, Véronique; Goldschmidt, Hartmut; Klein, Bernard

    2008-01-01

    Background The huge amount of data generated by DNA chips is a powerful basis to classify various pathologies. However, constant evolution of microarray technology makes it difficult to mix data from different chip types for class prediction of limited sample populations. Affymetrix® technology provides both a quantitative fluorescence signal and a decision (detection call: absent or present) based on signed-rank algorithms applied to several hybridization repeats of each gene, with a per-chip normalization. We developed a new prediction method for class belonging based on the detection call only from recent Affymetrix chip type. Biological data were obtained by hybridization on U133A, U133B and U133Plus 2.0 microarrays of purified normal B cells and cells from three independent groups of multiple myeloma (MM) patients. Results After a call-based data reduction step to filter out non class-discriminative probe sets, the gene list obtained was reduced to a predictor with correction for multiple testing by iterative deletion of probe sets that sequentially improve inter-class comparisons and their significance. The error rate of the method was determined using leave-one-out and 5-fold cross-validation. It was successfully applied to (i) determine a sex predictor with the normal donor group classifying gender with no error in all patient groups except for male MM samples with a Y chromosome deletion, (ii) predict the immunoglobulin light and heavy chains expressed by the malignant myeloma clones of the validation group and (iii) predict sex, light and heavy chain nature for every new patient. Finally, this method was shown powerful when compared to the popular classification method Prediction Analysis of Microarray (PAM). Conclusion This normalization-free method is routinely used for quality control and correction of collection errors in patient reports to clinicians. It can be easily extended to multiple class prediction suitable with clinical groups, and looks

  12. Tiling Microarray Analysis Tools

    2005-05-04

    TiMAT is a package of 23 command line Java applications for use in the analysis of Affymetrix tiled genomic microarray data. TiMAT enables: 1) Rebuilding the genome annotation for entire tiled arrays (repeat filtering, chromosomal coordinate assignment). 2) Post processing of oligo intensity values (quantile normalization, median scaling, PMMM transformation), 3) Significance testing (Wilcoxon rank sum and signed rank tests, intensity difference and ratio tests) and Interval refinement (filtering based on multiple statistics, overlap comparisons),more » 4) Data visualization (detailed thumbnail/zoomed view with Interval Plots and data export to Affymetrix's Integrated Genome Browser) and Data reports (spreadsheet summaries and detailed profiles)« less

  13. VIZARD: analysis of Affymetrix Arabidopsis GeneChip data

    NASA Technical Reports Server (NTRS)

    Moseyko, Nick; Feldman, Lewis J.

    2002-01-01

    SUMMARY: The Affymetrix GeneChip Arabidopsis genome array has proved to be a very powerful tool for the analysis of gene expression in Arabidopsis thaliana, the most commonly studied plant model organism. VIZARD is a Java program created at the University of California, Berkeley, to facilitate analysis of Arabidopsis GeneChip data. It includes several integrated tools for filtering, sorting, clustering and visualization of gene expression data as well as tools for the discovery of regulatory motifs in upstream sequences. VIZARD also includes annotation and upstream sequence databases for the majority of genes represented on the Affymetrix Arabidopsis GeneChip array. AVAILABILITY: VIZARD is available free of charge for educational, research, and not-for-profit purposes, and can be downloaded at http://www.anm.f2s.com/research/vizard/ CONTACT: moseyko@uclink4.berkeley.edu.

  14. DMET-Analyzer: automatic analysis of Affymetrix DMET Data

    PubMed Central

    2012-01-01

    Background Clinical Bioinformatics is currently growing and is based on the integration of clinical and omics data aiming at the development of personalized medicine. Thus the introduction of novel technologies able to investigate the relationship among clinical states and biological machineries may help the development of this field. For instance the Affymetrix DMET platform (drug metabolism enzymes and transporters) is able to study the relationship among the variation of the genome of patients and drug metabolism, detecting SNPs (Single Nucleotide Polymorphism) on genes related to drug metabolism. This may allow for instance to find genetic variants in patients which present different drug responses, in pharmacogenomics and clinical studies. Despite this, there is currently a lack in the development of open-source algorithms and tools for the analysis of DMET data. Existing software tools for DMET data generally allow only the preprocessing of binary data (e.g. the DMET-Console provided by Affymetrix) and simple data analysis operations, but do not allow to test the association of the presence of SNPs with the response to drugs. Results We developed DMET-Analyzer a tool for the automatic association analysis among the variation of the patient genomes and the clinical conditions of patients, i.e. the different response to drugs. The proposed system allows: (i) to automatize the workflow of analysis of DMET-SNP data avoiding the use of multiple tools; (ii) the automatic annotation of DMET-SNP data and the search in existing databases of SNPs (e.g. dbSNP), (iii) the association of SNP with pathway through the search in PharmaGKB, a major knowledge base for pharmacogenomic studies. DMET-Analyzer has a simple graphical user interface that allows users (doctors/biologists) to upload and analyse DMET files produced by Affymetrix DMET-Console in an interactive way. The effectiveness and easy use of DMET Analyzer is demonstrated through different case studies regarding

  15. ChIP-on-chip analysis methods for Affymetrix tiling arrays.

    PubMed

    Yoder, Sean J

    2015-01-01

    Although the ChIP-sequencing has gained significant attraction recently, ChIP analysis using microarrays is still an attractive option due to the low cost, ease of analysis, and access to legacy and public data sets. The analysis of ChIP-Chip data entails a multistep approach that requires several different applications to progress from the initial stages of raw data analysis to the identification and characterization of ChIP binding sites. There are multiple approaches to data analysis and there are several applications available for each stage of the analysis pipeline. Each application must be evaluated for its suitability for the particular experiment as well as the investigator's background with computational tools. This chapter is a review of the commonly available applications for Affymetrix ChIP-Chip data analysis, as well as the general workflow of a ChIP-Chip analysis approach. The purpose of the chapter is to allow the researcher to better select the appropriate applications and provide them with the direction necessary to proceed with a ChIP-Chip analysis.

  16. Microarray Analysis in Glioblastomas

    PubMed Central

    Bhawe, Kaumudi M.; Aghi, Manish K.

    2016-01-01

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

  17. Microarray Analysis in Glioblastomas.

    PubMed

    Bhawe, Kaumudi M; Aghi, Manish K

    2016-01-01

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

  18. Identification of biomarkers regulated by rexinoids (LGD1069, LG100268 and Ro25-7386) in human breast cells using Affymetrix microarray.

    PubMed

    Seo, Hye-Sook; Woo, Jong-Kyu; Shin, Yong Cheol; Ko, Seong-Gyu

    2015-07-01

    Retinoids possess anti-proliferative properties, which suggests that they possess chemopreventive and therapeutic potential against cancer. In the current study, genes modulated by rexinoids (retinoid X receptor (RXR)-pan agonists, LGD1069 and LG100268; and the RXRα agonist, Ro25-7386) were identified using an Affymetrix microarray in normal and malignant breast cells. It was observed that LGD1069, LG100268 and Ro25-7386 suppressed the growth of breast cells. Secondly, several rexinoid-regulated genes were identified, which are involved in cell death, cell growth/maintenance, signal transduction and response to stimulus. These genes may be associated with the growth-suppressive activity of rexinoids. Therefore, the identified genes may serve as biomarkers and novel molecular targets for the prevention and treatment of breast cancer.

  19. Starr: Simple Tiling ARRay analysis of Affymetrix ChIP-chip data

    PubMed Central

    2010-01-01

    Background Chromatin immunoprecipitation combined with DNA microarrays (ChIP-chip) is an assay used for investigating DNA-protein-binding or post-translational chromatin/histone modifications. As with all high-throughput technologies, it requires thorough bioinformatic processing of the data for which there is no standard yet. The primary goal is to reliably identify and localize genomic regions that bind a specific protein. Further investigation compares binding profiles of functionally related proteins, or binding profiles of the same proteins in different genetic backgrounds or experimental conditions. Ultimately, the goal is to gain a mechanistic understanding of the effects of DNA binding events on gene expression. Results We present a free, open-source R/Bioconductor package Starr that facilitates comparative analysis of ChIP-chip data across experiments and across different microarray platforms. The package provides functions for data import, quality assessment, data visualization and exploration. Starr includes high-level analysis tools such as the alignment of ChIP signals along annotated features, correlation analysis of ChIP signals with complementary genomic data, peak-finding and comparative display of multiple clusters of binding profiles. It uses standard Bioconductor classes for maximum compatibility with other software. Moreover, Starr automatically updates microarray probe annotation files by a highly efficient remapping of microarray probe sequences to an arbitrary genome. Conclusion Starr is an R package that covers the complete ChIP-chip workflow from data processing to binding pattern detection. It focuses on the high-level data analysis, e.g., it provides methods for the integration and combined statistical analysis of binding profiles and complementary functional genomics data. Starr enables systematic assessment of binding behaviour for groups of genes that are alingned along arbitrary genomic features. PMID:20398407

  20. Microarray Analysis of Microbial Weathering

    NASA Astrophysics Data System (ADS)

    Olsson-Francis, K.; van Houdt, R.; Leys, N.; Mergeay, M.; Cockell, C. S.

    2010-04-01

    Microarray analysis of the heavy metal resistant bacterium, Cupriavidus metallidurans CH34 was used to investigate the genes involved in the weathering. The results demonstrated that large porin and membrane transporter genes were unregulated.

  1. Microarray platform for omics analysis

    NASA Astrophysics Data System (ADS)

    Mecklenburg, Michael; Xie, Bin

    2001-09-01

    Microarray technology has revolutionized genetic analysis. However, limitations in genome analysis has lead to renewed interest in establishing 'omic' strategies. As we enter the post-genomic era, new microarray technologies are needed to address these new classes of 'omic' targets, such as proteins, as well as lipids and carbohydrates. We have developed a microarray platform that combines self- assembling monolayers with the biotin-streptavidin system to provide a robust, versatile immobilization scheme. A hydrophobic film is patterned on the surface creating an array of tension wells that eliminates evaporation effects thereby reducing the shear stress to which biomolecules are exposed to during immobilization. The streptavidin linker layer makes it possible to adapt and/or develop microarray based assays using virtually any class of biomolecules including: carbohydrates, peptides, antibodies, receptors, as well as them ore traditional DNA based arrays. Our microarray technology is designed to furnish seamless compatibility across the various 'omic' platforms by providing a common blueprint for fabricating and analyzing arrays. The prototype microarray uses a microscope slide footprint patterned with 2 by 96 flat wells. Data on the microarray platform will be presented.

  2. Comparison of Nanostring nCounter® Data on FFPE Colon Cancer Samples and Affymetrix Microarray Data on Matched Frozen Tissues.

    PubMed

    Chen, Xi; Deane, Natasha G; Lewis, Keeli B; Li, Jiang; Zhu, Jing; Washington, M Kay; Beauchamp, R Daniel

    2016-01-01

    The prognosis of colorectal cancer (CRC) stage II and III patients remains a challenge due to the difficulties of finding robust biomarkers suitable for testing clinical samples. The majority of published gene signatures of CRC have been generated on fresh frozen colorectal tissues. Because collection of frozen tissue is not practical for routine surgical pathology practice, a clinical test that improves prognostic capabilities beyond standard pathological staging of colon cancer will need to be designed for formalin-fixed paraffin-embedded (FFPE) tissues. The NanoString nCounter® platform is a gene expression analysis tool developed for use with FFPE-derived samples. We designed a custom nCounter® codeset based on elements from multiple published fresh frozen tissue microarray-based prognostic gene signatures for colon cancer, and we used this platform to systematically compare gene expression data from FFPE with matched microarray array data from frozen tissues. Our results show moderate correlation of gene expression between two platforms and discovery of a small subset of genes as candidate biomarkers for colon cancer prognosis that are detectable and quantifiable in FFPE tissue sections. PMID:27176004

  3. AMDA 2.13: A major update for automated cross-platform microarray data analysis.

    PubMed

    Kapetis, Dimos; Clarelli, Ferdinando; Vitulli, Federico; de Rosbo, Nicole Kerlero; Beretta, Ottavio; Foti, Maria; Ricciardi-Castagnoli, Paola; Zolezzi, Francesca

    2012-07-01

    Microarray platforms require analytical pipelines with modules for data pre-processing including data normalization, statistical analysis for identification of differentially expressed genes, cluster analysis, and functional annotation. We previously developed the Automated Microarray Data Analysis (AMDA, version 2.3.5) pipeline to process Affymetrix 3' IVT GeneChips. The availability of newer technologies that demand open-source tools for microarray data analysis has impelled us to develop an updated multi-platform version, AMDA 2.13. It includes additional quality control metrics, annotation-driven (annotation grade of Affymetrix NetAffx) and signal-driven (Inter-Quartile Range) gene filtering, and approaches to experimental design. To enhance understanding of biological data, differentially expressed genes have been mapped into KEGG pathways. Finally, a more stable and user-friendly interface was designed to integrate the requirements for different platforms. AMDA 2.13 allows the analysis of Affymetrix (cartridges and plates) and whole transcript probe design (Gene 1.0/1.1 ST and Exon 1.0 ST GeneChips), Illumina Bead Arrays, and one-channel Agilent 4×44 arrays. Relative to early versions, it supports various experimental designs and delivers more insightful biological understanding and up-to-date annotations.

  4. Lectin microarrays for glycomic analysis.

    PubMed

    Gupta, Garima; Surolia, Avadhesha; Sampathkumar, Srinivasa-Gopalan

    2010-08-01

    Glycomics is the study of comprehensive structural elucidation and characterization of all glycoforms found in nature and their dynamic spatiotemporal changes that are associated with biological processes. Glycocalyx of mammalian cells actively participate in cell-cell, cell-matrix, and cell-pathogen interactions, which impact embryogenesis, growth and development, homeostasis, infection and immunity, signaling, malignancy, and metabolic disorders. Relative to genomics and proteomics, glycomics is just growing out of infancy with great potential in biomedicine for biomarker discovery, diagnosis, and treatment. However, the immense diversity and complexity of glycan structures and their multiple modes of interactions with proteins pose great challenges for development of analytical tools for delineating structure function relationships and understanding glyco-code. Several tools are being developed for glycan profiling based on chromatography, mass spectrometry, glycan microarrays, and glyco-informatics. Lectins, which have long been used in glyco-immunology, printed on a microarray provide a versatile platform for rapid high throughput analysis of glycoforms of biological samples. Herein, we summarize technological advances in lectin microarrays and critically review their impact on glycomics analysis. Challenges remain in terms of expansion to include nonplant derived lectins, standardization for routine clinical use, development of recombinant lectins, and exploration of plant kingdom for discovery of novel lectins. PMID:20726799

  5. Lectin microarrays for glycomic analysis.

    PubMed

    Gupta, Garima; Surolia, Avadhesha; Sampathkumar, Srinivasa-Gopalan

    2010-08-01

    Glycomics is the study of comprehensive structural elucidation and characterization of all glycoforms found in nature and their dynamic spatiotemporal changes that are associated with biological processes. Glycocalyx of mammalian cells actively participate in cell-cell, cell-matrix, and cell-pathogen interactions, which impact embryogenesis, growth and development, homeostasis, infection and immunity, signaling, malignancy, and metabolic disorders. Relative to genomics and proteomics, glycomics is just growing out of infancy with great potential in biomedicine for biomarker discovery, diagnosis, and treatment. However, the immense diversity and complexity of glycan structures and their multiple modes of interactions with proteins pose great challenges for development of analytical tools for delineating structure function relationships and understanding glyco-code. Several tools are being developed for glycan profiling based on chromatography, mass spectrometry, glycan microarrays, and glyco-informatics. Lectins, which have long been used in glyco-immunology, printed on a microarray provide a versatile platform for rapid high throughput analysis of glycoforms of biological samples. Herein, we summarize technological advances in lectin microarrays and critically review their impact on glycomics analysis. Challenges remain in terms of expansion to include nonplant derived lectins, standardization for routine clinical use, development of recombinant lectins, and exploration of plant kingdom for discovery of novel lectins.

  6. Benchmarking the CATMA Microarray. A Novel Tool forArabidopsis Transcriptome Analysis1[w

    PubMed Central

    Allemeersch, Joke; Durinck, Steffen; Vanderhaeghen, Rudy; Alard, Philippe; Maes, Ruth; Seeuws, Kurt; Bogaert, Tom; Coddens, Kathleen; Deschouwer, Kirsten; Van Hummelen, Paul; Vuylsteke, Marnik; Moreau, Yves; Kwekkeboom, Jeroen; Wijfjes, André H.M.; May, Sean; Beynon, Jim; Hilson, Pierre; Kuiper, Martin T.R.

    2005-01-01

    Transcript profiling is crucial to study biological systems, and various platforms have been implemented to survey mRNAs at the genome scale. We have assessed the performance of the CATMA microarray designed for Arabidopsis (Arabidopsis thaliana) transcriptome analysis and compared it with the Agilent and Affymetrix commercial platforms. The CATMA array consists of gene-specific sequence tags of 150 to 500 bp, the Agilent (Arabidopsis 2) array of 60mer oligonucleotides, and the Affymetrix gene chip (ATH1) of 25mer oligonucleotide sets. We have matched each probe repertoire with the Arabidopsis genome annotation (The Institute for Genomic Research release 5.0) and determined the correspondence between them. Array performance was analyzed by hybridization with labeled targets derived from eight RNA samples made of shoot total RNA spiked with a calibrated series of 14 control transcripts. CATMA arrays showed the largest dynamic range extending over three to four logs. Agilent and Affymetrix arrays displayed a narrower range, presumably because signal saturation occurred for transcripts at concentrations beyond 1,000 copies per cell. Sensitivity was comparable for all three platforms. For Affymetrix GeneChip data, the RMA software package outperformed Microarray Suite 5.0 for all investigated criteria, confirming that the information provided by the mismatch oligonucleotides has no added value. In addition, taking advantage of replicates in our dataset, we conducted a robust statistical analysis of the platform propensity to yield false positive and false negative differentially expressed genes, and all gave satisfactory results. The results establish the CATMA array as a mature alternative to the Affymetrix and Agilent platforms. PMID:15710687

  7. Automated Microarray Image Analysis Toolbox for MATLAB

    SciTech Connect

    White, Amanda M.; Daly, Don S.; Willse, Alan R.; Protic, Miroslava; Chandler, Darrell P.

    2005-09-01

    The Automated Microarray Image Analysis (AMIA) Toolbox for MATLAB is a flexible, open-source microarray image analysis tool that allows the user to customize analysis of sets of microarray images. This tool provides several methods of identifying and quantify spot statistics, as well as extensive diagnostic statistics and images to identify poor data quality or processing. The open nature of this software allows researchers to understand the algorithms used to provide intensity estimates and to modify them easily if desired.

  8. Microarray data analysis and mining approaches.

    PubMed

    Cordero, Francesca; Botta, Marco; Calogero, Raffaele A

    2007-12-01

    Microarray based transcription profiling is now a consolidated methodology and has widespread use in areas such as pharmacogenomics, diagnostics and drug target identification. Large-scale microarray studies are also becoming crucial to a new way of conceiving experimental biology. A main issue in microarray transcription profiling is data analysis and mining. When microarrays became a methodology of general use, considerable effort was made to produce algorithms and methods for the identification of differentially expressed genes. More recently, the focus has switched to algorithms and database development for microarray data mining. Furthermore, the evolution of microarray technology is allowing researchers to grasp the regulative nature of transcription, integrating basic expression analysis with mRNA characteristics, i.e. exon-based arrays, and with DNA characteristics, i.e. comparative genomic hybridization, single nucleotide polymorphism, tiling and promoter structure. In this article, we will review approaches used to detect differentially expressed genes and to link differential expression to specific biological functions.

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

    SciTech Connect

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

    2006-02-13

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

  10. Microarray analysis of gene expression in mouse (strain 129) embryonic stem cells after typical synthetic musk exposure.

    PubMed

    Shi, Jiachen; Li, Ming; Jiao, Zhihao; Zhang, Jing; Feng, Yixing; Shao, Bing

    2013-01-01

    Synthetic musks are widely used in personal-care products and can readily accumulate in the adipose tissue, breast milk, and blood of humans. In this study, the Affymetrix Mouse Genome GeneChip was used to identify alterations in gene expression of embryonic stem cells from the 129 strain of the laboratory mouse after treatment with the synthetic musk tonalide (AHTN). Among the 45,037 transcripts in the microarray, 2,879 genes were differentially expressed. According to the microarray analysis, the potential influence of AHTN on the development to embryo should be of concern, and the toxicological effects of it and related musk compounds should be studied further.

  11. Microarray analysis in pulmonary hypertension.

    PubMed

    Hoffmann, Julia; Wilhelm, Jochen; Olschewski, Andrea; Kwapiszewska, Grazyna

    2016-07-01

    Microarrays are a powerful and effective tool that allows the detection of genome-wide gene expression differences between controls and disease conditions. They have been broadly applied to investigate the pathobiology of diverse forms of pulmonary hypertension, namely group 1, including patients with idiopathic pulmonary arterial hypertension, and group 3, including pulmonary hypertension associated with chronic lung diseases such as chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis. To date, numerous human microarray studies have been conducted to analyse global (lung homogenate samples), compartment-specific (laser capture microdissection), cell type-specific (isolated primary cells) and circulating cell (peripheral blood) expression profiles. Combined, they provide important information on development, progression and the end-stage disease. In the future, system biology approaches, expression of noncoding RNAs that regulate coding RNAs, and direct comparison between animal models and human disease might be of importance. PMID:27076594

  12. Microarray analysis in pulmonary hypertension

    PubMed Central

    Hoffmann, Julia; Wilhelm, Jochen; Olschewski, Andrea

    2016-01-01

    Microarrays are a powerful and effective tool that allows the detection of genome-wide gene expression differences between controls and disease conditions. They have been broadly applied to investigate the pathobiology of diverse forms of pulmonary hypertension, namely group 1, including patients with idiopathic pulmonary arterial hypertension, and group 3, including pulmonary hypertension associated with chronic lung diseases such as chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis. To date, numerous human microarray studies have been conducted to analyse global (lung homogenate samples), compartment-specific (laser capture microdissection), cell type-specific (isolated primary cells) and circulating cell (peripheral blood) expression profiles. Combined, they provide important information on development, progression and the end-stage disease. In the future, system biology approaches, expression of noncoding RNAs that regulate coding RNAs, and direct comparison between animal models and human disease might be of importance. PMID:27076594

  13. GENEVESTIGATOR. Arabidopsis Microarray Database and Analysis Toolbox1[w

    PubMed Central

    Zimmermann, Philip; Hirsch-Hoffmann, Matthias; Hennig, Lars; Gruissem, Wilhelm

    2004-01-01

    High-throughput gene expression analysis has become a frequent and powerful research tool in biology. At present, however, few software applications have been developed for biologists to query large microarray gene expression databases using a Web-browser interface. We present GENEVESTIGATOR, a database and Web-browser data mining interface for Affymetrix GeneChip data. Users can query the database to retrieve the expression patterns of individual genes throughout chosen environmental conditions, growth stages, or organs. Reversely, mining tools allow users to identify genes specifically expressed during selected stresses, growth stages, or in particular organs. Using GENEVESTIGATOR, the gene expression profiles of more than 22,000 Arabidopsis genes can be obtained, including those of 10,600 currently uncharacterized genes. The objective of this software application is to direct gene functional discovery and design of new experiments by providing plant biologists with contextual information on the expression of genes. The database and analysis toolbox is available as a community resource at https://www.genevestigator.ethz.ch. PMID:15375207

  14. The Impact of Photobleaching on Microarray Analysis.

    PubMed

    von der Haar, Marcel; Preuß, John-Alexander; von der Haar, Kathrin; Lindner, Patrick; Scheper, Thomas; Stahl, Frank

    2015-01-01

    DNA-Microarrays have become a potent technology for high-throughput analysis of genetic regulation. However, the wide dynamic range of signal intensities of fluorophore-based microarrays exceeds the dynamic range of a single array scan by far, thus limiting the key benefit of microarray technology: parallelization. The implementation of multi-scan techniques represents a promising approach to overcome these limitations. These techniques are, in turn, limited by the fluorophores' susceptibility to photobleaching when exposed to the scanner's laser light. In this paper the photobleaching characteristics of cyanine-3 and cyanine-5 as part of solid state DNA microarrays are studied. The effects of initial fluorophore intensity as well as laser scanner dependent variables such as the photomultiplier tube's voltage on bleaching and imaging are investigated. The resulting data is used to develop a model capable of simulating the expected degree of signal intensity reduction caused by photobleaching for each fluorophore individually, allowing for the removal of photobleaching-induced, systematic bias in multi-scan procedures. Single-scan applications also benefit as they rely on pre-scans to determine the optimal scanner settings. These findings constitute a step towards standardization of microarray experiments and analysis and may help to increase the lab-to-lab comparability of microarray experiment results. PMID:26378589

  15. MADS+: discovery of differential splicing events from Affymetrix exon junction array data

    PubMed Central

    Shen, Shihao; Warzecha, Claude C.; Carstens, Russ P.; Xing, Yi

    2010-01-01

    Motivation: The Affymetrix Human Exon Junction Array is a newly designed high-density exon-sensitive microarray for global analysis of alternative splicing. Contrary to the Affymetrix exon 1.0 array, which only contains four probes per exon and no probes for exon–exon junctions, this new junction array averages eight probes per probeset targeting all exons and exon–exon junctions observed in the human mRNA/EST transcripts, representing a significant increase in the probe density for alternative splicing events. Here, we present MADS+, a computational pipeline to detect differential splicing events from the Affymetrix exon junction array data. For each alternative splicing event, MADS+ evaluates the signals of probes targeting competing transcript isoforms to identify exons or splice sites with different levels of transcript inclusion between two sample groups. MADS+ is used routinely in our analysis of Affymetrix exon junction arrays and has a high accuracy in detecting differential splicing events. For example, in a study of the novel epithelial-specific splicing regulator ESRP1, MADS+ detects hundreds of exons whose inclusion levels are dependent on ESRP1, with a RT-PCR validation rate of 88.5% (153 validated out of 173 tested). Availability: MADS+ scripts, documentations and annotation files are available at http://www.medicine.uiowa.edu/Labs/Xing/MADSplus/. Contact: yi-xing@uiowa.edu PMID:19933160

  16. Pineal Function: Impact of Microarray Analysis

    PubMed Central

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

    2009-01-01

    Microarray analysis has provided a new understanding of pineal function by identifying genes that are highly expressed in this tissue relative to other tissues and also by identifying over 600 genes that are expressed on a 24-hour schedule. This effort has highlighted surprising similarity to the retina and has provided reason to explore new avenues of study including intracellular signaling, signal transduction, transcriptional cascades, thyroid/retinoic acid hormone signaling, metal biology, RNA splicing, and the role the pineal gland plays in the immune/inflammation response. The new foundation that microarray analysis has provided will broadly support future research on pineal function. PMID:19622385

  17. Data Analysis Strategies for Protein Microarrays

    PubMed Central

    Díez, Paula; Dasilva, Noelia; González-González, María; Matarraz, Sergio; Casado-Vela, Juan; Orfao, Alberto; Fuentes, Manuel

    2012-01-01

    Microarrays constitute a new platform which allows the discovery and characterization of proteins. According to different features, such as content, surface or detection system, there are many types of protein microarrays which can be applied for the identification of disease biomarkers and the characterization of protein expression patterns. However, the analysis and interpretation of the amount of information generated by microarrays remain a challenge. Further data analysis strategies are essential to obtain representative and reproducible results. Therefore, the experimental design is key, since the number of samples and dyes, among others aspects, would define the appropriate analysis method to be used. In this sense, several algorithms have been proposed so far to overcome analytical difficulties derived from fluorescence overlapping and/or background noise. Each kind of microarray is developed to fulfill a specific purpose. Therefore, the selection of appropriate analytical and data analysis strategies is crucial to achieve successful biological conclusions. In the present review, we focus on current algorithms and main strategies for data interpretation.

  18. Data Analysis Strategies for Protein Microarrays

    PubMed Central

    Díez, Paula; Dasilva, Noelia; González-González, María; Matarraz, Sergio; Casado-Vela, Juan; Orfao, Alberto; Fuentes, Manuel

    2012-01-01

    Microarrays constitute a new platform which allows the discovery and characterization of proteins. According to different features, such as content, surface or detection system, there are many types of protein microarrays which can be applied for the identification of disease biomarkers and the characterization of protein expression patterns. However, the analysis and interpretation of the amount of information generated by microarrays remain a challenge. Further data analysis strategies are essential to obtain representative and reproducible results. Therefore, the experimental design is key, since the number of samples and dyes, among others aspects, would define the appropriate analysis method to be used. In this sense, several algorithms have been proposed so far to overcome analytical difficulties derived from fluorescence overlapping and/or background noise. Each kind of microarray is developed to fulfill a specific purpose. Therefore, the selection of appropriate analytical and data analysis strategies is crucial to achieve successful biological conclusions. In the present review, we focus on current algorithms and main strategies for data interpretation. PMID:27605336

  19. MICROARRAY DATA ANALYSIS USING MULTIPLE STATISTICAL MODELS

    EPA Science Inventory

    Microarray Data Analysis Using Multiple Statistical Models

    Wenjun Bao1, Judith E. Schmid1, Amber K. Goetz1, Ming Ouyang2, William J. Welsh2,Andrew I. Brooks3,4, ChiYi Chu3,Mitsunori Ogihara3,4, Yinhe Cheng5, David J. Dix1. 1National Health and Environmental Effects Researc...

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

    PubMed

    Schweighofer, Bernhard; Rohringer, Sabrina; Pröll, Johannes; Holnthoner, Wolfgang

    2015-06-01

    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 podoplanin(high) 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.

  1. Microarray analysis at single molecule resolution

    PubMed Central

    Mureşan, Leila; Jacak, Jarosław; Klement, Erich Peter; Hesse, Jan; Schütz, Gerhard J.

    2010-01-01

    Bioanalytical chip-based assays have been enormously improved in sensitivity in the recent years; detection of trace amounts of substances down to the level of individual fluorescent molecules has become state of the art technology. The impact of such detection methods, however, has yet not fully been exploited, mainly due to a lack in appropriate mathematical tools for robust data analysis. One particular example relates to the analysis of microarray data. While classical microarray analysis works at resolutions of two to 20 micrometers and quantifies the abundance of target molecules by determining average pixel intensities, a novel high resolution approach [1] directly visualizes individual bound molecules as diffraction limited peaks. The now possible quantification via counting is less susceptible to labeling artifacts and background noise. We have developed an approach for the analysis of high-resolution microarray images. It consists first of a single molecule detection step, based on undecimated wavelet transforms, and second, of a spot identification step via spatial statistics approach (corresponding to the segmentation step in the classical microarray analysis). The detection method was tested on simulated images with a concentration range of 0.001 to 0.5 molecules per square micron and signal-to-noise ratio (SNR) between 0.9 and 31.6. For SNR above 15 the false negatives relative error was below 15%. Separation of foreground/background proved reliable, in case foreground density exceeds background by a factor of 2. The method has also been applied to real data from high-resolution microarray measurements. PMID:20123580

  2. Microarrays

    ERIC Educational Resources Information Center

    Plomin, Robert; Schalkwyk, Leonard C.

    2007-01-01

    Microarrays are revolutionizing genetics by making it possible to genotype hundreds of thousands of DNA markers and to assess the expression (RNA transcripts) of all of the genes in the genome. Microarrays are slides the size of a postage stamp that contain millions of DNA sequences to which single-stranded DNA or RNA can hybridize. This…

  3. Analysis of High-Throughput ELISA Microarray Data

    SciTech Connect

    White, Amanda M.; Daly, Don S.; Zangar, Richard C.

    2011-02-23

    Our research group develops analytical methods and software for the high-throughput analysis of quantitative enzyme-linked immunosorbent assay (ELISA) microarrays. ELISA microarrays differ from DNA microarrays in several fundamental aspects and most algorithms for analysis of DNA microarray data are not applicable to ELISA microarrays. In this review, we provide an overview of the steps involved in ELISA microarray data analysis and how the statistically sound algorithms we have developed provide an integrated software suite to address the needs of each data-processing step. The algorithms discussed are available in a set of open-source software tools (http://www.pnl.gov/statistics/ProMAT).

  4. Quality Visualization of Microarray Datasets Using Circos

    PubMed Central

    Koch, Martin; Wiese, Michael

    2012-01-01

    Quality control and normalization is considered the most important step in the analysis of microarray data. At present there are various methods available for quality assessments of microarray datasets. However there seems to be no standard visualization routine, which also depicts individual microarray quality. Here we present a convenient method for visualizing the results of standard quality control tests using Circos plots. In these plots various quality measurements are drawn in a circular fashion, thus allowing for visualization of the quality and all outliers of each distinct array within a microarray dataset. The proposed method is intended for use with the Affymetrix Human Genome platform (i.e., GPL 96, GPL570 and GPL571). Circos quality measurement plots are a convenient way for the initial quality estimate of Affymetrix datasets that are stored in publicly available databases.

  5. Microarray analysis in gastric cancer: A review

    PubMed Central

    D’Angelo, Giovanna; Di Rienzo, Teresa; Ojetti, Veronica

    2014-01-01

    Gastric cancer is one of the most common tumors worldwide. Although several treatment options have been developed, the mortality rate is increasing. Lymph node involvement is considered the most reliable prognostic indicator in gastric cancer. Early diagnosis improves the survival rate of patients and increases the likelihood of successful treatment. The most reliable diagnostic method is endoscopic examination, however, it is expensive and not feasible in poorer countries. Therefore, many innovative techniques have been studied to develop a new non-invasive screening test and to identify specific serum biomarkers. DNA microarray analysis is one of the new technologies able to measure the expression levels of a large number of genes simultaneously. It is possible to define the gene expression profile of the tumor and to correlate it with the prognosis and metastasis formation. Several studies in the literature have been published on the role of microarray analysis in gastric cancer and the mechanisms of proliferation and metastasis formation. The aim of this review is to analyze the importance of microarray analysis and its clinical applications to better define the genetic characteristics of gastric cancer and its possible implications in a more decisive treatment. PMID:25232233

  6. Transcript-Specific Expression Profiles Derived from Sequence-Based Analysis of Standard Microarrays

    PubMed Central

    Moll, Anton G.; Lindenmeyer, Maja T.; Kretzler, Matthias; Nelson, Peter J.; Zimmer, Ralf; Cohen, Clemens D.

    2009-01-01

    Background Alternative mRNA processing mechanisms lead to multiple transcripts (i.e. splice isoforms) of a given gene which may have distinct biological functions. Microarrays like Affymetrix GeneChips measure mRNA expression of genes using sets of nucleotide probes. Until recently probe sets were not designed for transcript specificity. Nevertheless, the re-analysis of established microarray data using newly defined transcript-specific probe sets may provide information about expression levels of specific transcripts. Methodology/Principal Findings In the present study alignment of probe sequences of the Affymetrix microarray HG-U133A with Ensembl transcript sequences was performed to define transcript-specific probe sets. Out of a total of 247,965 perfect match probes, 95,008 were designated “transcript-specific”, i.e. showing complete sequence alignment, no cross-hybridization, and transcript-, not only gene-specificity. These probes were grouped into 7,941 transcript-specific probe sets and 15,619 gene-specific probe sets, respectively. The former were used to differentiate 445 alternative transcripts of 215 genes. For selected transcripts, predicted by this analysis to be differentially expressed in the human kidney, confirmatory real-time RT-PCR experiments were performed. First, the expression of two specific transcripts of the genes PPM1A (PP2CA_HUMAN and P35813) and PLG (PLMN_HUMAN and Q5TEH5) in human kidneys was determined by the transcript-specific array analysis and confirmed by real-time RT-PCR. Secondly, disease-specific differential expression of single transcripts of PLG and ABCA1 (ABCA1_HUMAN and Q5VYS0_HUMAN) was computed from the available array data sets and confirmed by transcript-specific real-time RT-PCR. Conclusions Transcript-specific analysis of microarray experiments can be employed to study gene-regulation on the transcript level using conventional microarray data. In this study, predictions based on sufficient probe set size and

  7. Statistical Considerations for Analysis of Microarray Experiments

    PubMed Central

    Owzar, Kouros; Barry, William T.; Jung, Sin-Ho

    2014-01-01

    Microarray technologies enable the simultaneous interrogation of expressions from thousands of genes from a biospecimen sample taken from a patient. This large set of expressions generate a genetic profile of the patient that may be used to identify potential prognostic or predictive genes or genetic models for clinical outcomes. The aim of this article is to provide a broad overview of some of the major statistical considerations for the design and analysis of microarrays experiments conducted as correlative science studies to clinical trials. An emphasis will be placed on how the lack of understanding and improper use of statistical concepts and methods will lead to noise discovery and misinterpretation of experimental results. PMID:22212230

  8. Microarray analysis of the AHR system: Tissue-specific flexibility in signal and target genes

    SciTech Connect

    Frericks, Markus; Meissner, Marc; Esser, Charlotte . E-mail: chesser@uni-duesseldorf.de

    2007-05-01

    Data mining published microarray experiments require that expression profiles are directly comparable. We performed linear global normalization on the data of 1967 Affymetrix U74av2 microarrays, i.e. the transcriptomes of > 100 murine tissues or cell types. The mathematical transformation effectively nullifies inter-experimental or inter-laboratory differences between microarrays. The correctness of expression values was validated by quantitative RT-PCR. Using the database we analyze components of the aryl hydrocarbon receptor (AHR) signaling pathway in various tissues. We identified lineage and differentiation specific variant expression of AHR, ARNT, and HIF1{alpha} in the T-cell lineage and high expression of CYP1A1 in immature B cells and dendritic cells. Performing co-expression analysis we found unorthodox expression of the AHR in the absence of ARNT, particularly in stem cell populations, and can reject the hypothesis that ARNT2 takes over and is highly expressed when ARNT expression is low or absent. Furthermore the AHR shows no co-expression with any other transcript present on the chip. Analysis of differential gene expression under 308 conditions revealed 53 conditions under which the AHR is regulated, numerous conditions under which an intrinsic AHR action is modified as well as conditions activating the AHR even in the absence of known AHR ligands. Thus meta-analysis of published expression profiles is a powerful tool to gain novel insights into known and unknown systems.

  9. Chicken sperm transcriptome profiling by microarray analysis.

    PubMed

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

    2016-03-01

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

  10. Digital microarray analysis for digital artifact genomics

    NASA Astrophysics Data System (ADS)

    Jaenisch, Holger; Handley, James; Williams, Deborah

    2013-06-01

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

  11. Comments on selected fundamental aspects of microarray analysis.

    PubMed

    Riva, Alessandra; Carpentier, Anne-Sophie; Torrésani, Bruno; Hénaut, Alain

    2005-10-01

    Microarrays are becoming a ubiquitous tool of research in life sciences. However, the working principles of microarray-based methodologies are often misunderstood or apparently ignored by the researchers who actually perform and interpret experiments. This in turn seems to lead to a common over-expectation regarding the explanatory and/or knowledge-generating power of microarray analyses. In this note we intend to explain basic principles of five (5) major groups of analytical techniques used in studies of microarray data and their interpretation: the principal component analysis (PCA), the independent component analysis (ICA), the t-test, the analysis of variance (ANOVA), and self organizing maps (SOM). We discuss answers to selected practical questions related to the analysis of microarray data. We also take a closer look at the experimental setup and the rules, which have to be observed in order to exploit microarrays efficiently. Finally, we discuss in detail the scope and limitations of microarray-based methods. We emphasize the fact that no amount of statistical analysis can compensate for (or replace) a well thought through experimental setup. We conclude that microarrays are indeed useful tools in life sciences but by no means should they be expected to generate complete answers to complex biological questions. We argue that even well posed questions, formulated within a microarray-specific terminology, cannot be completely answered with the use of microarray analyses alone.

  12. Analysis of environmental transcriptomes by DNA microarrays.

    PubMed

    Parro, Víctor; Moreno-Paz, Mercedes; González-Toril, Elena

    2007-02-01

    In this work we investigated the correlations between global gene expression patterns and environmental parameters in natural ecosystems. We studied the preferential gene expression of the iron oxidizer bacterium Leptospirillum ferrooxidans to adapt its physiology to changes in the physicochemical parameters in its natural medium. Transcriptome analysis by DNA microarrays can proportionate an instant picture about the preferential gene expression between two different environmental samples. However, this type of analysis is very difficult and complex in natural ecosystems, mainly because of the broad biodiversity and multiple environmental parameters that may affect gene expression. The necessity of high-quality RNA preparations as well as complicated data analysis are also technological limitations. The low prokaryotic diversity of the extremely acidic and iron-rich waters of the Tinto River (Spain) ecosystem, where L. ferrooxidans is abundant, allows the opportunity to achieve global gene expression studies and to associate gene function with environmental parameters. We applied a total RNA amplification protocol validated previously for the amplification of the environmental transcriptome (meta-transcriptome). The meta-transcriptome of two sites from the Tinto River mainly differing in the salt and oxygen contents were amplified and analysed by a L. ferrooxidans DNA microarray. The results showed a clear preferential induction of genes involved in certain physicochemical parameters like: high salinity (ectAB, otsAB), low oxygen concentration (cydAB), iron uptake (fecA-exbBD-tonB), oxidative stress (carotenoid synthesis, oxyR, recG), potassium (kdpBAC) or phosphate concentrations (pstSCAB), etc. We conclude that specific gene expression patterns can be useful indicators for the physiological conditions in a defined ecosystem. Also, the upregulation of certain genes and operons reveals information about the environmental conditions (nutrient limitations, stresses

  13. Comparison of High-Level Microarray Analysis Methods in the Context of Result Consistency

    PubMed Central

    Chrominski, Kornel; Tkacz, Magdalena

    2015-01-01

    Motivation When we were asked for help with high-level microarray data analysis (on Affymetrix HGU-133A microarray), we faced the problem of selecting an appropriate method. We wanted to select a method that would yield "the best result" (detected as many "really" differentially expressed genes (DEGs) as possible, without false positives and false negatives). However, life scientists could not help us – they use their "favorite" method without special argumentation. We also did not find any norm or recommendation. Therefore, we decided to examine it for our own purpose. We considered whether the results obtained using different methods of high-level microarray data analyses – Significant Analysis of Microarrays, Rank Products, Bland-Altman, Mann-Whitney test, T test and the Linear Models for Microarray Data – would be in agreement. Initially, we conducted a comparative analysis of the results on eight real data sets from microarray experiments (from the Array Express database). The results were surprising. On the same array set, the set of DEGs by different methods were significantly different. We also applied the methods to artificial data sets and determined some measures that allow the preparation of the overall scoring of tested methods for future recommendation. Results We found a very low level concordance of results from tested methods on real array sets. The number of common DEGs (detected by all six methods on fixed array sets, checked on eight array sets) ranged from 6 to 433 (22,283 total array readings). Results on artificial data sets were better than those on the real data. However, they were not fully satisfying. We scored tested methods on accuracy, recall, precision, f-measure and Matthews correlation coefficient. Based on the overall scoring, the best methods were SAM and LIMMA. We also found TT to be acceptable. The worst scoring was MW. Based on our study, we recommend: 1. Carefully taking into account the need for study when choosing a

  14. Real-time DNA microarray analysis

    PubMed Central

    Hassibi, Arjang; Vikalo, Haris; Riechmann, José Luis; Hassibi, Babak

    2009-01-01

    We present a quantification method for affinity-based DNA microarrays which is based on the real-time measurements of hybridization kinetics. This method, i.e. real-time DNA microarrays, enhances the detection dynamic range of conventional systems by being impervious to probe saturation in the capturing spots, washing artifacts, microarray spot-to-spot variations, and other signal amplitude-affecting non-idealities. We demonstrate in both theory and practice that the time-constant of target capturing in microarrays, similar to all affinity-based biosensors, is inversely proportional to the concentration of the target analyte, which we subsequently use as the fundamental parameter to estimate the concentration of the analytes. Furthermore, to empirically validate the capabilities of this method in practical applications, we present a FRET-based assay which enables the real-time detection in gene expression DNA microarrays. PMID:19723688

  15. Real-time DNA microarray analysis.

    PubMed

    Hassibi, Arjang; Vikalo, Haris; Riechmann, José Luis; Hassibi, Babak

    2009-11-01

    We present a quantification method for affinity-based DNA microarrays which is based on the real-time measurements of hybridization kinetics. This method, i.e. real-time DNA microarrays, enhances the detection dynamic range of conventional systems by being impervious to probe saturation in the capturing spots, washing artifacts, microarray spot-to-spot variations, and other signal amplitude-affecting non-idealities. We demonstrate in both theory and practice that the time-constant of target capturing in microarrays, similar to all affinity-based biosensors, is inversely proportional to the concentration of the target analyte, which we subsequently use as the fundamental parameter to estimate the concentration of the analytes. Furthermore, to empirically validate the capabilities of this method in practical applications, we present a FRET-based assay which enables the real-time detection in gene expression DNA microarrays. PMID:19723688

  16. Ontology-Based Analysis of Microarray Data.

    PubMed

    Giuseppe, Agapito; Milano, Marianna

    2016-01-01

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

  17. Genomic-Wide Analysis with Microarrays in Human Oncology

    PubMed Central

    Inaoka, Kenichi; Inokawa, Yoshikuni; Nomoto, Shuji

    2015-01-01

    DNA microarray technologies have advanced rapidly and had a profound impact on examining gene expression on a genomic scale in research. This review discusses the history and development of microarray and DNA chip devices, and specific microarrays are described along with their methods and applications. In particular, microarrays have detected many novel cancer-related genes by comparing cancer tissues and non-cancerous tissues in oncological research. Recently, new methods have been in development, such as the double-combination array and triple-combination array, which allow more effective analysis of gene expression and epigenetic changes. Analysis of gene expression alterations in precancerous regions compared with normal regions and array analysis in drug-resistance cancer tissues are also successfully performed. Compared with next-generation sequencing, a similar method of genome analysis, several important differences distinguish these techniques and their applications. Development of novel microarray technologies is expected to contribute to further cancer research.

  18. Transcriptional Profiling of Hydrogen Production Metabolism of Rhodobacter capsulatus under Temperature Stress by Microarray Analysis

    PubMed Central

    Gürgan, Muazzez; Afşar Erkal, Nilüfer; Özgür, Ebru; Gündüz, Ufuk; Eroglu, Inci; Yücel, Meral

    2015-01-01

    Biohydrogen is a clean and renewable form of hydrogen, which can be produced by photosynthetic bacteria in outdoor large-scale photobioreactors using sunlight. In this study, the transcriptional response of Rhodobacter capsulatus to cold (4 °C) and heat (42 °C) stress was studied using microarrays. Bacteria were grown in 30/2 acetate/glutamate medium at 30 °C for 48 h under continuous illumination. Then, cold and heat stresses were applied for two and six hours. Growth and hydrogen production were impaired under both stress conditions. Microarray chips for R. capsulatus were custom designed by Affymetrix (GeneChip®. TR_RCH2a520699F). The numbers of significantly changed genes were 328 and 293 out of 3685 genes under cold and heat stress, respectively. Our results indicate that temperature stress greatly affects the hydrogen production metabolisms of R. capsulatus. Specifically, the expression of genes that participate in nitrogen metabolism, photosynthesis and the electron transport system were induced by cold stress, while decreased by heat stress. Heat stress also resulted in down regulation of genes related to cell envelope, transporter and binding proteins. Transcriptome analysis and physiological results were consistent with each other. The results presented here may aid clarification of the genetic mechanisms for hydrogen production in purple non-sulfur (PNS) bacteria under temperature stress. PMID:26086826

  19. Robin: An Intuitive Wizard Application for R-Based Expression Microarray Quality Assessment and Analysis1[W][OA

    PubMed Central

    Lohse, Marc; Nunes-Nesi, Adriano; Krüger, Peter; Nagel, Axel; Hannemann, Jan; Giorgi, Federico M.; Childs, Liam; Osorio, Sonia; Walther, Dirk; Selbig, Joachim; Sreenivasulu, Nese; Stitt, Mark; Fernie, Alisdair R.; Usadel, Björn

    2010-01-01

    The wide application of high-throughput transcriptomics using microarrays has generated a plethora of technical platforms, data repositories, and sophisticated statistical analysis methods, leaving the individual scientist with the problem of choosing the appropriate approach to address a biological question. Several software applications that provide a rich environment for microarray analysis and data storage are available (e.g. GeneSpring, EMMA2), but these are mostly commercial or require an advanced informatics infrastructure. There is a need for a noncommercial, easy-to-use graphical application that aids the lab researcher to find the proper method to analyze microarray data, without this requiring expert understanding of the complex underlying statistics, or programming skills. We have developed Robin, a Java-based graphical wizard application that harnesses the advanced statistical analysis functions of the R/BioConductor project. Robin implements streamlined workflows that guide the user through all steps of two-color, single-color, or Affymetrix microarray analysis. It provides functions for thorough quality assessment of the data and automatically generates warnings to notify the user of potential outliers, low-quality chips, or low statistical power. The results are generated in a standard format that allows ready use with both specialized analysis tools like MapMan and PageMan and generic spreadsheet applications. To further improve user friendliness, Robin includes both integrated help and comprehensive external documentation. To demonstrate the statistical power and ease of use of the workflows in Robin, we present a case study in which we apply Robin to analyze a two-color microarray experiment comparing gene expression in tomato (Solanum lycopersicum) leaves, flowers, and roots. PMID:20388663

  20. DNA Microarray Analysis of Estrogen-Responsive Genes.

    PubMed

    Eyster, Kathleen M

    2016-01-01

    DNA microarray is a powerful, non-biased discovery technology that allows the analysis of the expression of thousands of genes at a time. The technology can be used for the identification of differential gene expression, genetic mutations associated with diseases, DNA methylation, single-nucleotide polymorphisms, and microRNA expression, to name a few. This chapter describes microarray technology for the analysis of differential gene expression in response to estrogen treatment.

  1. The EADGENE Microarray Data Analysis Workshop (Open Access publication)

    PubMed Central

    de Koning, Dirk-Jan; Jaffrézic, Florence; Lund, Mogens Sandø; Watson, Michael; Channing, Caroline; Hulsegge, Ina; Pool, Marco H; Buitenhuis, Bart; Hedegaard, Jakob; Hornshøj, Henrik; Jiang, Li; Sørensen, Peter; Marot, Guillemette; Delmas, Céline; Cao, Kim-Anh Lê; San Cristobal, Magali; Baron, Michael D; Malinverni, Roberto; Stella, Alessandra; Brunner, Ronald M; Seyfert, Hans-Martin; Jensen, Kirsty; Mouzaki, Daphne; Waddington, David; Jiménez-Marín, Ángeles; Pérez-Alegre, Mónica; Pérez-Reinado, Eva; Closset, Rodrigue; Detilleux, Johanne C; Dovč, Peter; Lavrič, Miha; Nie, Haisheng; Janss, Luc

    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 from a direct comparison of two treatments (dye-balanced). While there was broader agreement with regards to methods of microarray normalisation and significance testing, there were major differences with regards to quality control. The quality control approaches varied from none, through using statistical weights, to omitting a large number of spots or omitting entire slides. Surprisingly, these very different approaches gave quite similar results when applied to the simulated data, although not all participating groups analysed both real and simulated data. The workshop was very successful in facilitating interaction between scientists with a diverse background but a common interest in microarray analyses. PMID:18053572

  2. Weighted analysis of general microarray experiments

    PubMed Central

    Sjögren, Anders; Kristiansson, Erik; Rudemo, Mats; Nerman, Olle

    2007-01-01

    Background In DNA microarray experiments, measurements from different biological samples are often assumed to be independent and to have identical variance. For many datasets these assumptions have been shown to be invalid and typically lead to too optimistic p-values. A method called WAME has been proposed where a variance is estimated for each sample and a covariance is estimated for each pair of samples. The current version of WAME is, however, limited to experiments with paired design, e.g. two-channel microarrays. Results The WAME procedure is extended to general microarray experiments, making it capable of handling both one- and two-channel datasets. Two public one-channel datasets are analysed and WAME detects both unequal variances and correlations. WAME is compared to other common methods: fold-change ranking, ordinary linear model with t-tests, LIMMA and weighted LIMMA. The p-value distributions are shown to differ greatly between the examined methods. In a resampling-based simulation study, the p-values generated by WAME are found to be substantially more correct than the alternatives when a relatively small proportion of the genes is regulated. WAME is also shown to have higher power than the other methods. WAME is available as an R-package. Conclusion The WAME procedure is generalized and the limitation to paired-design microarray datasets is removed. The examined other methods produce invalid p-values in many cases, while WAME is shown to produce essentially valid p-values when a relatively small proportion of genes is regulated. WAME is also shown to have higher power than the examined alternative methods. PMID:17937807

  3. The comparison of different pre- and post-analysis filters for determination of exon-level alternative splicing events using Affymetrix arrays.

    PubMed

    Whistler, Toni; Chiang, Cheng-Feng; Lin, Jin-Mann; Lonergan, William; Reeves, William C

    2010-04-01

    Understanding the biologic significance of alternative splicing has been impeded by the difficulty in systematically identifying and validating transcript isoforms. Current exon array workflows suggest several different filtration steps to reduce the number of tests and increase the detection of alternative splicing events. In this study, we examine the effects of the suggested pre-analysis filtration by detection above background P value or signal intensity. This is followed post-analytically by restriction of exon expression to a fivefold change between groups, limiting the analysis to known alternative splicing events, or using the intersection of the results from different algorithms. Combinations of the filters are also examined. We find that none of the filtering methods reduces the number of technical false-positive calls identified by visual inspection. These include edge effects, nonresponsive probe sets, and inclusion of intronic and untranslated region probe sets into transcript annotations. Modules for filtering the exon microarray data on the basis of annotation features are needed. We propose new approaches to data filtration that would reduce the number of technical false-positives and therefore, impact the time spent performing visual inspection of the exon arrays.

  4. Microarray analysis of relative gene expression stability for selection of internal reference genes in the rhesus macaque brain

    PubMed Central

    2010-01-01

    Background Normalization of gene expression data refers to the comparison of expression values using reference standards that are consistent across all conditions of an experiment. In PCR studies, genes designated as "housekeeping genes" have been used as internal reference genes under the assumption that their expression is stable and independent of experimental conditions. However, verification of this assumption is rarely performed. Here we assess the use of gene microarray analysis to facilitate selection of internal reference sequences with higher expression stability across experimental conditions than can be expected using traditional selection methods. We recently demonstrated that relative gene expression from qRT-PCR data normalized using GAPDH, ALG9 and RPL13A expression values mirrored relative expression using quantile normalization in Robust Multichip Analysis (RMA) on the Affymetrix® GeneChip® rhesus Macaque Genome Array. Having shown that qRT-PCR and Affymetrix® GeneChip® data from the same hormone replacement therapy (HRT) study yielded concordant results, we used quantile-normalized gene microarray data to identify the most stably expressed among probe sets for prospective internal reference genes across three brain regions from the HRT study and an additional study of normally menstruating rhesus macaques (cycle study). Gene selection was limited to 575 previously published human "housekeeping" genes. Twelve animals were used per study, and three brain regions were analyzed from each animal. Gene expression stabilities were determined using geNorm, NormFinder and BestKeeper software packages. Results Sequences co-annotated for ribosomal protein S27a (RPS27A), and ubiquitin were among the most stably expressed under all conditions and selection criteria used for both studies. Higher annotation quality on the human GeneChip® facilitated more targeted analysis than could be accomplished using the rhesus GeneChip®. In the cycle study, multiple

  5. Evaluation of the Affymetrix CytoScan® Dx Assay for Developmental Delay

    PubMed Central

    Webb, Bryn D.; Scharf, Rebecca J.; Spear, Emily A.; Edelmann, Lisa J.; Stroustrup, Annemarie

    2015-01-01

    The goal of molecular cytogenetic testing for children presenting with developmental delay is to identify or exclude genetic abnormalities that are associated with cognitive, behavioral, and/or motor symptoms. Until 2010, chromosome analysis was the standard first-line genetic screening test for evaluation of patients with developmental delay when a specific syndrome was not suspected. In 2010, The American College of Medical Genetics and several other groups recommended chromosomal microarray (CMA) as the first-line test in children with developmental delays, multiple congenital anomalies, and/or autism. This test is able to detect regions of genomic imbalances at a much finer resolution than G-banded karyotyping. Until recently, no CMA testing had been approved by the United States Food and Drug Administration (FDA). This review will focus on the use of the Affymetrix CytoScan® Dx Assay, the first CMA to receive FDA approval for the genetic evaluation of individuals with developmental delay. PMID:25350348

  6. Gene expression profiles in the rat streptococcal cell wall-induced arthritis model identified using microarray analysis.

    PubMed

    Rioja, Inmaculada; Clayton, Chris L; Graham, Simon J; Life, Paul F; Dickson, Marion C

    2005-01-01

    Experimental arthritis models are considered valuable tools for delineating mechanisms of inflammation and autoimmune phenomena. Use of microarray-based methods represents a new and challenging approach that allows molecular dissection of complex autoimmune diseases such as arthritis. In order to characterize the temporal gene expression profile in joints from the reactivation model of streptococcal cell wall (SCW)-induced arthritis in Lewis (LEW/N) rats, total RNA was extracted from ankle joints from naive, SCW injected, or phosphate buffered saline injected animals (time course study) and gene expression was analyzed using Affymetrix oligonucleotide microarray technology (RAE230A). After normalization and statistical analysis of data, 631 differentially expressed genes were sorted into clusters based on their levels and kinetics of expression using Spotfire profile search and K-mean cluster analysis. Microarray-based data for a subset of genes were validated using real-time PCR TaqMan analysis. Analysis of the microarray data identified 631 genes (441 upregulated and 190 downregulated) that were differentially expressed (Delta > 1.8, P < 0.01), showing specific levels and patterns of gene expression. The genes exhibiting the highest fold increase in expression on days -13.8, -13, or 3 were involved in chemotaxis, inflammatory response, cell adhesion and extracellular matrix remodelling. Transcriptome analysis identified 10 upregulated genes (Delta > 5), which have not previously been associated with arthritis pathology and are located in genomic regions associated with autoimmune disease. The majority of the downregulated genes were associated with metabolism, transport and regulation of muscle development. In conclusion, the present study describes the temporal expression of multiple disease-associated genes with potential pathophysiological roles in the reactivation model of SCW-induced arthritis in Lewis (LEW/N) rat. These findings improve our understanding of

  7. Analysis-Driven Lossy Compression of DNA Microarray Images.

    PubMed

    Hernández-Cabronero, Miguel; Blanes, Ian; Pinho, Armando J; Marcellin, Michael W; Serra-Sagristà, Joan

    2016-02-01

    DNA microarrays are one of the fastest-growing new technologies in the field of genetic research, and DNA microarray images continue to grow in number and size. Since analysis techniques are under active and ongoing development, storage, transmission and sharing of DNA microarray images need be addressed, with compression playing a significant role. However, existing lossless coding algorithms yield only limited compression performance (compression ratios below 2:1), whereas lossy coding methods may introduce unacceptable distortions in the analysis process. This work introduces a novel Relative Quantizer (RQ), which employs non-uniform quantization intervals designed for improved compression while bounding the impact on the DNA microarray analysis. This quantizer constrains the maximum relative error introduced into quantized imagery, devoting higher precision to pixels critical to the analysis process. For suitable parameter choices, the resulting variations in the DNA microarray analysis are less than half of those inherent to the experimental variability. Experimental results reveal that appropriate analysis can still be performed for average compression ratios exceeding 4.5:1.

  8. Microarray Analysis of Human Liver Cells irradiated by 80MeV/u Carbon Ions

    NASA Astrophysics Data System (ADS)

    Wang, Xiao; Tian, Xiaoling; Kong, Fuquan; Li, Qiang; Jin, Xiaodong; Dai, Zhongying; Zhang, Hong; Yang, Mingjian; Zhao, Kui

    Objective Biological effect of heavy ion beam has the important significance for cancer therapy and space exploring owing its high LET and RBE, low OER, especially forming Bragg spike at the end of the tracks of charged particles. More serious damage for cells are induced by heavy ions and difficult repair than other irradiation such as X-ray and ν-ray . To explore the molecular mechanism of biological effect caused by heavy ionizing radiation (HIR) and to construct the gene expression profile database of HIR-induced human liver cells L02 by microarray analysis. Methods In this study, L02 cells were irradiated by 80MeV/u carbon ions at 5 Gy delivered by HIRFL (Heavy Ion Research Facility in Lanzhou) at room temperature. Total RNAs of cells incubated 6 hours and 24hours after irradiation were extracted with Trizol. Unirradiated cells were used as a control. RNAs were transcripted into cDNA by reverse transcription and labelled with cy5-dCTP and cy3-dCTP respectively. A human genome oligonucleotide set consisting of 5 amino acid-modified 70-mer probes and representing 21,329 well-characterized Homo sapiens genes was selected for microarray analysis and printed on amino-silaned glass slides. Arrays were fabricated using an OmniGrid microarrayer. Only genes whose alteration tendency was consistent in both microarrays were selected as differentially expressed genes. The Affymetrix's short oligonucleotide (25-mer) HG U133A 2.0 array analyses were performed per the manufacturer's instructions. Results Of the 21,329 genes tested, 37 genes showed changes in expression level with ratio higher than 2.0 and lower than 0.5 at 6hrs after irradiation. There were 19 genes showing up-regulation in radiated L02 cells, whereas 18 genes showing down-regulation; At 24hrs after irradiation, 269 genes showed changes in expression level with ratio higher than 2.0 and lower than 0.5. There were 67 genes showing up-regulation in radiated L02 cells, whereas 202 genes showing down

  9. ProMAT: protein microarray analysis tool

    SciTech Connect

    White, Amanda M.; Daly, Don S.; Varnum, Susan M.; Anderson, Kevin K.; Bollinger, Nikki; Zangar, Richard C.

    2006-04-04

    Summary: ProMAT is a software tool for statistically analyzing data from ELISA microarray experiments. The software estimates standard curves, sample protein concentrations and their uncertainties for multiple assays. ProMAT generates a set of comprehensive figures for assessing results and diagnosing process quality. The tool is available for Windows or Mac, and is distributed as open-source Java and R code. Availability: ProMAT is available at http://www.pnl.gov/statistics/ProMAT. ProMAT requires Java version 1.5.0 and R version 1.9.1 (or more recent versions) which are distributed with the tool.

  10. Microarray analysis of the developing cortex.

    PubMed

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

    2006-12-01

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

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

    PubMed

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

    2011-12-01

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

  12. Identification of SNPs and INDELS in swine transcribed sequences using short oligonucleotide microarrays

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Genome-wide detection of single feature polymorphisms (SFP) in swine using transcriptome profiling of day 25 placental RNA by contrasting probe intensities from either Meishan or an occidental composite breed with Affymetrix porcine microarrays is presented. A linear mixed model analysis was used to...

  13. Using probe secondary structure information to enhance Affymetrix GeneChip background estimates

    PubMed Central

    Gharaibeh, Raad Z.; Fodor, Anthony A.; Gibas, Cynthia J.

    2007-01-01

    High-density short oligonucleotide microarrays are a primary research tool for assessing global gene expression. Background noise on microarrays comprises a significant portion of the measured raw data. A number of statistical techniques have been developed to correct for this background noise. Here, we demonstrate that probe minimum folding energy and structure can be used to enhance a previously existing model for background noise correction. We estimate that probe secondary structure accounts for up to 3% of all variation on Affymetrix microarrays. PMID:17387043

  14. DNA microarray data and contextual analysis of correlation graphs

    PubMed Central

    Rougemont, Jacques; Hingamp, Pascal

    2003-01-01

    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 . PMID:12720549

  15. Microarray analysis of thyroid hormone-induced changes in mRNA expression in the adult rat brain.

    PubMed

    Haas, Michael J; Mreyoud, Amjad; Fishman, Miriam; Mooradian, Arshag D

    2004-07-15

    To determine which genes in the adult rat brain are regulated by thyroid hormone (TH), we used microarrays to examine the effect of hyperthyroidism on neuron-specific gene expression. Four-month-old male Fisher 344 rats were rendered hyperthyroid by intraperitoneal injection of 3,5,3'-L-triiodothyronine (T3, 15 microg/100 g body weight) for 10 consecutive days. To minimize interindividual variability, pooled cerebral tissue RNA from four-control and five-hyperthyroid rats was hybridized in duplicates to the Affymetrix (Santa Clara, CA) U34N rat neurobiology microarray, which contains probes for 1224 neural-specific genes. Changes in gene expression were considered significant only if they were observed in both pair-wise comparisons as well as by Northern blot analysis. Hyperthyroidism was associated with modest changes in the expression of only 11 genes. The expression of the phosphodiesterase Enpp2, myelin oligodendrocyte glycoprotein (Mog), microtubule-associated protein 2 (MAP2), growth hormone (GH), Ca(2+)/calmodulin-dependent protein kinase beta-subunit (Camk2b), neuron-specific protein PEP-19 (Pcp4), a sodium-dependent neurotransmitter, and the myelin-associated glycoprotein (S-MAG) was significantly increased. Three genes were suppressed by hyperthyroidism, including the activity and neurotransmitter-induced early genes-1 and -7 (ANIA-1 and ANIA-7) and the guanine nucleotide-binding protein one (Gnb1). The present study underscores the paucity of TH responsive genes in adult cerebral tissue. PMID:15234464

  16. Transcriptomic response of murine liver to severe injury and hemorrhagic shock: a dual-platform microarray analysis

    PubMed Central

    Edmonds, Rebecca D.; Lagoa, Claudio; Dutta-Moscato, Joyeeta; Yang, Yawching; Fink, Mitchell P.; Levy, Ryan M.; Prince, Jose M.; Kaczorowski, David J.; Tseng, George C.; Billiar, Timothy R.

    2011-01-01

    Trauma-hemorrhagic shock (HS/T) is a complex process that elicits numerous molecular pathways. We hypothesized that a dual-platform microarray analysis of the liver, an organ that integrates immunology and metabolism, would reveal key pathways engaged following HS/T. C57BL/6 mice were divided into five groups (n = 4/group), anesthetized, and surgically treated to simulate a time course and trauma severity model: 1) nonmanipulated animals, 2) minor trauma, 3) 1.5 h of hemorrhagic shock and severe trauma (HS/T), 4) 1.5 h HS/T followed by 1 h resuscitation (HS/T+1.0R), 5) 1.5 h HS/T followed by 4.5 h resuscitation (HS/T+4.5R). Liver RNA was hybridized to CodeLink and Affymetrix mouse whole genome microarray chips. Common genes with a cross-platform correlation >0.6 (2,353 genes in total) were clustered using k-means clustering, and clusters were analyzed using Ingenuity Pathways Analysis. Genes involved in the stress response and immunoregulation were upregulated early and remained upregulated throughout the course of the experiment. Genes involved in cell death and inflammatory pathways were upregulated in a linear fashion with elapsed time and in severe injury compared with minor trauma. Three of the six clusters contained genes involved in metabolic function; these were downregulated with elapsed time. Transcripts involved in amino acid metabolism as well as signaling pathways associated with glucocorticoid receptors, IL-6, IL-10, and the acute phase response were elevated in a severity-dependent manner. This is the first study to examine the postinjury response using dual-platform microarray analysis, revealing responses that may enable novel therapies or diagnostics. PMID:21828244

  17. Examination of Oral Cancer Biomarkers by Tissue Microarray Analysis

    PubMed Central

    Choi, Peter; Jordan, C. Diana; Mendez, Eduardo; Houck, John; Yueh, Bevan; Farwell, D. Gregory; Futran, Neal; Chen, Chu

    2008-01-01

    Background Oral squamous cell carcinoma (OSCC) is a major healthcare problem worldwide. Efforts in our laboratory and others focusing on the molecular characterization of OSCC tumors with the use of DNA microarrays have yielded heterogeneous results. To validate the DNA microarray results on a subset of genes from these studies that could potentially serve as biomarkers of OSCC, we elected to examine their expression by an alternate quantitative method and by assessing their protein levels. Design Based on DNA microarray data from our lab and data reported in the literature, we identified six potential biomarkers of OSCC to investigate further. We employed quantitative, real-time polymerase chain reaction (qRT-PCR) to examine expression changes of CDH11, MMP3, SPARC, POSTN, TNC, TGM3 in OSCC and normal control tissues. We further examined validated markers on the protein level by immunohistochemistry (IHC) analysis of OSCC tissue microarray (TMA) sections. Results qRT-PCR analysis revealed up-regulation of CDH11, SPARC, POSTN, and TNC gene expression, and decreased TGM3 expression in OSCC compared to normal controls. MMP3 was not found to be differentially expressed. In TMA IHC analyses, SPARC, periostin, and tenascin C exhibited increased protein expression in cancer compared to normal tissues, and their expression was primarily localized within tumor-associated stroma rather than tumor epithelium. Conversely, transglutaminase-3 protein expression was found only within keratinocytes in normal controls, and was significantly down-regulated in cancer cells. Conclusions Of six potential gene markers of OSCC, initially identified by DNA microarray analyses, differential expression of CDH11, SPARC, POSTN, TNC, and TGM3 were validated by qRT-PCR. Differential expression and localization of proteins encoded by SPARC, POSTN, TNC, and TGM3 were clearly shown by TMA IHC. PMID:18490578

  18. Analysis of microarray experiments of gene expression profiling

    PubMed Central

    Tarca, Adi L.; Romero, Roberto; Draghici, Sorin

    2008-01-01

    The study of gene expression profiling of cells and tissue has become a major tool for discovery in medicine. Microarray experiments allow description of genome-wide expression changes in health and disease. The results of such experiments are expected to change the methods employed in the diagnosis and prognosis of disease in obstetrics and gynecology. Moreover, an unbiased and systematic study of gene expression profiling should allow the establishment of a new taxonomy of disease for obstetric and gynecologic syndromes. Thus, a new era is emerging in which reproductive processes and disorders could be characterized using molecular tools and fingerprinting. The design, analysis, and interpretation of microarray experiments require specialized knowledge that is not part of the standard curriculum of our discipline. This article describes the types of studies that can be conducted with microarray experiments (class comparison, class prediction, class discovery). We discuss key issues pertaining to experimental design, data preprocessing, and gene selection methods. Common types of data representation are illustrated. Potential pitfalls in the interpretation of microarray experiments, as well as the strengths and limitations of this technology, are highlighted. This article is intended to assist clinicians in appraising the quality of the scientific evidence now reported in the obstetric and gynecologic literature. PMID:16890548

  19. A microarray analysis for differential gene expression in the soybean genome using Bioconductor and R.

    PubMed

    Gregory Alvord, W; Roayaei, Jean A; Quiñones, Octavio A; Schneider, Katherine T

    2007-11-01

    This article describes specific procedures for conducting quality assessment of Affymetrix GeneChip(R) soybean genome data and for performing analyses to determine differential gene expression using the open-source R programming environment in conjunction with the open-source Bioconductor software. We describe procedures for extracting those Affymetrix probe set IDs related specifically to the soybean genome on the Affymetrix soybean chip and demonstrate the use of exploratory plots including images of raw probe-level data, boxplots, density plots and M versus A plots. RNA degradation and recommended procedures from Affymetrix for quality control are discussed. An appropriate probe-level model provides an excellent quality assessment tool. To demonstrate this, we discuss and display chip pseudo-images of weights, residuals and signed residuals and additional probe-level modeling plots that may be used to identify aberrant chips. The Robust Multichip Averaging (RMA) procedure was used for background correction, normalization and summarization of the AffyBatch probe-level data to obtain expression level data and to discover differentially expressed genes. Examples of boxplots and MA plots are presented for the expression level data. Volcano plots and heatmaps are used to demonstrate the use of (log) fold changes in conjunction with ordinary and moderated t-statistics for determining interesting genes. We show, with real data, how implementation of functions in R and Bioconductor successfully identified differentially expressed genes that may play a role in soybean resistance to a fungal pathogen, Phakopsora pachyrhizi. Complete source code for performing all quality assessment and statistical procedures may be downloaded from our web source: http://css.ncifcrf.gov/services/download/MicroarraySoybean.zip.

  20. Bioinformatics and Microarray Data Analysis on the Cloud.

    PubMed

    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. PMID:25863787

  1. Bioinformatics and Microarray Data Analysis on the Cloud.

    PubMed

    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.

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

    PubMed

    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. PMID:17517778

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

    NASA Astrophysics Data System (ADS)

    Getz, Gad; Levine, Erel; Domany, Eytan

    2000-10-01

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

  4. Molecular Sub-Classification of Renal Epithelial Tumors Using Meta-Analysis of Gene Expression Microarrays

    PubMed Central

    Sanford, Thomas; Chung, Paul H.; Reinish, Ariel; Valera, Vladimir; Srinivasan, Ramaprasad; Linehan, W. Marston; Bratslavsky, Gennady

    2011-01-01

    Purpose To evaluate the accuracy of the sub-classification of renal cortical neoplasms using molecular signatures. Experimental Design 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. Results 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. Conclusions 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. PMID:21818257

  5. Microarray Analysis of Port Wine Stains Before and After Pulsed Dye Laser Treatment

    PubMed Central

    Laquer, Vivian T.; Hevezi, Peter A.; Albrecht, Huguette; Chen, Tina S.; Zlotnik, Albert; Kelly, Kristen M.

    2014-01-01

    Background and Objectives Neither the pathogenesis of port wine stain (PWS) birthmarks nor tissue effects of pulsed dye laser (PDL) treatment of these lesions is fully understood. There are few published reports utilizing gene expression analysis in human PWS skin. We aim to compare gene expression in PWS before and after PDL, using DNA microarrays that represent most, if not all, human genes to obtain comprehensive molecular profiles of PWS lesions and PDL-associated tissue effects. Materials and Methods Five human subjects had PDL treatment of their PWS. One week later, three biopsies were taken from each subject: normal skin (N); untreated PWS (PWS); PWS post-PDL (PWS + PDL). Samples included two lower extremity lesions, two facial lesions, and one facial nodule. High-quality total RNA isolated from skin biopsies was processed and applied to Affymetrix Human gene 1.0ST microarrays for gene expression analysis. We performed a 16 pair-wise comparison identifying either up- or down-regulated genes between N versus PWS and PWS versus PWS + PDL for four of the donor samples. The PWS nodule (nPWS) was analyzed separately. Results There was significant variation in gene expression profiles between individuals. By doing pair-wise comparisons between samples taken from the same donor, we were able to identify genes that may participate in the formation of PWS lesions and PDL tissue effects. Genes associated with immune, epidermal, and lipid metabolism were up-regulated in PWS skin. The nPWS exhibited more profound differences in gene expression than the rest of the samples, with significant differential expression of genes associated with angiogenesis, tumorigenesis, and inflammation. Conclusion In summary, gene expression profiles from N, PWS, and PWS + PDL demonstrated significant variation within samples from the same donor and between donors. By doing pair-wise comparisons between samples taken from the same donor and comparing these results between donors, we were

  6. Analysis of variance of microarray data.

    PubMed

    Ayroles, Julien F; Gibson, Greg

    2006-01-01

    Analysis of variance (ANOVA) is an approach used to identify differentially expressed genes in complex experimental designs. It is based on testing for the significance of the magnitude of effect of two or more treatments taking into account the variance within and between treatment classes. ANOVA is a highly flexible analytical approach that allows investigators to simultaneously assess the contributions of multiple factors to gene expression variation, including technical (dye, batch) effects and biological (sex, genotype, drug, time) ones, as well as interactions between factors. This chapter provides an overview of the theory of linear mixture modeling and the sequence of steps involved in fitting gene-specific models and discusses essential features of experimental design. Commercial and open-source software for performing ANOVA is widely available.

  7. Microarray Analysis of Pneumococcal Gene Expression during Invasive Disease

    PubMed Central

    Orihuela, Carlos J.; Radin, Jana N.; Sublett, Jack E.; Gao, Geli; Kaushal, Deepak; Tuomanen, Elaine I.

    2004-01-01

    Streptococcus pneumoniae is a leading cause of invasive bacterial disease. This is the first study to examine the expression of S. pneumoniae genes in vivo by using whole-genome microarrays available from The Institute for Genomic Research. Total RNA was collected from pneumococci isolated from infected blood, infected cerebrospinal fluid, and bacteria attached to a pharyngeal epithelial cell line in vitro. Microarray analysis of pneumococcal genes expressed in these models identified body site-specific patterns of expression for virulence factors, transporters, transcription factors, translation-associated proteins, metabolism, and genes with unknown function. Contributions to virulence predicted for several unknown genes with enhanced expression in vivo were confirmed by insertion duplication mutagenesis and challenge of mice with the mutants. Finally, we cross-referenced our results with previous studies that used signature-tagged mutagenesis and differential fluorescence induction to identify genes that are potentially required by a broad range of pneumococcal strains for invasive disease. PMID:15385455

  8. Chromatin immunoprecipitation and microarray-based analysis of protein location

    PubMed Central

    Lee, Tong Ihn; Johnstone, Sarah E; Young, Richard A

    2010-01-01

    Genome-wide location analysis, also known as ChIP-Chip, combines chromatin immunoprecipitation and DNA microarray analysis to identify protein-DNA interactions that occur in living cells. Protein-DNA interactions are captured in vivo by chemical crosslinking. Cell lysis, DNA fragmentation and immunoaffinity purification of the desired protein will co-purify DNA fragments that are associated with that protein. The enriched DNA population is then labeled, combined with a differentially labeled reference sample and applied to DNA microarrays to detect enriched signals. Various computational and bioinformatic approaches are then applied to normalize the enriched and reference channels, to connect signals to the portions of the genome that are represented on the DNA microarrays, to provide confidence metrics and to generate maps of protein-genome occupancy. Here, we describe the experimental protocols that we use from crosslinking of cells to hybridization of labeled material, together with insights into the aspects of these protocols that influence the results. These protocols require approximately 1 week to complete once sufficient numbers of cells have been obtained, and have been used to produce robust, high-quality ChIP-chip results in many different cell and tissue types. PMID:17406303

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

    PubMed Central

    2012-01-01

    Background 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. Results 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. Conclusions 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

  10. Genopal™: A Novel Hollow Fibre Array for Focused Microarray Analysis

    PubMed Central

    Okuzaki, Daisuke; Fukushima, Tatsunobu; Tougan, Takahiro; Ishii, Tomonori; Kobayashi, Shigeto; Yoshizaki, Kazuyuki; Akita, Takashi; Nojima, Hiroshi

    2010-01-01

    Expression profiling of target genes in patient blood is a powerful tool for RNA diagnosis. Here, we describe Genopal™, a novel platform ideal for efficient focused microarray analysis. Genopal™, which consists of gel-filled fibres, is advantageous for high-quality mass production via large-scale slicing of the Genopal™ block. We prepared two arrays, infectant and autoimmunity, that provided highly reliable data in terms of repetitive scanning of the same and/or distinct microarrays. Moreover, we demonstrated that Genopal™ had sensitivity sufficient to yield signals in short hybridization times (0.5 h). Application of the autoimmunity array to blood samples allowed us to identify an expression pattern specific to Takayasu arteritis based on the Spearman rank correlation by comparing the reference profile with those of several autoimmune diseases and healthy volunteers (HVs). The comparison of these data with those obtained by other methods revealed that they exhibited similar expression profiles of many target genes. Taken together, these data demonstrate that Genopal™ is an advantageous platform for focused microarrays with regard to its low cost, rapid results and reliable quality. PMID:21059707

  11. Genopal™: a novel hollow fibre array for focused microarray analysis.

    PubMed

    Okuzaki, Daisuke; Fukushima, Tatsunobu; Tougan, Takahiro; Ishii, Tomonori; Kobayashi, Shigeto; Yoshizaki, Kazuyuki; Akita, Takashi; Nojima, Hiroshi

    2010-12-01

    Expression profiling of target genes in patient blood is a powerful tool for RNA diagnosis. Here, we describe Genopal™, a novel platform ideal for efficient focused microarray analysis. Genopal™, which consists of gel-filled fibres, is advantageous for high-quality mass production via large-scale slicing of the Genopal™ block. We prepared two arrays, infectant and autoimmunity, that provided highly reliable data in terms of repetitive scanning of the same and/or distinct microarrays. Moreover, we demonstrated that Genopal™ had sensitivity sufficient to yield signals in short hybridization times (0.5 h). Application of the autoimmunity array to blood samples allowed us to identify an expression pattern specific to Takayasu arteritis based on the Spearman rank correlation by comparing the reference profile with those of several autoimmune diseases and healthy volunteers (HVs). The comparison of these data with those obtained by other methods revealed that they exhibited similar expression profiles of many target genes. Taken together, these data demonstrate that Genopal™ is an advantageous platform for focused microarrays with regard to its low cost, rapid results and reliable quality. PMID:21059707

  12. inSilicoDb: an R/Bioconductor package for accessing human Affymetrix expert-curated datasets from GEO.

    PubMed

    Taminau, Jonatan; Steenhoff, David; Coletta, Alain; Meganck, Stijn; Lazar, Cosmin; de Schaetzen, Virginie; Duque, Robin; Molter, Colin; Bersini, Hugues; Nowé, Ann; Weiss Solís, David Y

    2011-11-15

    Microarray technology has become an integral part of biomedical research and increasing amounts of datasets become available through public repositories. However, re-use of these datasets is severely hindered by unstructured, missing or incorrect biological samples information; as well as the wide variety of preprocessing methods in use. The inSilicoDb R/Bioconductor package is a command-line front-end to the InSilico DB, a web-based database currently containing 86 104 expert-curated human Affymetrix expression profiles compiled from 1937 GEO repository series. The use of this package builds on the Bioconductor project's focus on reproducibility by enabling a clear workflow in which not only analysis, but also the retrieval of verified data is supported.

  13. DNA Microarray and Signal Transduction Analysis in Pulmonary Artery Smooth Muscle Cells From Heritable and Idiopathic Pulmonary Arterial Hypertension Subjects

    PubMed Central

    Yu, Jun; Wilson, Jamie; Taylor, Linda; Polgar, Peter

    2015-01-01

    Pulmonary arterial hypertension (PAH) is characterized by increased pulmonary vascular smooth muscle contraction and proliferation. Here, we analyze genome-wide mRNA expression in human pulmonary arterial smooth muscle cells (HPASMC) isolated from three control, three hereditary (HPAH), and three idiopathic PAH (IPAH) subjects using the Affymetrix Human Gene ST 1.0 chip. The microarray analysis reveals the expression of 537 genes in HPAH and 1024 genes in IPAH changed compared with control HPASMC. Among those genes, 227 genes show similar directionality of expression in both HPAH and IPAH HPASMC. Ingenuity™ Pathway Analysis (IPA) suggests that many of those genes are involved in cellular growth/proliferation and cell cycle regulation and that signaling pathways such as the mitotic activators, polo-like kinases, ATM signaling are activated under PAH conditions. Furthermore, the analysis demonstrates downregulated mRNA expression of certain vasoactive receptors such as bradykinin receptor B2 (BKB2R). Using real time PCR, we verified the downregulated BKB2R expression in the PAH cells. Bradykinin-stimulated calcium influx is also decreased in PAH PASMC. IPA also identified transcriptional factors such p53 and Rb as downregulated, and FoxM1 and Myc as upregulated in both HPAH and IPAH HPASMC. The decreased level of phospho-p53 in PAH cells was confirmed with a phospho-protein array; and we experimentally show a dysregulated proliferation of both HPAH and IPAH PASMC. Together, the microarray experiments and bioinformatics analysis highlight an aberrant proliferation and cell cycle regulation in HPASMC from PAH subjects. These newly identified pathways may provide new targets for the treatment of both hereditary and idiopathic PAH. PMID:25290246

  14. A Grid-based solution for management and analysis of microarrays in distributed experiments

    PubMed Central

    Porro, Ivan; Torterolo, Livia; Corradi, Luca; Fato, Marco; Papadimitropoulos, Adam; Scaglione, Silvia; Schenone, Andrea; Viti, Federica

    2007-01-01

    Several systems have been presented in the last years in order to manage the complexity of large microarray experiments. Although good results have been achieved, most systems tend to lack in one or more fields. A Grid based approach may provide a shared, standardized and reliable solution for storage and analysis of biological data, in order to maximize the results of experimental efforts. A Grid framework has been therefore adopted due to the necessity of remotely accessing large amounts of distributed data as well as to scale computational performances for terabyte datasets. Two different biological studies have been planned in order to highlight the benefits that can emerge from our Grid based platform. The described environment relies on storage services and computational services provided by the gLite Grid middleware. The Grid environment is also able to exploit the added value of metadata in order to let users better classify and search experiments. A state-of-art Grid portal has been implemented in order to hide the complexity of framework from end users and to make them able to easily access available services and data. The functional architecture of the portal is described. As a first test of the system performances, a gene expression analysis has been performed on a dataset of Affymetrix GeneChip® Rat Expression Array RAE230A, from the ArrayExpress database. The sequence of analysis includes three steps: (i) group opening and image set uploading, (ii) normalization, and (iii) model based gene expression (based on PM/MM difference model). Two different Linux versions (sequential and parallel) of the dChip software have been developed to implement the analysis and have been tested on a cluster. From results, it emerges that the parallelization of the analysis process and the execution of parallel jobs on distributed computational resources actually improve the performances. Moreover, the Grid environment have been tested both against the possibility of

  15. Microarray analysis of cultured human brain aggregates following cortisol exposure: implications for cellular functions relevant to mood disorders.

    PubMed

    Salaria, S; Chana, G; Caldara, F; Feltrin, E; Altieri, M; Faggioni, F; Domenici, E; Merlo-Pich, E; Everall, I P

    2006-09-01

    Increased cortisol levels in humans are often observed in patients suffering from mood disorders. In this study human fetal brain aggregates were exposed to cortisol at 500 nM for 3 weeks, as an in-vitro model of chronic cortisol exposure. Microarray analysis on extracted mRNA using the Affymetrix U133A platform was then performed. Our results demonstrated a significant effect of cortisol on 1648 transcripts; 736 up-regulated and 912 down-regulated genes. The most differentially regulated biological categories were: RNA processing, protein metabolism, and cell growth. Within these categories we observed a down-regulation of fibroblast growth factor 2 (FGF2) (-1.5-fold) and aquaporin4 (AQP4) (-1.7-fold), alongside an up-regulation of fibroblast growth factor 9 (FGF9) (+1.7-fold) and vesicle associated membrane protein2 (VAMP2) (+1.7-fold). FGF2, FGF9, AQP4 and VAMP2 changes were confirmed at the protein level by immunohistochemistry. Alterations in FGF transcripts are in keeping with recent literature demonstrating such effects in patients with mood disorders. PMID:16844382

  16. Microarray Analysis of LTR Retrotransposon Silencing Identifies Hdac1 as a Regulator of Retrotransposon Expression in Mouse Embryonic Stem Cells

    PubMed Central

    Madej, Monika J.; Taggart, Mary; Gautier, Philippe; Garcia-Perez, Jose Luis; Meehan, Richard R.; Adams, Ian R.

    2012-01-01

    Retrotransposons are highly prevalent in mammalian genomes due to their ability to amplify in pluripotent cells or developing germ cells. Host mechanisms that silence retrotransposons in germ cells and pluripotent cells are important for limiting the accumulation of the repetitive elements in the genome during evolution. However, although silencing of selected individual retrotransposons can be relatively well-studied, many mammalian retrotransposons are seldom analysed and their silencing in germ cells, pluripotent cells or somatic cells remains poorly understood. Here we show, and experimentally verify, that cryptic repetitive element probes present in Illumina and Affymetrix gene expression microarray platforms can accurately and sensitively monitor repetitive element expression data. This computational approach to genome-wide retrotransposon expression has allowed us to identify the histone deacetylase Hdac1 as a component of the retrotransposon silencing machinery in mouse embryonic stem cells, and to determine the retrotransposon targets of Hdac1 in these cells. We also identify retrotransposons that are targets of other retrotransposon silencing mechanisms such as DNA methylation, Eset-mediated histone modification, and Ring1B/Eed-containing polycomb repressive complexes in mouse embryonic stem cells. Furthermore, our computational analysis of retrotransposon silencing suggests that multiple silencing mechanisms are independently targeted to retrotransposons in embryonic stem cells, that different genomic copies of the same retrotransposon can be differentially sensitive to these silencing mechanisms, and helps define retrotransposon sequence elements that are targeted by silencing machineries. Thus repeat annotation of gene expression microarray data suggests that a complex interplay between silencing mechanisms represses retrotransposon loci in germ cells and embryonic stem cells. PMID:22570599

  17. Structural analysis of hepatitis C RNA genome using DNA microarrays

    PubMed Central

    Martell, María; Briones, Carlos; de Vicente, Aránzazu; Piron, María; Esteban, Juan I.; Esteban, Rafael; Guardia, Jaime; Gómez, Jordi

    2004-01-01

    Many studies have tried to identify specific nucleotide sequences in the quasispecies of hepatitis C virus (HCV) that determine resistance or sensitivity to interferon (IFN) therapy, unfortunately without conclusive results. Although viral proteins represent the most evident phenotype of the virus, genomic RNA sequences determine secondary and tertiary structures which are also part of the viral phenotype and can be involved in important biological roles. In this work, a method of RNA structure analysis has been developed based on the hybridization of labelled HCV transcripts to microarrays of complementary DNA oligonucleotides. Hybridizations were carried out at non-denaturing conditions, using appropriate temperature and buffer composition to allow binding to the immobilized probes of the RNA transcript without disturbing its secondary/tertiary structural motifs. Oligonucleotides printed onto the microarray covered the entire 5′ non-coding region (5′NCR), the first three-quarters of the core region, the E2–NS2 junction and the first 400 nt of the NS3 region. We document the use of this methodology to analyse the structural degree of a large region of HCV genomic RNA in two genotypes associated with different responses to IFN treatment. The results reported here show different structural degree along the genome regions analysed, and differential hybridization patterns for distinct genotypes in NS2 and NS3 HCV regions. PMID:15247323

  18. [Infrared fluorescent markers for microarray DNA analysis on biological microchip].

    PubMed

    Spitsyn, M A; Shershov, V E; Kuznetsova, V E; Barsky, V E; Egorov, E E; Emelyanova, M A; Kreindlin, E Ya; Lysov, Yu P; Guseinov, T O; Fesenko, D E; Lapa, S A; Surzhikov, S A; Abramov, I S; Nasedkina, T V; Zasedatelev, A S; Chudinov, A V

    2015-01-01

    To expand the informational capabilities of molecular genetic research, on the biological microchips, new indotricarbocyanine dyes that fluoresce in the near infrared (IR) spectral region have been synthesized. The developed IR dyes were studied using a biochip-based test system for detection of mutations in the BRCA1/BRCA2 and CHECK2 genes associated with breast cancer. The fluorescent label was introduced to the analyzed DNA during PCR using primers labeled with the synthesized IR dyes. An analyzer that allows recording and processing of images of fluorescent microarrays in the IR spectral region was designed and manufactured. It has been shown that the use of the synthesized dyes enables to conduct analysis in the IR region and improve the reliability of medical diagnostic tests due to low fluorescence intensity of sample components as well as of a biochip substrate and the reagents used for analysis. PMID:26510593

  19. Using Kepler for Tool Integration in Microarray Analysis Workflows

    PubMed Central

    Gan, Zhuohui; Stowe, Jennifer C.; Altintas, Ilkay; McCulloch, Andrew D.; Zambon, Alexander C.

    2015-01-01

    Increasing numbers of genomic technologies are leading to massive amounts of genomic data, all of which requires complex analysis. More and more bioinformatics analysis tools are being developed by scientist to simplify these analyses. However, different pipelines have been developed using different software environments. This makes integrations of these diverse bioinformatics tools difficult. Kepler provides an open source environment to integrate these disparate packages. Using Kepler, we integrated several external tools including Bioconductor packages, AltAnalyze, a python-based open source tool, and R-based comparison tool to build an automated workflow to meta-analyze both online and local microarray data. The automated workflow connects the integrated tools seamlessly, delivers data flow between the tools smoothly, and hence improves efficiency and accuracy of complex data analyses. Our workflow exemplifies the usage of Kepler as a scientific workflow platform for bioinformatics pipelines. PMID:26605000

  20. [Infrared fluorescent markers for microarray DNA analysis on biological microchip].

    PubMed

    Spitsyn, M A; Shershov, V E; Kuznetsova, V E; Barsky, V E; Egorov, E E; Emelyanova, M A; Kreindlin, E Ya; Lysov, Yu P; Guseinov, T O; Fesenko, D E; Lapa, S A; Surzhikov, S A; Abramov, I S; Nasedkina, T V; Zasedatelev, A S; Chudinov, A V

    2015-01-01

    To expand the informational capabilities of molecular genetic research, on the biological microchips, new indotricarbocyanine dyes that fluoresce in the near infrared (IR) spectral region have been synthesized. The developed IR dyes were studied using a biochip-based test system for detection of mutations in the BRCA1/BRCA2 and CHECK2 genes associated with breast cancer. The fluorescent label was introduced to the analyzed DNA during PCR using primers labeled with the synthesized IR dyes. An analyzer that allows recording and processing of images of fluorescent microarrays in the IR spectral region was designed and manufactured. It has been shown that the use of the synthesized dyes enables to conduct analysis in the IR region and improve the reliability of medical diagnostic tests due to low fluorescence intensity of sample components as well as of a biochip substrate and the reagents used for analysis.

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

    PubMed

    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.

  2. A microarray analysis of retinal transcripts that are controlled by image contrast in mice

    PubMed Central

    Brand, Christine; Schaeffel, Frank

    2007-01-01

    Purpose The development of myopia is controlled by still largely unknown retinal signals. The aim of this study was to investigate the changes in retinal mRNA expression after different periods of visual deprivation in mice, while controlling for retinal illuminance. Methods Each group consisted of three male C57BL/6 mice. Treatment periods were 30 min, 4 h, and 6+6 h. High spatial frequencies were filtered from the retinal image by frosted diffusers over one eye while the fellow eyes were covered by clear neutral density (ND) filters that exhibited similar light attenuating properties (0.1 log units) as the diffusers. For the final 30 min of the respective treatment period mice were individually placed in a clear Perspex cylinder that was positioned in the center of a rotating (60 degrees) large drum. The inside of the drum was covered with a 0.1 cyc/degree vertical square wave grating. This visual environment was chosen to standardize illuminances and contrasts seen by the mice. Labeled cRNA was prepared and hybridized to Affymetrix GeneChip® Mouse Genome 430 2.0 arrays. Alterations in mRNA expression levels of candidate genes with potential biological relevance were confirmed by semi-quantitative real-time reverse transcription polymerase chain reaction (RT-PCR). Results In all groups, Egr-1 mRNA expression was reduced in diffuser-treated eyes. Furthermore, the degradation of the spatial frequency spectrum also changed the cFos mRNA level, with reduced expression after 4 h of diffuser treatment. Other interesting candidates were Akt2, which was up-regulated after 30 min of deprivation and Mapk8ip3, a neuron specific JNK binding and scaffolding protein that was temporally regulated in the diffuser-treated eyes only. Conclusions The microarray analysis demonstrated a pattern of differential transcriptional changes, even though differences in the retinal images were restricted to spatial features. The candidate genes may provide further insight into the

  3. Comparison of Comparative Genomic Hybridization Technologies across Microarray Platforms

    EPA Science Inventory

    In the 2007 Association of Biomolecular Resource Facilities (ABRF) Microarray Research Group (MARG) project, we analyzed HL-60 DNA with five platforms: Agilent, Affymetrix 500K, Affymetrix U133 Plus 2.0, Illumina, and RPCI 19K BAC arrays. Copy number variation (CNV) was analyzed ...

  4. Assessing Agreement between miRNA Microarray Platforms

    PubMed Central

    Bassani, Niccolò P.; Ambrogi, Federico; Biganzoli, Elia M.

    2014-01-01

    Over the last few years, miRNA microarray platforms have provided great insights into the biological mechanisms underlying the onset and development of several diseases. However, only a few studies have evaluated the concordance between different microarray platforms using methods that took into account measurement error in the data. In this work, we propose the use of a modified version of the Bland–Altman plot to assess agreement between microarray platforms. To this aim, two samples, one renal tumor cell line and a pool of 20 different human normal tissues, were profiled using three different miRNA platforms (Affymetrix, Agilent, Illumina) on triplicate arrays. Intra-platform reliability was assessed by calculating pair-wise concordance correlation coefficients (CCC) between technical replicates and overall concordance correlation coefficient (OCCC) with bootstrap percentile confidence intervals, which revealed moderate-to-good repeatability of all platforms for both samples. Modified Bland–Altman analysis revealed good patterns of concordance for Agilent and Illumina, whereas Affymetrix showed poor-to-moderate agreement for both samples considered. The proposed method is useful to assess agreement between array platforms by modifying the original Bland–Altman plot to let it account for measurement error and bias correction and can be used to assess patterns of concordance between other kinds of arrays other than miRNA microarrays.

  5. Experimental Approaches to Microarray Analysis of Tumor Samples

    ERIC Educational Resources Information Center

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

    2008-01-01

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

  6. Clinical and microarray analysis of breast cancers of all subtypes from two prospective preoperative chemotherapy studies

    PubMed Central

    Okuma, H S; Koizumi, F; Hirakawa, A; Nakatochi, M; Komori, O; Hashimoto, J; Kodaira, M; Yunokawa, M; Yamamoto, H; Yonemori, K; Shimizu, C; Fujiwara, Y; Tamura, K

    2016-01-01

    Background: We aimed to analyse clinical and gene expression profiles to predict pathologic complete response and disease-free survival using two consecutive, prospective, preoperative chemotherapy trial cohorts. Methods: Clinicopathological and gene expression data were evaluated in a cohort from two consecutive phase II preoperative studies that included patients with stage IIA–IIIC breast cancer of all subtypes. Analysed specimens were obtained before preoperative chemotherapy, and cDNA microarray analyses were performed using the Affymetrix Gene Chip U133 plus 2.0. Results: Between December 2005 and December 2010, 122 patients were analysed. The pathologic complete response rate was significantly higher in HER2+ and HR−/HER2− cancers. Age, pathologic complete response, HR−/HER2− status, and lymph node positivity (⩾4) were significant poor prognostic factors for disease-free survival. For the cDNA microarray analyses, sufficient tumour samples were available from 78 of the 107 patients (73%). An 8-gene signature predictive of pathologic complete response and a 17-gene signature predictive of prognosis were identified. Patients were categorised into low-risk (n=45) and high-risk groups (n=33) (HR 70.0, P=0.004). Conclusions: This study yielded preliminary data on the expression of specific genes predicting pathologic complete response and disease-free survival in a cohort of chemonaïve breast cancer patients. Further validation may distinguish those who would benefit most from perioperative chemotherapy as well as those needing further intervention. PMID:27415010

  7. Microarray analysis of gene expression in vestibular schwannomas reveals SPP1/MET signaling pathway and androgen receptor deregulation

    PubMed Central

    TORRES-MARTIN, MIGUEL; LASSALETTA, LUIS; SAN-ROMAN-MONTERO, JESUS; DE CAMPOS, JOSE M.; ISLA, ALBERTO; GAVILAN, JAVIER; MELENDEZ, BARBARA; PINTO, GIOVANNY R.; BURBANO, ROMMEL R.; CASTRESANA, JAVIER S.; REY, JUAN A.

    2013-01-01

    Vestibular schwannomas are benign neoplasms that arise from the vestibular nerve. The hallmark of these tumors is the biallelic inactivation of neurofibromin 2 (NF2). Transcriptomic alterations, such as the neuregulin 1 (NRG1)/ErbB2 pathway, have been described in schwannomas. In this study, we performed a whole transcriptome analysis in 31 vestibular schwannomas and 9 control nerves in the Affymetrix Gene 1.0 ST platform, validated by quantitative real-time PCR (qRT-PCR) using TaqMan Low Density arrays. We performed a mutational analysis of NF2 by PCR/denaturing high-performance liquid chromatography (dHPLC) and multiplex ligation-dependent probe amplification (MLPA), as well as a microsatellite marker analysis of the loss of heterozygosity (LOH) of chromosome 22q. The microarray analysis demonstrated that 1,516 genes were deregulated and 48 of the genes were validated by qRT-PCR. At least 2 genetic hits (allelic loss and/or gene mutation) in NF2 were found in 16 tumors, seven cases showed 1 hit and 8 tumors showed no NF2 alteration. MET and associated genes, such as integrin, alpha 4 (ITGA4)/B6, PLEXNB3/SEMA5 and caveolin-1 (CAV1) showed a clear deregulation in vestibular schwannomas. In addition, androgen receptor (AR) downregulation may denote a hormonal effect or cause in this tumor. Furthermore, the osteopontin gene (SPP1), which is involved in merlin protein degradation, was upregulated, which suggests that this mechanism may also exert a pivotal role in schwannoma merlin depletion. Finally, no major differences were observed among tumors of different size, histological type or NF2 status, which suggests that, at the mRNA level, all schwannomas, regardless of their molecular and clinical characteristics, may share common features that can be used in their treatment. PMID:23354516

  8. TAMEE: data management and analysis for tissue microarrays

    PubMed Central

    Thallinger, Gerhard G; Baumgartner, Kerstin; Pirklbauer, Martin; Uray, Martina; Pauritsch, Elke; Mehes, Gabor; Buck, Charles R; Zatloukal, Kurt; Trajanoski, Zlatko

    2007-01-01

    Background With the introduction of tissue microarrays (TMAs) researchers can investigate gene and protein expression in tissues on a high-throughput scale. TMAs generate a wealth of data calling for extended, high level data management. Enhanced data analysis and systematic data management are required for traceability and reproducibility of experiments and provision of results in a timely and reliable fashion. Robust and scalable applications have to be utilized, which allow secure data access, manipulation and evaluation for researchers from different laboratories. Results TAMEE (Tissue Array Management and Evaluation Environment) is a web-based database application for the management and analysis of data resulting from the production and application of TMAs. It facilitates storage of production and experimental parameters, of images generated throughout the TMA workflow, and of results from core evaluation. Database content consistency is achieved using structured classifications of parameters. This allows the extraction of high quality results for subsequent biologically-relevant data analyses. Tissue cores in the images of stained tissue sections are automatically located and extracted and can be evaluated using a set of predefined analysis algorithms. Additional evaluation algorithms can be easily integrated into the application via a plug-in interface. Downstream analysis of results is facilitated via a flexible query generator. Conclusion We have developed an integrated system tailored to the specific needs of research projects using high density TMAs. It covers the complete workflow of TMA production, experimental use and subsequent analysis. The system is freely available for academic and non-profit institutions from . PMID:17343750

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

    SciTech Connect

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

    2008-08-15

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

  10. A comparative analysis of DNA barcode microarray feature size

    PubMed Central

    Ammar, Ron; Smith, Andrew M; Heisler, Lawrence E; Giaever, Guri; Nislow, Corey

    2009-01-01

    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. PMID:19825181

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

    PubMed

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

    2016-01-01

    Microarray-based proteomic platforms have emerged as valuable tools for studying various aspects of protein function, particularly in the field of chromatin biochemistry. Microarray technology itself is largely unrestricted in regard to printable material and platform design, and efficient multidimensional optimization of assay parameters requires fluidity in the design and analysis of custom print layouts. This motivates the need for streamlined software infrastructure that facilitates the combined planning and analysis of custom microarray experiments. To this end, we have developed ArrayNinja as a portable, open source, and interactive application that unifies the planning and visualization of microarray experiments and provides maximum flexibility to end users. Array experiments can be planned, stored to a private database, and merged with the imaged results for a level of data interaction and centralization that is not currently attainable with available microarray informatics tools. PMID:27423857

  12. Gene Expression Signature in Endemic Osteoarthritis by Microarray Analysis

    PubMed Central

    Wang, Xi; Ning, Yujie; Zhang, Feng; Yu, Fangfang; Tan, Wuhong; Lei, Yanxia; Wu, Cuiyan; Zheng, Jingjing; Wang, Sen; Yu, Hanjie; Li, Zheng; Lammi, Mikko J.; Guo, Xiong

    2015-01-01

    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. PMID:25997002

  13. Microarray analysis of Xenopus endoderm expressing Ptf1a

    PubMed Central

    Bilogan, Cassandra K.; Horb, Marko E.

    2012-01-01

    Pancreas specific transcription factor 1a (Ptf1a), a bHLH transcription factor, has two temporally distinct functions during pancreas development; initially it is required for early specification of the entire pancreas, while later it is required for proper differentiation and maintenance of only acinar cells. The importance of Ptf1a function was revealed by the fact that loss of Ptf1a leads to pancreas agenesis in humans. While Ptf1a is one of the most important pancreatic transcription factors, little is known about the differences between the regulatory networks it controls during initial specification of the pancreas as opposed to acinar cell development, and to date no comprehensive analysis of its downstream targets has been published. In this paper, we use Xenopus embryos to identify putative downstream targets of Ptf1a. We isolated anterior endoderm tissue overexpressing Ptf1a at two early stages, NF32 and NF36, and compared their gene expression profiles using microarrays. Our results revealed that Ptf1a regulates genes with a wide variety of functions, providing insight into the complexity of the regulatory network required for pancreas specification. PMID:22815262

  14. Identification of genes associated with osteoarthritis by microarray analysis.

    PubMed

    Sun, Jianwei; Yan, Bingshan; Yin, Wangping; Zhang, Xinchao

    2015-10-01

    The aim of the present study was to investigate the mechanisms of osteoarthritis (OA). Raw microarray data (GSE51588) were downloaded from Gene Expression Omnibus, including samples from OA (n=20) and non‑OA (n=5) knee lateral and medial tibial plateaus. Differentially expressed genes (DEGs) were identified using Student's t‑test. Functional and pathway enrichment analyses were performed for the upregulated and downregulated DEGs. A protein‑protein interaction network (PPI) was constructed according to the Search Tool for the Retrieval of Interacting Genes/Proteins database, and module analysis of the PPI network was performed using CFinder. The protein domain enrichment analysis for genes in modules was performed using the INTERPRO database. A total of 869 upregulated and 508 downregulated DEGs were identified. The enriched pathways of downregulated and upregulated DEGs were predominantly associated with the cell cycle (BUB1, BUB1B, CCNA2, CCNB1 and CCNE1), and extracellular matrix (ECM)‑receptor interaction (CD36, COL11A2, COL1A1, COL2A1 and COL3A1). Functional enrichment analysis of the DEGs demonstrated that FGF19, KIF11 and KIF2C were involved in the response to stress and that ACAN, ADAMTS10 and BGN were associated with proteinaceous ECM. The top protein domain was IPR001752: Kinesin motor region involving three genes (KIF2C, KIF11 and KIF20A). The identified DEGs, including KIF2C, KIF11 and KIF20A, may be significant in the pathogenesis of OA. PMID:26151199

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

    PubMed Central

    Kijimoto, Teiya; Costello, James; Tang, Zuojian; Moczek, Armin P; Andrews, Justen

    2009-01-01

    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. PMID:19878565

  16. Screening of differentially expressed genes in the growth plate of broiler chickens with Tibial Dyschondroplasia by microarray analysis

    PubMed Central

    2013-01-01

    microarray analysis will be used in future studies to clarify the molecular pathogenic mechanisms of TD. From these findings, potential pathways involved in early stage TD warrant further investigation. PMID:23617778

  17. Microarray-based detection and expression analysis of ABC and SLC transporters in drug-resistant ovarian cancer cell lines.

    PubMed

    Januchowski, Radosław; Zawierucha, Piotr; Andrzejewska, Małgorzata; Ruciński, Marcin; Zabel, Maciej

    2013-04-01

    Multiple drug resistance of cancer cells is multifactorial. A microarray technique may provide information about new candidate genes playing a role in drug resistance. Drug membrane transporters from ABC and SLC families play a main role in this phenomenon. This study demonstrates alterations in ABC and SLC gene expression levels in methotrexate, cisplatin, doxorubicin, vincristine, topotecan and paclitaxel-resistant variant of W1 ovarian cancer cell line. Resistant W1 cell lines were derived by stepwise selection of cells in increasing concentration of drugs. Affymetrix GeneChip(®) Human Genome U219 Array Strip was used for hybridizations. Statistical significance was determined by independent sample t-test. The genes having altered expression levels in drug-resistant sublines were selected and filtered by scater plot. Genes up/downregulated more than threefolds were selected and listed. Among ABC genes, seven were upregulated and three were downregulated. Three genes: ABCB1, ABCB4 and ABCG2 were upregulated very significantly (over tenfold). One ABCA8 was significantly downregulated. Among 38 SLC genes, 18 were upregulated, 16 were downregulated and four were up- or downregulated dependent on the cell line. Expression of 10 SLC genes was changed very significantly (over tenfold). Four genes were significantly increased: SLC6A1, SLC9A2, SLC12A1, SLC16A6 and six genes were significantly decreased: SLC2A14, SLC7A3, SLC7A8, SLC7A11, SLC16A14, SLC38A9. Based on the expression profiles, our results provide a preliminary insight into the relationship between drug resistance and expression of membrane transporters involved in drug resistance. Correlation of specific drug transporter with drug resistance requires further analysis.

  18. Issues in the analysis of oligonucleotide tiling microarrays for transcript mapping

    NASA Technical Reports Server (NTRS)

    Royce, Thomas E.; Rozowsky, Joel S.; Bertone, Paul; Samanta, Manoj; Stolc, Viktor; Weissman, Sherman; Snyder, Michael; Gerstein, Mark

    2005-01-01

    Traditional microarrays use probes complementary to known genes to quantitate the differential gene expression between two or more conditions. Genomic tiling microarray experiments differ in that probes that span a genomic region at regular intervals are used to detect the presence or absence of transcription. This difference means the same sets of biases and the methods for addressing them are unlikely to be relevant to both types of experiment. We introduce the informatics challenges arising in the analysis of tiling microarray experiments as open problems to the scientific community and present initial approaches for the analysis of this nascent technology.

  19. Network expansion and pathway enrichment analysis towards biologically significant findings from microarrays.

    PubMed

    Wu, Xiaogang; Huang, Hui; Wei, Tao; Pandey, Ragini; Reinhard, Christoph; Li, Shuyu D; Chen, Jake Y

    2012-01-01

    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.

  20. A comprehensive comparison of RNA-Seq-based transcriptome analysis from reads to differential gene expression and cross-comparison with microarrays: a case study in Saccharomyces cerevisiae

    PubMed Central

    Nookaew, Intawat; Papini, Marta; Pornputtapong, Natapol; Scalcinati, Gionata; Fagerberg, Linn; Uhlén, Matthias; Nielsen, Jens

    2012-01-01

    RNA-seq, has recently become an attractive method of choice in the studies of transcriptomes, promising several advantages compared with microarrays. In this study, we sought to assess the contribution of the different analytical steps involved in the analysis of RNA-seq data generated with the Illumina platform, and to perform a cross-platform comparison based on the results obtained through Affymetrix microarray. As a case study for our work we, used the Saccharomyces cerevisiae strain CEN.PK 113-7D, grown under two different conditions (batch and chemostat). Here, we asses the influence of genetic variation on the estimation of gene expression level using three different aligners for read-mapping (Gsnap, Stampy and TopHat) on S288c genome, the capabilities of five different statistical methods to detect differential gene expression (baySeq, Cuffdiff, DESeq, edgeR and NOISeq) and we explored the consistency between RNA-seq analysis using reference genome and de novo assembly approach. High reproducibility among biological replicates (correlation ≥0.99) and high consistency between the two platforms for analysis of gene expression levels (correlation ≥0.91) are reported. The results from differential gene expression identification derived from the different statistical methods, as well as their integrated analysis results based on gene ontology annotation are in good agreement. Overall, our study provides a useful and comprehensive comparison between the two platforms (RNA-seq and microrrays) for gene expression analysis and addresses the contribution of the different steps involved in the analysis of RNA-seq data. PMID:22965124

  1. BioArray Software Environment (BASE): a platform for comprehensive management and analysis of microarray data

    PubMed Central

    Saal, Lao H; Troein, Carl; Vallon-Christersson, Johan; Gruvberger, Sofia; Borg, Åke; Peterson, Carsten

    2002-01-01

    The microarray technique requires the organization and analysis of vast amounts of data. These data include information about the samples hybridized, the hybridization images and their extracted data matrices, and information about the physical array, the features and reporter molecules. We present a web-based customizable bioinformatics solution called BioArray Software Environment (BASE) for the management and analysis of all areas of microarray experimentation. All software necessary to run a local server is freely available. PMID:12186655

  2. Microarray analysis of copy number variation in single cells.

    PubMed

    Konings, Peter; Vanneste, Evelyne; Jackmaert, Sigrun; Ampe, Michèle; Verbeke, Geert; Moreau, Yves; Vermeesch, Joris Robert; Voet, Thierry

    2012-02-01

    We present a protocol for reliably detecting DNA copy number aberrations in a single human cell. Multiple displacement-amplified DNAs of a cell are hybridized to a 3,000-bacterial artificial chromosome (BAC) array and to an Affymetrix 250,000 (250K)-SNP array. Subsequent copy number calling is based on the integration of BAC probe-specific copy number probabilities that are estimated by comparing probe intensities with a single-cell whole-genome amplification (WGA) reference model for diploid chromosomes, as well as SNP copy number and loss-of-heterozygosity states estimated by hidden Markov models (HMM). All methods for detecting DNA copy number aberrations in single human cells have difficulty in confidently discriminating WGA artifacts from true genetic variants. Furthermore, some methods lack thorough validation for segmental DNA imbalance detection. Our protocol minimizes false-positive variant calling and enables uniparental isodisomy detection in single cells. Additionally, it provides quality assessment, allowing the exclusion of uninterpretable single-cell WGA samples. The protocol takes 5-7 d. PMID:22262009

  3. The Genopolis Microarray Database

    PubMed Central

    Splendiani, Andrea; Brandizi, Marco; Even, Gael; Beretta, Ottavio; Pavelka, Norman; Pelizzola, Mattia; Mayhaus, Manuel; Foti, Maria; Mauri, Giancarlo; Ricciardi-Castagnoli, Paola

    2007-01-01

    Background Gene expression databases are key resources for microarray data management and analysis and the importance of a proper annotation of their content is well understood. Public repositories as well as microarray database systems that can be implemented by single laboratories exist. However, there is not yet a tool that can easily support a collaborative environment where different users with different rights of access to data can interact to define a common highly coherent content. The scope of the Genopolis database is to provide a resource that allows different groups performing microarray experiments related to a common subject to create a common coherent knowledge base and to analyse it. The Genopolis database has been implemented as a dedicated system for the scientific community studying dendritic and macrophage cells functions and host-parasite interactions. Results The Genopolis Database system allows the community to build an object based MIAME compliant annotation of their experiments and to store images, raw and processed data from the Affymetrix GeneChip® platform. It supports dynamical definition of controlled vocabularies and provides automated and supervised steps to control the coherence of data and annotations. It allows a precise control of the visibility of the database content to different sub groups in the community and facilitates exports of its content to public repositories. It provides an interactive users interface for data analysis: this allows users to visualize data matrices based on functional lists and sample characterization, and to navigate to other data matrices defined by similarity of expression values as well as functional characterizations of genes involved. A collaborative environment is also provided for the definition and sharing of functional annotation by users. Conclusion The Genopolis Database supports a community in building a common coherent knowledge base and analyse it. This fills a gap between a local

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

    PubMed Central

    Yang, Jianji; Cohen, Aaron; Hersh, William

    2009-01-01

    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: PMID:19208193

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

    PubMed

    Polen, Tino; Wendisch, Volker F

    2004-01-01

    DNA microarray technology has become an important research tool for biotechnology and microbiology. It is now possible to characterize genetic diversity and gene expression in a genomewide manner. DNA microarrays have been applied extensively to study the biology of many bacteria including Escherichia coli, but only recently have they been developed for the Gram-positive Corynebacterium glutamicum. Both bacteria are widely used for biotechnological amino acid production. In this article, in addition to the design and generation of microarrays as well as their use in hybridization experiments and subsequent data analysis, we describe recent applications of DNA microarray technology regarding amino acid production in C. glutamicum and E. coli. We also discuss the impact of functional genomics studies on fundamental as well as applied aspects of amino acid production with C. glutamicum and E. coli. PMID:15304751

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

    PubMed

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

    2011-06-01

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

  7. DNA microarrays: experimental issues, data analysis, and application to bacterial systems.

    PubMed

    Dharmadi, Yandi; Gonzalez, Ramon

    2004-01-01

    DNA microarrays are currently used to study the transcriptional response of many organisms to genetic and environmental perturbations. Although there is much room for improvement of this technology, its potential has been clearly demonstrated in the past 5 years. The general consensus is that the bottleneck is now located in the processing and analysis of transcriptome data and its use for purposes other than the quantification of changes in gene expression levels. In this article we discuss technological aspects of DNA microarrays, statistical and biological issues pertinent to the design of microarray experiments, and statistical tools for microarray data analysis. A review on applications of DNA microarrays in the study of bacterial systems is presented. Special attention is given to studies in the following areas: (1) bacterial response to environmental changes; (2) gene identification, genome organization, and transcriptional regulation; and (3) genetic and metabolic engineering. Soon, the use of DNA microarray technologies in conjunction with other genome/system-wide analyses (e.g., proteomics, metabolomics, fluxomics, phenomics, etc.) will provide a better assessment of genotype-phenotype relationships in bacteria, which serve as a basis for understanding similar processes in more complex organisms.

  8. Robust Microarray Meta-Analysis Identifies Differentially Expressed Genes for Clinical Prediction

    PubMed Central

    Phan, John H.; Young, Andrew N.; Wang, May D.

    2012-01-01

    Combining multiple microarray datasets increases sample size and leads to improved reproducibility in identification of informative genes and subsequent clinical prediction. Although microarrays have increased the rate of genomic data collection, sample size is still a major issue when identifying informative genetic biomarkers. Because of this, feature selection methods often suffer from false discoveries, resulting in poorly performing predictive models. We develop a simple meta-analysis-based feature selection method that captures the knowledge in each individual dataset and combines the results using a simple rank average. In a comprehensive study that measures robustness in terms of clinical application (i.e., breast, renal, and pancreatic cancer), microarray platform heterogeneity, and classifier (i.e., logistic regression, diagonal LDA, and linear SVM), we compare the rank average meta-analysis method to five other meta-analysis methods. Results indicate that rank average meta-analysis consistently performs well compared to five other meta-analysis methods. PMID:23365541

  9. Fully automated analysis of multi-resolution four-channel micro-array genotyping data

    NASA Astrophysics Data System (ADS)

    Abbaspour, Mohsen; Abugharbieh, Rafeef; Podder, Mohua; Tebbutt, Scott J.

    2006-03-01

    We present a fully-automated and robust microarray image analysis system for handling multi-resolution images (down to 3-micron with sizes up to 80 MBs per channel). The system is developed to provide rapid and accurate data extraction for our recently developed microarray analysis and quality control tool (SNP Chart). Currently available commercial microarray image analysis applications are inefficient, due to the considerable user interaction typically required. Four-channel DNA microarray technology is a robust and accurate tool for determining genotypes of multiple genetic markers in individuals. It plays an important role in the state of the art trend where traditional medical treatments are to be replaced by personalized genetic medicine, i.e. individualized therapy based on the patient's genetic heritage. However, fast, robust, and precise image processing tools are required for the prospective practical use of microarray-based genetic testing for predicting disease susceptibilities and drug effects in clinical practice, which require a turn-around timeline compatible with clinical decision-making. In this paper we have developed a fully-automated image analysis platform for the rapid investigation of hundreds of genetic variations across multiple genes. Validation tests indicate very high accuracy levels for genotyping results. Our method achieves a significant reduction in analysis time, from several hours to just a few minutes, and is completely automated requiring no manual interaction or guidance.

  10. Analysis of protein tyrosine phosphatase interactions with microarrayed phosphopeptide substrates using imaging mass spectrometry

    PubMed Central

    McKee, Christopher J.; Hines, Harry B.; Ulrich, Robert G.

    2013-01-01

    Microarrays of peptide and recombinant protein libraries are routinely used for high-throughput studies of protein-protein interactions and enzymatic activities. Imaging mass spectrometry (IMS) is currently applied as a method to localize analytes on thin tissue sections and other surfaces. Here, we have applied IMS as a label-free means to analyze protein-peptide interactions in a microarray-based phosphatase assay. This IMS strategy visualizes the entire microarray in one composite image by collecting a pre-defined raster of MALDI-TOF MS spectra over the surface of the chip. Examining the bacterial tyrosine phosphatase YopH, we used IMS as a label-free means to visualize enzyme binding and activity with a microarrayed phosphopeptide library printed on chips coated with either gold or indium-tin oxide. Further, we demonstrate that microarray-based IMS can be coupled with surface plasmon resonance imaging to add kinetic analyses to measured binding interactions. The method described here is within the capabilities of many modern MALDI-TOF instruments and has general utility for the label-free analysis of microarray assays. PMID:23906642

  11. Biochemical pathways analysis of microarray results: regulation of myogenesis in pigs

    PubMed Central

    te Pas, Marinus FW; Hulsegge, Ina; Coster, Albart; Pool, Marco H; Heuven, Henri H; Janss, Luc LG

    2007-01-01

    Background Combining microarray results and biological pathway information will add insight into biological processes. Pathway information is widely available in databases through the internet. Mammalian muscle formation has been previously studied using microarray technology in pigs because these animals are an interesting animal model for muscle formation due to selection for increased muscle mass. Results indicated regulation of the expression of genes involved in proliferation and differentiation of myoblasts, and energy metabolism. The aim of the present study was to analyse microarrays studying myogenesis in pigs. It was necessary to develop methods to search biochemical pathways databases. Results PERL scripts were developed that used the names of the genes on the microarray to search databases. Synonyms of gene names were added to the list by searching the Gene Ontology database. The KEGG database was searched for pathway information using this updated gene list. The KEGG database returned 88 pathways. Most genes were found in a single pathway, but others were found in up to seven pathways. Combining the pathways and the microarray information 21 pathways showed sufficient information content for further analysis. These pathways were related to regulation of several steps in myogenesis and energy metabolism. Pathways regulating myoblast proliferation and muscle fibre formation were described. Furthermore, two networks of pathways describing the formation of the myoblast cytoskeleton and regulation of the energy metabolism during myogenesis were presented. Conclusion Combining microarray results and pathways information available through the internet provide biological insight in how the process of porcine myogenesis is regulated. PMID:17567520

  12. User-friendly solutions for microarray quality control and pre-processing on ArrayAnalysis.org.

    PubMed

    Eijssen, Lars M T; Jaillard, Magali; Adriaens, Michiel E; Gaj, Stan; de Groot, Philip J; Müller, Michael; Evelo, Chris T

    2013-07-01

    Quality control (QC) is crucial for any scientific method producing data. Applying adequate QC introduces new challenges in the genomics field where large amounts of data are produced with complex technologies. For DNA microarrays, specific algorithms for QC and pre-processing including normalization have been developed by the scientific community, especially for expression chips of the Affymetrix platform. Many of these have been implemented in the statistical scripting language R and are available from the Bioconductor repository. However, application is hampered by lack of integrative tools that can be used by users of any experience level. To fill this gap, we developed a freely available tool for QC and pre-processing of Affymetrix gene expression results, extending, integrating and harmonizing functionality of Bioconductor packages. The tool can be easily accessed through a wizard-like web portal at http://www.arrayanalysis.org or downloaded for local use in R. The portal provides extensive documentation, including user guides, interpretation help with real output illustrations and detailed technical documentation. It assists newcomers to the field in performing state-of-the-art QC and pre-processing while offering data analysts an integral open-source package. Providing the scientific community with this easily accessible tool will allow improving data quality and reuse and adoption of standards. PMID:23620278

  13. User-friendly solutions for microarray quality control and pre-processing on ArrayAnalysis.org.

    PubMed

    Eijssen, Lars M T; Jaillard, Magali; Adriaens, Michiel E; Gaj, Stan; de Groot, Philip J; Müller, Michael; Evelo, Chris T

    2013-07-01

    Quality control (QC) is crucial for any scientific method producing data. Applying adequate QC introduces new challenges in the genomics field where large amounts of data are produced with complex technologies. For DNA microarrays, specific algorithms for QC and pre-processing including normalization have been developed by the scientific community, especially for expression chips of the Affymetrix platform. Many of these have been implemented in the statistical scripting language R and are available from the Bioconductor repository. However, application is hampered by lack of integrative tools that can be used by users of any experience level. To fill this gap, we developed a freely available tool for QC and pre-processing of Affymetrix gene expression results, extending, integrating and harmonizing functionality of Bioconductor packages. The tool can be easily accessed through a wizard-like web portal at http://www.arrayanalysis.org or downloaded for local use in R. The portal provides extensive documentation, including user guides, interpretation help with real output illustrations and detailed technical documentation. It assists newcomers to the field in performing state-of-the-art QC and pre-processing while offering data analysts an integral open-source package. Providing the scientific community with this easily accessible tool will allow improving data quality and reuse and adoption of standards.

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

    PubMed Central

    Evans, Irene M.

    2010-01-01

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

  15. Similar Response Patterns to 5%Topical Minoxidil Foam in Frontal and Vertex Scalp of Men with Androgenetic Alopecia: A Microarray Analysis

    PubMed Central

    Mirmirani, P.; Consolo, M.; Oyetakin-White, P.; Baron, E.; Leahy, P.; Karnik, P.

    2014-01-01

    Summary Background There are regional variations in scalp hair miniaturization seen in androgenetic alopecia (AGA). Use of topical minoxidil can lead to reversal of miniaturization in the vertex scalp. However, its effects on other scalp regions are less well studied. Methods A placebo controlled double-blinded prospective pilot study of minoxidil topical foam 5% (MTF) vs placebo was conducted in sixteen healthy men ages 18-49 with Hamilton-Norwood type IV-V thinning. The subjects were asked to apply the treatment (active drug or placebo) to the scalp twice daily for eight weeks. Stereotactic scalp photographs were taken at the baseline and final visits to monitor global hair growth. Scalp biopsies were done at the leading edge of hair loss from the frontal and vertex scalp before and after treatment with MTF and placebo and microarray analysis was done using the Affymetrix GeneChip HG U133 Plus 2.0. Results Global stereotactic photographs showed that MTF induced hair growth in both the frontal and vertex scalp of AGA patients. Regional differences in gene expression profiles were observed before treatment. However, MTF treatment induced the expression of hair keratin associated genes and decreased the expression of epidermal differentiation complex (EDC) and inflammatory genes in both scalp regions. Conclusions These data suggest that MTF is effective in the treatment of both the frontal and vertex scalp of AGA patients. PMID:25204361

  16. An imputation approach for oligonucleotide microarrays.

    PubMed

    Li, Ming; Wen, Yalu; Lu, Qing; Fu, Wenjiang J

    2013-01-01

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

  17. Improvements to previous algorithms to predict gene structure and isoform concentrations using Affymetrix Exon arrays

    PubMed Central

    2010-01-01

    Background Exon arrays provide a way to measure the expression of different isoforms of genes in an organism. Most of the procedures to deal with these arrays are focused on gene expression or on exon expression. Although the only biological analytes that can be properly assigned a concentration are transcripts, there are very few algorithms that focus on them. The reason is that previously developed summarization methods do not work well if applied to transcripts. In addition, gene structure prediction, i.e., the correspondence between probes and novel isoforms, is a field which is still unexplored. Results We have modified and adapted a previous algorithm to take advantage of the special characteristics of the Affymetrix exon arrays. The structure and concentration of transcripts -some of them possibly unknown- in microarray experiments were predicted using this algorithm. Simulations showed that the suggested modifications improved both specificity (SP) and sensitivity (ST) of the predictions. The algorithm was also applied to different real datasets showing its effectiveness and the concordance with PCR validated results. Conclusions The proposed algorithm shows a substantial improvement in the performance over the previous version. This improvement is mainly due to the exploitation of the redundancy of the Affymetrix exon arrays. An R-Package of SPACE with the updated algorithms have been developed and is freely available. PMID:21110835

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

    PubMed Central

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

    2015-01-01

    Recurrent oral ulcer seriously threatens patients’ daily life and health. This study investigated potential genes and pathways that participate in the pathogenesis of recurrent oral ulcer by high throughput bioinformatic analysis. RT-PCR and Western blot were applied to further verify screened interleukins effect. Recurrent oral ulcer related genes were collected from websites and papers, and further found out from Human Genome 280 6.0 microarray data. Each pathway of recurrent oral ulcer related genes were got through chip hybridization. RT-PCR was applied to test four recurrent oral ulcer related genes to verify the microarray data. Data transformation, scatter plot, clustering analysis, and expression pattern analysis were used to analyze recurrent oral ulcer related gene expression changes. Recurrent oral ulcer gene microarray was successfully established. Microarray showed that 551 genes involved in recurrent oral ulcer activity and 196 genes were recurrent oral ulcer related genes. Of them, 76 genes up-regulated, 62 genes down-regulated, and 58 genes up-/down-regulated. Total expression level up-regulated 752 times (60%) and down-regulated 485 times (40%). IL-2 plays an important role in the occurrence, development and recurrence of recurrent oral ulcer on the mRNA and protein levels. Gene microarray can be used to analyze potential genes and pathways in recurrent oral ulcer. IL-2 may be involved in the pathogenesis of recurrent oral ulcer. PMID:26722428

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

    PubMed

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

    2015-01-01

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

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

    SciTech Connect

    Devi, Sachin S.; Mehendale, Harihara M. . E-mail: mehendale@ulm.edu

    2006-04-01

    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.

  1. Microarray analysis of bacterial diversity and distribution in aggregates from a desert agricultural soil

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The microbial community structure of inner and outer layer fractions of microaggregates from a desert agricultural soil were examined using low and high resolution methods employing PCR-DGGE and microarray analysis of 16S rRNA genes. Analysis of microbial community structures with PCR-DGGE, which d...

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

    PubMed Central

    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. PMID:26085952

  3. LS-CAP: an algorithm for identifying cytogenetic aberrations in hepatocellular carcinoma using microarray data.

    PubMed

    He, Xianmin; Wei, Qing; Sun, Meiqian; Fu, Xuping; Fan, Sichang; Li, Yao

    2006-05-01

    Biological techniques such as Array-Comparative genomic hybridization (CGH), fluorescent in situ hybridization (FISH) and affymetrix single nucleotide pleomorphism (SNP) array have been used to detect cytogenetic aberrations. However, on genomic scale, these techniques are labor intensive and time consuming. Comparative genomic microarray analysis (CGMA) has been used to identify cytogenetic changes in hepatocellular carcinoma (HCC) using gene expression microarray data. However, CGMA algorithm can not give precise localization of aberrations, fails to identify small cytogenetic changes, and exhibits false negatives and positives. Locally un-weighted smoothing cytogenetic aberrations prediction (LS-CAP) based on local smoothing and binomial distribution can be expected to address these problems. LS-CAP algorithm was built and used on HCC microarray profiles. Eighteen cytogenetic abnormalities were identified, among them 5 were reported previously, and 12 were proven by CGH studies. LS-CAP effectively reduced the false negatives and positives, and precisely located small fragments with cytogenetic aberrations.

  4. Protein Microarrays

    NASA Astrophysics Data System (ADS)

    Ricard-Blum, S.

    Proteins are key actors in the life of the cell, involved in many physiological and pathological processes. Since variations in the expression of messenger RNA are not systematically correlated with variations in the protein levels, the latter better reflect the way a cell functions. Protein microarrays thus supply complementary information to DNA chips. They are used in particular to analyse protein expression profiles, to detect proteins within complex biological media, and to study protein-protein interactions, which give information about the functions of those proteins [3-9]. They have the same advantages as DNA microarrays for high-throughput analysis, miniaturisation, and the possibility of automation. Section 18.1 gives a brief overview of proteins. Following this, Sect. 18.2 describes how protein microarrays can be made on flat supports, explaining how proteins can be produced and immobilised on a solid support, and discussing the different kinds of substrate and detection method. Section 18.3 discusses the particular format of protein microarrays in suspension. The diversity of protein microarrays and their applications are then reported in Sect. 18.4, with applications to therapeutics (protein-drug interactions) and diagnostics. The prospects for future developments of protein microarrays are then outlined in the conclusion. The bibliography provides an extensive list of reviews and detailed references for those readers who wish to go further in this area. Indeed, the aim of the present chapter is not to give an exhaustive or detailed analysis of the state of the art, but rather to provide the reader with the basic elements needed to understand how proteins are designed and used.

  5. Innovative instrumentation for microarray scanning and analysis: application for characterization of oligonucleotide duplexes behavior.

    PubMed

    Khomyakova, E B; Dreval, E V; Tran-Dang, M; Potier, M C; Soussaline, F P

    2004-05-01

    Accuracy in microarray technology requires new approaches to microarray reader development. A microarray reader system (optical scanning array or OSA reader) based on automated microscopy with large field of view, high speed 3 axis scanning at multiple narrow-band spectra of excitation light has been developed. It allows fast capture of high-resolution, multi-fluorescence images and is characterized by a linear dynamic range and sensitivity comparable to commonly used photo-multiplier tube (PMT)-based laser scanner. Controlled by high performance software, the instrument can be used for scanning and quantitative analysis of any type of dry microarray. Studies implying temperature-controlled hybridization chamber containing a microarray can also be performed. This enables the registration of kinetics and melting curves. This feature is required in a wide range of on-chip chemical and enzymatic reactions including on-chip PCR amplification. We used the OSA reader for the characterization of hybridization and melting behaviour of oligonucleotide:oligonucleotide duplexes on three-dimensional Code Link slides. PMID:15209342

  6. Microarray Analysis of Microbiota of Gingival Lesions in Noma Patients

    PubMed Central

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

    2013-01-01

    Noma (cancrum oris) is a gangrenous disease of unknown etiology affecting the maxillo-facial region of young children in extremely limited resource countries. In an attempt to better understand the microbiological events occurring during this disease, we used phylogenetic and low-density microarrays targeting the 16S rRNA gene to characterize the gingival flora of acute noma and acute necrotizing gingivitis (ANG) lesions, and compared them to healthy control subjects of the same geographical and social background. Our observations raise doubts about Fusobacterium necrophorum, a previously suspected causative agent of noma, as this species was not associated with noma lesions. Various oral pathogens were more abundant in noma lesions, notably Atopobium spp., Prevotella intermedia, Peptostreptococcus spp., Streptococcus pyogenes and Streptococcus anginosus. On the other hand, pathogens associated with periodontal diseases such as Aggregatibacter actinomycetemcomitans, Capnocytophaga spp., Porphyromonas spp. and Fusobacteriales were more abundant in healthy controls. Importantly, the overall loss of bacterial diversity observed in noma samples as well as its homology to that of ANG microbiota supports the hypothesis that ANG might be the immediate step preceding noma. PMID:24086784

  7. Evolutionary genomics of Salmonella: Gene acquisitions revealed by microarray analysis

    PubMed Central

    Porwollik, Steffen; Wong, Rita Mei-Yi; McClelland, Michael

    2002-01-01

    The presence of homologues of Salmonella enterica sv. Typhimurium LT2 genes was assessed in 22 other Salmonella including members of all seven subspecies and Salmonella bongori. Genomes were hybridized to a microarray of over 97% of the 4,596 annotated ORFs in the LT2 genome. A phylogenetic tree based on homologue content, relative to LT2, was largely concordant with previous studies using sequence information from several loci. Based on the topology of this tree, homologues of genes in LT2 acquired by various clades were predicted including 513 homologues acquired by the ancestor of all Salmonella, 111 acquired by S. enterica, 105 by diphasic Salmonella, and 216 by subspecies 1, most of which are of unknown function. Because this subspecies is responsible for almost all Salmonella infections of mammals and birds, these genes will be of particular interest for further mechanistic studies. Overall, a high level of gene gain, loss, or rapid divergence was predicted along all lineages. For example, at least 425 close homologues of LT2 genes may have been laterally transferred into Salmonella and then between Salmonella lineages. PMID:12072558

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

    PubMed

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

    2013-01-01

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

  9. Polypyrrole-peptide microarray for biomolecular interaction analysis by SPR imaging

    PubMed Central

    Villiers, Marie-Bernadette; Cortès, Sandra; Brakha, Carine; Marche, Patrice; Roget, André; Livache, Thierry

    2009-01-01

    Nowadays, high-throughput analysis of biological events is a great challenge which could take benefit of the recent development of microarray devices. The great potential of such technology is related to the availability of a chip bearing a large set of probes, stable and easy to obtain, and suitable for ligand binding detection. Here, we described a new method based on polypyrrole chemistry and allowing the covalent immobilization of peptides in a microarray format and on a gold surface compatible with the use of Surface Plasmon Resonance. This technique is then illustrated by the detection and characterization of antibodies induced by hepatitis C virus and present in patients’serums. PMID:19649603

  10. Quasi-confocal, multichannel parallel scan hyperspectral fluorescence imaging method optimized for analysis of multicolor microarrays.

    PubMed

    Liu, Zhiyi; Ma, Suihua; Ji, Yanhong; Liu, Le; Hu, Zhaoxu; Guo, Jihua; Ma, Hui; He, Yonghong

    2010-09-15

    The microarray technique, which can provide parallel detection with high throughput in biomedical research, has generated considerable interest since the end of the 20th century. A number of instruments have been reported for microarray detection. In this paper, we have developed a quasi-confocal, multichannel parallel scan hyperspectral fluorescence imaging system for multicolor microarray research. Hyperspectral imaging records the entire emission spectrum for every voxel within the imaged area in contrast to recording only fluorescence intensities of filter-based scanners. When coupled with data analysis, the recorded spectral information allows for quantitative identification of the contributions of multiple, spectrally overlapping fluorescent dyes and elimination of unwanted artifacts. This system is improved with a specifically designed, high performance spectrometer which can offer a spectral resolution of 0.2 nm and operates with spatial resolutions ranging from 2 to 30 μm. We demonstrate the application of the system by reading out arrays for identification of bacteria. PMID:20718427

  11. Microarray Meta-Analysis and Cross-Platform Normalization: Integrative Genomics for Robust Biomarker Discovery

    PubMed Central

    Walsh, Christopher J.; Hu, Pingzhao; Batt, Jane; Dos Santos, Claudia C.

    2015-01-01

    The diagnostic and prognostic potential of the vast quantity of publicly-available microarray data has driven the development of methods for integrating the data from different microarray platforms. Cross-platform integration, when appropriately implemented, has been shown to improve reproducibility and robustness of gene signature biomarkers. Microarray platform integration can be conceptually divided into approaches that perform early stage integration (cross-platform normalization) versus late stage data integration (meta-analysis). A growing number of statistical methods and associated software for platform integration are available to the user, however an understanding of their comparative performance and potential pitfalls is critical for best implementation. In this review we provide evidence-based, practical guidance to researchers performing cross-platform integration, particularly with an objective to discover biomarkers. PMID:27600230

  12. Microarray Meta-Analysis and Cross-Platform Normalization: Integrative Genomics for Robust Biomarker Discovery

    PubMed Central

    Walsh, Christopher J.; Hu, Pingzhao; Batt, Jane; Dos Santos, Claudia C.

    2015-01-01

    The diagnostic and prognostic potential of the vast quantity of publicly-available microarray data has driven the development of methods for integrating the data from different microarray platforms. Cross-platform integration, when appropriately implemented, has been shown to improve reproducibility and robustness of gene signature biomarkers. Microarray platform integration can be conceptually divided into approaches that perform early stage integration (cross-platform normalization) versus late stage data integration (meta-analysis). A growing number of statistical methods and associated software for platform integration are available to the user, however an understanding of their comparative performance and potential pitfalls is critical for best implementation. In this review we provide evidence-based, practical guidance to researchers performing cross-platform integration, particularly with an objective to discover biomarkers.

  13. Identification of key genes associated with cervical cancer by comprehensive analysis of transcriptome microarray and methylation microarray

    PubMed Central

    LIU, MING-YAN; ZHANG, HONG; HU, YUAN-JING; CHEN, YU-WEI; ZHAO, XIAO-NAN

    2016-01-01

    Cervical cancer is the second most commonly diagnosed type of cancer and the third leading cause of cancer-associated mortality in women. The current study aimed to determine the genes associated with cervical cancer development. Microarray data (GSE55940 and GSE46306) were downloaded from Gene Expression Omnibus. Overlapping genes between the differentially expressed genes (DEGs) in GSE55940 (identified by Limma package) and the differentially methylated genes were screened. Gene Ontology (GO) enrichment analysis was subsequently performed for these genes using the ToppGene database. In GSE55940, 91 downregulated and 151 upregulated DEGs were identified. In GSE46306, 561 overlapping differentially methylated genes were obtained through the differential methylation analysis at the CpG site level, CpG island level and gene level. A total of 5 overlapping genes [dipeptidyl peptidase 4 (DPP4); endothelin 3 (EDN3); fibroblast growth factor 14 (FGF14); tachykinin, precursor 1 (TAC1); and wingless-type MMTV integration site family, member 16 (WNT16)] between the 561 overlapping differentially methylated genes and the 242 DEGs were identified, which were downregulated and hypermethylated simultaneously in cervical cancer samples. Enriched GO terms were receptor binding (involving DPP4, EDN3, FGF14, TAC1 and WNT16), ameboidal-type cell migration (DPP4, EDN3 and TAC1), mitogen-activated protein kinase cascade (FGF14, EDN3 and WNT16) and cell proliferation (EDN3, WNT16, DPP4 and TAC1). These results indicate that DPP4, EDN3, FGF14, TAC1 and WNT16 may be involved in the pathogenesis of cervical cancer. PMID:27347167

  14. Fluorescence, XPS, and TOF-SIMS surface chemical state image analysis of DNA microarrays.

    PubMed

    Lee, Chi-Ying; Harbers, Gregory M; Grainger, David W; Gamble, Lara J; Castner, David G

    2007-08-01

    Performance improvements in DNA-modified surfaces required for microarray and biosensor applications rely on improved capabilities to accurately characterize the chemistry and structure of immobilized DNA molecules on micropatterned surfaces. Recent innovations in imaging X-ray photoelectron spectroscopy (XPS) and time-of-flight secondary ion mass spectrometry (TOF-SIMS) now permit more detailed studies of micropatterned surfaces. We have exploited the complementary information provided by imaging XPS and imaging TOF-SIMS to detail the chemical composition, spatial distribution, and hybridization efficiency of amine-terminated single-stranded DNA (ssDNA) bound to commercial polyacrylamide-based, amine-reactive microarray slides, immobilized in both macrospot and microarray diagnostic formats. Combinations of XPS imaging and small spot analysis were used to identify micropatterned DNA spots within printed DNA arrays on slide surfaces and quantify DNA elements within individual microarray spots for determination of probe immobilization and hybridization efficiencies. This represents the first report of imaging XPS of DNA immobilization and hybridization efficiencies for arrays fabricated on commercial microarray slides. Imaging TOF-SIMS provided distinct analytical data on the lateral distribution of DNA within single array microspots before and after target hybridization. Principal component analysis (PCA) applied to TOF-SIMS imaging datasets demonstrated that the combination of these two techniques provides information not readily observable in TOF-SIMS images alone, particularly in identifying species associated with array spot nonuniformities (e.g., "halo" or "donut" effects often observed in fluorescence images). Chemically specific spot images were compared to conventional fluorescence scanned images in microarrays to provide new information on spot-to-spot DNA variations that affect current diagnostic reliability, assay variance, and sensitivity.

  15. Introduction to the statistical analysis of two-color microarray data.

    PubMed

    Bremer, Martina; Himelblau, Edward; Madlung, Andreas

    2010-01-01

    Microarray experiments have become routine in the past few years in many fields of biology. Analysis of array hybridizations is often performed with the help of commercial software programs, which produce gene lists, graphs, and sometimes provide values for the statistical significance of the results. Exactly what is computed by many of the available programs is often not easy to reconstruct or may even be impossible to know for the end user. It is therefore not surprising that many biology students and some researchers using microarray data do not fully understand the nature of the underlying statistics used to arrive at the results.We have developed a module that we have used successfully in undergraduate biology and statistics education that allows students to get a better understanding of both the basic biological and statistical theory needed to comprehend primary microarray data. The module is intended for the undergraduate level but may be useful to anyone who is new to the field of microarray biology. Additional course material that was developed for classroom use can be found at http://www.polyploidy.org/ .In our undergraduate classrooms we encourage students to manipulate microarray data using Microsoft Excel to reinforce some of the concepts they learn. We have included instructions for some of these manipulations throughout this chapter (see the "Do this..." boxes). However, it should be noted that while Excel can effectively analyze our small sample data set, more specialized software would typically be used to analyze full microarray data sets. Nevertheless, we believe that manipulating a small data set with Excel can provide insights into the workings of more advanced analysis software. PMID:20652509

  16. Fluorescence, XPS, and TOF-SIMS surface chemical state image analysis of DNA microarrays.

    PubMed

    Lee, Chi-Ying; Harbers, Gregory M; Grainger, David W; Gamble, Lara J; Castner, David G

    2007-08-01

    Performance improvements in DNA-modified surfaces required for microarray and biosensor applications rely on improved capabilities to accurately characterize the chemistry and structure of immobilized DNA molecules on micropatterned surfaces. Recent innovations in imaging X-ray photoelectron spectroscopy (XPS) and time-of-flight secondary ion mass spectrometry (TOF-SIMS) now permit more detailed studies of micropatterned surfaces. We have exploited the complementary information provided by imaging XPS and imaging TOF-SIMS to detail the chemical composition, spatial distribution, and hybridization efficiency of amine-terminated single-stranded DNA (ssDNA) bound to commercial polyacrylamide-based, amine-reactive microarray slides, immobilized in both macrospot and microarray diagnostic formats. Combinations of XPS imaging and small spot analysis were used to identify micropatterned DNA spots within printed DNA arrays on slide surfaces and quantify DNA elements within individual microarray spots for determination of probe immobilization and hybridization efficiencies. This represents the first report of imaging XPS of DNA immobilization and hybridization efficiencies for arrays fabricated on commercial microarray slides. Imaging TOF-SIMS provided distinct analytical data on the lateral distribution of DNA within single array microspots before and after target hybridization. Principal component analysis (PCA) applied to TOF-SIMS imaging datasets demonstrated that the combination of these two techniques provides information not readily observable in TOF-SIMS images alone, particularly in identifying species associated with array spot nonuniformities (e.g., "halo" or "donut" effects often observed in fluorescence images). Chemically specific spot images were compared to conventional fluorescence scanned images in microarrays to provide new information on spot-to-spot DNA variations that affect current diagnostic reliability, assay variance, and sensitivity. PMID:17625851

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

    ERIC Educational Resources Information Center

    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…

  18. Parents' Perceptions of the Usefulness of Chromosomal Microarray Analysis for Children with Autism Spectrum Disorders

    ERIC Educational Resources Information Center

    Reiff, Marian; Giarelli, Ellen; Bernhardt, Barbara A.; Easley, Ebony; Spinner, Nancy B.; Sankar, Pamela L.; Mulchandani, Surabhi

    2015-01-01

    Clinical guidelines recommend chromosomal microarray analysis (CMA) for all children with autism spectrum disorders (ASDs). We explored the test's perceived usefulness among parents of children with ASD who had undergone CMA, and received a result categorized as pathogenic, variant of uncertain significance, or negative. Fifty-seven parents…

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

    ERIC Educational Resources Information Center

    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. Single nucleotide polymorphism-based microarray analysis for the diagnosis of hydatidiform moles

    PubMed Central

    XIE, YINGJUN; PEI, XIAOJUAN; DONG, YU; WU, HUIQUN; WU, JIANZHU; SHI, HUIJUAN; ZHUANG, XUYING; SUN, XIAOFANG; HE, JIALING

    2016-01-01

    In clinical diagnostics, single nucleotide polymorphism (SNP)-based microarray analysis enables the detection of copy number variations (CNVs), as well as copy number neutral regions, that are absent of heterozygosity throughout the genome. The aim of the present study was to evaluate the effectiveness and sensitivity of SNP-based microarray analysis in the diagnosis of hydatidiform mole (HM). By using whole-genome SNP microarray analysis, villous genotypes were detected, and the ploidy of villous tissue was determined to identify HMs. A total of 66 villous tissues and two twin tissues were assessed in the present study. Among these samples, 11 were triploid, one was tetraploid, 23 were abnormal aneuploidy, three were complete genome homozygosity, and the remaining ones were normal ploidy. The most noteworthy finding of the present study was the identification of six partial HMs and three complete HMs from those samples that were not identified as being HMs on the basis of the initial diagnosis of experienced obstetricians. This study has demonstrated that the application of an SNP-based microarray analysis was able to increase the sensitivity of diagnosis for HMs with partial and complete HMs, which makes the identification of these diseases at an early gestational age possible. PMID:27151252

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

    ERIC Educational Resources Information Center

    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…

  2. Multivariate curve resolution for hyperspectral image analysis :applications to microarray technology.

    SciTech Connect

    Van Benthem, Mark Hilary; Sinclair, Michael B.; Haaland, David Michael; Martinez, M. Juanita (University of New Mexico, Albuquerque, NM); Timlin, Jerilyn Ann; Werner-Washburne, Margaret C. (University of New Mexico, Albuquerque, NM); Aragon, Anthony D. (University of New Mexico, Albuquerque, NM)

    2003-01-01

    Multivariate curve resolution (MCR) using constrained alternating least squares algorithms represents a powerful analysis capability for a quantitative analysis of hyperspectral image data. We will demonstrate the application of MCR using data from a new hyperspectral fluorescence imaging microarray scanner for monitoring gene expression in cells from thousands of genes on the array. The new scanner collects the entire fluorescence spectrum from each pixel of the scanned microarray. Application of MCR with nonnegativity and equality constraints reveals several sources of undesired fluorescence that emit in the same wavelength range as the reporter fluorphores. MCR analysis of the hyperspectral images confirms that one of the sources of fluorescence is due to contaminant fluorescence under the printed DNA spots that is spot localized. Thus, traditional background subtraction methods used with data collected from the current commercial microarray scanners will lead to errors in determining the relative expression of low-expressed genes. With the new scanner and MCR analysis, we generate relative concentration maps of the background, impurity, and fluorescent labels over the entire image. Since the concentration maps of the fluorescent labels are relatively unaffected by the presence of background and impurity emissions, the accuracy and useful dynamic range of the gene expression data are both greatly improved over those obtained by commercial microarray scanners.

  3. MICROARRAY ANALYSIS OF DICHLOROACETIC ACID-INDUCED CHANGES IN GENE EXPRESSION

    EPA Science Inventory


    MICROARRAY ANALYSIS OF DICHLOROACETIC ACID-INDUCED CHANGES IN GENE EXPRESSION

    Dichloroacetic acid (DCA) is a major by-product of water disinfection by chlorination. Several studies have demonstrated the hepatocarcinogenicity of DCA in rodents when administered in dri...

  4. GPR-Analyzer: a simple tool for quantitative analysis of hierarchical multispecies microarrays.

    PubMed

    Dittami, Simon M; Edvardsen, Bente

    2013-10-01

    Monitoring of marine microalgae is important to predict and manage harmful algae blooms. It currently relies mainly on light-microscopic identification and enumeration of algal cells, yet several molecular tools are currently being developed to complement traditional methods. MIcroarray Detection of Toxic ALgae (MIDTAL) is an FP7-funded EU project aiming to establish a hierarchical multispecies microarray as one of these tools. Prototype arrays are currently being tested with field samples, yet the analysis of the large quantities of data generated by these arrays presents a challenge as suitable analysis tools or protocols are scarce. This paper proposes a two-part protocol for the analysis of the MIDTAL and other hierarchical multispecies arrays: Signal-to-noise ratios can be used to determine the presence or absence of signals and to identify potential false-positives considering parallel and hierarchical probes. In addition, normalized total signal intensities are recommended for comparisons between microarrays and in order to relate signals for specific probes to cell concentrations using external calibration curves. Hybridization- and probe-specific detection limits can be calculated to help evaluate negative results. The suggested analyses were implemented in "GPR-Analyzer", a platform-independent and graphical user interface-based application, enabling non-specialist users to quickly and quantitatively analyze hierarchical multispecies microarrays. It is available online at http://folk.uio.no/edvardse/gpranalyzer . PMID:22767354

  5. Application of Equilibrium Models of Solution Hybridization to Microarray Design and Analysis

    PubMed Central

    Gharaibeh, Raad Z.; Newton, Joshua M.; Weller, Jennifer W.; Gibas, Cynthia J.

    2010-01-01

    Background The probe percent bound value, calculated using multi-state equilibrium models of solution hybridization, is shown to be useful in understanding the hybridization behavior of microarray probes having 50 nucleotides, with and without mismatches. These longer oligonucleotides are in widespread use on microarrays, but there are few controlled studies of their interactions with mismatched targets compared to 25-mer based platforms. Principal Findings 50-mer oligonucleotides with centrally placed single, double and triple mismatches were spotted on an array. Over a range of target concentrations it was possible to discriminate binding to perfect matches and mismatches, and the type of mismatch could be predicted accurately in the concentration midrange (100 pM to 200 pM) using solution hybridization modeling methods. These results have implications for microarray design, optimization and analysis methods. Conclusions Our results highlight the importance of incorporating biophysical factors in both the design and the analysis of microarrays. Use of the probe “percent bound” value predicted by equilibrium models of hybridization is confirmed to be important for predicting and interpreting the behavior of long oligonucleotide arrays, as has been shown for short oligonucleotide arrays. PMID:20548788

  6. Tissue Microarrays.

    PubMed

    Dancau, Ana-Maria; Simon, Ronald; Mirlacher, Martina; Sauter, Guido

    2016-01-01

    Modern next-generation sequencing and microarray technologies allow for the simultaneous analysis of all human genes on the DNA, RNA, miRNA, and methylation RNA level. Studies using such techniques have lead to the identification of hundreds of genes with a potential role in cancer or other diseases. The validation of all of these candidate genes requires in situ analysis of high numbers of clinical tissues samples. The tissue microarray technology greatly facilitates such analysis. In this method minute tissue samples (typically 0.6 mm in diameter) from up to 1000 different tissues can be analyzed on one microscope glass slide. All in situ methods suitable for histological studies can be applied to TMAs without major changes of protocols, including immunohistochemistry, fluorescence in situ hybridization, or RNA in situ hybridization. Because all tissues are analyzed simultaneously with the same batch of reagents, TMA studies provide an unprecedented degree of standardization, speed, and cost efficiency.

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

    PubMed

    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.

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

    PubMed

    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. PMID:23748756

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

    PubMed Central

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

    2009-01-01

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

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

    PubMed Central

    2010-01-01

    Background 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. Results 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. Conclusion 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. PMID:20122245

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

    PubMed Central

    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

  12. A rapid automatic processing platform for bead label-assisted microarray analysis: application for genetic hearing-loss mutation detection.

    PubMed

    Zhu, Jiang; Song, Xiumei; Xiang, Guangxin; Feng, Zhengde; Guo, Hongju; Mei, Danyang; Zhang, Guohao; Wang, Dong; Mitchelson, Keith; Xing, Wanli; Cheng, Jing

    2014-04-01

    Molecular diagnostics using microarrays are increasingly being used in clinical diagnosis because of their high throughput, sensitivity, and accuracy. However, standard microarray processing takes several hours and involves manual steps during hybridization, slide clean up, and imaging. Here we describe the development of an integrated platform that automates these individual steps as well as significantly shortens the processing time and improves reproducibility. The platform integrates such key elements as a microfluidic chip, flow control system, temperature control system, imaging system, and automated analysis of clinical results. Bead labeling of microarray signals required a simple imaging system and allowed continuous monitoring of the microarray processing. To demonstrate utility, the automated platform was used to genotype hereditary hearing-loss gene mutations. Compared with conventional microarray processing procedures, the platform increases the efficiency and reproducibility of hybridization, speeding microarray processing through to result analysis. The platform also continuously monitors the microarray signals, which can be used to facilitate optimization of microarray processing conditions. In addition, the modular design of the platform lends itself to development of simultaneous processing of multiple microfluidic chips. We believe the novel features of the platform will benefit its use in clinical settings in which fast, low-complexity molecular genetic testing is required.

  13. Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories.

    PubMed

    Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

    2016-09-19

    Pre-processing of microarray data is a well-studied problem. Furthermore, all popular platforms come with their own recommended best practices for differential analysis of genes. However, for genome-scale network inference using microarray data collected from large public repositories, these methods filter out a considerable number of genes. This is primarily due to the effects of aggregating a diverse array of experiments with different technical and biological scenarios. Here we introduce a pre-processing pipeline suitable for inferring genome-scale gene networks from large microarray datasets. We show that partitioning of the available microarray datasets according to biological relevance into tissue- and process-specific categories significantly extends the limits of downstream network construction. We demonstrate the effectiveness of our pre-processing pipeline by inferring genome-scale networks for the model plant Arabidopsis thaliana using two different construction methods and a collection of 11,760 Affymetrix ATH1 microarray chips. Our pre-processing pipeline and the datasets used in this paper are made available at http://alurulab.cc.gatech.edu/microarray-pp.

  14. Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories

    PubMed Central

    Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

    2016-01-01

    Pre-processing of microarray data is a well-studied problem. Furthermore, all popular platforms come with their own recommended best practices for differential analysis of genes. However, for genome-scale network inference using microarray data collected from large public repositories, these methods filter out a considerable number of genes. This is primarily due to the effects of aggregating a diverse array of experiments with different technical and biological scenarios. Here we introduce a pre-processing pipeline suitable for inferring genome-scale gene networks from large microarray datasets. We show that partitioning of the available microarray datasets according to biological relevance into tissue- and process-specific categories significantly extends the limits of downstream network construction. We demonstrate the effectiveness of our pre-processing pipeline by inferring genome-scale networks for the model plant Arabidopsis thaliana using two different construction methods and a collection of 11,760 Affymetrix ATH1 microarray chips. Our pre-processing pipeline and the datasets used in this paper are made available at http://alurulab.cc.gatech.edu/microarray-pp. PMID:27657141

  15. Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories.

    PubMed

    Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

    2016-01-01

    Pre-processing of microarray data is a well-studied problem. Furthermore, all popular platforms come with their own recommended best practices for differential analysis of genes. However, for genome-scale network inference using microarray data collected from large public repositories, these methods filter out a considerable number of genes. This is primarily due to the effects of aggregating a diverse array of experiments with different technical and biological scenarios. Here we introduce a pre-processing pipeline suitable for inferring genome-scale gene networks from large microarray datasets. We show that partitioning of the available microarray datasets according to biological relevance into tissue- and process-specific categories significantly extends the limits of downstream network construction. We demonstrate the effectiveness of our pre-processing pipeline by inferring genome-scale networks for the model plant Arabidopsis thaliana using two different construction methods and a collection of 11,760 Affymetrix ATH1 microarray chips. Our pre-processing pipeline and the datasets used in this paper are made available at http://alurulab.cc.gatech.edu/microarray-pp. PMID:27657141

  16. Facilitating functional annotation of chicken microarray data

    PubMed Central

    2009-01-01

    Background Modeling results from chicken microarray studies is challenging for researchers due to little functional annotation associated with these arrays. The Affymetrix GenChip chicken genome array, one of the biggest arrays that serve as a key research tool for the study of chicken functional genomics, is among the few arrays that link gene products to Gene Ontology (GO). However the GO annotation data presented by Affymetrix is incomplete, for example, they do not show references linked to manually annotated functions. In addition, there is no tool that facilitates microarray researchers to directly retrieve functional annotations for their datasets from the annotated arrays. This costs researchers amount of time in searching multiple GO databases for functional information. Results We have improved the breadth of functional annotations of the gene products associated with probesets on the Affymetrix chicken genome array by 45% and the quality of annotation by 14%. We have also identified the most significant diseases and disorders, different types of genes, and known drug targets represented on Affymetrix chicken genome array. To facilitate functional annotation of other arrays and microarray experimental datasets we developed an Array GO Mapper (AGOM) tool to help researchers to quickly retrieve corresponding functional information for their dataset. Conclusion Results from this study will directly facilitate annotation of other chicken arrays and microarray experimental datasets. Researchers will be able to quickly model their microarray dataset into more reliable biological functional information by using AGOM tool. The disease, disorders, gene types and drug targets revealed in the study will allow researchers to learn more about how genes function in complex biological systems and may lead to new drug discovery and development of therapies. The GO annotation data generated will be available for public use via AgBase website and will be updated on regular

  17. Sequence-independent amplification coupled with DNA microarray analysis for detection and genotyping of noroviruses.

    PubMed

    Hu, Yuan; Yan, Huijun; Mammel, Mark; Chen, Haifeng

    2015-12-01

    Noroviruses (NoVs) have high levels of genetic sequence diversities, which lead to difficulties in designing robust universal primers to efficiently amplify specific viral genomes for molecular analysis. We here described the practicality of sequence-independent amplification combined with DNA microarray analysis for simultaneous detection and genotyping of human NoVs in fecal specimens. We showed that single primer isothermal linear amplification (Ribo-SPIA) of genogroup I (GI) and genogroup II (GII) NoVs could be run through the same amplification protocol without the need to design and use any virus-specific primers. Related virus could be subtyped by the unique pattern of hybridization with the amplified product to the microarray. By testing 22 clinical fecal specimens obtained from acute gastroenteritis cases as blinded samples, 2 were GI positive and 18 were GII positive as well as 2 negative for NoVs. A NoV GII positive specimen was also identified as having co-occurrence of hepatitis A virus. The study showed that there was 100 % concordance for positive NoV detection at genogroup level between the results of Ribo-SPIA/microarray and the phylogenetic analysis of viral sequences of the capsid gene. In addition, 85 % genotype agreement was observed for the new assay compared to the results of phylogenetic analysis. PMID:26556029

  18. Sequence-independent amplification coupled with DNA microarray analysis for detection and genotyping of noroviruses.

    PubMed

    Hu, Yuan; Yan, Huijun; Mammel, Mark; Chen, Haifeng

    2015-12-01

    Noroviruses (NoVs) have high levels of genetic sequence diversities, which lead to difficulties in designing robust universal primers to efficiently amplify specific viral genomes for molecular analysis. We here described the practicality of sequence-independent amplification combined with DNA microarray analysis for simultaneous detection and genotyping of human NoVs in fecal specimens. We showed that single primer isothermal linear amplification (Ribo-SPIA) of genogroup I (GI) and genogroup II (GII) NoVs could be run through the same amplification protocol without the need to design and use any virus-specific primers. Related virus could be subtyped by the unique pattern of hybridization with the amplified product to the microarray. By testing 22 clinical fecal specimens obtained from acute gastroenteritis cases as blinded samples, 2 were GI positive and 18 were GII positive as well as 2 negative for NoVs. A NoV GII positive specimen was also identified as having co-occurrence of hepatitis A virus. The study showed that there was 100 % concordance for positive NoV detection at genogroup level between the results of Ribo-SPIA/microarray and the phylogenetic analysis of viral sequences of the capsid gene. In addition, 85 % genotype agreement was observed for the new assay compared to the results of phylogenetic analysis.

  19. Gene expression analysis: teaching students to do 30,000 experiments at once with microarray.

    PubMed

    Carvalho, Felicia I; Johns, Christopher; Gillespie, Marc E

    2012-01-01

    Genome scale experiments routinely produce large data sets that require computational analysis, yet there are few student-based labs that illustrate the design and execution of these experiments. In order for students to understand and participate in the genomic world, teaching labs must be available where students generate and analyze large data sets. We present a microarray-based gene expression analysis experiment that is tailored for undergraduate students. The methods in this article describe an expression analysis experiment that can also be applied to CGH and SNP experiments. Factors such as technical difficulty, duration, cost, and availability of materials and equipments are considered in the lab design. The microarray teaching lab is performed in two sessions. The first is an introductory wet bench exercise that allows students to master the basic technical skills. The second builds on the concepts and skills with students acquiring and analyzing the microarray data. This lab exercise familiarizes students with large-scale data experiments and introduces them to the initial analysis steps.

  20. Microarray analysis of microRNA expression in mouse fetus at 13.5 and 14.5 days post-coitum in ear and back skin tissues.

    PubMed

    Torres, Leda; Juárez, Ulises; García, Laura; Miranda-Ríos, Juan; Frias, Sara

    2016-09-01

    There is no information regarding the role of microRNAs in the development of the external ear in mammals. The purpose of this study was to determine the stage-specific expression of microRNA during external ear development in mice under normal conditions. GeneChip miRNA 3.0 arrays by Affymetrix were used to obtain miRNA expression profiles from mice fetal pinnae and back skin tissues at 13.5 days-post-coitum (dpc) and 14.5 dpc. Biological triplicates for each tissue were analyzed; one litter represents one biological replica, each litter had 16 fetuses on average. The results were analyzed with Affymetrix's Transcriptome Analysis Console software to identify differentially expressed miRNAs. The inquiry showed significant differential expression of 25 miRNAs at 13.5 dpc and 31 at 14.5 dpc, some of these miRNAs were predicted to target genes implicated in external ear development. One example is mmu-miR-10a whose low expression in pinnae is known to impact ear development by modulating Hoxa1 mRNA levels Garzon et al. (2006), Gavalas et al. (1998) [1], [2]. Other findings like the upregulation of mmu-miR-200c and mmu-miR-205 in the pinnae tissues of healthy mice are in agreement with what has been reported in human patients with microtia, in which down regulation of both miRNAs has been found Li et al. (2013) [3]. This study uncovered a spatiotemporal pattern of miRNA expression in the external ear, which results from continuous transcriptional changes during normal development of body structures. All microarray data are available at the Gene Expression Omnibus (GEO) at NCBI under accession number GSE64945. PMID:27408816

  1. Microarray analysis of microRNA expression in mouse fetus at 13.5 and 14.5 days post-coitum in ear and back skin tissues.

    PubMed

    Torres, Leda; Juárez, Ulises; García, Laura; Miranda-Ríos, Juan; Frias, Sara

    2016-09-01

    There is no information regarding the role of microRNAs in the development of the external ear in mammals. The purpose of this study was to determine the stage-specific expression of microRNA during external ear development in mice under normal conditions. GeneChip miRNA 3.0 arrays by Affymetrix were used to obtain miRNA expression profiles from mice fetal pinnae and back skin tissues at 13.5 days-post-coitum (dpc) and 14.5 dpc. Biological triplicates for each tissue were analyzed; one litter represents one biological replica, each litter had 16 fetuses on average. The results were analyzed with Affymetrix's Transcriptome Analysis Console software to identify differentially expressed miRNAs. The inquiry showed significant differential expression of 25 miRNAs at 13.5 dpc and 31 at 14.5 dpc, some of these miRNAs were predicted to target genes implicated in external ear development. One example is mmu-miR-10a whose low expression in pinnae is known to impact ear development by modulating Hoxa1 mRNA levels Garzon et al. (2006), Gavalas et al. (1998) [1], [2]. Other findings like the upregulation of mmu-miR-200c and mmu-miR-205 in the pinnae tissues of healthy mice are in agreement with what has been reported in human patients with microtia, in which down regulation of both miRNAs has been found Li et al. (2013) [3]. This study uncovered a spatiotemporal pattern of miRNA expression in the external ear, which results from continuous transcriptional changes during normal development of body structures. All microarray data are available at the Gene Expression Omnibus (GEO) at NCBI under accession number GSE64945.

  2. Transcriptome analysis in Brassica rapa under the abiotic stresses using Brassica 24K oligo microarray.

    PubMed

    Lee, Sang-Choon; Lim, Myung-Ho; Kim, Jin A; Lee, Soo-In; Kim, Jung Sun; Jin, Mina; Kwon, Soo-Jin; Mun, Jeong-Hwan; Kim, Yeon-Ki; Kim, Hyun Uk; Hur, Yoonkang; Park, Beom-Seok

    2008-12-31

    Genome wide transcription analysis in response to stresses is essential to provide the basis of effective engineering strategies to improve stress tolerance in crop plants. In order to perform transcriptome analysis in Brassica rapa, we constructed a B. rapa oligo microarray, KBGP-24K, using sequence information from approximately 24,000 unigenes and analyzed cold (4 degrees C), salt (250 mM NaCl), and drought (air-dry) treated B. rapa plants. Among the B. rapa unigenes represented on the microarray, 417 (1.7%), 202 (0.8%), and 738 (3.1%) were identified as responsive genes that were differently expressed 5-fold or more at least once during a 48-h treatment with cold, salt, and drought, respectively. These results were confirmed by RT-PCR analysis. In the abiotic stress responsive genes identified, we found 56 transcription factor genes and 60 commonly responsive genes. It suggests that various transcriptional regulatory mechanisms and common signaling pathway are working together under the abiotic stresses in B. rapa. In conclusion, our new developed 24K oligo microarray will be a useful tool for transcriptome profiling and this work will provide valuable insight in the response to abiotic stress in B. rapa.

  3. Microarray analysis reveals altered circulating microRNA expression in mice infected with Coxsackievirus B3

    PubMed Central

    Sun, Chaoyu; Tong, Lei; Zhao, Wenran; Wang, Yan; Meng, Yuan; Lin, Lexun; Liu, Bingchen; Zhai, Yujia; Zhong, Zhaohua; Li, Xueqi

    2016-01-01

    Coxsackievirus B3 (CVB3) is a common causative agent in the development of inflammatory cardiomyopathy. However, whether the expression of peripheral blood microRNAs (miRNAs) is altered in this process is unknown. The present study investigated changes to miRNA expression in the peripheral blood of CVB3-infected mice. Utilizing miRNA microarray technology, differential miRNA expression was examined between normal and CVB3-infected mice. The present results suggest that specific miRNAs were differentially expressed in the peripheral blood of mice infected with CVB3, varying with infection duration. Using miRNA microarray analysis, a total of 96 and 89 differentially expressed miRNAs were identified in the peripheral blood of mice infected with CVB3 for 3 and 6 days, respectively. Quantitative polymerase chain reaction was used to validate differentially expressed miRNAs, revealing a consistency of these results with the miRNA microarray analysis results. The biological functions of the differentially expressed miRNAs were then predicted by bioinformatics analysis. The potential biological roles of differentially expressed miRNAs included hypertrophic cardiomyopathy, dilated cardiomyopathy and arrhythmogenic right ventricular cardiomyopathy. These results may provide important insights into the mechanisms responsible for the progression of CVB3 infection. PMID:27698715

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

    PubMed Central

    Butler, Merlin G.; Usrey, Kelly; Roberts, Jennifer L.; Schroeder, Stephen R.

    2014-01-01

    We report our experience with high resolution microarray analysis in infants and young children with developmental disability and/or aberrant behavior enrolled at the Centro Ann Sullivan del Peru in Lima, Peru, a low income country. Buccal cells were collected with cotton swabs from 233 participants for later DNA isolation and identification of copy number variation (deletions/duplications) and regions of homozygosity (ROH) for estimating consanguinity status in 15 infants and young children (12 males, 3 females; mean age ± SD = 28.1 m ±  7.9 m; age range 14 m–41 m) randomly selected for microarray analysis. An adequate DNA yield was found in about one-half of the enrolled participants. Ten participants showed deletions or duplications containing candidate genes reported to impact behavior or cognitive development. Five children had ROHs which could have harbored recessive gene alleles contributing to their clinical presentation. The coefficient of inbreeding was calculated and three participants showed first-second cousin relationships, indicating consanguinity. Our preliminary study showed that DNA isolated from buccal cells using cotton swabs was suboptimal, but yet in a subset of participants the yield was adequate for high resolution microarray analysis and several genes were found that impact development and behavior and ROHs identified to determine consanguinity status. PMID:25400949

  5. Microarray analysis reveals altered circulating microRNA expression in mice infected with Coxsackievirus B3

    PubMed Central

    Sun, Chaoyu; Tong, Lei; Zhao, Wenran; Wang, Yan; Meng, Yuan; Lin, Lexun; Liu, Bingchen; Zhai, Yujia; Zhong, Zhaohua; Li, Xueqi

    2016-01-01

    Coxsackievirus B3 (CVB3) is a common causative agent in the development of inflammatory cardiomyopathy. However, whether the expression of peripheral blood microRNAs (miRNAs) is altered in this process is unknown. The present study investigated changes to miRNA expression in the peripheral blood of CVB3-infected mice. Utilizing miRNA microarray technology, differential miRNA expression was examined between normal and CVB3-infected mice. The present results suggest that specific miRNAs were differentially expressed in the peripheral blood of mice infected with CVB3, varying with infection duration. Using miRNA microarray analysis, a total of 96 and 89 differentially expressed miRNAs were identified in the peripheral blood of mice infected with CVB3 for 3 and 6 days, respectively. Quantitative polymerase chain reaction was used to validate differentially expressed miRNAs, revealing a consistency of these results with the miRNA microarray analysis results. The biological functions of the differentially expressed miRNAs were then predicted by bioinformatics analysis. The potential biological roles of differentially expressed miRNAs included hypertrophic cardiomyopathy, dilated cardiomyopathy and arrhythmogenic right ventricular cardiomyopathy. These results may provide important insights into the mechanisms responsible for the progression of CVB3 infection.

  6. Microarray Analysis of the Abscission-Related Transcriptome in the Tomato Flower Abscission Zone in Response to Auxin Depletion1[C][W][OA

    PubMed Central

    Meir, Shimon; Philosoph-Hadas, Sonia; Sundaresan, Srivignesh; Selvaraj, K.S. Vijay; Burd, Shaul; Ophir, Ron; Kochanek, Bettina; Reid, Michael S.; Jiang, Cai-Zhong; Lers, Amnon

    2010-01-01

    The abscission process is initiated by changes in the auxin gradient across the abscission zone (AZ) and is triggered by ethylene. Although changes in gene expression have been correlated with the ethylene-mediated execution of abscission, there is almost no information on the molecular and biochemical basis of the increased AZ sensitivity to ethylene. We examined transcriptome changes in the tomato (Solanum lycopersicum ‘Shiran 1335’) flower AZ during the rapid acquisition of ethylene sensitivity following flower removal, which depletes the AZ from auxin, with or without preexposure to 1-methylcyclopropene or application of indole-3-acetic acid after flower removal. Microarray analysis using the Affymetrix Tomato GeneChip revealed changes in expression, occurring prior to and during pedicel abscission, of many genes with possible regulatory functions. They included a range of auxin- and ethylene-related transcription factors, other transcription factors and regulatory genes that are transiently induced early, 2 h after flower removal, and a set of novel AZ-specific genes. All gene expressions initiated by flower removal and leading to pedicel abscission were inhibited by indole-3-acetic acid application, while 1-methylcyclopropene pretreatment inhibited only the ethylene-induced expressions, including those induced by wound-associated ethylene signals. These results confirm our hypothesis that acquisition of ethylene sensitivity in the AZ is associated with altered expression of auxin-regulated genes resulting from auxin depletion. Our results shed light on the regulatory control of abscission at the molecular level and further expand our knowledge of auxin-ethylene cross talk during the initial controlling stages of the process. PMID:20947671

  7. Microarray Analysis Reveals Increased Transcriptional Repression and Reduced Metabolic Activity but Not Major Changes in the Core Apoptotic Machinery during Maturation of Sympathetic Neurons

    PubMed Central

    Raba, Mikk; Palgi, Jaan; Lehtivaara, Maria; Arumäe, Urmas

    2016-01-01

    Postnatal maturation of the neurons whose main phenotype and basic synaptic contacts are already established includes neuronal growth, refinement of synaptic contacts, final steps of differentiation, programmed cell death period (PCD) etc. In the sympathetic neurons, postnatal maturation includes permanent end of the PCD that occurs with the same time schedule in vivo and in vitro suggesting that the process could be genetically determined. Also many other changes in the neuronal maturation could be permanent and thus based on stable changes in the genome expression. However, postnatal maturation of the neurons is poorly studied. Here we compared the gene expression profiles of immature and mature sympathetic neurons using Affymetrix microarray assay. We found 1310 significantly up-regulated and 1151 significantly down-regulated genes in the mature neurons. Gene ontology analysis reveals up-regulation of genes related to neuronal differentiation, chromatin and epigenetic changes, extracellular factors and their receptors, and cell adhesion, whereas many down-regulated genes were related to metabolic and biosynthetic processes. We show that termination of PCD is not related to major changes in the expression of classical genes for apoptosis or cell survival. Our dataset is deposited to the ArrayExpress database and is a valuable source to select candidate genes in the studies of neuronal maturation. As an example, we studied the changes in the expression of selected genes Igf2bp3, Coro1A, Zfp57, Dcx, and Apaf1 in the young and mature sympathetic ganglia by quantitative PCR and show that these were strongly downregulated in the mature ganglia. PMID:27013977

  8. Microarray Analysis to Monitor Bacterial Cell Wall Homeostasis.

    PubMed

    Hong, Hee-Jeon; Hesketh, Andy

    2016-01-01

    Transcriptomics, the genome-wide analysis of gene transcription, has become an important tool for characterizing and understanding the signal transduction networks operating in bacteria. Here we describe a protocol for quantifying and interpreting changes in the transcriptome of Streptomyces coelicolor that take place in response to treatment with three antibiotics active against different stages of peptidoglycan biosynthesis. The results defined the transcriptional responses associated with cell envelope homeostasis including a generalized response to all three antibiotics involving activation of transcription of the cell envelope stress sigma factor σ(E), together with elements of the stringent response, and of the heat, osmotic, and oxidative stress regulons. Many antibiotic-specific transcriptional changes were identified, representing cellular processes potentially important for tolerance to each antibiotic. The principles behind the protocol are transferable to the study of cell envelope homeostatic mechanisms probed using alternative chemical/environmental insults or in other bacterial strains. PMID:27311662

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

    PubMed Central

    Dawson, Kevin; Rodriguez, Raymond L; Malyj, Wasyl

    2005-01-01

    Background Life processes are determined by the organism's genetic profile and multiple environmental variables. However the interaction between these factors is inherently non-linear [1]. Microarray data is one representation of the nonlinear interactions among genes and genes and environmental factors. Still most microarray studies use linear methods for the interpretation of nonlinear data. In this study, we apply Isomap, a nonlinear method of dimensionality reduction, to analyze three independent large Affymetrix high-density oligonucleotide microarray data sets. Results Isomap discovered low-dimensional structures embedded in the Affymetrix microarray data sets. These structures correspond to and help to interpret biological phenomena present in the data. This analysis provides examples of temporal, spatial, and functional processes revealed by the Isomap algorithm. In a spinal cord injury data set, Isomap discovers the three main modalities of the experiment – location and severity of the injury and the time elapsed after the injury. In a multiple tissue data set, Isomap discovers a low-dimensional structure that corresponds to anatomical locations of the source tissues. This model is capable of describing low- and high-resolution differences in the same model, such as kidney-vs.-brain and differences between the nuclei of the amygdala, respectively. In a high-throughput drug screening data set, Isomap discovers the monocytic and granulocytic differentiation of myeloid cells and maps several chemical compounds on the two-dimensional model. Conclusion Visualization of Isomap models provides useful tools for exploratory analysis of microarray data sets. In most instances, Isomap models explain more of the variance present in the microarray data than PCA or MDS. Finally, Isomap is a promising new algorithm for class discovery and class prediction in high-density oligonucleotide data sets. PMID:16076401

  10. Microarray analysis of gene expression in adult retinal ganglion cells.

    PubMed

    Ivanov, Dmitry; Dvoriantchikova, Galina; Nathanson, Lubov; McKinnon, Stuart J; Shestopalov, Valery I

    2006-01-01

    Retinal ganglion cells (RGCs) transfer visual information to the brain and are known to be susceptible to selective degeneration in various neuropathies such as glaucoma. This selective vulnerability suggests that these highly specialized neurons possess a distinct gene expression profile that becomes altered by neuropathy-associated stresses, which lead to the RGC death. In this study, to identify genes expressed predominantly in adult RGCs, a global transcriptional profile of purified primary RGCs has been compared to that of the whole retina. To avoid alterations of the original gene expression profile by cell culture conditions, we isolated RNA directly from adult RGCs purified by immunopanning without prior sub-cultivation. Genes expressed predominantly in RGCs included: Nrg1, Rgn, 14-3-3 family (Ywhah, Ywhaz, Ywhab), Nrn1, Gap43, Vsnl1, Rgs4. Some of these genes may serve as novel markers for these neurons. Our analysis revealed enrichment in genes controlling the pro-survival pathways in RGCs as compared to other retinal cells. PMID:16376886

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

    PubMed Central

    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

  12. Identification of Genes Expressed in Hyperpigmented Skin using Meta-Analysis of Microarray Datasets

    PubMed Central

    Yin, Lanlan; Coelho, Sergio G.; Valencia, Julio C.; Ebsen, Dominik; Mahns, Andre; Smuda, Christoph; Miller, Sharon A.; Beer, Janusz Z.; Kolbe, Ludger; Hearing, Vincent J.

    2015-01-01

    More than 375 genes have been identified that are involved in regulating skin pigmentation, and those act during development, survival, differentiation and/or responses of melanocytes to the environment. Many of those genes have been cloned and disruptions of their functions are associated with various pigmentary diseases, however many remain to be identified. We have performed a series of microarray analyses of hyperpigmented compared to less pigmented skin to identify genes responsible for those differences. The rationale and goal for this study was to perform a meta-analysis on those microarray databases to identify genes that may be significantly involved in regulating skin phenotype either directly or indirectly that might not have been identified due to subtle differences by any of those individual studies alone. The meta-analysis demonstrates that 1,271 probes representing 921 genes are differentially expressed at significant levels in the 5 microarray datasets compared, which provides new insights into the variety of genes involved in determining skin phenotype. Immunohistochemistry was used to validate 2 of those markers at the protein level (TRIM63 and QPCT) and we discuss the possible functions of those genes in regulating skin physiology. PMID:25950827

  13. Microarray analysis of differentially expressed genes engaged in fruit development between Prunus mume and Prunus armeniaca.

    PubMed

    Li, Xiaoying; Korir, Nicholas Kibet; Liu, Lili; Shangguan, Lingfei; Wang, Yuzhu; Han, Jian; Chen, Ming; Fang, Jinggui

    2012-11-15

    Microarray analysis is a technique that can be employed to provide expression profiles of single genes and new insights to elucidate the biological mechanisms responsible for fruit development. To evaluate expression of genes mostly engaged in fruit development between Prunus mume and Prunus armeniaca, we first identified differentially expressed transcripts along the entire fruit life cycle by using microarrays spotted with 10,641 ESTs collected from P. mume and other Prunus EST sequences. A total of 1418 ESTs were selected after quality control of microarray spots and analysis for differential gene expression patterns during fruit development of P. mume and P. Armeniaca. From these, 707 up-regulated and 711 down-regulated genes showing more than two-fold differences in expression level were annotated by GO based on biological processes, molecular functions and cellular components. These differentially expressed genes were found to be involved in several important pathways of carbohydrate, galactose, and starch and sucrose metabolism as well as in biosynthesis of other secondary metabolites via KEGG. This could provide detailed information on the fruit quality differences during development and ripening of these two species. With the results obtained, we provide a practical database for comprehensive understanding of molecular events during fruit development and also lay a theoretical foundation for the cloning of genes regulating in a series of important rate-limiting enzymes involved in vital metabolic pathways during fruit development.

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

    PubMed

    Hsu, Jessie J; Finkelstein, Dianne M; Schoenfeld, David A

    2015-01-01

    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. PMID:26562156

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

    PubMed Central

    Hsu, Jessie J.; Finkelstein, Dianne M.; Schoenfeld, David A.

    2015-01-01

    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. PMID:26562156

  16. ZODET: Software for the Identification, Analysis and Visualisation of Outlier Genes in Microarray Expression Data

    PubMed Central

    Roden, Daniel L.; Sewell, Gavin W.; Lobley, Anna; Levine, Adam P.; Smith, Andrew M.; Segal, Anthony W.

    2014-01-01

    Summary 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. Availability The software is freely available from http://www.ucl.ac.uk/medicine/molecular-medicine/publications/microarray-outlier-analysis. PMID:24416128

  17. Array painting: a protocol for the rapid analysis of aberrant chromosomes using DNA microarrays

    PubMed Central

    Gribble, Susan M; Ng, Bee Ling; Prigmore, Elena; Fitzgerald, Tomas; Carter, Nigel P

    2012-01-01

    Aarray painting is a technique that uses microarray technology to rapidly map chromosome translocation breakpoints. previous methods to map translocation breakpoints have used fluorescence in situ hybridization (FIsH) and have consequently been labor-intensive, time-consuming and restricted to the low breakpoint resolution imposed by the use of metaphase chromosomes. array painting combines the isolation of derivative chromosomes (chromosomes with translocations) and high-resolution microarray analysis to refine the genomic location of translocation breakpoints in a single experiment. In this protocol, we describe array painting by isolation of derivative chromosomes using a MoFlo flow sorter, amplification of these derivatives using whole-genome amplification and hybridization onto commercially available oligonucleotide microarrays. although the sorting of derivative chromosomes is a specialized procedure requiring sophisticated equipment, the amplification, labeling and hybridization of Dna is straightforward, robust and can be completed within 1 week. the protocol described produces good quality data; however, array painting is equally achievable using any combination of the available alternative methodologies for chromosome isolation, amplification and hybridization. PMID:19893508

  18. Hybridization of genomic DNA to microarrays: a challenge for the analysis of environmental samples.

    PubMed

    Avarre, Jean-Christophe; de Lajudie, Philippe; Béna, Gilles

    2007-05-01

    The use of DNA microarrays for detection and identification of bacteria and genes of interest from various environments (e.g. soil, sediment, water column...) is a major challenge for microbiologists working on functional diversity. So far, most of the genomic methods that have been described rely on the use of taxonomic markers (such as 16S rRNA) that can be easily amplified by PCR prior to hybridization on microarrays. However, taxonomical markers are not always informative on the functions present in these bacteria. Moreover, genes for which sequence database is limited or that lack any conserved regions will be difficult to amplify and thus to detect in unknown samples. Furthermore, PCR amplification often introduces biases that lead to inaccurate analysis of microbial communities. An alternative solution to overcome these strong limitations is to use genomic DNA (gDNA) as target for hybridisation, without prior PCR amplification. Though hybridization of gDNA is already used for comparative genome hybridization or sequencing by hybridization, yet to the high cost of tiling strategies and important data filtering, its adaptation for use in environmental research poses great challenges in terms of specificity, sensitivity and reproducibility of hybridization. Considering the very faint number of publications that have described hybridization of gDNA to microarrays for environmental applications, we confront in this review the different approaches that have been developed so far, and propose alternative strategies that may contribute to improve the development of microarrays for studying the microbial genetic structure and composition of samples of high environmental and ecological value.

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

    PubMed Central

    Zhao, Peng; Hu, Wei; Wang, Hongyun; Yu, Shengyuan; Li, Chuzhong; Bai, Jiwei; Gui, Songbai; Zhang, Yazhuo

    2015-01-01

    Pituitary adenomas, monoclonal in origin, are the most common intracranial neoplasms. Altered gene expression as well as somatic mutations is detected frequently in pituitary adenomas. The purpose of this study was to detect differentially expressed genes (DEGs) and biological processes during tumor formation of pituitary adenomas. We performed an integrated analysis of publicly available GEO datasets of pituitary adenomas to identify DEGs between pituitary adenomas and normal control (NC) tissues. Gene function analysis including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and protein-protein interaction (PPI) networks analysis was conducted to interpret the biological role of those DEGs. In this study we detected 3994 DEGs (2043 upregulated and 1951 downregulated) in pituitary adenoma through an integrated analysis of 5 different microarray datasets. Gene function analysis revealed that the functions of those DEGs were highly correlated with the development of pituitary adenoma. This integrated analysis of microarray data identified some genes and pathways associated with pituitary adenoma, which may help to understand the pathology underlying pituitary adenoma and contribute to the successful identification of therapeutic targets for pituitary adenoma. PMID:25642247

  20. Krylov subspace algorithms for computing GeneRank for the analysis of microarray data mining.

    PubMed

    Wu, Gang; Zhang, Ying; Wei, Yimin

    2010-04-01

    GeneRank is a new engine technology for the analysis of microarray experiments. It combines gene expression information with a network structure derived from gene notations or expression profile correlations. Using matrix decomposition techniques, we first give a matrix analysis of the GeneRank model. We reformulate the GeneRank vector as a linear combination of three parts in the general case when the matrix in question is non-diagonalizable. We then propose two Krylov subspace methods for computing GeneRank. Numerical experiments show that, when the GeneRank problem is very large, the new algorithms are appropriate choices. PMID:20426695

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

    PubMed

    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

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

    PubMed

    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. PMID:24312246

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

    PubMed Central

    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

  4. Microarrays in hematology.

    PubMed

    Walker, Josef; Flower, Darren; Rigley, Kevin

    2002-01-01

    Microarrays are fast becoming routine tools for the high-throughput analysis of gene expression in a wide range of biologic systems, including hematology. Although a number of approaches can be taken when implementing microarray-based studies, all are capable of providing important insights into biologic function. Although some technical issues have not been resolved, microarrays will continue to make a significant impact on hematologically important research. PMID:11753074

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

    PubMed Central

    2011-01-01

    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. Comparative analyses with

  6. Routine Chromosomal Microarray Analysis is Necessary in Korean Patients With Unexplained Developmental Delay/Mental Retardation/Autism Spectrum Disorder

    PubMed Central

    Shin, Saeam; Yu, Nae; Choi, Jong Rak; Jeong, Seri

    2015-01-01

    Background All over the world, chromosomal microarray (CMA) is now the first tier diagnostic assay for genetic testing to evaluate developmental delay (DD), mental retardation (MR), and autism spectrum disorder (ASD) with unknown etiology. The average diagnostic yield of the CMA test is known to be about 12.2%, while that of conventional G-banding karyotype is below 3%. This study aimed to assess the usefulness of CMA for the purpose of clinical diagnostic testing in the Korean population. Methods We performed CMA and multiplex ligation-dependent probe amplification (MLPA) tests in 96 patients with normal karyotype and unexplained DD, MR, or ASD. The CMA was conducted with CytoScan 750K array (Affymetrix, USA) with an average resolution of 100 kb. Results Pathogenic copy number variations (CNVs) were detected in 15 patients by CMA and in two patients by MLPA for four known microdeletion syndromes (Prader-Willi/Angelman syndrome, DiGeorge syndrome, Miller-Dieker syndrome and Williams syndrome) designated by National Health Insurance system in Korea. The diagnostic yield was 15.6% and 2.1%, respectively. Thirteen (13.5%) patients (excluding cases with pathogenic CNVs) had variants of uncertain clinical significance. There was one patient with a 17.1-megabase (Mb) region of homozygosity on chromosome 4q. Conclusions Our findings suggest the necessity of CMA as a routine diagnostic test for unexplained DD, MR, and ASD in Korea. PMID:26206688

  7. Image analysis and data normalization procedures are crucial for microarray analyses.

    PubMed

    Kadanga, Ali Kpatcha; Leroux, Christine; Bonnet, Muriel; Chauvet, Stéphanie; Meunier, Bruno; Cassar-Malek, Isabelle; Hocquette, Jean-François

    2008-03-17

    This study was conducted with the aim of optimizing the experimental design of array experiments. We compared two image analysis and normalization procedures prior to data analysis using two experimental designs. For this, RNA samples from Charolais steers Longissimus thoracis muscle and subcutaneous adipose tissues were labeled and hybridized to a bovine 8,400 oligochip either in triplicate or in a dye-swap design. Image analysis and normalization were processed by either GenePix/MadScan or ImaGene/GeneSight. Statistical data analysis was then run using either the SAM method or a Student's t-test using a multiple test correction run on R 2.1 software. Our results show that image analysis and normalization procedure had an impact whereas the statistical methods much less influenced the outcome of differentially expressed genes. Image analysis and data normalization are thus an important aspect of microarray experiments, having a potentially significant impact on downstream analyses such as the identification of differentially expressed genes. This study provides indications on the choice of raw data preprocessing in microarray technology.

  8. Image Analysis and Data Normalization Procedures are Crucial for Microarray Analyses

    PubMed Central

    Kadanga, Ali Kpatcha; Leroux, Christine; Bonnet, Muriel; Chauvet, Stéphanie; Meunier, Bruno; Cassar-Malek, Isabelle; Hocquette, Jean-François

    2008-01-01

    This study was conducted with the aim of optimizing the experimental design of array experiments. We compared two image analysis and normalization procedures prior to data analysis using two experimental designs. For this, RNA samples from Charolais steers Longissimus thoracis muscle and subcutaneous adipose tissues were labeled and hybridized to a bovine 8,400 oligochip either in triplicate or in a dye-swap design. Image analysis and normalization were processed by either GenePix/MadScan or ImaGene/GeneSight. Statistical data analysis was then run using either the SAM method or a Student’s t-test using a multiple test correction run on R 2.1 software. Our results show that image analysis and normalization procedure had an impact whereas the statistical methods much less influenced the outcome of differentially expressed genes. Image analysis and data normalization are thus an important aspect of microarray experiments, having a potentially significant impact on downstream analyses such as the identification of differentially expressed genes. This study provides indications on the choice of raw data preprocessing in microarray technology. PMID:19787079

  9. Global Expression Patterns of Three Festuca Species Exposed to Different Doses of Glyphosate Using the Affymetrix GeneChip Wheat Genome Array.

    PubMed

    Cebeci, Ozge; Budak, Hikmet

    2009-01-01

    Glyphosate has been shown to act as an inhibitor of an aromatic amino acid biosynthetic pathway, while other pathways that may be affected by glyphosate are not known. Cross species hybridizations can provide a tool for elucidating biological pathways conserved among organisms. Comparative genome analyses have indicated a high level of colinearity among grass species and Festuca, on which we focus here, and showed rearrangements common to the Pooideae family. Based on sequence conservation among grass species, we selected the Affymetrix GeneChip Wheat Genome Array as a tool for the analysis of expression profiles of three Festuca (fescue) species with distinctly different tolerances to varying levels of glyphosate. Differences in transcript expression were recorded upon foliar glyphosate application at 1.58 mM and 6.32 mM, representing 5% and 20%, respectively, of the recommended rate. Differences highlighted categories of general metabolic processes, such as photosynthesis, protein synthesis, stress responses, and a larger number of transcripts responded to 20% glyphosate application. Differential expression of genes encoding proteins involved in the shikimic acid pathway could not be identified by cross hybridization. Microarray data were confirmed by RT-PCR and qRT-PCR analyses. This is the first report to analyze the potential of cross species hybridization in Fescue species and the data and analyses will help extend our knowledge on the cellular processes affected by glyphosate.

  10. A Microarray Analysis for Differential Gene Expression in the Soybean Genome Using Bioconductor and R

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This paper describes specific procedures for conducting quality assessment of Affymetrix GeneChip® soybean genome data and performing analyses to determine differential gene expression using the open-source R language and environment in conjunction with the open-source Bioconductor package. Procedu...

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

    PubMed

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

    2016-04-01

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

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

    PubMed

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

    2016-04-01

    Microarray-based gene expression profiling has emerged as an efficient technique for classification, prognosis, diagnosis, and treatment of cancer. Frequent changes in the behavior of this disease generates an enormous volume of data. Microarray data satisfies both the veracity and velocity properties of big data, as it keeps changing with time. Therefore, the analysis of microarray datasets in a small amount of time is essential. They often contain a large amount of expression, but only a fraction of it comprises genes that are significantly expressed. The precise identification of genes of interest that are responsible for causing cancer are imperative in microarray data analysis. Most existing schemes employ a two-phase process such as feature selection/extraction followed by classification. In this paper, various statistical methods (tests) based on MapReduce are proposed for selecting relevant features. After feature selection, a MapReduce-based K-nearest neighbor (mrKNN) classifier is also employed to classify microarray data. These algorithms are successfully implemented in a Hadoop framework. A comparative analysis is done on these MapReduce-based models using microarray datasets of various dimensions. From the obtained results, it is observed that these models consume much less execution time than conventional models in processing big data. PMID:26975600

  13. Web-based tissue microarray image data analysis: initial validation testing through prostate cancer Gleason grading.

    PubMed

    Bova, G S; Parmigiani, G; Epstein, J I; Wheeler, T; Mucci, N R; Rubin, M A

    2001-04-01

    Tissue microarray technology promises to enhance tissue-based molecular research by allowing improved conservation of tissue resources and experimental reagents, improved internal experimental control, and increased sample numbers per experiment. Organized, well-validated collection and analysis of the voluminous image data produced by tissue microarray technology is critical to maximize its value. Web-based technology for visual analysis and searchable storage of microarray image data could provide optimal flexibility for research groups in meeting this goal, but this approach has not been examined scientifically. Toward this goal, a prostate tissue microarray block containing 432 tissue cores (0.6 mm diameter) was constructed. Moderately compressed (200 kb).jpg images of each tissue spot were acquired and were saved using a naming convention developed by the SPORE Prostate Tissue Microarray Collaborative Group. Four hundred three tissue array spot images were uploaded into a database developed for this study and were converted to.fpx format to decrease Internet transmission times for high-resolution image data. In phase I of the image analysis portion of the study, testing and preliminary analysis of the Web technology was performed by 2 pathologists (M.A.R. and G.S.B.). In phase II, 2 pathologists (J.I.E. and T.M.W.) with no previous exposure to this technology and no knowledge of the structure of the study were presented a set of 130 sequential tissue spot images via the Web on their office computers. In phase III, the same pathologists were presented a set of 193 images, including all 130 from phase II and 63 others, with image presentation order randomized. With each zoomable tissue spot image, each pathologist was presented with a nested set of questions regarding overall interpretability of the image, presence or absence of cancer, and predominant and second most frequent Gleason grade. In phases II and III of the study, 319 of 323 (99%) image presentations

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

    NASA Astrophysics Data System (ADS)

    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.

  15. Study on the antiendotoxin action of Pulsatillae Decoction using an Affymetrix rat genome array.

    PubMed

    Hu, Yiyi; Chen, Xi; Lin, Hong; Hu, Yuanliang; Mu, Xiang

    2009-01-01

    A high-throughput and efficient Affymetrix rat genome array was used to investigate the pharmacological mechanism of the traditional Chinese medicine, Pulsatillae Decoction (PD), used for the treatment of diseases induced by lipopolysaccharide (LPS). Rat intestinal microvascular endothelial cells (RIMECs) were challenged with 1mug/ml LPS for 3h, and then treated with PD at a concentration of 1mg/ml for 24h. Total RNA from each treatment group was extracted from cultured RIMECs for detection by the Affymetrix Rat Genome 230 2.0 Array. The results showed that 36 genes were upregulated and 33 genes were downregulated in the LPS group vs. the blank control group; 566 genes were upregulated and 12 genes were downregulated in the PD-treated group vs. the LPS group; and 93 genes were upregulated and 29 genes were downregulated in the PD-treated group vs. the blank control group. The analysis of these data suggested that PD specifically and effectively reduce damage induced by LPS, and improved physiological and biochemical responses to counteract the effects of LPS.

  16. ACNE: a summarization method to estimate allele-specific copy numbers for Affymetrix SNP arrays

    PubMed Central

    Ortiz-Estevez, Maria; Bengtsson, Henrik; Rubio, Angel

    2010-01-01

    Motivation: Current algorithms for estimating DNA copy numbers (CNs) borrow concepts from gene expression analysis methods. However, single nucleotide polymorphism (SNP) arrays have special characteristics that, if taken into account, can improve the overall performance. For example, cross hybridization between alleles occurs in SNP probe pairs. In addition, most of the current CN methods are focused on total CNs, while it has been shown that allele-specific CNs are of paramount importance for some studies. Therefore, we have developed a summarization method that estimates high-quality allele-specific CNs. Results: The proposed method estimates the allele-specific DNA CNs for all Affymetrix SNP arrays dealing directly with the cross hybridization between probes within SNP probesets. This algorithm outperforms (or at least it performs as well as) other state-of-the-art algorithms for computing DNA CNs. It better discerns an aberration from a normal state and it also gives more precise allele-specific CNs. Availability: The method is available in the open-source R package ACNE, which also includes an add on to the aroma.affymetrix framework (http://www.aroma-project.org/). Contact: arubio@ceit.es Supplementaruy information: Supplementary data are available at Bioinformatics online. PMID:20529889

  17. High-Throughput Analysis of Serum Antigens Using Sandwich ELISAs on Microarrays

    SciTech Connect

    Servoss, Shannon; Gonzalez, Rachel M.; Varnum, Susan M.; Zangar, Richard C.

    2009-05-11

    Enzyme-linked immunosorbent assay (ELISA) microarrays promise to be a powerful tool for the detection and validation of disease biomarkers. ELISA microarrays are capable of simultaneous detection of many proteins using a small sample volume. Although there are many potential pitfalls to the use of ELISA microarrays, these can be avoided by careful planning of experiments. In this chapter we describe a high-throughput protocol for processing ELISA microarrays that will result in reliable and reproducible data.

  18. Increasing the Number of Thyroid Lesions Classes in Microarray Analysis Improves the Relevance of Diagnostic Markers

    PubMed Central

    Fontaine, Jean-Fred; Mirebeau-Prunier, Delphine; Raharijaona, Mahatsangy; Franc, Brigitte; Triau, Stephane; Rodien, Patrice; Goëau-Brissonniére, Olivier; Karayan-Tapon, Lucie; Mello, Marielle; Houlgatte, Rémi; Malthiery, Yves; Savagner, Frédérique

    2009-01-01

    Background Genetic markers for thyroid cancers identified by microarray analysis have offered limited predictive accuracy so far because of the few classes of thyroid lesions usually taken into account. To improve diagnostic relevance, we have simultaneously analyzed microarray data from six public datasets covering a total of 347 thyroid tissue samples representing 12 histological classes of follicular lesions and normal thyroid tissue. Our own dataset, containing about half the thyroid tissue samples, included all categories of thyroid lesions. Methodology/Principal Findings Classifier predictions were strongly affected by similarities between classes and by the number of classes in the training sets. In each dataset, sample prediction was improved by separating the samples into three groups according to class similarities. The cross-validation of differential genes revealed four clusters with functional enrichments. The analysis of six of these genes (APOD, APOE, CLGN, CRABP1, SDHA and TIMP1) in 49 new samples showed consistent gene and protein profiles with the class similarities observed. Focusing on four subclasses of follicular tumor, we explored the diagnostic potential of 12 selected markers (CASP10, CDH16, CLGN, CRABP1, HMGB2, ALPL2, ADAMTS2, CABIN1, ALDH1A3, USP13, NR2F2, KRTHB5) by real-time quantitative RT-PCR on 32 other new samples. The gene expression profiles of follicular tumors were examined with reference to the mutational status of the Pax8-PPARγ, TSHR, GNAS and NRAS genes. Conclusion/Significance We show that diagnostic tools defined on the basis of microarray data are more relevant when a large number of samples and tissue classes are used. Taking into account the relationships between the thyroid tumor pathologies, together with the main biological functions and pathways involved, improved the diagnostic accuracy of the samples. Our approach was particularly relevant for the classification of microfollicular adenomas. PMID:19893615

  19. Analysis of hypertrophic and normal scar gene expression with cDNA microarrays.

    PubMed

    Tsou, R; Cole, J K; Nathens, A B; Isik, F F; Heimbach, D M; Engrav, L H; Gibran, N S

    2000-01-01

    Hypertrophic scar is one form of abnormal wound healing. Previous studies have suggested that hypertrophic scar formation results from altered gene expression of extracellular matrix molecules. A broadscale evaluation of gene expression in hypertrophic scars has not been reported. To better understand abnormalities in hypertrophic scar gene expression, we compared messenger RNA expression in hypertrophic scars, normal scars, and uninjured skin with the use of complementary (c)DNA microarrays. Total RNA was extracted from freshly excised human hypertrophic scars, normal scars, or uninjured skin and reverse transcribed into cDNA with the incorporation of [33P] deoxycytidine triphosphate. The resulting radioactive cDNA probes were hybridized onto cDNA microarrays of 4000 genes. Hybridization signals were normalized and analyzed. In the comparison of tissue samples, mean intensities were calculated for each gene within each group (hypertrophic scars, normal scars, and uninjured skin). Ratios of the mean intensities of hypertrophic scars to normal scars, hypertrophic scars to uninjured skin, and normal scars to uninjured skin were generated. A ratio that was greater than 1 indicated upregulation of any particular gene and a ratio that was less than 1 indicated downregulation of any particular gene. Our data indicated that 142 genes were overexpressed and 50 genes were underexpressed in normal scars compared with uninjured skin, 107 genes were overexpressed and 71 were underexpressed in hypertrophic scars compared with uninjured skin, and 44 genes were overexpressed and 124 were underexpressed in hypertrophic scars compared with normal scars. Our analysis of collagen, growth factor, and metalloproteinase gene expression confirmed that our molecular data were consistent with published biochemical and clinical observations of normal scars and hypertrophic scars. cDNA microarray analysis provides a powerful tool for the investigation of differential gene expression in

  20. Concordance between RNA-sequencing data and DNA microarray data in transcriptome analysis of proliferative and quiescent fibroblasts.

    PubMed

    Trost, Brett; Moir, Catherine A; Gillespie, Zoe E; Kusalik, Anthony; Mitchell, Jennifer A; Eskiw, Christopher H

    2015-09-01

    DNA microarrays and RNA sequencing (RNA-seq) are major technologies for performing high-throughput analysis of transcript abundance. Recently, concerns have been raised regarding the concordance of data derived from the two techniques. Using cDNA libraries derived from normal human foreskin fibroblasts, we measured changes in transcript abundance as cells transitioned from proliferative growth to quiescence using both DNA microarrays and RNA-seq. The internal reproducibility of the RNA-seq data was greater than that of the microarray data. Correlations between the RNA-seq data and the individual microarrays were low, but correlations between the RNA-seq values and the geometric mean of the microarray values were moderate. The two technologies had good agreement when considering probes with the largest (both positive and negative) fold change (FC) values. An independent technique, quantitative reverse-transcription PCR (qRT-PCR), was used to measure the FC of 76 genes between proliferative and quiescent samples, and a higher correlation was observed between the qRT-PCR data and the RNA-seq data than between the qRT-PCR data and the microarray data.

  1. A new 12-gene diagnostic biomarker signature of melanoma revealed by integrated microarray analysis

    PubMed Central

    Liu, Wanting

    2013-01-01

    Genome-wide microarray technology has facilitated the systematic discovery of diagnostic biomarkers of cancers and other pathologies. However, meta-analyses of published arrays often uncover significant inconsistencies that hinder advances in clinical practice. Here we present an integrated microarray analysis framework, based on a genome-wide relative significance (GWRS) and genome-wide global significance (GWGS) model. When applied to five microarray datasets on melanoma published between 2000 and 2011, this method revealed a new signature of 200 genes. When these were linked to so-called ‘melanoma driver’ genes involved in MAPK, Ca2+, and WNT signaling pathways we were able to produce a new 12-gene diagnostic biomarker signature for melanoma (i.e., EGFR, FGFR2, FGFR3, IL8, PTPRF, TNC, CXCL13, COL11A1, CHP2, SHC4, PPP2R2C, and WNT4). We have begun to experimentally validate a subset of these genes involved in MAPK signaling at the protein level, including CXCL13, COL11A1, PTPRF and SHC4 and found these to be over-expressed in metastatic and primary melanoma cells in vitro and in situ compared to melanocytes cultured from healthy skin epidermis and normal healthy human skin. While SHC4 has been reported previously to be associated to melanoma, this is the first time CXCL13, COL11A1, and PTPRF have been associated with melanoma on experimental validation. Our computational evaluation indicates that this 12-gene biomarker signature achieves excellent diagnostic power in distinguishing metastatic melanoma from normal skin and benign nevus. Further experimental validation of the role of these 12 genes in a new signaling network may provide new insights into the underlying biological mechanisms driving the progression of melanoma. PMID:23638386

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

    PubMed

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

    2012-01-01

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

  3. Time-Frequency Analysis of Peptide Microarray Data: Application to Brain Cancer Immunosignatures

    PubMed Central

    O’Donnell, Brian; Maurer, Alexander; Papandreou-Suppappola, Antonia; Stafford, Phillip

    2015-01-01

    One of the gravest dangers facing cancer patients is an extended symptom-free lull between tumor initiation and the first diagnosis. Detection of tumors is critical for effective intervention. Using the body’s immune system to detect and amplify tumor-specific signals may enable detection of cancer using an inexpensive immunoassay. Immunosignatures are one such assay: they provide a map of antibody interactions with random-sequence peptides. They enable detection of disease-specific patterns using classic train/test methods. However, to date, very little effort has gone into extracting information from the sequence of peptides that interact with disease-specific antibodies. Because it is difficult to represent all possible antigen peptides in a microarray format, we chose to synthesize only 330,000 peptides on a single immunosignature microarray. The 330,000 random-sequence peptides on the microarray represent 83% of all tetramers and 27% of all pentamers, creating an unbiased but substantial gap in the coverage of total sequence space. We therefore chose to examine many relatively short motifs from these random-sequence peptides. Time-variant analysis of recurrent subsequences provided a means to dissect amino acid sequences from the peptides while simultaneously retaining the antibody–peptide binding intensities. We first used a simple experiment in which monoclonal antibodies with known linear epitopes were exposed to these random-sequence peptides, and their binding intensities were used to create our algorithm. We then demonstrated the performance of the proposed algorithm by examining immunosignatures from patients with Glioblastoma multiformae (GBM), an aggressive form of brain cancer. Eight different frameshift targets were identified from the random-sequence peptides using this technique. If immune-reactive antigens can be identified using a relatively simple immune assay, it might enable a diagnostic test with sufficient sensitivity to detect tumors

  4. Focused microarray analysis of peripheral mononuclear blood cells from Churg-Strauss syndrome patients.

    PubMed

    Tougan, Takahiro; Onda, Hiroaki; Okuzaki, Daisuke; Kobayashi, Shigeto; Hashimoto, Hiroshi; Nojima, Hiroshi

    2008-04-30

    DNA diagnostics are useful but are hampered by difficult ethical issues. Moreover, it cannot provide enough information on the environmental factors that are important for pathogenesis of certain diseases. However, this is not a problem for RNA diagnostics, which evaluate the expression of the gene in question. We here report a novel RNA diagnostics tool that can be employed with peripheral blood mononuclear cells (PBMCs). To establish this tool, we identified 290 genes that are highly expressed in normal PBMCs but not in TIG-1, a normal human fibroblast cell. These genes were entitled PREP after predominantly expressed in PBMC and included 50 uncharacterized genes. We then conducted PREP gene-focused microarray analysis on PBMCs from seven cases of Churg-Strauss syndrome (CSS), which is a small-vessel necrotizing vasculitis. We found that PREP135 (coactosin-like protein), PREP77 (prosaposin), PREP191 (cathepsin D), PREP234 (c-fgr), and PREP136 (lysozyme) were very highly up-regulated in all seven CSS patients. Another 28 genes were also up-regulated, albeit more moderately, and three were down-regulated in all CSS patients. The nature of these up- and down-regulated genes suggest that the immune systems of the patients are activated in response to invading microorganisms. These observations indicate that focused microarray analysis of PBMCs may be a practical, useful, and low-cost bedside diagnostics tool. PMID:18263571

  5. Focused Microarray Analysis of Peripheral Mononuclear Blood Cells from Churg–Strauss Syndrome Patients

    PubMed Central

    Tougan, Takahiro; Onda, Hiroaki; Okuzaki, Daisuke; Kobayashi, Shigeto; Hashimoto, Hiroshi; Nojima, Hiroshi

    2008-01-01

    DNA diagnostics are useful but are hampered by difficult ethical issues. Moreover, it cannot provide enough information on the environmental factors that are important for pathogenesis of certain diseases. However, this is not a problem for RNA diagnostics, which evaluate the expression of the gene in question. We here report a novel RNA diagnostics tool that can be employed with peripheral blood mononuclear cells (PBMCs). To establish this tool, we identified 290 genes that are highly expressed in normal PBMCs but not in TIG-1, a normal human fibroblast cell. These genes were entitled PREP after predominantly expressed in PBMC and included 50 uncharacterized genes. We then conducted PREP gene-focused microarray analysis on PBMCs from seven cases of Churg–Strauss syndrome (CSS), which is a small-vessel necrotizing vasculitis. We found that PREP135 (coactosin-like protein), PREP77 (prosaposin), PREP191 (cathepsin D), PREP234 (c-fgr), and PREP136 (lysozyme) were very highly up-regulated in all seven CSS patients. Another 28 genes were also up-regulated, albeit more moderately, and three were down-regulated in all CSS patients. The nature of these up- and down-regulated genes suggest that the immune systems of the patients are activated in response to invading microorganisms. These observations indicate that focused microarray analysis of PBMCs may be a practical, useful, and low-cost bedside diagnostics tool. PMID:18263571

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

    PubMed

    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

    2015-10-01

    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. PMID:26339978

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

    PubMed Central

    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.

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

    PubMed

    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

    2015-10-01

    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.

  9. Phylogenetic Microarray Analysis of a Microbial Community Performing Reductive Dechlorination at a TCE-contaminated Site

    PubMed Central

    Lee, Patrick K. H.; Warnecke, F.; Brodie, Eoin L.; Macbeth, Tamzen W.; Conrad, Mark E.; Andersen, Gary L.; Alvarez-Cohen, Lisa

    2012-01-01

    A high-density phylogenetic microarray (PhyloChip) was applied to track bacterial and archaeal populations through different phases of remediation at Ft. Lewis, WA, a trichloroethene (TCE)-contaminated groundwater site. Biostimulation with whey, and bioaugmentation with a Dehalococcoides-containing enrichment culture were strategies implemented to enhance dechlorination. As a measure of species richness, over 1300 operational taxonomic units (OTUs) were detected in DNA from groundwater samples extracted during different stages of treatment and in the bioaugmentation culture. In order to determine active members within the community, 16S rRNA from samples were analyzed by microarray and ~600 OTUs identified. A cDNA clone library of the expressed 16S rRNA corroborated the observed diversity and activity of some of the phyla. Principle component analysis of the treatment plot samples revealed that the microbial populations were constantly changing during the course of the study. Dynamic analysis of the archaeal population showed significant increases in methanogens at the later stages of treatment that correlated with increases in methane concentrations of over two orders of magnitude. Overall, the PhyloChip analyses in this study have provided insights into the microbial ecology and population dynamics at the TCE-contaminated field site useful for understanding the in situ reductive dechlorination processes. PMID:22091783

  10. Microarray analysis of ripening-regulated gene expression and its modulation by 1-MCP and hexanal.

    PubMed

    Tiwari, Krishnaraj; Paliyath, Gopinadhan

    2011-03-01

    Hexanal, an inhibitor of phospholipase D, has been successfully applied for the pre- and post-harvest treatment of fruits, vegetables and flowers. Changes in gene expression induced by hexanal and the ethylene antagonist 1-MCP, were analyzed by microarray using TOM2 tomato oligo-array containing approximately 12 000 unigenes. Mature green tomato fruits were treated with 1-MCP and hexanal, RNA isolated after 10 days of storage, and labeled cDNA synthesized for microarray analysis. A large variation in gene expression profile was observed in 1-MCP-treated fruits. Genes for ethylene biosynthetic pathway enzymes such as ACC- synthase/oxidase, ethylene receptor and ethylene response factors were heavily down-regulated in 1-MCP-treated fruits. In addition, genes for key enzymes involved in cell wall degradation and carotenoid development pathways were down-regulated. Hexanal treatment significantly down-regulated ACC-synthase, and to a lesser extent, other components of ethylene signal transduction. By contrast to MCP-treated fruits, hexanal-treated fruits gradually ripened and showed higher levels of lycopene and β-carotene. GC-MS analysis of volatiles showed a higher level of major volatile components in hexanal-treated fruits. Similarities in the modulation of gene expression by hexanal and 1-MCP suggest that hexanal, in addition to being a PLD inhibitor, may also act as a weak ethylene inhibitor.

  11. Microarray analysis of differential gene expression in sensitive and resistant pig to Escherichia coli F18.

    PubMed

    Bao, W B; Ye, L; Pan, Z Y; Zhu, J; Du, Z D; Zhu, G Q; Huang, X G; Wu, S L

    2012-10-01

    In this study, Agilent two-colour microarray-based gene expression profiling was used to detect differential gene expression in duodenal tissues collected from eight full-sib pairs of Sutai pigs differing in adhesion phenotype (sensitivity and resistance to Escherichia coli F18). Using a two-fold change minimum threshold, we found 18 genes that were differentially expressed (10 up-regulated and eight down-regulated) between the sensitive and resistant animal groups. Our gene ontology analysis revealed that these differentially expressed genes are involved in a variety of biological processes, including immune responses, extracellular modification (e.g. glycosylation), cell adhesion and signal transduction, all of which are related to the anabolic metabolism of glycolipids, as well as to inflammation- and immune-related pathways. Based on the genes identified in the screen and the pathway analysis results, real-time PCR was used to test the involvement of ST3GAL1 and A genes (of glycolipid-related pathways), SLA-1 and SLA-3 genes (of inflammation- and immune-related pathways), as well as the differential genes FUT1, TAP1 and SLA-DQA. Subsequently, real-time PCR was performed to validate seven differentially expressed genes screened out by the microarray approach, and sufficient consistency was observed between the two methods. The results support the conclusion that these genes are related to the E. coli F18 receptor and susceptibility to E. coli F18. PMID:22497274

  12. Phylogenetic microarray analysis of a microbial community performing reductive dechlorination at a TCE-contaminated site.

    PubMed

    Lee, Patrick K H; Warnecke, F; Brodie, Eoin L; Macbeth, Tamzen W; Conrad, Mark E; Andersen, Gary L; Alvarez-Cohen, Lisa

    2012-01-17

    A high-density phylogenetic microarray (PhyloChip) was applied to track bacterial and archaeal populations through different phases of remediation at Ft. Lewis, WA, a trichloroethene (TCE)-contaminated groundwater site. Biostimulation with whey, and bioaugmentation with a Dehalococcoides-containing enrichment culture were strategies implemented to enhance dechlorination. As a measure of species richness, over 1300 operational taxonomic units (OTUs) were detected in DNA from groundwater samples extracted during different stages of treatment and in the bioaugmentation culture. In order to determine active members within the community, 16S rRNA from samples were analyzed by microarray and ∼600 OTUs identified. A cDNA clone library of the expressed 16S rRNA corroborated the observed diversity and activity of some of the phyla. Principle component analysis of the treatment plot samples revealed that the microbial populations were constantly changing during the course of the study. Dynamic analysis of the archaeal population showed significant increases in methanogens at the later stages of treatment that correlated with increases in methane concentrations of over 2 orders of magnitude. Overall, the PhyloChip analyses in this study have provided insights into the microbial ecology and population dynamics at the TCE-contaminated field site useful for understanding the in situ reductive dechlorination processes.

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

    PubMed

    Aharoni, Asaph; O'Connell, Ann P

    2002-10-01

    Large-scale, single pass sequencing and parallel gene expression analysis using DNA microarrays were employed for the comprehensive investigation of ripening in strawberry fruit. A total of 1701 cDNA clones (comprising 1100 strawberry ESTs and 601 unsequenced cDNAs) obtained from a strawberry (Fragariaxananassa) ripe fruit cDNA library were displayed on microarrays, and used for monitoring concurrent gene expression in receptacle and achene tissues. Analysis of expression ratios identified 66 out of the 259 (25%) achene-related clones and 80 out of 182 (44%) receptacle-related clones with more than a 4-fold difference in expression between the two tissue types. Half of the achene-associated genes putatively encode proteins with unknown function, and a large number of the remainder were proteins predicted to form part of the signal and regulation cascades related to achene maturation and acquisition of stress and desiccation tolerance. These included phosphatases, protein kinases, 14-3-3 proteins, transcription factors, and others. In the receptacle, key processes and novel genes that could be associated with ripening were identified. Genes putatively encoding proteins related to stress, the cell wall, DNA/RNA/protein, and primary metabolism were highly represented. Apart from providing a global observation on gene expression programmes and metabolic pathways in the developing strawberry, this study has made available a large database and unique information for gene discovery, promoter selection and markers for molecular breeding approaches.

  14. Workflows for microarray data processing in the Kepler environment

    PubMed Central

    2012-01-01

    Background Microarray data analysis has been the subject of extensive and ongoing pipeline development due to its complexity, the availability of several options at each analysis step, and the development of new analysis demands, including integration with new data sources. Bioinformatics pipelines are usually custom built for different applications, making them typically difficult to modify, extend and repurpose. Scientific workflow systems are intended to address these issues by providing general-purpose frameworks in which to develop and execute such pipelines. The Kepler workflow environment is a well-established system under continual development that is employed in several areas of scientific research. Kepler provides a flexible graphical interface, featuring clear display of parameter values, for design and modification of workflows. It has capabilities for developing novel computational components in the R, Python, and Java programming languages, all of which are widely used for bioinformatics algorithm development, along with capabilities for invoking external applications and using web services. Results We developed a series of fully functional bioinformatics pipelines addressing common tasks in microarray processing in the Kepler workflow environment. These pipelines consist of a set of tools for GFF file processing of NimbleGen chromatin immunoprecipitation on microarray (ChIP-chip) datasets and more comprehensive workflows for Affymetrix gene expression microarray bioinformatics and basic primer design for PCR experiments, which are often used to validate microarray results. Although functional in themselves, these workflows can be easily customized, extended, or repurposed to match the needs of specific projects and are designed to be a toolkit and starting point for specific applications. These workflows illustrate a workflow programming paradigm focusing on local resources (programs and data) and therefore are close to traditional shell scripting or

  15. Microarray gene expression analysis of fixed archival tissue permits molecular classification and identification of potential therapeutic targets in diffuse large B-cell lymphoma.

    PubMed

    Linton, Kim; Howarth, Christopher; Wappett, Mark; Newton, Gillian; Lachel, Cynthia; Iqbal, Javeed; Pepper, Stuart; Byers, Richard; Chan, Wing John; Radford, John

    2012-01-01

    Refractory/relapsed diffuse large B-cell lymphoma (DLBCL) has a poor prognosis. Novel drugs targeting the constitutively activated NF-κB pathway characteristic of ABC-DLBCL are promising, but evaluation depends on accurate activated B cell-like (ABC)/germinal center B cell-like (GCB) molecular classification. This is traditionally performed on gene microarray expression profiles of fresh biopsies, which are not routinely collected, or by immunohistochemistry on formalin-fixed, paraffin-embedded (FFPE) tissue, which lacks reproducibility and classification accuracy. We explored the possibility of using routine archival FFPE tissue for gene microarray applications. We examined Affymetrix HG U133 Plus 2.0 gene expression profiles from paired archival FFPE and fresh-frozen tissues of 40 ABC/GCB-classified DLBCL cases to compare classification accuracy and test the potential for this approach to aid the discovery of therapeutic targets and disease classifiers in DLBCL. Unsupervised hierarchical clustering of unselected present probe sets distinguished ABC/GCB in FFPE with remarkable accuracy, and a Bayesian classifier correctly assigned 32 of 36 cases with >90% probability. Enrichment for NF-κB genes was appropriately seen in ABC-DLBCL FFPE tissues. The top discriminatory genes expressed in FFPE separated cases with high statistical significance and contained novel biology with potential therapeutic insights, warranting further investigation. These results support a growing understanding that archival FFPE tissues can be used in microarray experiments aimed at molecular classification, prognostic biomarker discovery, and molecular exploration of rare diseases.

  16. Microarray Based Gene Expression Analysis of Murine Brown and Subcutaneous Adipose Tissue: Significance with Human

    PubMed Central

    Boparai, Ravneet K.; Kondepudi, Kanthi Kiran; Mantri, Shrikant; Bishnoi, Mahendra

    2015-01-01

    Background Two types of adipose tissues, white (WAT) and brown (BAT) are found in mammals. Increasingly novel strategies are being proposed for the treatment of obesity and its associated complications by altering amount and/or activity of BAT using mouse models. Methodology/Principle Findings The present study was designed to: (a) investigate the differential expression of genes in LACA mice subcutaneous WAT (sWAT) and BAT using mouse DNA microarray, (b) to compare mouse differential gene expression with previously published human data; to understand any inter- species differences between the two and (c) to make a comparative assessment with C57BL/6 mouse strain. In mouse microarray studies, over 7003, 1176 and 401 probe sets showed more than two-fold, five-fold and ten-fold change respectively in differential expression between murine BAT and WAT. Microarray data was validated using quantitative RT-PCR of key genes showing high expression in BAT (Fabp3, Ucp1, Slc27a1) and sWAT (Ms4a1, H2-Ob, Bank1) or showing relatively low expression in BAT (Pgk1, Cox6b1) and sWAT (Slc20a1, Cd74). Multi-omic pathway analysis was employed to understand possible links between the organisms. When murine two fold data was compared with published human BAT and sWAT data, 90 genes showed parallel differential expression in both mouse and human. Out of these 90 genes, 46 showed same pattern of differential expression whereas the pattern was opposite for the remaining 44 genes. Based on our microarray results and its comparison with human data, we were able to identify genes (targets) (a) which can be studied in mouse model systems to extrapolate results to human (b) where caution should be exercised before extrapolation of murine data to human. Conclusion Our study provides evidence for inter species (mouse vs human) differences in differential gene expression between sWAT and BAT. Critical understanding of this data may help in development of novel ways to engineer one form of adipose

  17. Microarray Comparative Genomic Hybridisation Analysis Incorporating Genomic Organisation, and Application to Enterobacterial Plant Pathogens

    PubMed Central

    Pritchard, Leighton; Liu, Hui; Booth, Clare; Douglas, Emma; François, Patrice; Schrenzel, Jacques; Hedley, Peter E.; Birch, Paul R. J.; Toth, Ian K.

    2009-01-01

    Microarray comparative genomic hybridisation (aCGH) provides an estimate of the relative abundance of genomic DNA (gDNA) taken from comparator and reference organisms by hybridisation to a microarray containing probes that represent sequences from the reference organism. The experimental method is used in a number of biological applications, including the detection of human chromosomal aberrations, and in comparative genomic analysis of bacterial strains, but optimisation of the analysis is desirable in each problem domain. We present a method for analysis of bacterial aCGH data that encodes spatial information from the reference genome in a hidden Markov model. This technique is the first such method to be validated in comparisons of sequenced bacteria that diverge at the strain and at the genus level: Pectobacterium atrosepticum SCRI1043 (Pba1043) and Dickeya dadantii 3937 (Dda3937); and Lactococcus lactis subsp. lactis IL1403 and L. lactis subsp. cremoris MG1363. In all cases our method is found to outperform common and widely used aCGH analysis methods that do not incorporate spatial information. This analysis is applied to comparisons between commercially important plant pathogenic soft-rotting enterobacteria (SRE) Pba1043, P. atrosepticum SCRI1039, P. carotovorum 193, and Dda3937. Our analysis indicates that it should not be assumed that hybridisation strength is a reliable proxy for sequence identity in aCGH experiments, and robustly extends the applicability of aCGH to bacterial comparisons at the genus level. Our results in the SRE further provide evidence for a dynamic, plastic ‘accessory’ genome, revealing major genomic islands encoding gene products that provide insight into, and may play a direct role in determining, variation amongst the SRE in terms of their environmental survival, host range and aetiology, such as phytotoxin synthesis, multidrug resistance, and nitrogen fixation. PMID:19696881

  18. Development and application of a 6.5 million feature Affymetrix Genechip® for massively parallel discovery of single position polymorphisms in lettuce (Lactuca spp.)

    PubMed Central

    2012-01-01

    Background High-resolution genetic maps are needed in many crops to help characterize the genetic diversity that determines agriculturally important traits. Hybridization to microarrays to detect single feature polymorphisms is a powerful technique for marker discovery and genotyping because of its highly parallel nature. However, microarrays designed for gene expression analysis rarely provide sufficient gene coverage for optimal detection of nucleotide polymorphisms, which limits utility in species with low rates of polymorphism such as lettuce (Lactuca sativa). Results We developed a 6.5 million feature Affymetrix GeneChip® for efficient polymorphism discovery and genotyping, as well as for analysis of gene expression in lettuce. Probes on the microarray were designed from 26,809 unigenes from cultivated lettuce and an additional 8,819 unigenes from four related species (L. serriola, L. saligna, L. virosa and L. perennis). Where possible, probes were tiled with a 2 bp stagger, alternating on each DNA strand; providing an average of 187 probes covering approximately 600 bp for each of over 35,000 unigenes; resulting in up to 13 fold redundancy in coverage per nucleotide. We developed protocols for hybridization of genomic DNA to the GeneChip® and refined custom algorithms that utilized coverage from multiple, high quality probes to detect single position polymorphisms in 2 bp sliding windows across each unigene. This allowed us to detect greater than 18,000 polymorphisms between the parental lines of our core mapping population, as well as numerous polymorphisms between cultivated lettuce and wild species in the lettuce genepool. Using marker data from our diversity panel comprised of 52 accessions from the five species listed above, we were able to separate accessions by species using both phylogenetic and principal component analyses. Additionally, we estimated the diversity between different types of cultivated lettuce and distinguished morphological types

  19. Transcript profiling by microarray and marker analysis of the short cotton (Gossypium hirsutum L.) fiber mutant Ligon lintless-1 (Li1)

    PubMed Central

    2013-01-01

    Background Cotton fiber length is very important to the quality of textiles. Understanding the genetics and physiology of cotton fiber elongation can provide valuable tools to the cotton industry by targeting genes or other molecules responsible for fiber elongation. Ligon Lintless-1 (Li1) is a monogenic mutant in Upland cotton (Gossypium hirsutum) which exhibits an early cessation of fiber elongation resulting in very short fibers (< 6 mm) at maturity. This presents an excellent model system for studying the underlying molecular and cellular processes involved with cotton fiber elongation. Previous reports have characterized Li1 at early cell wall elongation and during later secondary cell wall synthesis, however there has been very limited analysis of the transition period between these developmental time points. Results Physical and morphological measurements of the Li1 mutant fibers were conducted, including measurement of the cellulose content during development. Affymetrix microarrays were used to analyze transcript profiles at the critical developmental time points of 3 days post anthesis (DPA), the late elongation stage of 12 DPA and the early secondary cell wall synthesis stage of 16 DPA. The results indicated severe disruption to key hormonal and other pathways related to fiber development, especially pertaining to the transition stage from elongation to secondary cell wall synthesis. Gene Ontology enrichment analysis identified several key pathways at the transition stage that exhibited altered regulation. Genes involved in ethylene biosynthesis and primary cell wall rearrangement were affected, and a primary cell wall-related cellulose synthase was transcriptionally repressed. Linkage mapping using a population of 2,553 F2 individuals identified SSR markers associated with the Li1 genetic locus on chromosome 22. Linkage mapping in combination with utilizing the diploid G. raimondii genome sequences permitted additional analysis of the region containing

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

    DOE PAGES

    Thomas, E. V.; Phillippy, K. H.; Brahamsha, B.; Haaland, D. M.; Timlin, J. A.; Elbourne, L. D. H.; Palenik, B.; Paulsen, I. T.

    2009-01-01

    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 partmore » 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.« less

  1. Microarray-Based Comparative Genomic and Transcriptome Analysis of Borrelia burgdorferi

    PubMed Central

    Iyer, Radha; Schwartz, Ira

    2016-01-01

    Borrelia burgdorferi, the spirochetal agent of Lyme disease, is maintained in nature in a cycle involving a tick vector and a mammalian host. Adaptation to the diverse conditions of temperature, pH, oxygen tension and nutrient availability in these two environments requires the precise orchestration of gene expression. Over 25 microarray analyses relating to B. burgdorferi genomics and transcriptomics have been published. The majority of these studies has explored the global transcriptome under a variety of conditions and has contributed substantially to the current understanding of B. burgdorferi transcriptional regulation. In this review, we present a summary of these studies with particular focus on those that helped define the roles of transcriptional regulators in modulating gene expression in the tick and mammalian milieus. By performing comparative analysis of results derived from the published microarray expression profiling studies, we identified composite gene lists comprising differentially expressed genes in these two environments. Further, we explored the overlap between the regulatory circuits that function during the tick and mammalian phases of the enzootic cycle. Taken together, the data indicate that there is interplay among the distinct signaling pathways that function in feeding ticks and during adaptation to growth in the mammal. PMID:27600075

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

    SciTech Connect

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

    2009-12-01

    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 kappaB; 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.

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

    PubMed Central

    Wei, Hengxi; Liu, Xiangjie; Yuan, Jihong; Li, Li; Zhang, Dongdong; Guo, Xinzheng; Liu, Lin; Zhang, Shouquan

    2015-01-01

    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. PMID:26421297

  4. Quantitative analysis of microRNAs in tissue microarrays by in situ hybridization

    PubMed Central

    Hanna, Jason A.; Wimberly, Hallie; Kumar, Salil; Slack, Frank; Agarwal, Seema; Rimm, David L.

    2013-01-01

    MicroRNAs (miRNAs) have emerged as key regulators in the pathogenesis of cancers where they can act as either oncogenes or tumor suppressors. Most miRNA measurement methods require total RNA extracts which lack critical spatial information and present challenges for standardization. We have developed and validated a method for the quantitative analysis of miRNA expression by in situ hybridization (ISH) allowing for the direct assessment of tumor epithelial expression of miRNAs. This co-localization based approach (called qISH) utilizes DAPI and cytokeratin immunofluorescence to establish subcellular compartments in the tumor epithelia, then multiplexed with the miRNA ISH, allows for quantitative measurement of miRNA expression within these compartments. We use this approach to assess miR-21, miR-92a, miR-34a, and miR-221 expression in 473 breast cancer specimens on tissue microarrays. We found that miR-221 levels are prognostic in breast cancer illustrating the high-throughput method and confirming that miRNAs can be valuable biomarkers in cancer. Furthermore, in applying this method we found that the inverse relationship between miRNAs and proposed target proteins is difficult to discern in large population cohorts. Our method demonstrates an approach for large cohort, tissue microarray-based assessment of miRNA expression. PMID:22482439

  5. Microarray and Co-expression Network Analysis of Genes Associated with Acute Doxorubicin Cardiomyopathy in Mice.

    PubMed

    Wei, Sheng-Nan; Zhao, Wen-Jie; Zeng, Xiang-Jun; Kang, Yu-Ming; Du, Jie; Li, Hui-Hua

    2015-10-01

    Clinical use of doxorubicin (DOX) in cancer therapy is limited by its dose-dependent cardiotoxicity. But molecular mechanisms underlying this phenomenon have not been well defined. This study was to investigate the effect of DOX on the changes of global genomics in hearts. Acute cardiotoxicity was induced by giving C57BL/6J mice a single intraperitoneal injection of DOX (15 mg/kg). Cardiac function and apoptosis were monitored using echocardiography and TUNEL assay at days 1, 3 and 5. Myocardial glucose and ATP levels were measured. Microarray assays were used to screen gene expression profiles in the hearts at day 5, and the results were confirmed with qPCR analysis. DOX administration caused decreased cardiac function, increased cardiomyocyte apoptosis and decreased glucose and ATP levels. Microarrays showed 747 up-regulated genes and 438 down-regulated genes involved in seven main functional categories. Among them, metabolic pathway was the most affected by DOX. Several key genes, including 2,3-bisphosphoglycerate mutase (Bpgm), hexokinase 2, pyruvate dehydrogenase kinase, isoenzyme 4 and fructose-2,6-bisphosphate 2-phosphatase, are closely related to glucose metabolism. Gene co-expression networks suggested the core role of Bpgm in DOX cardiomyopathy. These results obtained in mice were further confirmed in cultured cardiomyocytes. In conclusion, genes involved in glucose metabolism, especially Bpgm, may play a central role in the pathogenesis of DOX-induced cardiotoxicity. PMID:25575753

  6. Testing for mean and correlation changes in microarray experiments: an application for pathway analysis

    PubMed Central

    2010-01-01

    Background Microarray experiments examine the change in transcript levels of tens of thousands of genes simultaneously. To derive meaningful data, biologists investigate the response of genes within specific pathways. Pathways are comprised of genes that interact to carry out a particular biological function. Existing methods for analyzing pathways focus on detecting changes in the mean or over-representation of the number of differentially expressed genes relative to the total of genes within the pathway. The issue of how to incorporate the influence of correlation among the genes is not generally addressed. Results In this paper, we propose a non-parametric rank test for analyzing pathways that takes into account the correlation among the genes and compared two existing methods, Global and Gene Set Enrichment Analysis (GSEA), using two publicly available data sets. A simulation study was conducted to demonstrate the advantage of the rank test method. Conclusions The data indicate the advantages of the rank test. The method can distinguish significant changes in pathways due to either correlations or changes in the mean or both. From the simulation study the rank test out performed Global and GSEA. The greatest gain in performance was for the sample size case which makes the application of the rank test ideal for microarray experiments. PMID:20109181

  7. Inference of Disease-Related Molecular Logic from Systems-Based Microarray Analysis

    PubMed Central

    Varadan, Vinay; Anastassiou, Dimitris

    2006-01-01

    Computational analysis of gene expression data from microarrays has been useful for medical diagnosis and prognosis. The ability to analyze such data at the level of biological modules, rather than individual genes, has been recognized as important for improving our understanding of disease-related pathways. It has proved difficult, however, to infer pathways from microarray data by deriving modules of multiple synergistically interrelated genes, rather than individual genes. Here we propose a systems-based approach called Entropy Minimization and Boolean Parsimony (EMBP) that identifies, directly from gene expression data, modules of genes that are jointly associated with disease. Furthermore, the technique provides insight into the underlying biomolecular logic by inferring a logic function connecting the joint expression levels in a gene module with the outcome of disease. Coupled with biological knowledge, this information can be useful for identifying disease-related pathways, suggesting potential therapeutic approaches for interfering with the functions of such pathways. We present an example providing such gene modules associated with prostate cancer from publicly available gene expression data, and we successfully validate the results on additional independently derived data. Our results indicate a link between prostate cancer and cellular damage from oxidative stress combined with inhibition of apoptotic mechanisms normally triggered by such damage. PMID:16789819

  8. Glycosylation and post-translational modification gene expression analysis by DNA microarrays for cultured mammalian cells

    PubMed Central

    Brodsky, Arthur Nathan; Caldwell, Mary; Harcum, Sarah W.

    2011-01-01

    DNA microarray analysis of gene expression has become a valuable tool for bioprocessing research aimed at improving therapeutic protein yields. The highly parallel nature of DNA microarray technology allows researchers to assess hundreds of gene simultaneously, essentially enabling genome-wide snapshots. The quality and amount of therapeutic proteins produced by cultured mammalian cells rely heavily on the culture environment. In order to implement beneficial changes to the culture environment, a better understanding of the relationship between the product quality and culture environment must be developed. By analyzing gene expression levels under various environmental conditions, light can be shed on the underlying mechanisms. This paper describes a method for evaluating gene expression changes for cultured NS0 cells, a mouse-derived myeloma cell line, under culture environment conditions, such as ammonia buildup, known to affect product quality. These procedures can be easily adapted to other environmental conditions and any mammalian cell lines cultured in suspension, so long as a sufficient number of gene sequences are publicly available. PMID:22033470

  9. Microarray-Based Comparative Genomic and Transcriptome Analysis of Borrelia burgdorferi.

    PubMed

    Iyer, Radha; Schwartz, Ira

    2016-01-01

    Borrelia burgdorferi, the spirochetal agent of Lyme disease, is maintained in nature in a cycle involving a tick vector and a mammalian host. Adaptation to the diverse conditions of temperature, pH, oxygen tension and nutrient availability in these two environments requires the precise orchestration of gene expression. Over 25 microarray analyses relating to B. burgdorferi genomics and transcriptomics have been published. The majority of these studies has explored the global transcriptome under a variety of conditions and has contributed substantially to the current understanding of B. burgdorferi transcriptional regulation. In this review, we present a summary of these studies with particular focus on those that helped define the roles of transcriptional regulators in modulating gene expression in the tick and mammalian milieus. By performing comparative analysis of results derived from the published microarray expression profiling studies, we identified composite gene lists comprising differentially expressed genes in these two environments. Further, we explored the overlap between the regulatory circuits that function during the tick and mammalian phases of the enzootic cycle. Taken together, the data indicate that there is interplay among the distinct signaling pathways that function in feeding ticks and during adaptation to growth in the mammal. PMID:27600075

  10. Principal components analysis and the reported low intrinsic dimensionality of gene expression microarray data.

    PubMed

    Lenz, Michael; Müller, Franz-Josef; Zenke, Martin; Schuppert, Andreas

    2016-01-01

    Principal components analysis (PCA) is a common unsupervised method for the analysis of gene expression microarray data, providing information on the overall structure of the analyzed dataset. In the recent years, it has been applied to very large datasets involving many different tissues and cell types, in order to create a low dimensional global map of human gene expression. Here, we reevaluate this approach and show that the linear intrinsic dimensionality of this global map is higher than previously reported. Furthermore, we analyze in which cases PCA fails to detect biologically relevant information and point the reader to methods that overcome these limitations. Our results refine the current understanding of the overall structure of gene expression spaces and show that PCA critically depends on the effect size of the biological signal as well as on the fraction of samples containing this signal. PMID:27254731

  11. Microarray analysis of Neosartorya fischeri using different carbon sources, petroleum asphaltenes and glucose-peptone

    PubMed Central

    Hernández-López, Edna L.; Ramírez-Puebla, Shamayim T.; Vazquez-Duhalt, Rafael

    2015-01-01

    Asphaltenes are considered as the most recalcitrant petroleum fraction and represent a big problem for the recovery, separation and processing of heavy oils and bitumens. Neosartorya fischeri is a saprophytic fungus that is able to grow using asphaltenes as the sole carbon source [1]. We performed transcription profiling using a custom designed microarray with the complete genome from N. fischeri NRRL 181 in order to identify genes related to the transformation of asphaltenes [1]. Data analysis was performed using the genArise software. Results showed that 287 genes were up-regulated and 118 were down-regulated. Here we describe experimental procedures and methods about our dataset (NCBI GEO accession number GSE68146) and describe the data analysis to identify different expression levels in N. fischeri using this recalcitrant carbon source. PMID:26484261

  12. INCLUSive: a web portal and service registry for microarray and regulatory sequence analysis

    PubMed Central

    Coessens, Bert; Thijs, Gert; Aerts, Stein; Marchal, Kathleen; De Smet, Frank; Engelen, Kristof; Glenisson, Patrick; Moreau, Yves; Mathys, Janick; De Moor, Bart

    2003-01-01

    INCLUSive is a suite of algorithms and tools for the analysis of gene expression data and the discovery of cis-regulatory sequence elements. The tools allow normalization, filtering and clustering of microarray data, functional scoring of gene clusters, sequence retrieval, and detection of known and unknown regulatory elements using probabilistic sequence models and Gibbs sampling. All tools are available via different web pages and as web services. The web pages are connected and integrated to reflect a methodology and facilitate complex analysis using different tools. The web services can be invoked using standard SOAP messaging. Example clients are available for download to invoke the services from a remote computer or to be integrated with other applications. All services are catalogued and described in a web service registry. The INCLUSive web portal is available for academic purposes at http://www.esat.kuleuven.ac.be/inclusive. PMID:12824346

  13. Principal components analysis and the reported low intrinsic dimensionality of gene expression microarray data

    PubMed Central

    Lenz, Michael; Müller, Franz-Josef; Zenke, Martin; Schuppert, Andreas

    2016-01-01

    Principal components analysis (PCA) is a common unsupervised method for the analysis of gene expression microarray data, providing information on the overall structure of the analyzed dataset. In the recent years, it has been applied to very large datasets involving many different tissues and cell types, in order to create a low dimensional global map of human gene expression. Here, we reevaluate this approach and show that the linear intrinsic dimensionality of this global map is higher than previously reported. Furthermore, we analyze in which cases PCA fails to detect biologically relevant information and point the reader to methods that overcome these limitations. Our results refine the current understanding of the overall structure of gene expression spaces and show that PCA critically depends on the effect size of the biological signal as well as on the fraction of samples containing this signal. PMID:27254731

  14. Phytoremediation potential of Arabidopsis with reference to acrylamide and microarray analysis of acrylamide-response genes.

    PubMed

    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.

  15. RNA Microarray Analysis of Macroscopically Normal Articular Cartilage from Knees Undergoing Partial Medial Meniscectomy: Potential Prediction of the Risk for Developing Osteoarthritis

    PubMed Central

    Sandell, Linda J.; Zhang, Bo; Wright, Rick W.; Brophy, Robert H.

    2016-01-01

    Objectives (i) To provide baseline knowledge of gene expression in macroscopically normal articular cartilage, (ii) to test the hypothesis that age, body-mass-index (BMI), and sex are associated with cartilage RNA transcriptome, and (iii) to predict individuals at potential risk for developing “pre-osteoarthritis” (OA) based on screening of genetic risk-alleles associated with OA and gene transcripts differentially expressed between normal and OA cartilage. Design Healthy-appearing cartilage was obtained from the medial femoral notch of 12 knees with a meniscus tear undergoing arthroscopic partial meniscectomy. Cartilage had no radiographic, magnetic-resonance-imaging or arthroscopic evidence for degeneration. RNA was subjected to Affymetrix microarrays followed by validation of selected transcripts by microfluidic digital polymerase-chain-reaction. The underlying biological processes were explored computationally. Transcriptome-wide gene expression was probed for association with known OA genetic risk-alleles assembled from published literature and for comparison with gene transcripts differentially expressed between healthy and OA cartilage from other studies. Results We generated a list of 27,641 gene transcripts in healthy cartilage. Several gene transcripts representing numerous biological processes were correlated with age and BMI and differentially expressed by sex. Based on disease-specific Ingenuity Pathways Analysis, gene transcripts associated with aging were enriched for bone/cartilage disease while the gene expression profile associated with BMI was enriched for growth-plate calcification and OA. When segregated by genetic risk-alleles, two clusters of study patients emerged, one cluster containing transcripts predicted by risk studies. When segregated by OA-associated gene transcripts, three clusters of study patients emerged, one of which is remarkably similar to gene expression pattern in OA. Conclusions Our study provides a list of gene

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

    PubMed Central

    Depiereux, Sophie; De Meulder, Bertrand; Bareke, Eric; Berger, Fabrice; Le Gac, Florence; Depiereux, Eric; Kestemont, Patrick

    2015-01-01

    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 lowest p

  17. Detection of Herpesviridae in whole blood by multiplex PCR DNA-based microarray analysis after hematopoietic stem cell transplantation.

    PubMed

    Debaugnies, France; Busson, Laurent; Ferster, Alina; Lewalle, Philippe; Azzi, Nadira; Aoun, Mickael; Verhaegen, Godelieve; Mahadeb, Bhavna; de Marchin, Jérôme; Vandenberg, Olivier; Hallin, Marie

    2014-07-01

    Viral infections are important causes of morbidity and mortality in patients after hematopoietic stem cell transplantation. The monitoring by PCR of Herpesviridae loads in blood samples has become a critical part of posttransplant follow-up, representing mounting costs for the laboratory. In this study, we assessed the clinical performance of the multiplex PCR DNA microarray Clart Entherpex kit for detection of cytomegalovirus (CMV), Epstein-Barr virus (EBV), and human herpesvirus 6 (HHV-6) as a screening test for virological follow-up. Two hundred fifty-five blood samples from 16 transplanted patients, prospectively tested by routine PCR assays, were analyzed by microarray. Routine PCR detected single or multiple viruses in 42% and 10% of the samples, respectively. Microarray detected single or multiple viruses in 34% and 18% of the samples, respectively. Microarray results correlated well with CMV and EBV detections by routine PCR (kappa tests = 0.79 and 0.78, respectively), whereas a weak correlation was observed with HHV-6 (0.43). HHV-7 was also detected in 48 samples by microarray. In conclusion, the microarray is a reliable screening assay for a posttransplant virological follow-up to detect CMV and EBV infections in blood. However, positive samples must be subsequently confirmed and viral loads must be quantified by PCR assays. Limitations were identified regarding HHV-6 detection. Although it is promising, is easy to use as a first-line test, and allows a reduction in the cost of analysis without undue delay in the reporting of the final quantitative result to the clinician, some characteristics of this microarray should be improved, particularly regarding quality control and the targeted virus panel, such that it could then be used as a routine test.

  18. Microarray-based detection and expression analysis of extracellular matrix proteins in drug‑resistant ovarian cancer cell lines.

    PubMed

    Januchowski, Radosław; Zawierucha, Piotr; Ruciński, Marcin; Zabel, Maciej

    2014-11-01

    Ovarian cancer is the most lethal gynecological malignancy. Multiple drug resistance (MDR) development leads to resistance of cancer cells to chemotherapy. Microarray methods can provide information regarding new candidate genes that can play a role in resistance to cytostatic drugs. Extracellular matrix (ECM) can influence drug resistance by inhibiting the penetration of the drug into cancer tissue as well as increased apoptosis resistance. In the present study, we report changes in the ECM and related gene expression pattern in methotrexate-, cisplatin-, doxorubicin-, vincristine-, topotecan- and paclitaxel-resistant variants of the W1 ovarian cancer cell line. The resistant variants of the W1 cell line were generated by stepwise selection of cells with an increasing concentration of the indicated drugs. Affymetrix GeneChip® Human Genome U219 Array Strips were used for hybridizations. Independent t-tests were used to determinate the statistical significance of results. Genes whose expression levels were higher than the assumed threshold (upregulated, >5-fold and downregulated, <5-fold) were visualized using the scatter plot method, selected and listed in the tables. Among the investigated genes, expression of 24 genes increased, expression of 14 genes decreased and expression of three genes increased or decreased depending on the cell line. Among the increased genes, expression of 10 increased very significantly, >20-fold. These genes were: ITGB1BP3, COL3A1, COL5A2, COL15A1, TGFBI, DCN, LUM, MATN2, POSTN and EGFL6. The expression of seven genes decreased very significantly: ITGA1, COL1A2, LAMA2, GPC3, KRT23, VIT and HMCN1. The expression pattern of ECM and related genes provided the preliminary view into the role of ECM components in cytostatic drug resistance of cancer cells. The exact role of the investigated genes in drug resistance requires further investigation.

  19. Microarray-based detection and expression analysis of extracellular matrix proteins in drug‑resistant ovarian cancer cell lines.

    PubMed

    Januchowski, Radosław; Zawierucha, Piotr; Ruciński, Marcin; Zabel, Maciej

    2014-11-01

    Ovarian cancer is the most lethal gynecological malignancy. Multiple drug resistance (MDR) development leads to resistance of cancer cells to chemotherapy. Microarray methods can provide information regarding new candidate genes that can play a role in resistance to cytostatic drugs. Extracellular matrix (ECM) can influence drug resistance by inhibiting the penetration of the drug into cancer tissue as well as increased apoptosis resistance. In the present study, we report changes in the ECM and related gene expression pattern in methotrexate-, cisplatin-, doxorubicin-, vincristine-, topotecan- and paclitaxel-resistant variants of the W1 ovarian cancer cell line. The resistant variants of the W1 cell line were generated by stepwise selection of cells with an increasing concentration of the indicated drugs. Affymetrix GeneChip® Human Genome U219 Array Strips were used for hybridizations. Independent t-tests were used to determinate the statistical significance of results. Genes whose expression levels were higher than the assumed threshold (upregulated, >5-fold and downregulated, <5-fold) were visualized using the scatter plot method, selected and listed in the tables. Among the investigated genes, expression of 24 genes increased, expression of 14 genes decreased and expression of three genes increased or decreased depending on the cell line. Among the increased genes, expression of 10 increased very significantly, >20-fold. These genes were: ITGB1BP3, COL3A1, COL5A2, COL15A1, TGFBI, DCN, LUM, MATN2, POSTN and EGFL6. The expression of seven genes decreased very significantly: ITGA1, COL1A2, LAMA2, GPC3, KRT23, VIT and HMCN1. The expression pattern of ECM and related genes provided the preliminary view into the role of ECM components in cytostatic drug resistance of cancer cells. The exact role of the investigated genes in drug resistance requires further investigation. PMID:25199881

  20. Microarray analysis reveals overlapping and specific transcriptional responses to different plant hormones in rice.

    PubMed

    Garg, Rohini; Tyagi, Akhilesh K; Jain, Mukesh

    2012-08-01

    Hormones exert pleiotropic effects on plant growth and development throughout the life cycle. Many of these effects are mediated at molecular level via altering gene expression. In this study, we investigated the exogenous effect of plant hormones, including auxin, cytokinin, abscisic acid, ethylene, salicylic acid and jasmonic acid, on the transcription of rice genes at whole genome level using microarray. Our analysis identified a total of 4171 genes involved in several biological processes, whose expression was altered significantly in the presence of different hormones. Further, 28% of these genes exhibited overlapping transcriptional responses in the presence of any two hormones, indicating crosstalk among plant hormones. In addition, we identified genes showing only a particular hormone-specific response, which can be used as hormone-specific markers. The results of this study will facilitate further studies in hormone biology in rice.

  1. Antimicrobial resistance determinant microarray for analysis of multi-drug resistant isolates

    NASA Astrophysics Data System (ADS)

    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.

  2. RNA Expression Microarray Analysis in Mouse Prospermatogonia: Identification of Candidate Epigenetic Modifiers

    PubMed Central

    Lefèvre, Christophe; Mann, Jeffrey R.

    2011-01-01

    The mammalian totipotent and pluripotent lineage exhibits genome-wide dynamics in respect to DNA methylation content. The first phase of global DNA demethylation and de novo remethylation occurs during preimplantation development and gastrulation, respectively, while the second phase occurs in primordial germ cells and primary oocytes/prospermatogonia, respectively. These dynamics are indicative of a comprehensive epigenetic resetting or reprogramming of the genome in preparation for major differentiation events. To gain further insight into the mechanisms driving DNA methylation dynamics and other types of epigenetic modification, we performed an RNA expression microarray analysis of fetal prospermatogonia at the stage when they are undergoing rapid de novo DNA remethylation. We have identified a number of highly or specifically expressed genes which could be important for determining epigenetic change in prospermatogonia. These data provide a useful resource in the discovery of molecular pathways involved in epigenetic reprogramming in the mammalian germ line. PMID:18330932

  3. Microarray analysis on archival multiple sclerosis tissue: pathogenic authenticity outweighs technical obstacles.

    PubMed

    Bradl, Monika; Lassmann, Hans

    2012-08-01

    Probably all neuropathologists know this dilemma: on the one hand, they have extremely precious archival material in their possession, which has been collected over many years from many different laboratories. Typically, this material is extremely well characterized, and often, it contains especially significant tissue specimens from unique cases. On the other hand, they face severe scepticism when they plan to use this archival material for large-scale gene expression studies by microarray analysis, since previous handling in the absence of RNA protection, prolonged storage at room temperature, and fixation with formaldehyde may dramatically reduce the amount of retrievable RNA. Fortunately, this dilemma can be solved. We give here examples from our own, multiple sclerosis-centered laboratory and explain why archival tissue might be more authentic for the disease process and might yield more information about the molecular and cellular substrates driving CNS inflammation in MS patients than more recently acquired tissues.

  4. Surface plasmon resonance imaging analysis of protein binding to a sialoside-based carbohydrate microarray.

    PubMed

    Linman, Matthew J; Yu, Hai; Chen, Xi; Cheng, Quan

    2012-01-01

    Monitoring multiple biological interactions in a multiplexed array format has numerous advantages. However, converting well-developed surface chemistry for spectroscopic measurements to array-based, high-throughput screening is not a trivial process and often proves to be the bottleneck in method development. This chapter reports the fabrication and characterization of a new carbohydrate microarray with synthetic sialosides for surface plasmon resonance imaging analysis of lectin-carbohydrate interactions. Contact printing of functional sialosides on neutravidin-coated surfaces was carried out and the properties of the resulting elements were characterized by fluorescence microscopy. Sambucus nigra agglutinin (SNA) was used for testing on four different carbohydrate-functionalized surfaces and differential binding was analyzed. Multiplexed detection of SNA/biotinylated sialoside interactions on arrays up to 400 elements has been performed with good data correlation, demonstrating the effectiveness of the biotin-neutravidin-based biointerface to control probe orientation for reproducible and efficient protein binding to carbohydrates.

  5. Analysis of mRNA translation states in Arabidopsis over the diurnal cycle by polysome microarray.

    PubMed

    Missra, Anamika; von Arnim, Albrecht G

    2014-01-01

    Gene regulation at the level of translation occurs in response to environmental perturbation and is increasingly recognized as a factor affecting plant development. Despite extensive knowledge of transcriptional control, very little is known about translational regulation of genes in response to the daily light/dark cycles. Here we describe the experimental layout designed to address how the translation states of genes change at various times during a diurnal cycle in Arabidopsis thaliana seedlings. We have adopted a strategy combining sucrose-gradient profiling of ribosomes and high-throughput microarray analysis of the ribosome-associated mRNA to investigate the translational landscape of the Arabidopsis genome. This is a powerful technique that can be easily extended to study translation regulation in different genetic backgrounds and under various environmental conditions.

  6. Chromosomal Microarray Analysis (CMA) a Clinical Diagnostic Tool in the Prenatal and Postnatal Settings.

    PubMed

    Batzir, Nurit Assia; Shohat, Mordechai; Maya, Idit

    2015-09-01

    Chromosomal microarray analysis (CMA) is a technology used for the detection of clinically-significant microdeietions or duplications, with a high sensitivity for submicroscopic aberrations. It is able to detect changes as small as 5-10Kb in size - a resolution up to 1000 times higher than that of conventional karyotyping. CMA is used for uncovering copy number variants (CNVs) thought to play an important role in the pathogenesis of a variety of disorders, primarily neurodevelopmental disorders and congenital anomalies. CMA may be applied in the prenatal or postnatal setting, with unique benefits and limitations in each setting. The growing use of CMA makes it essential for practicing physicians to understand the principles of this technology and be aware of its powers and limitations.

  7. A survey on filter techniques for feature selection in gene expression microarray analysis.

    PubMed

    Lazar, Cosmin; Taminau, Jonatan; Meganck, Stijn; Steenhoff, David; Coletta, Alain; Molter, Colin; de Schaetzen, Virginie; Duque, Robin; Bersini, Hugues; Nowé, Ann

    2012-01-01

    A plenitude of feature selection (FS) methods is available in the literature, most of them rising as a need to analyze data of very high dimension, usually hundreds or thousands of variables. Such data sets are now available in various application areas like combinatorial chemistry, text mining, multivariate imaging, or bioinformatics. As a general accepted rule, these methods are grouped in filters, wrappers, and embedded methods. More recently, a new group of methods has been added in the general framework of FS: ensemble techniques. The focus in this survey is on filter feature selection methods for informative feature discovery in gene expression microarray (GEM) analysis, which is also known as differentially expressed genes (DEGs) discovery, gene prioritization, or biomarker discovery. We present them in a unified framework, using standardized notations in order to reveal their technical details and to highlight their common characteristics as well as their particularities.

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

    PubMed Central

    Kruhøffer, Mogens; Dyrskjøt, Lars; Voss, Thorsten; Lindberg, Raija L.P.; Wyrich, Ralf; Thykjaer, Thomas; Orntoft, Torben F.

    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 microRNA 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. PMID:17690207

  9. DNA microarray analysis of Staphylococcus aureus causing bloodstream infection: bacterial genes associated with mortality?

    PubMed

    Blomfeldt, A; Aamot, H V; Eskesen, A N; Monecke, S; White, R A; Leegaard, T M; Bjørnholt, J V

    2016-08-01

    Providing evidence for microbial genetic determinants' impact on outcome in Staphylococcus aureus bloodstream infections (SABSI) is challenging due to the complex and dynamic microbe-host interaction. Our recent population-based prospective study reported an association between the S. aureus clonal complex (CC) 30 genotype and mortality in SABSI patients. This follow-up investigation aimed to examine the genetic profiles of the SABSI isolates and test the hypothesis that specific genetic characteristics in S. aureus are associated with mortality. SABSI isolates (n = 305) and S. aureus CC30 isolates from asymptomatic nasal carriers (n = 38) were characterised by DNA microarray analysis and spa typing. Fisher's exact test, least absolute shrinkage and selection operator (LASSO) and elastic net regressions were performed to discern within four groups defined by patient outcome and characteristics. No specific S. aureus genetic determinants were found to be associated with mortality in SABSI patients. By applying LASSO and elastic net regressions, we found evidence suggesting that agrIII and cna were positively and setC (=selX) and seh were negatively associated with S. aureus CC30 versus non-CC30 isolates. The genes chp and sak, encoding immune evasion molecules, were found in higher frequencies in CC30 SABSI isolates compared to CC30 carrier isolates, indicating a higher virulence potential. In conclusion, no specific S. aureus genes were found to be associated with mortality by DNA microarray analysis and state-of-the-art statistical analyses. The next natural step is to test the hypothesis in larger samples with higher resolution methods, like whole genome sequencing. PMID:27177754

  10. Gene (mRNA) expression in canine atopic dermatitis: microarray analysis.

    PubMed

    Merryman-Simpson, Annemarie E; Wood, Shona H; Fretwell, Neale; Jones, Paul G; McLaren, William M; McEwan, Neil A; Clements, Dylan N; Carter, Stuart D; Ollier, William E; Nuttall, Tim

    2008-04-01

    Genes potentially involved in the pathology of canine atopic dermatitis (AD) were identified using gene expression microarrays. Total RNA extracted from skin biopsies was hybridized to an Agilent Technologies custom-designed 22K canine array. The arrays were analysed using Genedata Analyst software. Data were corrected for multiple hypothesis testing and tested for significance using the National Institute on Aging array analysis tool. For comparison, data were divided into separate groups: lesional atopic (n = 16), nonlesional atopic (n = 17) and healthy controls (n = 9). Fifty-four genes were differentially expressed at a significance level of 0.05 in canine AD compared to healthy controls. Sixteen genes were differentially expressed in both nonlesional and lesional atopic skin, 26 genes only in nonlesional skin and 12 only in lesional skin. These genes were associated with innate immune and inflammatory responses, cell cycle, apoptosis, barrier formation and transcriptional regulation. The most dysregulated gene in lesional skin was S100A8, which showed an almost 23-fold increase in expression. This is a pro-inflammatory cytokine located in the epidermal differentiation complex. Microarray analysis is a novel technique in canine AD. Significant changes in gene expression were identified in atopic skin. These were relevant to skin barrier formation and the immune response, suggesting that they both participate in AD. Gene expression restricted to lesional skin may be involved in inflammatory changes, whereas those shared or restricted to nonlesional skin may reflect the atopic phenotype. Investigating gene polymorphisms in the targets identified in this study will help improve our understanding of the genetic basis of this disease. PMID:18336422

  11. Microarray analysis identifies candidate genes for key roles in coral development

    PubMed Central

    Grasso, Lauretta C; Maindonald, John; Rudd, Stephen; Hayward, David C; Saint, Robert; Miller, David J; Ball, Eldon E

    2008-01-01

    Background Anthozoan cnidarians are amongst the simplest animals at the tissue level of organization, but are surprisingly complex and vertebrate-like in terms of gene repertoire. As major components of tropical reef ecosystems, the stony corals are anthozoans of particular ecological significance. To better understand the molecular bases of both cnidarian development in general and coral-specific processes such as skeletogenesis and symbiont acquisition, microarray analysis was carried out through the period of early development – when skeletogenesis is initiated, and symbionts are first acquired. Results Of 5081 unique peptide coding genes, 1084 were differentially expressed (P ≤ 0.05) in comparisons between four different stages of coral development, spanning key developmental transitions. Genes of likely relevance to the processes of settlement, metamorphosis, calcification and interaction with symbionts were characterised further and their spatial expression patterns investigated using whole-mount in situ hybridization. Conclusion This study is the first large-scale investigation of developmental gene expression for any cnidarian, and has provided candidate genes for key roles in many aspects of coral biology, including calcification, metamorphosis and symbiont uptake. One surprising finding is that some of these genes have clear counterparts in higher animals but are not present in the closely-related sea anemone Nematostella. Secondly, coral-specific processes (i.e. traits which distinguish corals from their close relatives) may be analogous to similar processes in distantly related organisms. This first large-scale application of microarray analysis demonstrates the potential of this approach for investigating many aspects of coral biology, including the effects of stress and disease. PMID:19014561

  12. DNA microarray analysis of Staphylococcus aureus causing bloodstream infection: bacterial genes associated with mortality?

    PubMed

    Blomfeldt, A; Aamot, H V; Eskesen, A N; Monecke, S; White, R A; Leegaard, T M; Bjørnholt, J V

    2016-08-01

    Providing evidence for microbial genetic determinants' impact on outcome in Staphylococcus aureus bloodstream infections (SABSI) is challenging due to the complex and dynamic microbe-host interaction. Our recent population-based prospective study reported an association between the S. aureus clonal complex (CC) 30 genotype and mortality in SABSI patients. This follow-up investigation aimed to examine the genetic profiles of the SABSI isolates and test the hypothesis that specific genetic characteristics in S. aureus are associated with mortality. SABSI isolates (n = 305) and S. aureus CC30 isolates from asymptomatic nasal carriers (n = 38) were characterised by DNA microarray analysis and spa typing. Fisher's exact test, least absolute shrinkage and selection operator (LASSO) and elastic net regressions were performed to discern within four groups defined by patient outcome and characteristics. No specific S. aureus genetic determinants were found to be associated with mortality in SABSI patients. By applying LASSO and elastic net regressions, we found evidence suggesting that agrIII and cna were positively and setC (=selX) and seh were negatively associated with S. aureus CC30 versus non-CC30 isolates. The genes chp and sak, encoding immune evasion molecules, were found in higher frequencies in CC30 SABSI isolates compared to CC30 carrier isolates, indicating a higher virulence potential. In conclusion, no specific S. aureus genes were found to be associated with mortality by DNA microarray analysis and state-of-the-art statistical analyses. The next natural step is to test the hypothesis in larger samples with higher resolution methods, like whole genome sequencing.

  13. DNA Microarrays

    NASA Astrophysics Data System (ADS)

    Nguyen, C.; Gidrol, X.

    Genomics has revolutionised biological and biomedical research. This revolution was predictable on the basis of its two driving forces: the ever increasing availability of genome sequences and the development of new technology able to exploit them. Up until now, technical limitations meant that molecular biology could only analyse one or two parameters per experiment, providing relatively little information compared with the great complexity of the systems under investigation. This gene by gene approach is inadequate to understand biological systems containing several thousand genes. It is essential to have an overall view of the DNA, RNA, and relevant proteins. A simple inventory of the genome is not sufficient to understand the functions of the genes, or indeed the way that cells and organisms work. For this purpose, functional studies based on whole genomes are needed. Among these new large-scale methods of molecular analysis, DNA microarrays provide a way of studying the genome and the transcriptome. The idea of integrating a large amount of data derived from a support with very small area has led biologists to call these chips, borrowing the term from the microelectronics industry. At the beginning of the 1990s, the development of DNA chips on nylon membranes [1, 2], then on glass [3] and silicon [4] supports, made it possible for the first time to carry out simultaneous measurements of the equilibrium concentration of all the messenger RNA (mRNA) or transcribed RNA in a cell. These microarrays offer a wide range of applications, in both fundamental and clinical research, providing a method for genome-wide characterisation of changes occurring within a cell or tissue, as for example in polymorphism studies, detection of mutations, and quantitative assays of gene copies. With regard to the transcriptome, it provides a way of characterising differentially expressed genes, profiling given biological states, and identifying regulatory channels.

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

    NASA Astrophysics Data System (ADS)

    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.

  15. Outcome prediction based on microarray analysis: a critical perspective on methods

    PubMed Central

    Zervakis, Michalis; Blazadonakis, Michalis E; Tsiliki, Georgia; Danilatou, Vasiliki; Tsiknakis, Manolis; Kafetzopoulos, Dimitris

    2009-01-01

    Background Information extraction from microarrays has not yet been widely used in diagnostic or prognostic decision-support systems, due to the diversity of results produced by the available techniques, their instability on different data sets and the inability to relate statistical significance with biological relevance. Thus, there is an urgent need to address the statistical framework of microarray analysis and identify its drawbacks and limitations, which will enable us to thoroughly compare methodologies under the same experimental set-up and associate results with confidence intervals meaningful to clinicians. In this study we consider gene-selection algorithms with the aim to reveal inefficiencies in performance evaluation and address aspects that can reduce uncertainty in algorithmic validation. Results A computational study is performed related to the performance of several gene selection methodologies on publicly available microarray data. Three basic types of experimental scenarios are evaluated, i.e. the independent test-set and the 10-fold cross-validation (CV) using maximum and average performance measures. Feature selection methods behave differently under different validation strategies. The performance results from CV do not mach well those from the independent test-set, except for the support vector machines (SVM) and the least squares SVM methods. However, these wrapper methods achieve variable (often low) performance, whereas the hybrid methods attain consistently higher accuracies. The use of an independent test-set within CV is important for the evaluation of the predictive power of algorithms. The optimal size of the selected gene-set also appears to be dependent on the evaluation scheme. The consistency of selected genes over variation of the training-set is another aspect important in reducing uncertainty in the evaluation of the derived gene signature. In all cases the presence of outlier samples can seriously affect algorithmic

  16. Diagnostic Yield of Chromosomal Microarray Analysis in a Cohort of Patients with Autism Spectrum Disorders from a Highly Consanguineous Population

    ERIC Educational Resources Information Center

    Al-Mamari, Watfa; Al-Saegh, Abeer; Al-Kindy, Adila; Bruwer, Zandre; Al-Murshedi, Fathiya; Al-Thihli, Khalid

    2015-01-01

    Autism Spectrum Disorders are a complicated group of disorders characterized with heterogeneous genetic etiologies. The genetic investigations for this group of disorders have expanded considerably over the past decade. In our study we designed a tired approach and studied the diagnostic yield of chromosomal microarray analysis on patients…

  17. Transcriptional analysis of the innate immune response using the avian innate immunity microarray

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The avian innate immunity microarray (AIIM) is a genomics tool designed to study the transcriptional activity of the avian immune response (Cytogenet. Genome Res. 117:139-145, 2007). It is an avian cDNA microarray representing 4,959 avian genes spotted in triplicate. The AIIM contains 25 avian int...

  18. GSVA: gene set variation analysis for microarray and RNA-Seq data

    PubMed Central

    2013-01-01

    Background Gene set enrichment (GSE) analysis is a popular framework for condensing information from gene expression profiles into a pathway or signature summary. The strengths of this approach over single gene analysis include noise and dimension reduction, as well as greater biological interpretability. As molecular profiling experiments move beyond simple case-control studies, robust and flexible GSE methodologies are needed that can model pathway activity within highly heterogeneous data sets. Results To address this challenge, we introduce Gene Set Variation Analysis (GSVA), a GSE method that estimates variation of pathway activity over a sample population in an unsupervised manner. We demonstrate the robustness of GSVA in a comparison with current state of the art sample-wise enrichment methods. Further, we provide examples of its utility in differential pathway activity and survival analysis. Lastly, we show how GSVA works analogously with data from both microarray and RNA-seq experiments. Conclusions GSVA provides increased power to detect subtle pathway activity changes over a sample population in comparison to corresponding methods. While GSE methods are generally regarded as end points of a bioinformatic analysis, GSVA constitutes a starting point to build pathway-centric models of biology. Moreover, GSVA contributes to the current need of GSE methods for RNA-seq data. GSVA is an open source software package for R which forms part of the Bioconductor project and can be downloaded at http://www.bioconductor.org. PMID:23323831

  19. Microarray analysis in rat liver slices correctly predicts in vivo hepatotoxicity

    SciTech Connect

    Elferink, M.G.L. Olinga, P.; Draaisma, A.L.; Merema, M.T.; Bauerschmidt, S.; Polman, J.; Schoonen, W.G.; Groothuis, G.M.M.

    2008-06-15

    The microarray technology, developed for the simultaneous analysis of a large number of genes, may be useful for the detection of toxicity in an early stage of the development of new drugs. The effect of different hepatotoxins was analyzed at the gene expression level in the rat liver both in vivo and in vitro. As in vitro model system the precision-cut liver slice model was used, in which all liver cell types are present in their natural architecture. This is important since drug-induced toxicity often is a multi-cellular process involving not only hepatocytes but also other cell types such as Kupffer and stellate cells. As model toxic compounds lipopolysaccharide (LPS, inducing inflammation), paracetamol (necrosis), carbon tetrachloride (CCl{sub 4}, fibrosis and necrosis) and gliotoxin (apoptosis) were used. The aim of this study was to validate the rat liver slice system as in vitro model system for drug-induced toxicity studies. The results of the microarray studies show that the in vitro profiles of gene expression cluster per compound and incubation time, and when analyzed in a commercial gene expression database, can predict the toxicity and pathology observed in vivo. Each toxic compound induces a specific pattern of gene expression changes. In addition, some common genes were up- or down-regulated with all toxic compounds. These data show that the rat liver slice system can be an appropriate tool for the prediction of multi-cellular liver toxicity. The same experiments and analyses are currently performed for the prediction of human specific toxicity using human liver slices.

  20. Microarray-based Analysis of Microbial Community RNAs by Whole Community RNA Amplification (WCRA)

    SciTech Connect

    Gao, Haichun; Yang, Zamin Koo; Gentry, Terry; Wu, Liyou; Schadt, Christopher Warren; Zhou, Jizhong

    2007-01-01

    A new approach, termed whole-community RNA amplification (WCRA), was developed to provide sufficient amounts of mRNAs from environmental samples for microarray analysis. This method employs fusion primers (six to nine random nucleotides with an attached T7 promoter) for the first-strand synthesis. The shortest primer (T7N6S) gave the best results in terms of the yield and representativeness of amplification. About 1,200- to 1,800-fold amplification was obtained with amounts of the RNA templates ranging from 10 to 100 ng, and very representative detection was obtained with 50 to 100 ng total RNA. Evaluation with a Shewanella oneidensis {Delta}fur strain revealed that the amplification method which we developed could preserve the original abundance relationships of mRNAs. In addition, to determine whether representative detection of RNAs can be achieved with mixed community samples, amplification biases were evaluated with a mixture containing equal quantities of RNAs (100 ng each) from four bacterial species, and representative amplification was also obtained. Finally, the method which we developed was applied to the active microbial populations in a denitrifying fluidized bed reactor used for denitrification of contaminated groundwater and ethanol-stimulated groundwater samples for uranium reduction. The genes expressed were consistent with the expected functions of the bioreactor and groundwater system, suggesting that this approach is useful for analyzing the functional activities of microbial communities. This is one of the first demonstrations that microarray-based technology can be used to successfully detect the activities of microbial communities from real environmental samples in a high-throughput fashion.

  1. Microarray analysis of female- and larval-specific gene expression in the horn fly (Diptera: Muscidae).

    PubMed

    Guerrero, Felix D; Dowd, Scot E; Sun, Yan; Saldivar, Leonel; Wiley, Graham B; Macmil, Simone L; Najar, Fares; Roe, Bruce A; Foil, Lane D

    2009-03-01

    The horn fly, Haematobia irritans L., is an obligate blood-feeding parasite of cattle, and control of this pest is a continuing problem because the fly is becoming resistant to pesticides. Dominant conditional lethal gene systems are being studied as population control technologies against agricultural pests. One of the components of these systems is a female-specific gene promoter that drives expression of a lethality-inducing gene. To identify candidate genes to supply this promoter, microarrays were designed from a horn fly expressed sequence tag (EST) database and probed to identify female-specific and larval-specific gene expression. Analysis of dye swap experiments found 432 and 417 transcripts whose expression levels were higher or lower in adult female flies, respectively, compared with adult male flies. Additionally, 419 and 871 transcripts were identified whose expression levels were higher or lower in first-instar larvae compared with adult flies, respectively. Three transcripts were expressed more highly in adult females flies compared with adult males and also higher in the first-instar larval lifestage compared with adult flies. One of these transcripts, a putative nanos ortholog, has a high female-to-male expression ratio, a moderate expression level in first-instar larvae, and has been well characterized in Drosophila. melanogaster (Meigen). In conclusion, we used microarray technology, verified by reverse transcriptase-polymerase chain reaction and massively parallel pyrosequencing, to study life stage- and sex-specific gene expression in the horn fly and identified three gene candidates for detailed evaluation as a gene promoter source for the development of a female-specific conditional lethality system.

  2. Molecular Features of Triple Negative Breast Cancer: Microarray Evidence and Further Integrated Analysis

    PubMed Central

    Chen, Weicai; Wu, Huisheng; Yuan, Zishan; Wang, Kun; Li, Guojin; Sun, Jie; Yu, Limin

    2015-01-01

    Purpose Breast cancer is a heterogeneous disease usually including four molecular subtypes such as luminal A, luminal B, HER2-enriched, and triple-negative breast cancer (TNBC). TNBC is more aggressive than other breast cancer subtypes. Despite major advances in ER-positive or HER2-amplified breast cancer, there is no targeted agent currently available for TNBC, so it is urgent to identify new potential therapeutic targets for TNBC. Methods We first used microarray analysis to compare gene expression profiling between TNBC and non-TNBC. Furthermore an integrated analysis was conducted based on our own and published data, leading to more robust, reproducible and accurate predictions. Additionally, we performed qRT-PCR in breast cancer cell lines to verify the findings in integrated analysis. Results After searching Gene Expression Omnibus database (GEO), two microarray studies were obtained according to the inclusion criteria. The integrated analysis was conducted, including 30 samples of TNBC and 77 samples of non-TNBC. 556 genes were found to be consistently differentially expressed (344 up-regulated genes and 212 down-regulated genes in TNBC). Functional annotation for these differentially expressed genes (DEGs) showed that the most significantly enriched Gene Ontology (GO) term for molecular functions was protein binding (GO: 0005515, P = 6.09E-21), while that for biological processes was signal transduction (GO: 0007165, P = 9.46E-08), and that for cellular component was cytoplasm (GO: 0005737, P = 2.09E-21). The most significant pathway was Pathways in cancer (P = 6.54E-05) based on Kyoto Encyclopedia of Genes and Genomes (KEGG). DUSP1 (Degree = 21), MYEOV2 (Degree = 15) and UQCRQ (Degree = 14) were identified as the significant hub proteins in the protein-protein interaction (PPI) network. Five genes were selected to perform qRT-PCR in seven breast cancer cell lines, and qRT-PCR results showed that the expression pattern of selected genes in TNBC lines and

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

    PubMed Central

    Neerincx, Pieter BT; Casel, Pierrot; Prickett, Dennis; Nie, Haisheng; Watson, Michael; Leunissen, Jack AM; Groenen, Martien AM; Klopp, Christophe

    2009-01-01

    Background Reliable annotation linking oligonucleotide probes to target genes is essential for functional biological analysis of microarray experiments. We used the IMAD, OligoRAP and sigReannot pipelines to update the annotation for the ARK-Genomics Chicken 20 K array as part of a joined EADGENE/SABRE workshop. In this manuscript we compare their annotation strategies and results. Furthermore, we analyse the effect of differences in updated annotation on functional analysis for an experiment involving Eimeria infected chickens and finally we propose guidelines for optimal annotation strategies. Results IMAD, OligoRAP and sigReannot update both annotation and estimated target specificity. The 3 pipelines can assign oligos to target specificity categories although with varying degrees of resolution. Target specificity is judged based on the amount and type of oligo versus target-gene alignments (hits), which are determined by filter thresholds that users can adjust based on their experimental conditions. Linking oligos to annotation on the other hand is based on rigid rules, which differ between pipelines. For 52.7% of the oligos from a subset selected for in depth comparison all pipelines linked to one or more Ensembl genes with consensus on 44.0%. In 31.0% of the cases none of the pipelines could assign an Ensembl gene to an oligo and for the remaining 16.3% the coverage differed between pipelines. Differences in updated annotation were mainly due to different thresholds for hybridisation potential filtering of oligo versus target-gene alignments and different policies for expanding annotation using indirect links. The differences in updated annotation packages had a significant effect on GO term enrichment analysis with consensus on only 67.2% of the enriched terms. Conclusion In addition to flexible thresholds to determine target specificity, annotation tools should provide metadata describing the relationships between oligos and the annotation assigned to them

  4. Identification of several hub-genes associated with periodontitis using integrated microarray analysis

    PubMed Central

    GUO, XINXING; WANG, YILING; WANG, CHUNLING; CHEN, JING

    2015-01-01

    The aim of the present study was to identify differentially expressed genes and biological processes associated with periodontitis. In this study, the most significant 200 differentially expressed genes associated with periodontitis were identified using integrated analysis of multiple microarray data in combination with screening for genome-wide relative significance and genome-wide global significance. Gene Ontology (GO) enrichment analysis and pathway analysis were performed using the GO website and Kyoto Encyclopedia of Genes and Genomes (KEGG). A protein-protein interaction (PPI) network was constructed based on the Search Tool for the Retrieval of Interacting Genes/Proteins. The top 200 differentially expressed genes were found to be highly associated with periodontitis. GO enrichment analyses revealed that the identified genes were significantly enriched in terms of response to organic substance, response to wounding and cell migration. The most common term of the KEGG pathway was cytokine-cytokine receptor interaction. PPI network analysis indicated that interleukin (IL)8, IL1β, vascular endothelial growth factor A, intercellular adhesion molecule 1, PTGS2 and CXCL10 were hub genes, which formed numerous interactions with several genes. In conclusion, the present study identified numerous genes that were differentially expressed in periodontitis, as well as determined the biological pathways and PPI network associated with those genes. PMID:25483140

  5. A note on joint versus gene-specific mixed model analysis of microarray gene expression data.

    PubMed

    Hoeschele, Ina; Li, Hua

    2005-04-01

    Currently, linear mixed model analyses of expression microarray experiments are performed either in a gene-specific or global mode. The joint analysis provides more flexibility in terms of how parameters are fitted and estimated and tends to be more powerful than the gene-specific analysis. Here we show how to implement the gene-specific linear mixed model analysis as an exact algorithm for the joint linear mixed model analysis. The gene-specific algorithm is exact, when the mixed model equations can be partitioned into unrelated components: One for all global fixed and random effects and the others for the gene-specific fixed and random effects for each gene separately. This unrelatedness holds under three conditions: (1) any gene must have the same number of replicates or probes on all arrays, but these numbers can differ among genes; (2) the residual variance of the (transformed) expression data must be homogeneous or constant across genes (other variance components need not be homogeneous) and (3) the number of genes in the experiment is large. When these conditions are violated, the gene-specific algorithm is expected to be nearly exact.

  6. Chaperone network composition in Solanum lycopersicum explored by transcriptome profiling and microarray meta-analysis.

    PubMed

    Fragkostefanakis, Sotirios; Simm, Stefan; Paul, Puneet; Bublak, Daniela; Scharf, Klaus-Dieter; Schleiff, Enrico

    2015-04-01

    Heat shock proteins (Hsps) are molecular chaperones primarily involved in maintenance of protein homeostasis. Their function has been best characterized in heat stress (HS) response during which Hsps are transcriptionally controlled by HS transcription factors (Hsfs). The role of Hsfs and Hsps in HS response in tomato was initially examined by transcriptome analysis using the massive analysis of cDNA ends (MACE) method. Approximately 9.6% of all genes expressed in leaves are enhanced in response to HS, including a subset of Hsfs and Hsps. The underlying Hsp-Hsf networks with potential functions in stress responses or developmental processes were further explored by meta-analysis of existing microarray datasets. We identified clusters with differential transcript profiles with respect to abiotic stresses, plant organs and developmental stages. The composition of two clusters points towards two major chaperone networks. One cluster consisted of constitutively expressed plastidial chaperones and other genes involved in chloroplast protein homeostasis. The second cluster represents genes strongly induced by heat, drought and salinity stress, including HsfA2 and many stress-inducible chaperones, but also potential targets of HsfA2 not related to protein homeostasis. This observation attributes a central regulatory role to HsfA2 in controlling different aspects of abiotic stress response and tolerance in tomato. PMID:25124075

  7. VennMaster: Area-proportional Euler diagrams for functional GO analysis of microarrays

    PubMed Central

    Kestler, Hans A; Müller, André; Kraus, Johann M; Buchholz, Malte; Gress, Thomas M; Liu, Hongfang; Kane, David W; Zeeberg, Barry R; Weinstein, John N

    2008-01-01

    Background Microarray experiments generate vast amounts of data. The functional context of differentially expressed genes can be assessed by querying the Gene Ontology (GO) database via GoMiner. Directed acyclic graph representations, which are used to depict GO categories enriched with differentially expressed genes, are difficult to interpret and, depending on the particular analysis, may not be well suited for formulating new hypotheses. Additional graphical methods are therefore needed to augment the GO graphical representation. Results We present an alternative visualization approach, area-proportional Euler diagrams, showing set relationships with semi-quantitative size information in a single diagram to support biological hypothesis formulation. The cardinalities of sets and intersection sets are represented by area-proportional Euler diagrams and their corresponding graphical (circular or polygonal) intersection areas. Optimally proportional representations are obtained using swarm and evolutionary optimization algorithms. Conclusion VennMaster's area-proportional Euler diagrams effectively structure and visualize the results of a GO analysis by indicating to what extent flagged genes are shared by different categories. In addition to reducing the complexity of the output, the visualizations facilitate generation of novel hypotheses from the analysis of seemingly unrelated categories that share differentially expressed genes. PMID:18230172

  8. Cancer Classification in Microarray Data using a Hybrid Selective Independent Component Analysis and υ-Support Vector Machine Algorithm.

    PubMed

    Saberkari, Hamidreza; Shamsi, Mousa; Joroughi, Mahsa; Golabi, Faegheh; Sedaaghi, Mohammad Hossein

    2014-10-01

    Microarray data have an important role in identification and classification of the cancer tissues. Having a few samples of microarrays in cancer researches is always one of the most concerns which lead to some problems in designing the classifiers. For this matter, preprocessing gene selection techniques should be utilized before classification to remove the noninformative genes from the microarray data. An appropriate gene selection method can significantly improve the performance of cancer classification. In this paper, we use selective independent component analysis (SICA) for decreasing the dimension of microarray data. Using this selective algorithm, we can solve the instability problem occurred in the case of employing conventional independent component analysis (ICA) methods. First, the reconstruction error and selective set are analyzed as independent components of each gene, which have a small part in making error in order to reconstruct new sample. Then, some of the modified support vector machine (υ-SVM) algorithm sub-classifiers are trained, simultaneously. Eventually, the best sub-classifier with the highest recognition rate is selected. The proposed algorithm is applied on three cancer datasets (leukemia, breast cancer and lung cancer datasets), and its results are compared with other existing methods. The results illustrate that the proposed algorithm (SICA + υ-SVM) has higher accuracy and validity in order to increase the classification accuracy. Such that, our proposed algorithm exhibits relative improvements of 3.3% in correctness rate over ICA + SVM and SVM algorithms in lung cancer dataset.

  9. Cancer Classification in Microarray Data using a Hybrid Selective Independent Component Analysis and υ-Support Vector Machine Algorithm

    PubMed Central

    Saberkari, Hamidreza; Shamsi, Mousa; Joroughi, Mahsa; Golabi, Faegheh; Sedaaghi, Mohammad Hossein

    2014-01-01

    Microarray data have an important role in identification and classification of the cancer tissues. Having a few samples of microarrays in cancer researches is always one of the most concerns which lead to some problems in designing the classifiers. For this matter, preprocessing gene selection techniques should be utilized before classification to remove the noninformative genes from the microarray data. An appropriate gene selection method can significantly improve the performance of cancer classification. In this paper, we use selective independent component analysis (SICA) for decreasing the dimension of microarray data. Using this selective algorithm, we can solve the instability problem occurred in the case of employing conventional independent component analysis (ICA) methods. First, the reconstruction error and selective set are analyzed as independent components of each gene, which have a small part in making error in order to reconstruct new sample. Then, some of the modified support vector machine (υ-SVM) algorithm sub-classifiers are trained, simultaneously. Eventually, the best sub-classifier with the highest recognition rate is selected. The proposed algorithm is applied on three cancer datasets (leukemia, breast cancer and lung cancer datasets), and its results are compared with other existing methods. The results illustrate that the proposed algorithm (SICA + υ-SVM) has higher accuracy and validity in order to increase the classification accuracy. Such that, our proposed algorithm exhibits relative improvements of 3.3% in correctness rate over ICA + SVM and SVM algorithms in lung cancer dataset. PMID:25426433

  10. Comparative study of joint analysis of microarray gene expression data in survival prediction and risk assessment of breast cancer patients.

    PubMed

    Yasrebi, Haleh

    2016-09-01

    Microarray gene expression data sets are jointly analyzed to increase statistical power. They could either be merged together or analyzed by meta-analysis. For a given ensemble of data sets, it cannot be foreseen which of these paradigms, merging or meta-analysis, works better. In this article, three joint analysis methods, Z-score normalization, ComBat and the inverse normal method (meta-analysis) were selected for survival prognosis and risk assessment of breast cancer patients. The methods were applied to eight microarray gene expression data sets, totaling 1324 patients with two clinical endpoints, overall survival and relapse-free survival. The performance derived from the joint analysis methods was evaluated using Cox regression for survival analysis and independent validation used as bias estimation. Overall, Z-score normalization had a better performance than ComBat and meta-analysis. Higher Area Under the Receiver Operating Characteristic curve and hazard ratio were also obtained when independent validation was used as bias estimation. With a lower time and memory complexity, Z-score normalization is a simple method for joint analysis of microarray gene expression data sets. The derived findings suggest further assessment of this method in future survival prediction and cancer classification applications.

  11. A novel mechanism of gall midge resistance in the rice variety Kavya revealed by microarray analysis.

    PubMed

    Rawat, Nidhi; Chiruvuri Naga, Neeraja; Raman Meenakshi, Sundaram; Nair, Suresh; Bentur, Jagadish S

    2012-06-01

    The Asian rice gall midge [Orseolia oryzae (Wood-Mason)] is an important rice pest causing an annual average yield loss of about US $80 million in India. Rice varieties possess several discrete resistance (R) genes conferring resistance against the pest in two distinct ways, i.e., with (HR+ type) or without (HR- type) the expression of hypersensitive reaction (HR). The aim of the present work is to understand the molecular basis of compatible and incompatible (HR- type) rice gall midge interactions between the rice variety Kavya and the two gall midge biotypes: the virulent GMB4M and the avirulent GMB1 using transcriptional microarray gene expression analysis. A large number of differentially expressed genes (602genes in incompatible interaction and 1,330 genes in compatible interaction with at least twofold changes, p value <0.05) was obtained from the microarray analysis that could be grouped into six clusters based on their induction during both or either of the interactions. MapMan software was used for functional characterization of these genes into 13 categories (BINs). Real-time polymerase chain reaction validation of 26 genes selected through the analysis revealed four genes viz. NADPH oxidase, AtrbohF, cinnamoyl-CoA reductase, and von Willebrand factor type A domain containing protein coding genes to be significantly upregulated during the incompatible interaction. But most of the signature genes related to HR+ type resistance like salicylic acid pathway-related genes and disease resistance protein coding genes were downregulated. On the other hand, during the compatible interaction, genes related to primary metabolism and nutrient transport were upregulated and genes for defense and signaling were downregulated. We propose a hypothesis that HR- type of resistance in the rice variety Kavya against gall midge could be due to the constitutive expression of an R gene and a case of extreme resistance which is devoid of cell death. Compatible interaction

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

    PubMed Central

    Honders, M. W.; Kremer, A. N.; van Kooten, C.; Out, C.; Hiemstra, P. S.; de Boer, H. C.; Jager, M. J.; Schmelzer, E.; Vries, R. G.; Al Hinai, A. S.; Kroes, W. G.; Monajemi, R.; Goeman, J. J.; Böhringer, S.; Marijt, W. A. F.; Falkenburg, J. H. F.; Griffioen, M.

    2016-01-01

    Cellular immunotherapy has proven to be effective in the treatment of hematological cancers by donor lymphocyte infusion after allogeneic hematopoietic stem cell transplantation and more recently by targeted therapy with chimeric antigen or T-cell receptor-engineered T cells. However, dependent on the tissue distribution of the antigens that are targeted, anti-tumor responses can be accompanied by undesired side effects. Therefore, detailed tissue distribution analysis is essential to estimate potential efficacy and toxicity of candidate targets for immunotherapy of hematological malignancies. We performed microarray gene expression analysis of hematological malignancies of different origins, healthy hematopoietic cells and various non-hematopoietic cell types from organs that are often targeted in detrimental immune responses after allogeneic stem cell transplantation leading to graft-versus-host disease. Non-hematopoietic cells were also cultured in the presence of IFN-γ to analyze gene expression under inflammatory circumstances. Gene expression was investigated by Illumina HT12.0 microarrays and quality control analysis was performed to confirm the cell-type origin and exclude contamination of non-hematopoietic cell samples with peripheral blood cells. Microarray data were validated by quantitative RT-PCR showing strong correlations between both platforms. Detailed gene expression profiles were generated for various minor histocompatibility antigens and B-cell surface antigens to illustrate the value of the microarray dataset to estimate efficacy and toxicity of candidate targets for immunotherapy. In conclusion, our microarray database provides a relevant platform to analyze and select candidate antigens with hematopoietic (lineage)-restricted expression as potential targets for immunotherapy of hematological cancers. PMID:27171398

  13. Gene set enrichment analysis of microarray data from Pimephales promelas (Rafinesque), a non-mammalian model organism

    PubMed Central

    2011-01-01

    Background Methods for gene-class testing, such as Gene Set Enrichment Analysis (GSEA), incorporate biological knowledge into the analysis and interpretation of microarray data by comparing gene expression patterns to pathways, systems and emergent phenotypes. However, to use GSEA to its full capability with non-mammalian model organisms, a microarray platform must be annotated with human gene symbols. Doing so enables the ability to relate a model organism's gene expression, in response to a given treatment, to potential human health consequences of that treatment. We enhanced the annotation of a microarray platform from a non-mammalian model organism, and then used the GSEA approach in a reanalysis of a study examining the biological significance of acute and chronic methylmercury exposure on liver tissue of fathead minnow (Pimephales promelas). Using GSEA, we tested the hypothesis that fathead livers, in response to methylmercury exposure, would exhibit gene expression patterns similar to diseased human livers. Results We describe an enhanced annotation of the fathead minnow microarray platform with human gene symbols. This resource is now compatible with the GSEA approach for gene-class testing. We confirmed that GSEA, using this enhanced microarray platform, is able to recover results consistent with a previous analysis of fathead minnow exposure to methylmercury using standard analytical approaches. Using GSEA to compare fathead gene expression profiles to human phenotypes, we also found that fathead methylmercury-treated livers exhibited expression profiles that are homologous to human systems & pathways and results in damage that is similar to those of human liver damage associated with hepatocellular carcinoma and hepatitis B. Conclusions This study describes a powerful resource for enabling the use of non-mammalian model organisms in the study of human health significance. Results of microarray gene expression studies involving fathead minnow, typically

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

    PubMed

    Paraboschi, Elvezia Maria; Cardamone, Giulia; Rimoldi, Valeria; Gemmati, Donato; Spreafico, Marta; Duga, Stefano; Soldà, Giulia; Asselta, Rosanna

    2015-09-30

    Abnormalities in RNA metabolism and alternative splicing (AS) are emerging as important players in complex disease phenotypes. In particular, accumulating evidence suggests the existence of pathogenic links between multiple sclerosis (MS) and altered AS, including functional studies showing that an imbalance in alternatively-spliced isoforms may contribute to disease etiology. Here, we tested whether the altered expression of AS-related genes represents a MS-specific signature. A comprehensive comparative analysis of gene expression profiles of publicly-available microarray datasets (190 MS cases, 182 controls), followed by gene-ontology enrichment analysis, highlighted a significant enrichment for differentially-expressed genes involved in RNA metabolism/AS. In detail, a total of 17 genes were found to be differentially expressed in MS in multiple datasets, with CELF1 being dysregulated in five out of seven studies. We confirmed CELF1 downregulation in MS (p=0.0015) by real-time RT-PCRs on RNA extracted from blood cells of 30 cases and 30 controls. As a proof of concept, we experimentally verified the unbalance in alternatively-spliced isoforms in MS of the NFAT5 gene, a putative CELF1 target. In conclusion, for the first time we provide evidence of a consistent dysregulation of splicing-related genes in MS and we discuss its possible implications in modulating specific AS events in MS susceptibility genes.

  15. Multi-tissue microarray analysis identifies a molecular signature of regeneration.

    PubMed

    Mercer, Sarah E; Cheng, Chia-Ho; Atkinson, Donald L; Krcmery, Jennifer; Guzman, Claudia E; Kent, David T; Zukor, Katherine; Marx, Kenneth A; Odelberg, Shannon J; Simon, Hans-Georg

    2012-01-01

    The inability to functionally repair tissues that are lost as a consequence of disease or injury remains a significant challenge for regenerative medicine. The molecular and cellular processes involved in complete restoration of tissue architecture and function are expected to be complex and remain largely unknown. Unlike humans, certain salamanders can completely regenerate injured tissues and lost appendages without scar formation. A parsimonious hypothesis would predict that all of these regenerative activities are regulated, at least in part, by a common set of genes. To test this hypothesis and identify genes that might control conserved regenerative processes, we performed a comprehensive microarray analysis of the early regenerative response in five regeneration-competent tissues from the newt Notophthalmus viridescens. Consistent with this hypothesis, we established a molecular signature for regeneration that consists of common genes or gene family members that exhibit dynamic differential regulation during regeneration in multiple tissue types. These genes include members of the matrix metalloproteinase family and its regulators, extracellular matrix components, genes involved in controlling cytoskeleton dynamics, and a variety of immune response factors. Gene Ontology term enrichment analysis validated and supported their functional activities in conserved regenerative processes. Surprisingly, dendrogram clustering and RadViz classification also revealed that each regenerative tissue had its own unique temporal expression profile, pointing to an inherent tissue-specific regenerative gene program. These new findings demand a reconsideration of how we conceptualize regenerative processes and how we devise new strategies for regenerative medicine.

  16. Multi-Tissue Microarray Analysis Identifies a Molecular Signature of Regeneration

    PubMed Central

    Mercer, Sarah E.; Cheng, Chia-Ho; Atkinson, Donald L.; Krcmery, Jennifer; Guzman, Claudia E.; Kent, David T.; Zukor, Katherine; Marx, Kenneth A.; Odelberg, Shannon J.; Simon, Hans-Georg

    2012-01-01

    The inability to functionally repair tissues that are lost as a consequence of disease or injury remains a significant challenge for regenerative medicine. The molecular and cellular processes involved in complete restoration of tissue architecture and function are expected to be complex and remain largely unknown. Unlike humans, certain salamanders can completely regenerate injured tissues and lost appendages without scar formation. A parsimonious hypothesis would predict that all of these regenerative activities are regulated, at least in part, by a common set of genes. To test this hypothesis and identify genes that might control conserved regenerative processes, we performed a comprehensive microarray analysis of the early regenerative response in five regeneration-competent tissues from the newt Notophthalmus viridescens. Consistent with this hypothesis, we established a molecular signature for regeneration that consists of common genes or gene family members that exhibit dynamic differential regulation during regeneration in multiple tissue types. These genes include members of the matrix metalloproteinase family and its regulators, extracellular matrix components, genes involved in controlling cytoskeleton dynamics, and a variety of immune response factors. Gene Ontology term enrichment analysis validated and supported their functional activities in conserved regenerative processes. Surprisingly, dendrogram clustering and RadViz classification also revealed that each regenerative tissue had its own unique temporal expression profile, pointing to an inherent tissue-specific regenerative gene program. These new findings demand a reconsideration of how we conceptualize regenerative processes and how we devise new strategies for regenerative medicine. PMID:23300656

  17. A meta analysis of pancreatic microarray datasets yields new targets as cancer genes and biomarkers.

    PubMed

    Goonesekere, Nalin C W; Wang, Xiaosheng; Ludwig, Lindsey; Guda, Chittibabu

    2014-01-01

    The lack of specific symptoms at early tumor stages, together with a high biological aggressiveness of the tumor contribute to the high mortality rate for pancreatic cancer (PC), which has a five year survival rate of less than 5%. Improved screening for earlier diagnosis, through the detection of diagnostic and prognostic biomarkers provides the best hope of increasing the rate of curatively resectable carcinomas. Though many serum markers have been reported to be elevated in patients with PC, so far, most of these markers have not been implemented into clinical routine due to low sensitivity or specificity. In this study, we have identified genes that are significantly upregulated in PC, through a meta-analysis of large number of microarray datasets. We demonstrate that the biological functions ascribed to these genes are clearly associated with PC and metastasis, and that that these genes exhibit a strong link to pathways involved with inflammation and the immune response. This investigation has yielded new targets for cancer genes, and potential biomarkers for pancreatic cancer. The candidate list of cancer genes includes protein kinase genes, new members of gene families currently associated with PC, as well as genes not previously linked to PC. In this study, we are also able to move towards developing a signature for hypomethylated genes, which could be useful for early detection of PC. We also show that the significantly upregulated 800+ genes in our analysis can serve as an enriched pool for tissue and serum protein biomarkers in pancreatic cancer.

  18. Transcriptomic profiling of long non-coding RNAs in dermatomyositis by microarray analysis

    PubMed Central

    Peng, Qing-Lin; Zhang, Ya-Mei; Yang, Han-Bo; Shu, Xiao-Ming; Lu, Xin; Wang, Guo-Chun

    2016-01-01

    Long non-coding RNAs (lncRNAs) are prevalently transcribed in the genome and have been found to be of functional importance. However, the potential roles of lncRNAs in dermatomyositis (DM) remain unknown. In this study, a lncRNA + mRNA microarray analysis was performed to profile lncRNAs and mRNAs from 15 treatment-naive DM patients and 5 healthy controls. We revealed a total of 1198 lncRNAs (322 up-regulated and 876 down-regulated) and 1213 mRNAs (665 up-regulated and 548 down-regulated) were significantly differentially expressed in DM patients compared with the healthy controls (fold change>2, P < 0.05). Subgrouping DM patients according to the presence of interstitial lung disease and anti-Jo-1 antibody revealed different expression patterns of the lncRNAs. Pathway and gene ontology analysis for the differentially expressed mRNAs confirmed that type 1 interferon signaling was the most significantly dysregulated pathway in all DM subgroups. In addition, distinct pathways that uniquely associated with DM subgroup were also identified. Bioinformatics prediction suggested that linc-DGCR6-1 may be a lncRNA that regulates type 1 interferon-inducible gene USP18, which was found highly expressed in the perifascicular areas of the muscle fibers of DM patients. Our findings provide an overview of aberrantly expressed lncRNAs in DM muscle and further broaden the understanding of DM pathogenesis. PMID:27605457

  19. Recent advances in i-Gene tools and analysis: microarrays, next generation sequencing and mass spectrometry.

    PubMed

    Moorhouse, Michael J; Sharma, Hari S

    2011-08-01

    Recent advances in technology and associated methodology have made the current period one of the most exciting in molecular biology and medicine. Underlying these is an appreciation that modern research is driven by increasing large amounts of data being interpreted by interdisciplinary collaborative teams which are often geographically dispersed. The availability of cheap computing power, high speed informatics networks and high quality analysis software has been essential to this as has the application of modern quality assurance methodologies. In this review, we discuss the application of modern 'High-Throughput' molecular biological technologies such as 'Microarrays' and 'Next Generation Sequencing' to scientific and biomedical research as we have observed. Furthermore in this review, we also offer some guidance that enables the reader as to understand certain features of these as well as new strategies and help them to apply these i-Gene tools in their endeavours successfully. Collectively, we term this 'i-Gene Analysis'. We also offer predictions as to the developments that are anticipated in the near and more distant future.

  20. Variance component estimation for mixed model analysis of cDNA microarray data.

    PubMed

    Sarholz, Barbara; Piepho, Hans-Peter

    2008-12-01

    Microarrays provide a valuable tool for the quantification of gene expression. Usually, however, there is a limited number of replicates leading to unsatisfying variance estimates in a gene-wise mixed model analysis. As thousands of genes are available, it is desirable to combine information across genes. When more than two tissue types or treatments are to be compared it might be advisable to consider the array effect as random. Then information between arrays may be recovered, which can increase accuracy in estimation. We propose a method of variance component estimation across genes for a linear mixed model with two random effects. The method may be extended to models with more than two random effects. We assume that the variance components follow a log-normal distribution. Assuming that the sums of squares from the gene-wise analysis, given the true variance components, follow a scaled chi(2)-distribution, we adopt an empirical Bayes approach. The variance components are estimated by the expectation of their posterior distribution. The new method is evaluated in a simulation study. Differentially expressed genes are more likely to be detected by tests based on these variance estimates than by tests based on gene-wise variance estimates. This effect is most visible in studies with small array numbers. Analyzing a real data set on maize endosperm the method is shown to work well. PMID:19035549

  1. Expression profiling of potato cultivars with contrasting tuberization at elevated temperature using microarray analysis.

    PubMed

    Singh, Anupama; Siddappa, Sunderasha; Bhardwaj, Vinay; Singh, Brajesh; Kumar, Devendra; Singh, Bir Pal

    2015-12-01

    Temperature is one of the most significant factors affecting potato yield. Night temperature beyond 18-22 °C drastically reduces tuber formation, constraining potato cultivation in tropics and subtropics. Identification of genes and pathways affected by high temperature is crucial for developing thermo tolerant cultivars for these regions. In the present study, two cultivars with contrasting tuberization behavior at night temperatures (24 °C) were selected for gene expression analysis using a customized microarray chip representing 39,031 potato genes. A total of 2500 genes were differentially expressed on 21 d and 4096 genes on 14 d after stress. Gene ontology and pathway analysis provided insights into the probable biological processes and pathways governing tuberization at elevated temperature. Pathway maps were constructed to graphically represent the gene expression patterns. Genes associated with photosynthesis, hormonal activity, sugar transporters and transcription factors were differentially expressed. The results are presented and discussed in terms of tuberization at high temperature. The effect of high temperature on expression of genes controlling tuberization was also analyzed. This study provided useful information on potato tuberization at elevated temperature and make available a framework for further investigations into heat stress in potato.

  2. A comprehensive comparison of different clustering methods for reliability analysis of microarray data.

    PubMed

    Kafieh, Rahele; Mehridehnavi, Alireza

    2013-01-01

    In this study, we considered some competitive learning methods including hard competitive learning and soft competitive learning with/without fixed network dimensionality for reliability analysis in microarrays. In order to have a more extensive view, and keeping in mind that competitive learning methods aim at error minimization or entropy maximization (different kinds of function optimization), we decided to investigate the abilities of mixture decomposition schemes. Therefore, we assert that this study covers the algorithms based on function optimization with particular insistence on different competitive learning methods. The destination is finding the most powerful method according to a pre-specified criterion determined with numerical methods and matrix similarity measures. Furthermore, we should provide an indication showing the intrinsic ability of the dataset to form clusters before we apply a clustering algorithm. Therefore, we proposed Hopkins statistic as a method for finding the intrinsic ability of a data to be clustered. The results show the remarkable ability of Rayleigh mixture model in comparison with other methods in reliability analysis task.

  3. A Comprehensive Comparison of Different Clustering Methods for Reliability Analysis of Microarray Data

    PubMed Central

    Kafieh, Rahele; Mehridehnavi, Alireza

    2013-01-01

    In this study, we considered some competitive learning methods including hard competitive learning and soft competitive learning with/without fixed network dimensionality for reliability analysis in microarrays. In order to have a more extensive view, and keeping in mind that competitive learning methods aim at error minimization or entropy maximization (different kinds of function optimization), we decided to investigate the abilities of mixture decomposition schemes. Therefore, we assert that this study covers the algorithms based on function optimization with particular insistence on different competitive learning methods. The destination is finding the most powerful method according to a pre-specified criterion determined with numerical methods and matrix similarity measures. Furthermore, we should provide an indication showing the intrinsic ability of the dataset to form clusters before we apply a clustering algorithm. Therefore, we proposed Hopkins statistic as a method for finding the intrinsic ability of a data to be clustered. The results show the remarkable ability of Rayleigh mixture model in comparison with other methods in reliability analysis task. PMID:24083134

  4. Hyperspectral microscopic analysis of normal, benign and carcinoma microarray tissue sections

    NASA Astrophysics Data System (ADS)

    Maggioni, Mauro; Davis, Gustave L.; Warner, Frederick J.; Geshwind, Frank B.; Coppi, Andreas C.; DeVerse, Richard A.; Coifman, Ronald R.

    2006-02-01

    We apply a unique micro-optoelectromechanical tuned light source and new algorithms to the hyper-spectral microscopic analysis of human colon biopsies. The tuned light prototype (Plain Sight Systems Inc.) transmits any combination of light frequencies, range 440nm 700nm, trans-illuminating H and E stained tissue sections of normal (N), benign adenoma (B) and malignant carcinoma (M) colon biopsies, through a Nikon Biophot microscope. Hyper-spectral photomicrographs, randomly collected 400X magnication, are obtained with a CCD camera (Sensovation) from 59 different patient biopsies (20 N, 19 B, 20 M) mounted as a microarray on a single glass slide. The spectra of each pixel are normalized and analyzed to discriminate among tissue features: gland nuclei, gland cytoplasm and lamina propria/lumens. Spectral features permit the automatic extraction of 3298 nuclei with classification as N, B or M. When nuclei are extracted from each of the 59 biopsies the average classification among N, B and M nuclei is 97.1%; classification of the biopsies, based on the average nuclei classification, is 100%. However, when the nuclei are extracted from a subset of biopsies, and the prediction is made on nuclei in the remaining biopsies, there is a marked decrement in performance to 60% across the 3 classes. Similarly the biopsy classification drops to 54%. In spite of these classification differences, which we believe are due to instrument and biopsy normalization issues, hyper-spectral analysis has the potential to achieve diagnostic efficiency needed for objective microscopic diagnosis.

  5. Transcriptomic profiling of long non-coding RNAs in dermatomyositis by microarray analysis.

    PubMed

    Peng, Qing-Lin; Zhang, Ya-Mei; Yang, Han-Bo; Shu, Xiao-Ming; Lu, Xin; Wang, Guo-Chun

    2016-01-01

    Long non-coding RNAs (lncRNAs) are prevalently transcribed in the genome and have been found to be of functional importance. However, the potential roles of lncRNAs in dermatomyositis (DM) remain unknown. In this study, a lncRNA + mRNA microarray analysis was performed to profile lncRNAs and mRNAs from 15 treatment-naive DM patients and 5 healthy controls. We revealed a total of 1198 lncRNAs (322 up-regulated and 876 down-regulated) and 1213 mRNAs (665 up-regulated and 548 down-regulated) were significantly differentially expressed in DM patients compared with the healthy controls (fold change>2, P < 0.05). Subgrouping DM patients according to the presence of interstitial lung disease and anti-Jo-1 antibody revealed different expression patterns of the lncRNAs. Pathway and gene ontology analysis for the differentially expressed mRNAs confirmed that type 1 interferon signaling was the most significantly dysregulated pathway in all DM subgroups. In addition, distinct pathways that uniquely associated with DM subgroup were also identified. Bioinformatics prediction suggested that linc-DGCR6-1 may be a lncRNA that regulates type 1 interferon-inducible gene USP18, which was found highly expressed in the perifascicular areas of the muscle fibers of DM patients. Our findings provide an overview of aberrantly expressed lncRNAs in DM muscle and further broaden the understanding of DM pathogenesis. PMID:27605457

  6. Identification of B cells participated in the mechanism of postmenopausal women osteoporosis using microarray analysis

    PubMed Central

    Yan, Bing; Li, Jie; Zhang, Li

    2015-01-01

    To further understand the molecular mechanism of lymphocytes B cells in postmenopausal women osteoporosis. Microarray data (GSE7429) were downloaded from Gene Expression Omnibus, in which B cells were separated from the whole blood of postmenopausal women, including 10 with high bone mineral density (BMD) and 10 with low BMD. Differentially expressed genes (DEGs) between high and low BMD women were identified by Student’s t-test, and P < 0.01 was used as the significant criterion. Functional enrichment analysis was performed for up- and down-regulated DEGs using KEGG, REACTOME, and Gene Ontology (GO) databases. Protein-protein interaction network (PPI) of up- and down-regulated DEGs was respectively constructed by Cytoscape software using the STRING data. Total of 169 up-regulated and 69 down-regulated DEGs were identified. Functional enrichment analysis indicated that the genes (ITPA, ATIC, UMPS, HPRT1, COX10 and COX15) might participate in metabolic pathways, MAP3K10 and MAP3K9 might participate in the activation of JNKK activity, COX10 and COX15 might involve in mitochondrial electron transport, and ATIC, UMPS and HPRT1 might involve in transferase activity. MAPK3, ITPA, ATIC, UMPS and HPRT1 with a higher degree in PPI network were identified. MAPK3, MAP3K10, MAP3K9, COX10, COX15, ATIC, UMPS and HPRT1 might participate in the pathogenesis of osteoporosis. PMID:25785089

  7. Text-based over-representation analysis of microarray gene lists with annotation bias

    PubMed Central

    Leong, Hui Sun; Kipling, David

    2009-01-01

    A major challenge in microarray data analysis is the functional interpretation of gene lists. A common approach to address this is over-representation analysis (ORA), which uses the hypergeometric test (or its variants) to evaluate whether a particular functionally defined group of genes is represented more than expected by chance within a gene list. Existing applications of ORA have been largely limited to pre-defined terminologies such as GO and KEGG. We report our explorations of whether ORA can be applied to a wider mining of free-text. We found that a hitherto underappreciated feature of experimentally derived gene lists is that the constituents have substantially more annotation associated with them, as they have been researched upon for a longer period of time. This bias, a result of patterns of research activity within the biomedical community, is a major problem for classical hypergeometric test-based ORA approaches, which cannot account for such bias. We have therefore developed three approaches to overcome this bias, and demonstrate their usability in a wide range of published datasets covering different species. A comparison with existing tools that use GO terms suggests that mining PubMed abstracts can reveal additional biological insight that may not be possible by mining pre-defined ontologies alone. PMID:19429895

  8. A Meta Analysis of Pancreatic Microarray Datasets Yields New Targets as Cancer Genes and Biomarkers

    PubMed Central

    Goonesekere, Nalin C. W.; Wang, Xiaosheng; Ludwig, Lindsey; Guda, Chittibabu

    2014-01-01

    The lack of specific symptoms at early tumor stages, together with a high biological aggressiveness of the tumor contribute to the high mortality rate for pancreatic cancer (PC), which has a five year survival rate of less than 5%. Improved screening for earlier diagnosis, through the detection of diagnostic and prognostic biomarkers provides the best hope of increasing the rate of curatively resectable carcinomas. Though many serum markers have been reported to be elevated in patients with PC, so far, most of these markers have not been implemented into clinical routine due to low sensitivity or specificity. In this study, we have identified genes that are significantly upregulated in PC, through a meta-analysis of large number of microarray datasets. We demonstrate that the biological functions ascribed to these genes are clearly associated with PC and metastasis, and that that these genes exhibit a strong link to pathways involved with inflammation and the immune response. This investigation has yielded new targets for cancer genes, and potential biomarkers for pancreatic cancer. The candidate list of cancer genes includes protein kinase genes, new members of gene families currently associated with PC, as well as genes not previously linked to PC. In this study, we are also able to move towards developing a signature for hypomethylated genes, which could be useful for early detection of PC. We also show that the significantly upregulated 800+ genes in our analysis can serve as an enriched pool for tissue and serum protein biomarkers in pancreatic cancer. PMID:24740004

  9. Analysis of differentially expressed genes based on microarray data of glioma

    PubMed Central

    Jiang, Chun-Ming; Wang, Xiao-Hua; Shu, Jin; Yang, Wei-Xia; Fu, Ping; Zhuang, Li-Li; Zhou, Guo-Ping

    2015-01-01

    Glioma represents one of the main causes of cancer-related death worldwide. Unfortunately, its exact molecular mechanisms remain poorly understood, which limits the prognosis and therapy. This study aimed to identify the critical genes, transcription factors and the possible biochemical pathways that may affect glioma progression at transcription level. After downloading micro-array data from Gene Expression Omnibus (GEO), the differentially expressed genes (DEGs) between glioma and normal samples were screened. We predicted novel glioma-related genes and carried on online software DAVID to conduct GO enrichment and transcription factor analysis of these selected genes. String software was applied to construct a PPI protein interaction network, as well as to find the key genes and transcription factors in the regulation of glioma. A total of 97 DEGs were identified associated with cancer, the GO enrichment analysis indicated these DEGs were mainly relevant to immune responses as well as regulation of cell growth. In addition, the transcription factor analysis showed these DEGs were regulated by the binding sites of transcription factors GLI2, SP1, SMAD7, SMAD3, RELA, STAT5B, CTNNB1, STAT5A, TFAP2A and SP3. PPI protein interaction network analysis demonstrated the hub nodes in the interaction network were EGFR, TGFB1, FN1 and MYC. The hub DEGs may be the most critical in glioma and could be considered as drug targets for glioma therapy after further exploration. Besides, with the identification of regulating transcription factors, the pathogenesis of glioma at transcription level might be brought to light. PMID:26770324

  10. Optimization of gene expression microarray protocol for formalin-fixed paraffin-embedded tissues.

    PubMed

    Belder, Nevin; Coşkun, Öznur; Erdoğan, Beyza Doğanay; Savaş, Berna; Ensari, Arzu; Özdağ, Hilal

    2016-03-01

    Formalin-fixed paraffin-embedded (FFPE) tissue is a widely available clinical specimen for retrospective studies. The possibility of long-term clinical follow-up of FFPE samples makes them a valuable source to evaluate links between molecular and clinical information. Working with FFPE samples in the molecular research area, especially using high-throughput molecular techniques such as microarray gene expression profiling, has come into prominence. Because of the harmful effects of formalin fixation process such as degradation of nucleic acids, cross-linking with proteins, and chemical modifications on DNA and RNA, there are some limitations in gene expression profiling studies using FFPE samples. To date many studies have been conducted to evaluate gene expression profiling using microarrays (Thomas et al., Thomas et al. (2013) [1]; Scicchitano et al., Scicchitano et al. (2006) [2]; Frank et al., Frank et al. (2007) [3]; Fedorowicz et al., Fedorowicz et al. (2009) [4]). However, there is still no generally accepted, efficient and standardized procedure for microarray analysis of FFPE samples. This paper describes the microarray data presented in our recently accepted to be published article showing a standard protocol from deparaffinization of FFPE tissue sections and RNA extraction to microarray gene expression analysis. Here we represent our data in detail, deposited in the gene expression omnibus (GEO) database with the accession number GSE73883. Four combinations of two different cRNA/cDNA preparation and labeling protocols with two different array platforms (Affymetrix Human Genome U133 Plus 2.0 and U133_X3P) were evaluated to determine which combination gives the best percentage of present call. The study presents a dataset for comparative analysis which has a potential in terms of providing a robust protocol for gene expression profiling with FFPE tissue samples. PMID:26981433

  11. Optimization of gene expression microarray protocol for formalin-fixed paraffin-embedded tissues.

    PubMed

    Belder, Nevin; Coşkun, Öznur; Erdoğan, Beyza Doğanay; Savaş, Berna; Ensari, Arzu; Özdağ, Hilal

    2016-03-01

    Formalin-fixed paraffin-embedded (FFPE) tissue is a widely available clinical specimen for retrospective studies. The possibility of long-term clinical follow-up of FFPE samples makes them a valuable source to evaluate links between molecular and clinical information. Working with FFPE samples in the molecular research area, especially using high-throughput molecular techniques such as microarray gene expression profiling, has come into prominence. Because of the harmful effects of formalin fixation process such as degradation of nucleic acids, cross-linking with proteins, and chemical modifications on DNA and RNA, there are some limitations in gene expression profiling studies using FFPE samples. To date many studies have been conducted to evaluate gene expression profiling using microarrays (Thomas et al., Thomas et al. (2013) [1]; Scicchitano et al., Scicchitano et al. (2006) [2]; Frank et al., Frank et al. (2007) [3]; Fedorowicz et al., Fedorowicz et al. (2009) [4]). However, there is still no generally accepted, efficient and standardized procedure for microarray analysis of FFPE samples. This paper describes the microarray data presented in our recently accepted to be published article showing a standard protocol from deparaffinization of FFPE tissue sections and RNA extraction to microarray gene expression analysis. Here we represent our data in detail, deposited in the gene expression omnibus (GEO) database with the accession number GSE73883. Four combinations of two different cRNA/cDNA preparation and labeling protocols with two different array platforms (Affymetrix Human Genome U133 Plus 2.0 and U133_X3P) were evaluated to determine which combination gives the best percentage of present call. The study presents a dataset for comparative analysis which has a potential in terms of providing a robust protocol for gene expression profiling with FFPE tissue samples.

  12. MmPalateMiRNA, an R package compendium illustrating analysis of miRNA microarray data

    PubMed Central

    2013-01-01

    Background MicroRNAs (miRNAs) constitute the largest family of noncoding RNAs involved in gene silencing and represent critical regulators of cell and tissue differentiation. Microarray expression profiling of miRNAs is an effective means of acquiring genome-level information of miRNA activation and inhibition, as well as the potential regulatory role that these genes play within a biological system. As with mRNA expression profiling arrays, miRNA microarrays come in a variety of platforms from numerous manufacturers, and there are a multitude of techniques available for reducing and analyzing these data. Results In this paper, we present an analysis of a typical two-color miRNA microarray experiment using publicly available packages from R and Bioconductor, the open-source software project for the analysis of genomic data. Covered topics include visualization, normalization, quality checking, differential expression, cluster analysis, miRNA target identification, and gene set enrichment analysis. Many of these tools carry-over from the analysis of mRNA microarrays, but with some notable differences that require special attention. The paper is presented as a “compendium” which, along with the accompanying R package MmPalateMiRNA, contains all of the experimental data and source code to reproduce the analyses contained in the paper. Conclusions The compendium presented in this paper will provide investigators with an access point for applying the methods available in R and Bioconductor for analysis of their own miRNA array data. PMID:23298515

  13. Microarray Analysis of Genes Involved with Shell Strength in Layer Shell Gland at the Early Stage of Active Calcification

    PubMed Central

    Liu, Zhangguo; Zheng, Qi; Zhang, Xueyu; Lu, Lizhi

    2013-01-01

    The objective of this study was to get a comprehensive understanding of how genes in chicken shell gland modulate eggshell strength at the early stage of active calcification. Four 32-week old of purebred Xianju hens with consistent high or low shell breakage strength were grouped into two pairs. Using Affymetrix Chicken Array, a whole-transcriptome analysis was performed on hen’s shell gland at 9 h post oviposition. Gene ontology enrichment analysis for differentially expressed (DE) transcripts was performed using the web-based GOEAST, and the validation of DE-transcripts was tested by qRT-PCR. 1,195 DE-transcripts, corresponding to 941 unique genes were identified in hens with strong eggshell compared to weak shell hens. According to gene ontology annotations, there are 77 DE-transcripts encoding ion transporters and secreted extracellular matrix proteins, and at least 26 DE-transcripts related to carbohydrate metabolism or post-translation glycosylation modification; furthermore, there are 88 signaling DE-transcripts. GO term enrichment analysis suggests that some DE-transcripts mediate reproductive hormones or neurotransmitters to affect eggshell quality through a complex suite of biophysical processes. These results reveal some candidate genes involved with eggshell strength at the early stage of active calcification which may facilitate our understanding of regulating mechanisms of eggshell quality. PMID:25049830

  14. Deciphering the Mesodermal Potency of Porcine Skin-Derived Progenitors (SKP) by Microarray Analysis

    PubMed Central

    Zhao, Ming-Tao; Whitworth, Kristin M.; Zhang, Xia; Zhao, Jianguo; Miao, Yi-Liang; Zhang, Yong

    2010-01-01

    Abstract Skin stem cells have an essential role in maintaining tissue homeostasis by dynamically replenishing those constantly lost during tissue turnover or following injury. Multipotent skin derived progenitors (SKP) can generate both neural and mesodermal progeny, representing neural crest-derived progenitors during embryogenesis through adulthood. SKP cells develop into spheres in suspension and can differentiate into fibroblast-like cells (SFC) in adhesive culture with serum. Concomitantly they gradually lose the neural potential but retain certain mesodermal potential. However, little is known about the molecular mechanism of the transition of SKP spheres into SFC in vitro. Here we characterized the transcriptional profiles of porcine SKP spheres and SFC by microarray analysis. We found 305 upregulated and 96 downregulated genes, respectively. The downregulated genes are mostly involved in intrinsic programs like the Dicer pathway and asymmetric cell division, whereas upregulated genes are likely to participate in extrinsic signaling pathways such as ErbB signaling, MAPK signaling, ECM-receptor reaction, Wnt signaling, cell communication, and tumor growth factor (TGF)-β signaling pathways. These intrinsic programs and extrinsic signaling pathways collaborate to mediate the transcription-state transition between SKP spheres and SFC. We speculate that these potential signaling pathways may play an important role in regulating the cell fate transition between SKP spheres and SFC in vitro. PMID:20436954

  15. Microarray analysis of New Green Cocoon associated genes in silkworm, Bombyx mori.

    PubMed

    Lu, Ya-Ru; He, Song-Zhen; Tong, Xiao-Ling; Han, Min-Jin; Li, Chun-Lin; Li, Zhi-Quan; Dai, Fang-Yin

    2016-06-01

    Green cocoons in silkworm, Bombyx mori, are caused by flavonoids accumulation in the silk proteins, fibroin and sericin. Despite the economic value of natural green cocoon and medical value of flavonoids, there is limited understanding of the molecular mechanism regulating flavonoids uptake in silkworm, which is tightly associated with the trait of green cocoon. The purpose of this study is to perform a comprehensive analysis to understand the molecular mechanisms of flavonoids uptake in silkworm based on microarray analyses. The study subject was the New Green Cocoon from the silkworm strains, G200 and N100, a new spontaneous dominant green cocoon trait identified in the 2000s. The genes regulating this trait are independent of other green cocoon genes previously reported. Genome-wide gene expression was compared between the New Green Cocoon producing silkworm strains, G200 and N100, and the control sample, which is the white cocoon producing strain 872B. Among these strains, N100 and 872B are near-isogenic lines. The results showed that 130 genes have consistently changing expression patterns in the green cocoon strains when compared with the white cocoon strain. Among these, we focused on the genes related to flavonoids metabolism and absorption, such as sugar transporter genes and UDP-glucosyltransferase genes. Based on our findings, we propose the potential mechanisms for flavonoids absorption and metabolism in silkworm. Our results imply that silkworm might be used as an underlying model for flavonoids in pharmaceutical research.

  16. Predicting MicroRNA Biomarkers for Cancer Using Phylogenetic Tree and Microarray Analysis.

    PubMed

    Wang, Hsiuying

    2016-01-01

    MicroRNAs (miRNAs) are shown to be involved in the initiation and progression of cancers in the literature, and the expression of miRNAs is used as an important cancer prognostic tool. The aim of this study is to predict high-confidence miRNA biomarkers for cancer. We adopt a method that combines miRNA phylogenetic structure and miRNA microarray data analysis to discover high-confidence miRNA biomarkers for colon, prostate, pancreatic, lung, breast, bladder and kidney cancers. There are 53 miRNAs selected through this method that either have potential to involve a single cancer's development or to involve several cancers' development. These miRNAs can be used as high-confidence miRNA biomarkers of these seven investigated cancers for further experiment validation. miR-17, miR-20, miR-106a, miR-106b, miR-92, miR-25, miR-16, miR-195 and miR-143 are selected to involve a single cancer's development in these seven cancers. They have the potential to be useful miRNA biomarkers when the result can be confirmed by experiments. PMID:27213352

  17. Predicting MicroRNA Biomarkers for Cancer Using Phylogenetic Tree and Microarray Analysis

    PubMed Central

    Wang, Hsiuying

    2016-01-01

    MicroRNAs (miRNAs) are shown to be involved in the initiation and progression of cancers in the literature, and the expression of miRNAs is used as an important cancer prognostic tool. The aim of this study is to predict high-confidence miRNA biomarkers for cancer. We adopt a method that combines miRNA phylogenetic structure and miRNA microarray data analysis to discover high-confidence miRNA biomarkers for colon, prostate, pancreatic, lung, breast, bladder and kidney cancers. There are 53 miRNAs selected through this method that either have potential to involve a single cancer’s development or to involve several cancers’ development. These miRNAs can be used as high-confidence miRNA biomarkers of these seven investigated cancers for further experiment validation. miR-17, miR-20, miR-106a, miR-106b, miR-92, miR-25, miR-16, miR-195 and miR-143 are selected to involve a single cancer’s development in these seven cancers. They have the potential to be useful miRNA biomarkers when the result can be confirmed by experiments. PMID:27213352

  18. Microarray Expression Analysis for the Paradoxical Roles of Acanthopanax senticosus Harms in Treating α-Synucleinopathies.

    PubMed

    Li, Xu-zhao; Zhang, Shuai-nan; Lu, Fang; Liu, Shu-min

    2016-02-01

    α-Synuclein is a key player in the pathogenesis of neurodegenerative disorders with Lewy bodies. Our previous studies have also showed that Acanthopanax senticosus harms (AS) could significantly suppress α-synuclein overexpression and toxicity. Identifying the RNAs related to α-synucleinopathies may facilitate understanding the pathogenesis of the diseases and the safe application of AS in the clinic. Microarray expression profiling of long non-coding RNAs (lncRNAs) and mRNAs was undertaken in control non-transgenic and human α-synuclein transgenic mice. The effects of AS on central nervous system (CNS) in pathology and physiology were investigated based on the lncRNA/mRNA targets analysis. In total, 341 lncRNAs and 279 mRNAs were differentially expressed by α-synuclein stimulus, among which 29 lncRNAs and 25 mRNAs were involved in the anti-α-synucleinopathies mechanism of AS. However, the levels of 19/29 lncRNAs and 12/25 mRNAs in AS group were similar to those in α-synuclein group, which may cause potential neurotoxicity analogous to α-synuclein. This study demonstrated that some of lncRNAs/mRNAs were involved in α-synuclein related pathophysiology, and AS produced the bidirectional effects on CNS under pathological and physiological conditions. PMID:26612828

  19. Screening for beneficial effects of oral intake of sweet corn by DNA microarray analysis.

    PubMed

    Tokuji, Yoshihiko; Akiyama, Kyoko; Yunoki, Keita; Kinoshita, Mikio; Sasaki, Keiko; Kobayashi, Hitoshi; Wada, Masahiro; Ohnishi, Masao

    2009-09-01

    To identify novel functions of the oral intake of sweet corn, we performed DNA microarray analysis of the livers of sweet corn-fed mice. Functional annotation clustering 1600 genes with expression levels that were affected (more than 1.5-fold change) by dietary sweet corn indicated that both cell proliferation and programmed cell death were modulated by sweet corn intake. In the Wnt signaling pathway, which is involved in cell proliferation, the levels of Jun and beta-catenin expression were downregulated by dietary sweet corn. The mRNA levels of Rb and p53, negative regulators of the cell cycle, were increased in mice fed with sweet corn. Dietary corn upregulated expression levels of genes that regulate apoptosis positively (for example, BOK, BID, CASP4). These results suggested that sweet corn is a valuable food for suppressing cancer. Oral administration of sweet corn inhibited tumor growth (36.6% reduce in tumor weight, P < 0.05) in mice inoculated with Ehrlich tumor cells. PMID:19895470

  20. Microarray and whole-exome sequencing analysis of familial Behçet’s disease patients

    PubMed Central

    Okuzaki, Daisuke; Yoshizaki, Kazuyuki; Tanaka, Toshio; Hirano, Toru; Fukushima, Kohshiro; Washio, Takanori; Nojima, Hiroshi

    2016-01-01

    Behçet’s disease (BD), a chronic systemic inflammatory disorder, is characterized by recurrent oral and genital mucous ulcers, uveitis, and skin lesions. We performed DNA microarray analysis of peripheral blood mononuclear cell (PBMC) mRNA from 41 Japanese BD patients and revealed elevated levels of interleukin (IL) 23 receptor (IL23R) mRNA in many BD patients. DNA sequencing around a SNV (Rs12119179) tightly linked to BD revealed an elevated frequency of the C genotype, consistent with a previous report that IL23R is a susceptibility locus for BD. Notably, four of these BD patients are members of familial BD; a whole-exome sequencing (WES) of these BD patients identified 19 novel single-nucleotide variations (SNVs) specific to these patients. They include heterozygous SNVs in the genes encoding IL-1 receptor-associated kinase 4 (IRAK4), nucleotide-binding oligomerization domain (NOD)-like receptor family pyrin domain-containing 14 (NRP14) and melanoma antigen-encoding gene E2 (MAGEE2); IRAK4 harbors a missense mutation, whereas NRP14 and MAGEE2 harbor nonsense mutations. These SNVs may serve as genetic markers that characterize BD. PMID:26785681

  1. Technical approaches for efficient high-precision nucleic acid analysis using DNA microarrays

    NASA Astrophysics Data System (ADS)

    Pinkel, Daniel; Hamilton, Gregory; Brown, Nils; Segraves, Richard; Huey, Bing; Snijders, Anoine; Blackwood, Stephanie; Hindle, Kate; Law, Sindy; Gray, Joe W.; Jain, Ajay; Hanson, John; Nordmeyer, Robert; Albertson, Donna

    2002-06-01

    Microarray measurements offer the potential to compare the abundances of numerous nucleic acid sequences in parallel. Using linker-adapter PCR products from mapped BAC clones we have made arrays that permit scanning the human genome for single copy gains and losses of DNA sequence, which requires reliable detection of 50 percent changes. The DNA is printed at high concentration on amino-silane or chromium coated surface using a custom-built capillary pin printing system. Spots are printed on 130 micrometers centers or closer to minimize the size of the arrays. Hybridization occurs in a dextran sulfate/formamide buffer at 37 degrees C, using slow rocking to mix the reaction. The entire array is imaged in a single CCD frame using a custom built system that employs mercury arc illumination. Up to four fluorochromes can be imaged from a single array with adequate spectral separation. Typically we use DAPI to stain the DNA in the array spots to facilitate automatic image segmentation during analysis, and fluorescein, Cy3, and Cy5 or their spectral equivalents, for labeling specimen nucleic acids. Array spots are segmented and quantitative fluorescence intensities and intensity ratios are automatically calculated in < 1 minute per approximately 8000 element array using the custom software UCSF SPOT.

  2. Knowledge-based analysis of microarray gene expression data by using support vector machines

    SciTech Connect

    William Grundy; Manuel Ares, Jr.; David Haussler

    2001-06-18

    The authors introduce a method of functionally classifying genes by using gene expression data from DNA microarray hybridization experiments. The method is based on the theory of support vector machines (SVMs). SVMs are considered a supervised computer learning method because they exploit prior knowledge of gene function to identify unknown genes of similar function from expression data. SVMs avoid several problems associated with unsupervised clustering methods, such as hierarchical clustering and self-organizing maps. SVMs have many mathematical features that make them attractive for gene expression analysis, including their flexibility in choosing a similarity function, sparseness of solution when dealing with large data sets, the ability to handle large feature spaces, and the ability to identify outliers. They test several SVMs that use different similarity metrics, as well as some other supervised learning methods, and find that the SVMs best identify sets of genes with a common function using expression data. Finally, they use SVMs to predict functional roles for uncharacterized yeast ORFs based on their expression data.

  3. Protein turnover in atrophying muscle: from nutritional intervention to microarray expression analysis

    NASA Technical Reports Server (NTRS)

    Stein, T. Peter; Wade, Charles E.

    2003-01-01

    PURPOSE OF REVIEW: In response to decreased usage, skeletal muscle undergoes adaptive reductive remodeling due to the decrease in tension on the weight bearing components of the musculo-skeletal system. This response occurs with uncomplicated disuse (e.g. bed rest, space flight), as a secondary consequence of several widely prevalent chronic diseases for which activity is reduced (e.g. chronic obstructive pulmonary disease and chronic heart failure) and is part of the aging process. The problem is therefore one of considerable clinical importance. RECENT FINDINGS: The impaired function and exercise intolerance is related more to the associated muscle wasting rather than to the specific organ system primarily impacted by the disease. Progress has continued in describing the use of anabolic drugs and dietary manipulation. The major advance in the field has been: (i) the discovery of the atrogin-1 gene and (ii) the application of microarray expression analysis and proteomics with the objectives of obtaining comprehensive understanding of the pathways changed with disuse atrophy. SUMMARY: Disuse atrophy is a common clinical problem. There is a need for therapeutic interventions that do not involve exercise. A better understanding of the changes, particularly at the molecular level, could indicate hitherto unsuspected sites for nutritional and pharmacological intervention.

  4. Independent component analysis: mining microarray data for fundamental human gene expression modules.

    PubMed

    Engreitz, Jesse M; Daigle, Bernie J; Marshall, Jonathan J; Altman, Russ B

    2010-12-01

    As public microarray repositories rapidly accumulate gene expression data, these resources contain increasingly valuable information about cellular processes in human biology. This presents a unique opportunity for intelligent data mining methods to extract information about the transcriptional modules underlying these biological processes. Modeling cellular gene expression as a combination of functional modules, we use independent component analysis (ICA) to derive 423 fundamental components of human biology from a 9395-array compendium of heterogeneous expression data. Annotation using the Gene Ontology (GO) suggests that while some of these components represent known biological modules, others may describe biology not well characterized by existing manually-curated ontologies. In order to understand the biological functions represented by these modules, we investigate the mechanism of the preclinical anti-cancer drug parthenolide (PTL) by analyzing the differential expression of our fundamental components. Our method correctly identifies known pathways and predicts that N-glycan biosynthesis and T-cell receptor signaling may contribute to PTL response. The fundamental gene modules we describe have the potential to provide pathway-level insight into new gene expression datasets.

  5. Surface ligation-based resonance light scattering analysis of methylated genomic DNA on a microarray platform.

    PubMed

    Ma, Lan; Lei, Zhen; Liu, Xia; Liu, Dianjun; Wang, Zhenxin

    2016-05-10

    DNA methylation is a crucial epigenetic modification and is closely related to tumorigenesis. Herein, a surface ligation-based high throughput method combined with bisulfite treatment is developed for analysis of methylated genomic DNA. In this method, a DNA microarray is employed as a reaction platform, and resonance light scattering (RLS) of nanoparticles is used as the detection principle. The specificity stems from allele-specific ligation of Taq DNA ligase, which is further enhanced by improving the fidelity of Taq DNA ligase in a heterogeneous reaction. Two amplification techniques, rolling circle amplification (RCA) and silver enhancement, are employed after the ligation reaction and a gold nanoparticle (GNP) labeling procedure is used to amplify the signal. As little as 0.01% methylated DNA (i.e. 2 pmol L(-1)) can be distinguished from the cocktail of methylated and unmethylated DNA by the proposed method. More importantly, this method shows good accuracy and sensitivity in profiling the methylation level of genomic DNA of three selected colonic cancer cell lines. This strategy provides a high throughput alternative with reasonable sensitivity and resolution for cancer study and diagnosis.

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

    PubMed

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

    2011-10-25

    Bovine spongiform encephalopathy (BSE) is a fatal disorder in cattle characterized by progressive neurodegeneration of the central nervous system. We investigated the molecular mechanisms involved in neurodegeneration during prion infection through the identification of genes that are differentially expressed (DE) between experimentally infected and non-challenged cattle. Gene expression of caudal medulla from control and orally infected animals was compared by microarray analysis using 24,000 bovine oligonucleotides representing 16,846 different genes to identify DE genes associated with BSE disease. In total, 182 DE genes were identified between normal and BSE-infected tissues (>2.0-fold change, P < 0.01); 81 DE genes had gene ontology functions, which included synapse function, calcium ion regulation, immune and inflammatory response, apoptosis, and cytoskeleton organization; 13 of these genes were found to be involved in 26 different Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The expression of five DE genes associated with synapse function (tachykinin, synuclein, neuropeptide Y, cocaine, amphetamine-responsive transcript, and synaptosomal-associated protein 25 kDa) and three DE genes associated with calcium ion regulation (parvalbumin, visinin-like, and cadherin) was further validated in the medulla tissue of cattle at different infection times (6, 12, 42, and 45 months post-infection) by qRT-PCR. These data will contribute to a better understanding of the molecular mechanisms of neuropathology in bovine species.

  7. Identification of Novel Epigenetic Markers of Prostate Cancer by NotI-Microarray Analysis

    PubMed Central

    Dmitriev, Alexey A.; Rosenberg, Eugenia E.; Krasnov, George S.; Gerashchenko, Ganna V.; Gordiyuk, Vasily V.; Pavlova, Tatiana V.; Kudryavtseva, Anna V.; Beniaminov, Artemy D.; Belova, Anastasia A.; Bondarenko, Yuriy N.; Danilets, Rostislav O.; Glukhov, Alexander I.; Kondratov, Aleksandr G.; Alexeyenko, Andrey; Alekseev, Boris Y.; Klein, George; Senchenko, Vera N.; Kashuba, Vladimir I.

    2015-01-01

    A significant need for reliable and accurate cancer diagnostics and prognosis compels the search for novel biomarkers that would be able to discriminate between indolent and aggressive tumors at the early stages of disease. The aim of this work was identification of potential diagnostic biomarkers for characterization of different types of prostate tumors. NotI-microarrays with 180 clones associated with chromosome 3 genes/loci were applied to determine genetic and epigenetic alterations in 33 prostate tumors. For 88 clones, aberrations were detected in more than 10% of tumors. The major types of alterations were DNA methylation and/or deletions. Frequent methylation of the discovered loci was confirmed by bisulfite sequencing on selective sampling of genes: FGF12, GATA2, and LMCD1. Three genes (BHLHE40, BCL6, and ITGA9) were tested for expression level alterations using qPCR, and downregulation associated with hypermethylation was shown in the majority of tumors. Based on these data, we proposed the set of potential biomarkers for detection of prostate cancer and discrimination between prostate tumors with different malignancy and aggressiveness: BHLHE40, FOXP1, LOC285205, ITGA9, CTDSPL, FGF12, LOC440944/SETD5, VHL, CLCN2, OSBPL10/ZNF860, LMCD1, FAM19A4, CAND2, MAP4, KY, and LRRC58. Moreover, we probabilistically estimated putative functional relations between the genes within each set using the network enrichment analysis. PMID:26491211

  8. Meta-Analysis of Microarray Data of Rainbow Trout Fry Gonad Differentiation Modulated by Ethynylestradiol

    PubMed Central

    Depiereux, Sophie; Le Gac, Florence; De Meulder, Bertrand; Pierre, Michael; Helaers, Raphaël; Guiguen, Yann; Kestemont, Patrick; Depiereux, Eric

    2015-01-01

    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 (eco)toxicogenomics studies for environmental risk assessment purposes. PMID

  9. DNA microarrays in neuropsychopharmacology.

    PubMed

    Marcotte, E R; Srivastava, L K; Quirion, R

    2001-08-01

    Recent advances in experimental genomics, coupled with the wealth of sequence information available for a variety of organisms, have the potential to transform the way pharmacological research is performed. At present, high-density DNA microarrays allow researchers to quickly and accurately quantify gene-expression changes in a massively parallel manner. Although now well established in other biomedical fields, such as cancer and genetics research, DNA microarrays have only recently begun to make significant inroads into pharmacology. To date, the major focus in this field has been on the general application of DNA microarrays to toxicology and drug discovery and design. This review summarizes the major microarray findings of relevance to neuropsychopharmacology, as a prelude to the design and analysis of future basic and clinical microarray experiments. The ability of DNA microarrays to monitor gene expression simultaneously in a large-scale format is helping to usher in a post-genomic age, where simple constructs about the role of nature versus nurture are being replaced by a functional understanding of gene expression in living organisms. PMID:11479006

  10. Reproducibility, Fidelity, and Discriminant Validity of mRNA Amplification for Microarray Analysis from Primary Hematopoietic Cells

    PubMed Central

    Li, Liang; Roden, Joe; Shapiro, Bruce E.; Wold, Barbara J.; Bhatia, Smita; Forman, Stephen J.; Bhatia, Ravi

    2005-01-01

    Analysis of gene expression in clinical samples poses special challenges, including limited RNA availability and poor RNA quality. Quantitative information regarding reliability of RNA amplification methodologies applied to primary cells and representativeness of resulting gene expression profiles is limited. We evaluated four protocols for RNA amplification from peripheral blood mononuclear cells. Results obtained with 100 ng or 10 ng of RNA amplified using two rounds of cDNA synthesis and in vitro transcription were compared with control 2.5-μg RNA samples processed using a single round of in vitro transcription. Samples were hybridized to Affymetrix HG-U133A arrays. Considerable differences in results were obtained with different protocols. The optimal protocol resulted in highly reproducible gene expression profiles from amplified samples (r = 0.98) and good correlation between amplified and control samples (r = 0.94). Using the optimal protocol dissimilarities of gene expression between mononuclear cells from a normal individual and a patient with myelodysplastic syndrome were primarily maintained after amplification compared with controls. We conclude that small variations in methodology introduce considerable distortion of gene expression profiles obtained after RNA amplification from clinical samples and too strong a focus on a very small number of genes picked from an array analysis could be unduly influenced by seemingly acceptable methodologies. However, it is possible to obtain reproducible and representative results using optimized protocols. PMID:15681474

  11. A tiling microarray for global analysis of chloroplast genome expression in cucumber and other plants

    PubMed Central

    2011-01-01

    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. PMID:21952044

  12. Co-expression network analysis of Down's syndrome based on microarray data

    PubMed Central

    Zhao, Jianping; Zhang, Zhengguo; Ren, Shumin; Zong, Yanan; Kong, Xiangdong

    2016-01-01

    Down's syndrome (DS) is a type of chromosome disease. The present study aimed to explore the underlying molecular mechanisms of DS. GSE5390 microarray data downloaded from the gene expression omnibus database was used to identify differentially expressed genes (DEGs) in DS. Pathway enrichment analysis of the DEGs was performed, followed by co-expression network construction. Significant differential modules were mined by mutual information, followed by functional analysis. The accuracy of sample classification for the significant differential modules of DEGs was evaluated by leave-one-out cross-validation. A total of 997 DEGs, including 638 upregulated and 359 downregulated genes, were identified. Upregulated DEGs were enriched in 15 pathways, such as cell adhesion molecules, whereas downregulated DEGs were enriched in maturity onset diabetes of the young. Three significant differential modules with the highest discriminative scores (mutual information>0.35) were selected from a co-expression network. The classification accuracy of GSE16677 expression profile samples was 54.55% and 72.73% when characterized by 12 DEGs and 3 significant differential modules, respectively. Genes in significant differential modules were significantly enriched in 5 functions, including the endoplasmic reticulum (P=0.018) and regulation of apoptosis (P=0.061). The identified DEGs, in particular the 12 DEGs in the significant differential modules, such as B-cell lymphoma 2-associated transcription factor 1, heat shock protein 90 kDa beta member 1, UBX domain-containing protein 2 and transmembrane protein 50B, may serve important roles in the pathogenesis of DS. PMID:27588071

  13. Clinical Implementation of Chromosomal Microarray Analysis: Summary of 2513 Postnatal Cases

    PubMed Central

    Lu, Xinyan; Shaw, Chad A.; Patel, Ankita; Li, Jiangzhen; Cooper, M. Lance; Wells, William R.; Sullivan, Cathy M.; Sahoo, Trilochan; Yatsenko, Svetlana A.; Bacino, Carlos A.; Stankiewicz, Pawel; Ou, Zhishu; Chinault, A. Craig; Beaudet, Arthur L.; Lupski, James R.; Cheung, Sau W.; Ward, Patricia A.

    2007-01-01

    Background Array Comparative Genomic Hybridization (a-CGH) is a powerful molecular cytogenetic tool to detect genomic imbalances and study disease mechanism and pathogenesis. We report our experience with the clinical implementation of this high resolution human genome analysis, referred to as Chromosomal Microarray Analysis (CMA). Methods and Findings CMA was performed clinically on 2513 postnatal samples from patients referred with a variety of clinical phenotypes. The initial 775 samples were studied using CMA array version 4 and the remaining 1738 samples were analyzed with CMA version 5 containing expanded genomic coverage. Overall, CMA identified clinically relevant genomic imbalances in 8.5% of patients: 7.6% using V4 and 8.9% using V5. Among 117 cases referred for additional investigation of a known cytogenetically detectable rearrangement, CMA identified the majority (92.5%) of the genomic imbalances. Importantly, abnormal CMA findings were observed in 5.2% of patients (98/1872) with normal karyotypes/FISH results, and V5, with expanded genomic coverage, enabled a higher detection rate in this category than V4. For cases without cytogenetic results available, 8.0% (42/524) abnormal CMA results were detected; again, V5 demonstrated an increased ability to detect abnormality. Improved diagnostic potential of CMA is illustrated by 90 cases identified with 51 cryptic microdeletions and 39 predicted apparent reciprocal microduplications in 13 specific chromosomal regions associated with 11 known genomic disorders. In addition, CMA identified copy number variations (CNVs) of uncertain significance in 262 probands; however, parental studies usually facilitated clinical interpretation. Of these, 217 were interpreted as familial variants and 11 were determined to be de novo; the remaining 34 await parental studies to resolve the clinical significance. Conclusions This large set of clinical results demonstrates the significantly improved sensitivity of CMA for the

  14. Comparative Analysis of Human Conjunctival and Corneal Epithelial Gene Expression with Oligonucleotide Microarrays

    PubMed Central

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

    2010-01-01

    Purpose To determine global mRNA expression levels in corneal and conjunctival epithelia and identify transcripts that exhibit preferential tissue expression. Methods 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 β-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. Results 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, sPLA2-IIA, lipocalin 2, IGFBP3, multiple MCH class II proteins, and the Na-Pi cotransporter type IIb. Conclusions Comparative gene expression profiling leads to the identification of many biological processes

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

    PubMed

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

    2005-09-15

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

  16. Changes in the peripheral blood transcriptome associated with occupational benzene exposure identified by cross-comparison on two microarray platforms

    SciTech Connect

    McHale, Cliona M.; Zhang, Luoping; Lan, Qing; Li, Guilan; Hubbard, Alan E.; Forrest, Matthew S.; Vermeulen, Roel; Chen, Jinsong; Shen, Min; Rappaport, Stephen M.; Yin, Songnian; Smith, Martyn T.; Rothman, Nathaniel

    2009-03-01

    Benzene is an established cause of leukemia and a possible cause of lymphoma in humans but the molecular pathways underlying this remain largely undetermined. This study sought to determine if the use of two different microarray platforms could identify robust global gene expression and pathway changes associated with occupational benzene exposure in the peripheral blood mononuclear cell (PBMC) gene expression of a population of shoe-factory workers with well-characterized occupational exposures to benzene. Microarray data was analyzed by a robust t-test using a Quantile Transformation (QT) approach. Differential expression of 2692 genes using the Affymetrix platform and 1828 genes using the Illumina platform was found. While the overall concordance in genes identified as significantly associated with benzene exposure between the two platforms was 26% (475 genes), the most significant genes identified by either array were more likely to be ranked as significant by the other platform (Illumina = 64%, Affymetrix = 58%). Expression ratios were similar among the concordant genes (mean difference in expression ratio = 0.04, standard deviation = 0.17). Four genes (CXCL16, ZNF331, JUN and PF4), which we previously identified by microarray and confirmed by real-time PCR, were identified by both platforms in the current study and were among the top 100 genes. Gene Ontology analysis showed over representation of genes involved in apoptosis among the concordant genes while Ingenuity{reg_sign} Pathway Analysis (IPA) identified pathways related to lipid metabolism. Using a two-platform approach allows for robust changes in the PBMC transcriptome of benzene-exposed individuals to be identified.

  17. Unsupervised assessment of microarray data quality using a Gaussian mixture model

    PubMed Central

    Howard, Brian E; Sick, Beate; Heber, Steffen

    2009-01-01

    Background Quality assessment of microarray data is an important and often challenging aspect of gene expression analysis. This task frequently involves the examination of a variety of summary statistics and diagnostic plots. The interpretation of these diagnostics is often subjective, and generally requires careful expert scrutiny. Results We show how an unsupervised classification technique based on the Expectation-Maximization (EM) algorithm and the naïve Bayes model can be used to automate microarray quality assessment. The method is flexible and can be easily adapted to accommodate alternate quality statistics and platforms. We evaluate our approach using Affymetrix 3' gene expression and exon arrays and compare the performance of this method to a similar supervised approach. Conclusion This research illustrates the efficacy of an unsupervised classification approach for the purpose of automated microarray data quality assessment. Since our approach requires only unannotated training data, it is easy to customize and to keep up-to-date as technology evolves. In contrast to other "black box" classification systems, this method also allows for intuitive explanations. PMID:19545436

  18. A MICROARRAY ANALYSIS OF GENE EXPRESSION IN THE EMBRYONIC FORELIMB OF THE C57BL/6J MOUSE REVEALS SIGNIFICANT ALTERATIONS METABOLIC AND DEVELOPMENTAL REGULATION FOLLOWING ETHANOL EXPOSURE.

    EPA Science Inventory

    The observation of transcriptional changes following embryonic ethanol exposure may provide significant insights into the biological response to ethanol exposure. In this study, we used microarray analysis to examine the transcriptional response of the developing limb to a dose ...

  19. DNA microarray analysis reveals a role for lysophosphatidic acid in the regulation of anti-inflammatory genes in MC3T3-E1 cells

    SciTech Connect

    Waters, Katrina M.; Tan, Ruimin; Genetos, Damian C.; Verma, Seema; Yellowley, Clare E.; Karin, Norm J.

    2007-11-01

    DNA microarray analysis revealed that treatment of bone cells with a lipid growth factor led to extensive changes in gene expression. Particular relevance to fracture healing and inflammation was revealed.

  20. Microarray analysis of responsible genes in increased growth rate in the subline of HL60 (HL60RG) cells.

    PubMed

    Luan, Yang; Kogi, Mieko; Rajaguru, Palanisamy; Ren, Jin; Yamaguchi, Teruhide; Suzuki, Kazuhiro; Suzuki, Takayoshi

    2012-03-01

    HL60RG, a subline of human promyelocytic leukemia HL60 cells, has a increased growth rate than their parental cells. To gain information of the mechanisms involved in the increased growth rate of HL60RG, we performed a multiplex fluorescence in situ hybridization (M-FISH), standard cytogenetics analysis (G-banding) and genome scan using 10K SNP mapping array on both cell types. Characteristic genomic alterations in HL60RG cells were identified including uniparental disomy (UPD) of chromosome 1, and hemizygous deletion in 10p and 11p. However, no such defects were observed in HL60 cells. Changes in gene expression in HL60RG cells were determined using expression arrays (Affymetrix GeneChip, HU133A). Candidate genes associated with the rapid growth of HL60RG cells were identified. Two tumor necrosis factor receptors, TNFRSF1B (type II tumor necrosis factor-α receptor) and TNFRSF8 (also known as a tumor marker CD30), which are adjacently located on chromosome 1 showed opposing changes in gene expression in HL60RG cells-over-expression of TNFRSF8 and repression of TNFRSF1B. Differences in the DNA methylation status in the transcriptional regulatory regions of both genes between HL60 and HL60RG was detected by a methylation-specific PCR assay. In conclusion, alterations in chromosome and gene expression in HL60RG may be associated with increased growth rate.

  1. Transcriptomic Analysis of Trout Gill Ionocytes in Fresh Water and Sea Water Using Laser Capture Microdissection Combined with Microarray Analysis

    PubMed Central

    Leguen, Isabelle; Le Cam, Aurélie; Montfort, Jérôme; Peron, Sandrine; Fautrel, Alain

    2015-01-01

    Fish gills represent a complex organ composed of several cell types that perform multiple physiological functions. Among these cells, ionocytes are implicated in the maintenance of ion homeostasis. However, because the ionocyte represents only a small percent of whole gill tissue, its specific transcriptome can be overlooked among the numerous cell types included in the gill. The objective of this study is to better understand ionocyte functions by comparing the RNA expression of this cell type in freshwater and seawater acclimated rainbow trout. To realize this objective, ionocytes were captured from gill cryosections using laser capture microdissection after immunohistochemistry. Then, transcriptome analyses were performed on an Agilent trout oligonucleotide microarray. Gene expression analysis identified 108 unique annotated genes differentially expressed between freshwater and seawater ionocytes, with a fold change higher than 3. Most of these genes were up-regulated in freshwater cells. Interestingly, several genes implicated in ion transport, extracellular matrix and structural cellular proteins appeared up-regulated in freshwater ionocytes. Among them, several ion transporters, such as CIC2, SLC26A6, and NBC, were validated by qPCR and/or in situ hybridization. The latter technique allowed us to localize the transcripts of these ion transporters in only ionocytes and more particularly in the freshwater cells. Genes involved in metabolism and also several genes implicated in transcriptional regulation, cell signaling and the cell cycle were also enhanced in freshwater ionocytes. In conclusion, laser capture microdissection combined with microarray analysis allowed for the determination of the transcriptional signature of scarce cells in fish gills, such as ionocytes, and aided characterization of the transcriptome of these cells in freshwater and seawater acclimated trout. PMID:26439495

  2. Transcriptomic Analysis of Trout Gill Ionocytes in Fresh Water and Sea Water Using Laser Capture Microdissection Combined with Microarray Analysis.

    PubMed

    Leguen, Isabelle; Le Cam, Aurélie; Montfort, Jérôme; Peron, Sandrine; Fautrel, Alain

    2015-01-01

    Fish gills represent a complex organ composed of several cell types that perform multiple physiological functions. Among these cells, ionocytes are implicated in the maintenance of ion homeostasis. However, because the ionocyte represents only a small percent of whole gill tissue, its specific transcriptome can be overlooked among the numerous cell types included in the gill. The objective of this study is to better understand ionocyte functions by comparing the RNA expression of this cell type in freshwater and seawater acclimated rainbow trout. To realize this objective, ionocytes were captured from gill cryosections using laser capture microdissection after immunohistochemistry. Then, transcriptome analyses were performed on an Agilent trout oligonucleotide microarray. Gene expression analysis identified 108 unique annotated genes differentially expressed between freshwater and seawater ionocytes, with a fold change higher than 3. Most of these genes were up-regulated in freshwater cells. Interestingly, several genes implicated in ion transport, extracellular matrix and structural cellular proteins appeared up-regulated in freshwater ionocytes. Among them, several ion transporters, such as CIC2, SLC26A6, and NBC, were validated by qPCR and/or in situ hybridization. The latter technique allowed us to localize the transcripts of these ion transporters in only ionocytes and more particularly in the freshwater cells. Genes involved in metabolism and also several genes implicated in transcriptional regulation, cell signaling and the cell cycle were also enhanced in freshwater ionocytes. In conclusion, laser capture microdissection combined with microarray analysis allowed for the determination of the transcriptional signature of scarce cells in fish gills, such as ionocytes, and aided characterization of the transcriptome of these cells in freshwater and seawater acclimated trout.

  3. Microarray Analysis of Gene Expression in Soybean Roots Susceptible to the Soybean Cyst Nematode Two Days Post Invasion

    PubMed Central

    Khan, R.; Alkharouf, N.; Beard, H.; MacDonald, M.; Chouikha, I.; Meyer, S.; Grefenstette, J.; Knap, H.; Matthews, B.

    2004-01-01

    Soybean root cells undergo dramatic morphological and biochemical changes during the establishment of a feeding site in a compatible interaction with the soybean cyst nematode (SCN). We constructed a cDNA microarray with approximately 1,300 cDNA inserts targeted to identify differentially expressed genes during the compatible interaction of SCN with soybean roots 2 days after infection. Three independent biological replicates were grown and inoculated with SCN, and 2 days later RNA was extracted for hybridization to microarrays and compared to noninoculated controls. Statistical analysis indicated that approximately 8% of the genes monitored were induced and more than 50% of these were genes of unknown function. Notable genes that were more highly expressed 2 days after inoculation with SCN as compared to noninoculated roots included the repetitive proline-rich glycoprotein, the stress-induced gene SAM22, ß-1,3-endoglucanase, peroxidase, and those involved in carbohydrate metabolism, plant defense, and signaling. PMID:19262812

  4. Microarray analysis of gene expression in soybean roots susceptible to the soybean cyst nematode two days post invasion.

    PubMed

    Khan, R; Alkharouf, N; Beard, H; Macdonald, M; Chouikha, I; Meyer, S; Grefenstette, J; Knap, H; Matthews, B

    2004-09-01

    Soybean root cells undergo dramatic morphological and biochemical changes during the establishment of a feeding site in a compatible interaction with the soybean cyst nematode (SCN). We constructed a cDNA microarray with approximately 1,300 cDNA inserts targeted to identify differentially expressed genes during the compatible interaction of SCN with soybean roots 2 days after infection. Three independent biological replicates were grown and inoculated with SCN, and 2 days later RNA was extracted for hybridization to microarrays and compared to noninoculated controls. Statistical analysis indicated that approximately 8% of the genes monitored were induced and more than 50% of these were genes of unknown function. Notable genes that were more highly expressed 2 days after inoculation with SCN as compared to noninoculated roots included the repetitive proline-rich glycoprotein, the stress-induced gene SAM22, ss-1,3-endoglucanase, peroxidase, and those involved in carbohydrate metabolism, plant defense, and signaling.

  5. CDNA microarray analysis of gene expression patterns in blood mononuclear cells of SLA-DRB1-defined Yorkshire pigs.

    PubMed

    Nino-Soto, M I; Jozani, R J; Bridle, B; Mallard, B A

    2008-01-01

    Three lines of commercialYorkshire pigs with defined SLA-DRB1 alleles were developed at the University of Guelph for xenotransplantation and immune response studies. Two of the SLA-DRB1 alleles have been previously reported (SLA-DRB1*0502 and *0701), whereas the third one is a new allele. The influence of defined SLA-DRB1 alleles on transcriptional patterns of immune-related genes in blood mononuclear cells (BMCs) of pigs was explored using cDNA microarray. Microarray analysis showed significant differential expression of inflammatory genes in association with the various SLA-DRB1 alleles. A better understanding of the association between SLA genotypes and gene activity can increase the knowledge of the function of these molecules, as well as define new strategies to control animal health and optimize animal production.

  6. 16S rRNA based microarray analysis of ten periodontal bacteria in patients with different forms of periodontitis.

    PubMed

    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.

  7. Microarray analysis of the Ler regulon in enteropathogenic and enterohaemorrhagic Escherichia coli strains.

    PubMed

    Bingle, Lewis E H; Constantinidou, Chrystala; Shaw, Robert K; Islam, Md Shahidul; Patel, Mala; Snyder, Lori A S; Lee, David J; Penn, Charles W; Busby, Stephen J W; Pallen, Mark J

    2014-01-01

    The type III protein secretion system is an important pathogenicity factor of enteropathogenic and enterohaemorrhagic Escherichia coli pathotypes. The genes encoding this apparatus are located on a pathogenicity island (the locus of enterocyte effacement) and are transcriptionally activated by the master regulator Ler. In each pathotype Ler is also known to regulate genes located elsewhere on the chromosome, but the full extent of the Ler regulon is unclear, especially for enteropathogenic E. coli. The Ler regulon was defined for two strains of E. coli: E2348/69 (enteropathogenic) and EDL933 (enterohaemorrhagic) in mid and late log phases of growth by DNA microarray analysis of the transcriptomes of wild-type and ler mutant versions of each strain. In both strains the Ler regulon is focused on the locus of enterocyte effacement - all major transcriptional units of which are activated by Ler, with the sole exception of the LEE1 operon during mid-log phase growth in E2348/69. However, the Ler regulon does extend more widely and also includes unlinked pathogenicity genes: in E2348/69 more than 50 genes outside of this locus were regulated, including a number of known or potential pathogenicity determinants; in EDL933 only 4 extra-LEE genes, again including known pathogenicity factors, were activated. In E2348/69, where the Ler regulon is clearly growth phase dependent, a number of genes including the plasmid-encoded regulator operon perABC, were found to be negatively regulated by Ler. Negative regulation by Ler of PerC, itself a positive regulator of the ler promoter, suggests a negative feedback loop involving these proteins.

  8. Aligning ontologies and integrating textual evidence for pathway analysis of microarray data

    SciTech Connect

    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.

  9. Association between FOXM1 and hedgehog signaling pathway in human cervical carcinoma by tissue microarray analysis

    PubMed Central

    Chen, Hong; Wang, Jingjing; Yang, Hong; Chen, Dan; Li, Panpan

    2016-01-01

    Forkhead box M1 (FOXM1) and hedgehog (Hh) signaling pathway are implicated in the formation and development of human tumors, including cervical cancer. Previous studies have indicated that FOXM1 may be a downstream target gene of the Hh signaling pathway, but their association in cervical cancer is largely unknown. In the present study, the expression of FOXM1 and Hh signaling molecules was evaluated by immunohistochemical analysis in a tissue microarray that contained 70 cervical cancer tissues and 10 normal cervical tissues. In addition, the association of these molecules with clinicopathological parameters, and the association between FOXM1 and various molecules involved in the Hh signaling pathway was investigated. The results indicated that FOXM1 and Hh signaling molecules were overexpressed in cervical cancer tissues. The protein expression levels of FOXM1, glioma-associated oncogene 1 (GLI1) and smoothened (SMO) correlated with the clinical stage of the tumors, while the protein expression levels of Sonic Hh (SHh), patched 1 (PTCH1) and GLI1 correlated with the pathological grade of the tumors. The expression levels of GLI1 were lower in tissues without lymph node metastasis than in tissues with lymph node metastasis. In addition, FOXM1 expression correlated with GLI1, SHh and PTCH1 expression in cancer tissues. These findings confirmed the participation of FOXM1 and the Hh signaling pathway in cervical cancer. Furthermore, the finding that FOXM1 may be a downstream target gene of the Hh signaling pathway in cervical cancer provides a potential novel diagnostic and therapeutic target for cervical cancer.

  10. Chromosomal microarray analysis as a first-tier clinical diagnostic test: Estonian experience

    PubMed Central

    Žilina, Olga; Teek, Rita; Tammur, Pille; Kuuse, Kati; Yakoreva, Maria; Vaidla, Eve; Mölter-Väär, Triin; Reimand, Tiia; Kurg, Ants; Õunap, Katrin

    2014-01-01

    Chromosomal microarray analysis (CMA) is now established as the first-tier cytogenetic diagnostic test for fast and accurate detection of chromosomal abnormalities in patients with developmental delay/intellectual disability (DD/ID), multiple congenital anomalies (MCA), and autism spectrum disorders (ASD). We present our experience with using CMA for postnatal and prenatal diagnosis in Estonian patients during 2009–2012. Since 2011, CMA is on the official service list of the Estonian Health Insurance Fund and is performed as the first-tier cytogenetic test for patients with DD/ID, MCA or ASD. A total of 1191 patients were analyzed, including postnatal (1072 [90%] patients and 59 [5%] family members) and prenatal referrals (60 [5%] fetuses). Abnormal results were reported in 298 (25%) patients, with a total of 351 findings (1–3 per individual): 147 (42%) deletions, 106 (30%) duplications, 89 (25%) long contiguous stretches of homozygosity (LCSH) events (>5 Mb), and nine (3%) aneuploidies. Of all findings, 143 (41%) were defined as pathogenic or likely pathogenic; for another 143 findings (41%), most of which were LCSH, the clinical significance remained unknown, while 61 (18%) reported findings can now be reclassified as benign or likely benign. Clinically relevant findings were detected in 126 (11%) patients. However, the proportion of variants of unknown clinical significance was quite high (41% of all findings). It seems that our ability to detect chromosomal abnormalities has far outpaced our ability to understand their role in disease. Thus, the interpretation of CMA findings remains a rather difficult task requiring a close collaboration between clinicians and cytogeneticists. PMID:24689080

  11. Chromosomal microarray analysis as a first-tier clinical diagnostic test: Estonian experience.

    PubMed

    Zilina, Olga; Teek, Rita; Tammur, Pille; Kuuse, Kati; Yakoreva, Maria; Vaidla, Eve; Mölter-Väär, Triin; Reimand, Tiia; Kurg, Ants; Ounap, Katrin

    2014-03-01

    Chromosomal microarray analysis (CMA) is now established as the first-tier cytogenetic diagnostic test for fast and accurate detection of chromosomal abnormalities in patients with developmental delay/intellectual disability (DD/ID), multiple congenital anomalies (MCA), and autism spectrum disorders (ASD). We present our experience with using CMA for postnatal and prenatal diagnosis in Estonian patients during 2009-2012. Since 2011, CMA is on the official service list of the Estonian Health Insurance Fund and is performed as the first-tier cytogenetic test for patients with DD/ID, MCA or ASD. A total of 1191 patients were analyzed, including postnatal (1072 [90%] patients and 59 [5%] family members) and prenatal referrals (60 [5%] fetuses). Abnormal results were reported in 298 (25%) patients, with a total of 351 findings (1-3 per individual): 147 (42%) deletions, 106 (30%) duplications, 89 (25%) long contiguous stretches of homozygosity (LCSH) events (>5 Mb), and nine (3%) aneuploidies. Of all findings, 143 (41%) were defined as pathogenic or likely pathogenic; for another 143 findings (41%), most of which were LCSH, the clinical significance remained unknown, while 61 (18%) reported findings can now be reclassified as benign or likely benign. Clinically relevant findings were detected in 126 (11%) patients. However, the proportion of variants of unknown clinical significance was quite high (41% of all findings). It seems that our ability to detect chromosomal abnormalities has far outpaced our ability to understand their role in disease. Thus, the interpretation of CMA findings remains a rather difficult task requiring a close collaboration between clinicians and cytogeneticists.

  12. Association between FOXM1 and hedgehog signaling pathway in human cervical carcinoma by tissue microarray analysis

    PubMed Central

    Chen, Hong; Wang, Jingjing; Yang, Hong; Chen, Dan; Li, Panpan

    2016-01-01

    Forkhead box M1 (FOXM1) and hedgehog (Hh) signaling pathway are implicated in the formation and development of human tumors, including cervical cancer. Previous studies have indicated that FOXM1 may be a downstream target gene of the Hh signaling pathway, but their association in cervical cancer is largely unknown. In the present study, the expression of FOXM1 and Hh signaling molecules was evaluated by immunohistochemical analysis in a tissue microarray that contained 70 cervical cancer tissues and 10 normal cervical tissues. In addition, the association of these molecules with clinicopathological parameters, and the association between FOXM1 and various molecules involved in the Hh signaling pathway was investigated. The results indicated that FOXM1 and Hh signaling molecules were overexpressed in cervical cancer tissues. The protein expression levels of FOXM1, glioma-associated oncogene 1 (GLI1) and smoothened (SMO) correlated with the clinical stage of the tumors, while the protein expression levels of Sonic Hh (SHh), patched 1 (PTCH1) and GLI1 correlated with the pathological grade of the tumors. The expression levels of GLI1 were lower in tissues without lymph node metastasis than in tissues with lymph node metastasis. In addition, FOXM1 expression correlated with GLI1, SHh and PTCH1 expression in cancer tissues. These findings confirmed the participation of FOXM1 and the Hh signaling pathway in cervical cancer. Furthermore, the finding that FOXM1 may be a downstream target gene of the Hh signaling pathway in cervical cancer provides a potential novel diagnostic and therapeutic target for cervical cancer. PMID:27698840

  13. Responses of Cultured Human Keratocytes and Myofibroblasts to Ethyl Pyruvate: A Microarray Analysis of Gene Expression

    PubMed Central

    Guerriero, Emily; Charukamnoetkanok, Nahthai; Piluek, Jordan; Schuman, Joel S.; SundarRaj, Nirmala

    2010-01-01

    Purpose. Ethyl pyruvate (EP) has pharmacologic effects that remediate cellular stress. In the organ-cultured murine lens, EP ameliorates oxidative stress, and in a rat cataract model, it attenuates cataract formation. However, corneal responses to EP have not been elucidated. In this study, the potential of EP as a therapeutic agent in corneal wound healing was determined by examining its effects on the transition of quiescent corneal stromal keratocytes into contractile myofibroblasts. Methods. Three independent preparations of cultured human keratocytes were treated with TGF-β1, to elicit a phenotypic transition to myofibroblasts in the presence or absence of 10 or 15 mM EP. Gene expression profiles of the 12 samples (keratocytes ± EP ± TGF-β1 for three preparations) were produced by using gene microarrays. Results. TGF-β1–driven twofold changes in at least two of three experiments defined a group of 1961 genes. Genes showing twofold modulation by EP in at least two experiments appeared exclusively in myofibroblasts (857 genes), exclusively in keratocytes (409 genes), or in both phenotypes (252 genes). Analysis of these three EP-modulated groups showed that EP (1) inhibited myofibroblast proliferation with concomitant modulation of some cell cycle genes, (2) augmented the NRF2-mediated antioxidant response in both keratocytes and myofibroblasts, and (3) modified the TGF-β1–driven transition of keratocytes to myofibroblasts by inhibiting the upregulation of a subset of profibrotic genes. Conclusions. These EP-induced phenotypic changes in myofibroblasts indicate the potential of EP as a therapeutic agent in corneal wound healing. PMID:20053976

  14. DNA Microarray Analysis in Screening Features of Genes Involved in Spinal Cord Injury

    PubMed Central

    Liu, Yugang; Wang, Ying; Teng, Zhaowei; Zhang, Xiufeng; Ding, Min; Zhang, Zhaojun; Chen, Junli; Xu, Yanli

    2016-01-01

    Background Spinal cord injury (SCI) is the most critical complication of spinal injury. We aimed to identify differentially expressed genes (DEGs) and to find associated pathways that may function as targets for SCI prognosis and therapy. Material/Methods Seven gene microarray expression profiles, downloaded from the GEO database (ID: GSE33886), were used to screen the DEGs of leg tissue and to compare these between SCI patients and corresponding normal specimens. Then, GO enrichment analysis was performed on these selected DEGs. Afterwards, interactions among these DEGs were analyzed by String database and then a PPI network was constructed to obtain topology character and modules in the PPI network. Finally, roles of the critical proteins in the pathway were explained by comparing the enrichment results of the genes in sub-modules and all the DEGs. Results A total of 113 DEGs were determined. We found that 21 up-regulated genes were enriched in 7 biological processes, while 9 down-regulated genes were significantly enriched in 4 KEGG pathways. The PPI network was constructed, including 40 interacting genes and 73 interactions. Three obvious function modules were identified by exploring the PPI network, and ACTC1 was identified as the critical protein in the 3 enriched signal pathways. However, no obvious difference was found in the signal pathway in which both the 11 genes in module 1 and all 113 DEGs participated. Conclusions Core proteins in the signal pathway associated with spinal cord injury may serve as potential prognostic and predictive markers for the diagnosis and treatment of spinal cord injury in clinical applications. PMID:27160807

  15. Equivalence testing in microarray analysis: similarities in the transcriptome of human atherosclerotic and nonatherosclerotic macrophages.

    PubMed

    Eijgelaar, Wouter J; Horrevoets, Anton J G; Bijnens, Ann-Pascale J J; Daemen, Mat J A P; Verhaegh, Wim F J

    2010-05-01

    We focus on similarities in the transcriptome of human Kupffer cells and alveolar, splenic, and atherosclerotic plaque-residing macrophages. We hypothesized that these macrophages share a common expression signature. We performed microarray analysis on mRNA from these subsets (4 patients) and developed a novel statistical method to identify genes with significantly similar expression levels. Phenotypic and functional diversity between macrophage subpopulations reflects their plasticity to respond to microenvironmental signals. Apart from detecting differences in expression profiles, the comparison of the transcriptomes of different macrophage populations may also allow the definition of molecular similarities between these subsets. This new method calculates the maximum difference in gene expression level, based on the estimated confidence interval on that gene's expression variance. We listed the genes by equivalence ranking relative to expression level. FDR estimation was used to determine significance. We identified 500 genes with significantly equivalent expression levels in the macrophage subsets at 5.5% FDR using a confidence level of α = 0.05 for equivalence. Among these are the established macrophage marker CD68, IL1 receptor antagonist, and MHC-related CD1C. These 500 genes were submitted to IPA and GO clustering using DAVID. Additionally, hierarchical clustering of these genes in the Novartis human gene expression atlas revealed a subset of 200 genes specifically expressed in macrophages. Equivalently expressed genes, identified by this new method, may not only help to dissect common molecular mechanisms, but also to identify cell- or condition-specific sets of marker genes that can be used for drug targeting and molecular imaging. PMID:20068025

  16. Identification of genes associated with tumorigenesis and metastatic potential of hypopharyngeal cancer by microarray analysis.

    PubMed

    Cromer, Anne; Carles, Annaïck; Millon, Régine; Ganguli, Gitali; Chalmel, Frédéric; Lemaire, Frédéric; Young, Julia; Dembélé, Doulaye; Thibault, Christelle; Muller, Danièle; Poch, Olivier; Abecassis, Joseph; Wasylyk, Bohdan

    2004-04-01

    Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer among men in the developed world. There is a need, for both clinical and scientific reasons, to find markers to identify patients with aggressive disease as early as possible, and to understand the events leading to malignant transformation and susceptibility to metastasis. We report the first large-scale gene expression analysis of a unique HNSCC location, the hypopharynx. Four normal and 34 tumour samples were analysed with 12 600 gene microarrays. Clusters of differentially expressed genes were identified in the chromosomal regions 3q27.3, 17q21.2-q21.31, 7q11.22-q22.1 and 11q13.1-q13.3, which, interestingly, have already been identified by comparative genomic hybridization (CGH) as major regions of gene amplification. We showed that six overexpressed genes (EIF4G1, DVL3, EPHB4, MCM7, BRMS1 and SART1) located in these regions are indeed amplified. We report 119 genes that are highly differentially expressed between 'early' tumours and normal samples. Of these, we validated by quantitative PCR six novel poorly characterized genes. These genes are potential new markers of HNSCC. Comparing patients with relatively nonaggressive and aggressive tumours (without or with clinical evidence of metastasis 3 years after surgery), we identified 164 differentially expressed genes potentially involved in the acquisition of metastatic potential. This study contributes to the understanding of HNSCC, staging patients into prognostic groups and identifying high-risk patients who may benefit from more aggressive treatment.

  17. Identification of human metapneumovirus-induced gene networks in airway epithelial cells by microarray analysis

    SciTech Connect

    Bao, X.; Sinha, M. |; Liu, T.; Hong, C.; Luxon, B.A. |; Garofalo, R.P. ||; Casola, A. ||

    2008-04-25

    Human metapneumovirus (hMPV) is a major cause of lower respiratory tract infections in infants, elderly and immunocompromised patients. Little is known about the response to hMPV infection of airway epithelial cells, which play a pivotal role in initiating and shaping innate and adaptive immune responses. In this study, we analyzed the transcriptional profiles of airway epithelial cells infected with hMPV using high-density oligonucleotide microarrays. Of the 47,400 transcripts and variants represented on the Affimetrix GeneChip Human Genome HG-U133 plus 2 array, 1601 genes were significantly altered following hMPV infection. Altered genes were then assigned to functional categories and mapped to signaling pathways. Many up-regulated genes are involved in the initiation of pro-inflammatory and antiviral immune responses, including chemokines, cytokines, type I interferon and interferon-inducible proteins. Other important functional classes up-regulated by hMPV infection include cellular signaling, gene transcription and apoptosis. Notably, genes associated with antioxidant and membrane transport activity, several metabolic pathways and cell proliferation were down-regulated in response to hMPV infection. Real-time PCR and Western blot assays were used to confirm the expression of genes related to several of these functional groups. The overall result of this study provides novel information on host gene expression upon infection with hMPV and also serves as a foundation for future investigations of genes and pathways involved in the pathogenesis of this important viral infection. Furthermore, it can facilitate a comparative analysis of other paramyxoviral infections to determine the transcriptional changes that are conserved versus the one that are specific to individual pathogens.

  18. Microarray Cluster Analysis of Irradiated Growth Plate Zones Following Laser Microdissection

    SciTech Connect

    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.

    2009-07-01

    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.

  19. T Cell Dynamic Activation and Functional Analysis in Nanoliter Droplet Microarray

    PubMed Central

    Sarkar, Saheli; Motwani, Vinny; Sabhachandani, Pooja; Cohen, Noa; Konry, Tania

    2015-01-01

    Objective Characterization of the heterogeneity in immune reactions requires assessing dynamic single cell responses as well as interactions between the various immune cell subsets. Maturation and activation of effector cells is regulated by cell contact-dependent and soluble factor-mediated paracrine signalling. Currently there are few methods available that allow dynamic investigation of both processes simultaneously without physically constraining non-adherent cells and eliminating crosstalk from neighboring cell pairs. We describe here a microfluidic droplet microarray platform that permits rapid functional analysis of single cell responses and co-encapsulation of heterotypic cell pairs, thereby allowing us to evaluate the dynamic activation state of primary T cells. Methods The microfluidic droplet platform enables generation and docking of monodisperse nanoliter volume (0.523 nl) droplets, with the capacity of monitoring a thousand droplets per experiment. Single human T cells were encapsulated in droplets and stimulated on-chip with the calcium ionophore ionomycin. T cells were also co-encapsulated with dendritic cells activated by ovalbumin peptide, followed by dynamic calcium signal monitoring. Results Ionomycin-stimulated cells depicted fluctuation in calcium signalling compared to control. Both cell populations demonstrated marked heterogeneity in responses. Calcium signalling was observed in T cells immediately following contact with DCs, suggesting an early activation signal. T cells further showed non-contact mediated increase in calcium level, although this response was delayed compared to contact-mediated signals. Conclusions Our results suggest that this nanoliter droplet array-based microfluidic platform is a promising technique for assessment of heterogeneity in various types of cellular responses, detection of early/delayed signalling events and live cell phenotyping of immune cells. PMID:26613065

  20. Quantitative analysis of p53 expression in human normal and cancer tissue microarray with global normalization method

    PubMed Central

    Idikio, Halliday A

    2011-01-01

    Tissue microarray based immunohistochemical staining and proteomics are important tools to create and validate clinically relevant cancer biomarkers. Immunohistochemical stains using formalin-fixed tissue microarray sections for protein expression are scored manually and semi-quantitatively. Digital image analysis methods remove some of the drawbacks of manual scoring but may need other methods such as normalization to provide across the board utility. In the present study, quantitative proteomics-based global normalization method was used to evaluate its utility in the analysis of p53 protein expression in mixed human normal and cancer tissue microarray. Global normalization used the mean or median of β-actin to calculate ratios of individual core stain intensities, then log transformed the ratios, calculate a mean or median and subtracted the value from the log of ratios. In the absence of global normalization of p53 protein expression, 44% (42 of 95) of tissue cores were positive using the median of intensity values and 40% (38 of 95) using the mean of intensities as cut-off points. With global normalization, p53 positive cores changed to 20% (19 of 95) when using median of intensities and 15.8%(15 of 95) when the mean of intensities were used. In conclusion, the global normalization method helped to define positive p53 staining in the tissue microarray set used. The method used helped to define clear cut-off points and confirmed all negatively stained tissue cores. Such normalization methods should help to better define clinically useful biomarkers. PMID:21738821

  1. ValWorkBench: an open source Java library for cluster validation, with applications to microarray data analysis.

    PubMed

    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.

  2. Assembly of a gene sequence tag microarray by reversible biotin-streptavidin capture for transcript analysis of Arabidopsis thaliana

    PubMed Central

    Wirta, Valtteri; Holmberg, Anders; Lukacs, Morten; Nilsson, Peter; Hilson, Pierre; Uhlén, Mathias; Bhalerao, Rishikesh P; Lundeberg, Joakim

    2005-01-01

    Background Transcriptional profiling using microarrays has developed into a key molecular tool for the elucidation of gene function and gene regulation. Microarray platforms based on either oligonucleotides or purified amplification products have been utilised in parallel to produce large amounts of data. Irrespective of platform examined, the availability of genome sequence or a large number of representative expressed sequence tags (ESTs) is, however, a pre-requisite for the design and selection of specific and high-quality microarray probes. This is of great importance for organisms, such as Arabidopsis thaliana, with a high number of duplicated genes, as cross-hybridisation signals between evolutionary related genes cannot be distinguished from true signals unless the probes are carefully designed to be specific. Results We present an alternative solid-phase purification strategy suitable for efficient preparation of short, biotinylated and highly specific probes suitable for large-scale expression profiling. Twenty-one thousand Arabidopsis thaliana gene sequence tags were amplified and subsequently purified using the described technology. The use of the arrays is exemplified by analysis of gene expression changes caused by a four-hour indole-3-acetic (auxin) treatment. A total of 270 genes were identified as differentially expressed (120 up-regulated and 150 down-regulated), including several previously known auxin-affected genes, but also several previously uncharacterised genes. Conclusions The described solid-phase procedure can be used to prepare gene sequence tag microarrays based on short and specific amplified probes, facilitating the analysis of more than 21 000 Arabidopsis transcripts. PMID:15689241

  3. Identifying the impact of G-quadruplexes on Affymetrix 3' arrays using cloud computing.

    PubMed

    Memon, Farhat N; Owen, Anne M; Sanchez-Graillet, Olivia; Upton, Graham J G; Harrison, Andrew P

    2010-01-15

    A tetramer quadruplex structure is formed by four parallel strands of DNA/ RNA containing runs of guanine. These quadruplexes are able to form because guanine can Hoogsteen hydrogen bond to other guanines, and a tetrad of guanines can form a stable arrangement. Recently we have discovered that probes on Affymetrix GeneChips that contain runs of guanine do not measure gene expression reliably. We associate this finding with the likelihood that quadruplexes are forming on the surface of GeneChips. In order to cope with the rapidly expanding size of GeneChip array datasets in the public domain, we are exploring the use of cloud computing to replicate our experiments on 3' arrays to look at the effect of the location of G-spots (runs of guanines). Cloud computing is a recently introduced high-performance solution that takes advantage of the computational infrastructure of large organisations such as Amazon and Google. We expect that cloud computing will become widely adopted because it enables bioinformaticians to avoid capital expenditure on expensive computing resources and to only pay a cloud computing provider for what is used. Moreover, as well as financial efficiency, cloud computing is an ecologically-friendly technology, it enables efficient data-sharing and we expect it to be faster for development purposes. Here we propose the advantageous use of cloud computing to perform a large data-mining analysis of public domain 3' arrays.

  4. Microarray as a First Genetic Test in Global Developmental Delay: A Cost-Effectiveness Analysis

    ERIC Educational Resources Information Center

    Trakadis, Yannis; Shevell, Michael

    2011-01-01

    Aim: Microarray technology has a significantly higher clinical yield than karyotyping in individuals with global developmental delay (GDD). Despite this, it has not yet been routinely implemented as a screening test owing to the perception that this approach is more expensive. We aimed to evaluate the effect that replacing karyotype with…

  5. Microarray analysis of iron deficiency chlorosis in near-isogenic soybean lines

    Technology Transfer Automated Retrieval System (TEKTRAN)

    RNA isolated from the roots of two near isogenic lines, which differ in iron efficiency, PI548533 (Clark; iron efficient) and PI547430 (IsoClark; iron inefficient), were compared on a spotted microarray slide containing 9,728 cDNAs from root specific EST libraries. A comparison of RNA transcripts i...

  6. Profiling Humoral Immune Responses to Clostridium difficile-Specific Antigens by Protein Microarray Analysis

    PubMed Central

    Negm, Ola H.; Hamed, Mohamed R.; Dilnot, Elizabeth M.; Shone, Clifford C.; Marszalowska, Izabela; Lynch, Mark; Loscher, Christine E.; Edwards, Laura J.; Tighe, Patrick J.; Wilcox, Mark H.

    2015-01-01

    Clostridium difficile is an anaerobic, Gram-positive, and spore-forming bacterium that is the leading worldwide infective cause of hospital-acquired and antibiotic-associated diarrhea. Several studies have reported associations between humoral immunity and the clinical course of C. difficile infection (CDI). Host humoral immune responses are determined using conventional enzyme-linked immunosorbent assay (ELISA) techniques. Herein, we report the first use of a novel protein microarray assay to determine systemic IgG antibody responses against a panel of highly purified C. difficile-specific antigens, including native toxins A and B (TcdA and TcdB, respectively), recombinant fragments of toxins A and B (TxA4 and TxB4, respectively), ribotype-specific surface layer proteins (SLPs; 001, 002, 027), and control proteins (tetanus toxoid and Candida albicans). Microarrays were probed with sera from a total of 327 individuals with CDI, cystic fibrosis without diarrhea, and healthy controls. For all antigens, precision profiles demonstrated <10% coefficient of variation (CV). Significant correlation was observed between microarray and ELISA in the quantification of antitoxin A and antitoxin B IgG. These results indicate that microarray is a suitable assay for defining humoral immune responses to C. difficile protein antigens and may have potential advantages in throughput, convenience, and cost. PMID:26178385

  7. DNA methylation analysis using CpG microarrays is impaired in benzopyrene exposed cells

    SciTech Connect

    Sadikovic, Bekim; Andrews, Joseph; Rodenhiser, David I.

    2007-12-15

    Epigenetic alterations have emerged as a key mechanism involved in tumorigenesis. These disruptions are partly due to environmental factors that change normal DNA methylation patterns necessary for transcriptional regulation and chromatin compaction. Microarray technologies are allowing environmentally susceptible epigenetic patterns to be mapped and the precise targets of environmentally induced alterations to be identified. Previously, we observed BaP-induced epigenetic events and cell cycle disruptions in breast cancer cell lines that included time- and concentration-dependent loss of proliferation as well as sequence-specific hypo- and hypermethylation events. In this present report, we further characterized epigenetic changes in BaP-exposed MCF-7 cells. We analyzed DNA methylation on a CpG island microarray platform with over 5400 unique genomic regions. Depleted and enriched microarray targets, representative of putative DNA methylation changes, were identified across the genome; however, subsequent sodium bisulfite analyses revealed no changes in DNA methylation at a number of these loci. Instead, we found that the identification of DNA methylation changes using this restriction enzyme-based microarray approach corresponded with the regions of DNA bound by the BaP derived DNA adducts. This DNA adduct formation occurs at both methylated and unmethylated CpG dinucleotides and affects PCR amplification during sample preparation. Our data suggest that caution should be exercised when interpreting data from comparative microarray experiments that rely on enzymatic reactions. These results are relevant to genome screening approaches involving environmental exposures in which DNA adduct formation at specific nucleotide sites may bias target acquisition and compromise the correct identification of epigenetically responsive genes.

  8. The Microarray Revolution: Perspectives from Educators

    ERIC Educational Resources Information Center

    Brewster, Jay L.; Beason, K. Beth; Eckdahl, Todd T.; Evans, Irene M.

    2004-01-01

    In recent years, microarray analysis has become a key experimental tool, enabling the analysis of genome-wide patterns of gene expression. This review approaches the microarray revolution with a focus upon four topics: 1) the early development of this technology and its application to cancer diagnostics; 2) a primer of microarray research,…

  9. A Unique Procedure to Identify Cell Surface Markers Through a Spherical Self-Organizing Map Applied to DNA Microarray Analysis.

    PubMed

    Sugii, Yuh; Kasai, Tomonari; Ikeda, Masashi; Vaidyanath, Arun; Kumon, Kazuki; Mizutani, Akifumi; Seno, Akimasa; Tokutaka, Heizo; Kudoh, Takayuki; Seno, Masaharu

    2016-01-01

    To identify cell-specific markers, we designed a DNA microarray platform with oligonucleotide probes for human membrane-anchored proteins. Human glioma cell lines were analyzed using microarray and compared with normal and fetal brain tissues. For the microarray analysis, we employed a spherical self-organizing map, which is a clustering method suitable for the conversion of multidimensional data into two-dimensional data and displays the relationship on a spherical surface. Based on the gene expression profile, the cell surface characteristics were successfully mirrored onto the spherical surface, thereby distinguishing normal brain tissue from the disease model based on the strength of gene expression. The clustered glioma-specific genes were further analyzed by polymerase chain reaction procedure and immunocytochemical staining of glioma cells. Our platform and the following procedure were successfully demonstrated to categorize the genes coding for cell surface proteins that are specific to glioma cells. Our assessment demonstrates that a spherical self-organizing map is a valuable tool for distinguishing cell surface markers and can be employed in marker discovery studies for the treatment of cancer.

  10. A Unique Procedure to Identify Cell Surface Markers Through a Spherical Self-Organizing Map Applied to DNA Microarray Analysis

    PubMed Central

    Sugii, Yuh; Kasai, Tomonari; Ikeda, Masashi; Vaidyanath, Arun; Kumon, Kazuki; Mizutani, Akifumi; Seno, Akimasa; Tokutaka, Heizo; Kudoh, Takayuki; Seno, Masaharu

    2016-01-01

    To identify cell-specific markers, we designed a DNA microarray platform with oligonucleotide probes for human membrane-anchored proteins. Human glioma cell lines were analyzed using microarray and compared with normal and fetal brain tissues. For the microarray analysis, we employed a spherical self-organizing map, which is a clustering method suitable for the conversion of multidimensional data into two-dimensional data and displays the relationship on a spherical surface. Based on the gene expression profile, the cell surface characteristics were successfully mirrored onto the spherical surface, thereby distinguishing normal brain tissue from the disease model based on the strength of gene expression. The clustered glioma-specific genes were further analyzed by polymerase chain reaction procedure and immunocytochemical staining of glioma cells. Our platform and the following procedure were successfully demonstrated to categorize the genes coding for cell surface proteins that are specific to glioma cells. Our assessment demonstrates that a spherical self-organizing map is a valuable tool for distinguishing cell surface markers and can be employed in marker discovery studies for the treatment of cancer. PMID:26966393

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

    PubMed

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

    2014-02-01

    Chromosomal microarray analysis is now commonly used in clinical practice to identify copy number variants (CNVs) in the human genome. We report our experience with the use of the 105 K and 180K oligonucleotide microarrays in 215 consecutive patients referred with either autism or autism spectrum disorders (ASD) or developmental delay/learning disability for genetic services at the University of Kansas Medical Center during the past 4 years (2009-2012). Of the 215 patients [140 males and 75 females (male/female ratio=1.87); 65 with ASD and 150 with learning disability], abnormal microarray results were seen in 45 individuals (21%) with a total of 49 CNVs. Of these findings, 32 represented a known diagnostic CNV contributing to the clinical presentation and 17 represented non-diagnostic CNVs (variants of unknown significance). Thirteen patients with ASD had a total of 14 CNVs, 6 CNVs recognized as diagnostic and 8 as non-diagnostic. The most common chromosome involved in the ASD group was chromosome 15. For those with a learning disability, 32 patients had a total of 35 CNVs. Twenty-six of the 35 CNVs were classified as a known diagnostic CNV, usually a deletion (n=20). Nine CNVs were classified as an unknown non-diagnostic CNV, usually a duplication (n=8). For the learning disability subgroup, chromosomes 2 and 22 were most involved. Thirteen out of 65 patients (20%) with ASD had a CNV compared with 32 out of 150 patients (21%) with a learning disability. The frequency of chromosomal microarray abnormalities compared by subject group or gender was not statistically different. A higher percentage of individuals with a learning disability had clinical findings of seizures, dysmorphic features and microcephaly, but not statistically significant. While both groups contained more males than females, a significantly higher percentage of males were present in the ASD group. PMID:24188901

  12. Chromosomal Microarray Analysis of Consecutive Individuals with Autism Spectrum Disorders or Learning Disability Presenting for Genetic Services

    PubMed Central

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

    2015-01-01

    Chromosomal microarray analysis is now commonly used in clinical practice to identify copy number variants (CNVs) in the human genome. We report our experience with the use of the 105K and 180K oligonucleotide microarrays in 215 consecutive patients referred with either autism or autism spectrum disorders (ASD) or developmental delay/learning disability for genetic services at the University of Kansas Medical Center during the past 4 years (2009–2012). Of the 215 patients [140 males and 75 females (male/female ratio = 1.87); 65 with ASD and 150 with learning disability], abnormal microarray results were seen in 45 individuals (21%) with a total of 49 CNVs. Of these findings, 32 represented a known diagnostic CNV contributing to the clinical presentation and 17 represented non-diagnostic CNVs (variants of unknown significance). Thirteen patients with ASD had a total of 14 CNVs, 6 CNVs recognized as diagnostic and 8 as non-diagnostic. The most common chromosome involved in the ASD group was chromosome 15. For those with a learning disability, 32 patients had a total of 35 CNVs. Twenty-six of the 35 CNVs were classified as a known diagnostic CNV, usually a deletion (n = 20). Nine CNVs were classified as an unknown non-diagnostic CNV, usually a duplication (n = 8). For the learning disability subgroup, chromosomes 2 and 22 were most involved. Thirteen out of 65 patients (20%) with ASD had a CNV compared with 32 out of 150 patients (21%) with a learning disability. The frequency of chromosomal microarray abnormalities compared by subject group or gender was not statistically different. A higher percentage of individuals with a learning disability had clinical findings of seizures, dysmorphic features and microcephaly, but not statistically significant. While both groups contained more males than females, a significantly higher percentage of males were present in the ASD group. PMID:24188901

  13. Chromosome Microarray.

    PubMed

    Anderson, Sharon

    2016-01-01

    Over the last half century, knowledge about genetics, genetic testing, and its complexity has flourished. Completion of the Human Genome Project provided a foundation upon which the accuracy of genetics, genomics, and integration of bioinformatics knowledge and testing has grown exponentially. What is lagging, however, are efforts to reach and engage nurses about this rapidly changing field. The purpose of this article is to familiarize nurses with several frequently ordered genetic tests including chromosomes and fluorescence in situ hybridization followed by a comprehensive review of chromosome microarray. It shares the complexity of microarray including how testing is performed and results analyzed. A case report demonstrates how this technology is applied in clinical practice and reveals benefits and limitations of this scientific and bioinformatics genetic technology. Clinical implications for maternal-child nurses across practice levels are discussed. PMID:27276104

  14. Sex-related gene expression profiles in the adrenal cortex in the mature rat: Microarray analysis with emphasis on genes involved in steroidogenesis

    PubMed Central

    TREJTER, MARCIN; HOCHOL, ANNA; TYCZEWSKA, MARIANNA; ZIOLKOWSKA, AGNIESZKA; JOPEK, KAROL; SZYSZKA, MARTA; MALENDOWICZ, LUDWIK K; RUCINSKI, MARCIN

    2015-01-01

    Notable sex-related differences exist in mammalian adrenal cortex structure and function. In adult rats, the adrenal weight and the average volume of zona fasciculata cells of females are larger and secrete greater amounts of corticosterone than those of males. The molecular bases of these sex-related differences are poorly understood. In this study, to explore the molecular background of these differences, we defined zone- and sex-specific transcripts in adult male and female (estrous cycle phase) rats. Twelve-week-old rats of both genders were used and samples were taken from the zona glomerulosa (ZG) and zona fasciculata/reticularis (ZF/R) zones. Transcriptome identification was carried out using the Affymetrix® Rat Gene 1.1 ST Array. The microarray data were compared by fold change with significance according to moderated t-statistics. Subsequently, we performed functional annotation clustering using the Gene Ontology (GO) and Database for Annotation, Visualization and Integrated Discovery (DAVID). In the first step, we explored differentially expressed transcripts in the adrenal ZG and ZF/R. The number of differentially expressed transcripts was notably higher in the female than in the male rats (702 vs. 571). The differentially expressed genes which were significantly enriched included genes involved in steroid hormone metabolism, and their expression levels in the ZF/R of adult female rats were significantly higher compared with those in the male rats. In the female ZF/R, when compared with that of the males, prevailing numbers of genes linked to cell fraction, oxidation/reduction processes, response to nutrients and to extracellular stimuli or steroid hormone stimuli were downregulated. The microarray data for key genes involved directly in steroidogenesis were confirmed by qPCR. Thus, when compared with that of the males, in the female ZF/R, higher expression levels of genes involved directly in steroid hormone synthesis were accompanied by lower

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

    PubMed

    Li, Lu; Wang, Xianwei; Zhang, Xiaoli; Wang, Jinxing; Jin, Wenrui

    2015-01-01

    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(-16) mol L(-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 types of cDNAs corresponding to beta-2-microglobulin, glyceraldehyde-3-phosphate dehydrogenase and ribosomal protein, large, P2 mRNAs in single human breast cancer cells and 5 random synthetic DNAts are simultaneously quantified to examine the SMA and SMA-based single-cell multiple gene expression analysis. PMID:25479875

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

    PubMed

    Li, Lu; Wang, Xianwei; Zhang, Xiaoli; Wang, Jinxing; Jin, Wenrui

    2015-01-01

    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(-16) mol L(-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 types of cDNAs corresponding to beta-2-microglobulin, glyceraldehyde-3-phosphate dehydrogenase and ribosomal protein, large, P2 mRNAs in single human breast cancer cells and 5 random synthetic DNAts are simultaneously quantified to examine the SMA and SMA-based single-cell multiple gene expression analysis.

  17. Collection of Epithelial Cells from Rodent Mammary Gland Via Laser Capture Microdissection Yielding High-Quality RNA Suitable for Microarray Analysis

    PubMed Central

    2010-01-01

    Laser capture microdissection (LCM) enables collection of cell populations highly enriched for specific cell types that have the potential of yielding critical information about physiological and pathophysiological processes. One use of cells collected by LCM is for gene expression profiling. Samples intended for transcript analyses should be of the highest quality possible. RNA degradation is an ever-present concern in molecular biological assays, and LCM is no exception. This paper identifies issues related to preparation, collection, and processing in a lipid-rich tissue, rodent mammary gland, in which the epithelial to stromal cell ratio is low and the stromal component is primarily adipocytes, a situation that presents numerous technical challenges for high-quality RNA isolation. Our goal was to improve the procedure so that a greater probe set present call rate would be obtained when isolated RNA was evaluated using Affymetrix microarrays. The results showed that the quality of RNA isolated from epithelial cells of both mammary gland and mammary adenocarcinomas was high with a probe set present call rate of 65% and a high signal-to-noise ratio. PMID:21406068

  18. Microarrays for Undergraduate Classes

    ERIC Educational Resources Information Center

    Hancock, Dale; Nguyen, Lisa L.; Denyer, Gareth S.; Johnston, Jill M.

    2006-01-01

    A microarray experiment is presented that, in six laboratory sessions, takes undergraduate students from the tissue sample right through to data analysis. The model chosen, the murine erythroleukemia cell line, can be easily cultured in sufficient quantities for class use. Large changes in gene expression can be induced in these cells by…

  19. DNA microarray analysis of functionally discrete human brain regions reveals divergent transcriptional profiles

    PubMed Central

    Evans, S.J.; Choudary, P.V.; Vawter, M.P.; Li, J.; Meador-Woodruff, J.H.; Lopez, J.F.; Burke, S.M.; Thompson, R.C.; Myers, R.M.; Jones, E.G.; Bunney, W.E.; Watson, S.J.; Akil, H.

    2010-01-01

    Transcriptional profiles within discrete human brain regions are likely to reflect structural and functional specialization. Using DNA microarray technology, this study investigates differences in transcriptional profiles of highly divergent brain regions (the cerebellar cortex and the cerebral cortex) as well as differences between two closely related brain structures (the anterior cingulate cortex and the dorsolateral prefrontal cortex). Replication of this study across three independent laboratories, to address false-positive and false-negative results using microarray technology, is also discussed. We find greater than a thousand transcripts to be differentially expressed between cerebellum and cerebral cortex and very few transcripts to be differentially expressed between the two neocortical regions. We further characterized transcripts that were found to be specifically expressed within brain regions being compared and found that ontological classes representing signal transduction machinery, neurogenesis, synaptic transmission, and transcription factors were most highly represented. PMID:14572446

  20. DNA microarray analysis suggests that zinc pyrithione causes iron starvation to the yeast Saccharomyces cerevisiae.

    PubMed

    Yasokawa, Daisuke; Murata, Satomi; Iwahashi, Yumiko; Kitagawa, Emiko; Kishi, Katsuyuki; Okumura, Yukihiro; Iwahashi, Hitoshi

    2010-05-01

    Zinc pyrithione has been used in anti-dandruff shampoos and in anti-fouling paint on ships. However, little is known of its mode of action. We characterized the effects of sub-lethal concentrations of zinc pyrithione (Zpt) on Saccharomyces cerevisiae using DNA microarrays. The majority of the strongly upregulated genes are related to iron transport, and many of the strongly downregulated genes are related to the biosynthesis of cytochrome (heme). These data suggest that Zpt induces severe iron starvation. To confirm the DNA microarray data, we supplemented cultures containing Zpt with iron, and the growth of the yeast was restored significantly. From these results, we propose that the principal toxicity of zinc pyrithione arises from iron starvation. PMID:20347771

  1. A custom microarray platform for analysis of microRNA gene expression.

    PubMed

    Thomson, J Michael; Parker, Joel; Perou, Charles M; Hammond, Scott M

    2004-10-01

    MicroRNAs are short, noncoding RNA transcripts that post-transcriptionally regulate gene expression. Several hundred microRNA genes have been identified in Caenorhabditis elegans, Drosophila, plants and mammals. MicroRNAs have been linked to developmental processes in C. elegans, plants and humans and to cell growth and apoptosis in Drosophila. A major impediment in the study of microRNA function is the lack of quantitative expression profiling methods. To close this technological gap, we have designed dual-channel microarrays that monitor expression levels of 124 mammalian microRNAs. Using these tools, we observed distinct patterns of expression among adult mouse tissues and embryonic stem cells. Expression profiles of staged embryos demonstrate temporal regulation of a large class of microRNAs, including members of the let-7 family. This microarray technology enables comprehensive investigation of microRNA expression, and furthers our understanding of this class of recently discovered noncoding RNAs.

  2. A New Modified Histogram Matching Normalization for Time Series Microarray Analysis

    PubMed Central

    Astola, Laura; Molenaar, Jaap

    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 continuous time ODE model. We propose an alternative normalization method that is better suited for network inference from time series data.

  3. Analysis of sensitivity and rapid hybridization of a multiplexed Microbial Detection Microarray

    SciTech Connect

    Thissen, James B.; McLoughlin, Kevin; Gardner, Shea; Gu, Pauline; Mabery, Shalini; Slezak, Tom; Jaing, Crystal

    2014-06-01

    Microarrays have proven to be useful in rapid detection of many viruses and bacteria. Pathogen detection microarrays have been used to diagnose viral and bacterial infections in clinical samples and to evaluate the safety of biological drug materials. A multiplexed version of the Lawrence Livermore Microbial Detection Array (LLMDA) was developed and evaluated with minimum detectable concentrations for pure unamplified DNA viruses, along with mixtures of viral and bacterial DNA subjected to different whole genome amplification protocols. In addition the performance of the array was tested when hybridization time was reduced from 17 h to 1 h. The LLMDA was able to detect unamplified vaccinia virus DNA at a concentration of 14 fM, or 100,000 genome copies in 12 μL of sample. With amplification, positive identification was made with only 100 genome copies of input material. When tested against human stool samples from patients with acute gastroenteritis, the microarray detected common gastroenteritis viral and bacterial infections such as rotavirus and E. coli. Accurate detection was found but with a 4-fold drop in sensitivity for a 1 h compared to a 17 h hybridization. The array detected 2 ng (equivalent concentration of 15.6 fM) of labeled DNA from a virus with 1 h hybridization without any amplification, and was able to identify the components of a mixture of viruses and bacteria at species and in some cases strain level resolution. Sensitivity improved by three orders of magnitude with random whole genome amplification prior to hybridization; for instance, the array detected a DNA virus with only 20 fg or 100 genome copies as input. This multiplexed microarray is an efficient tool to analyze clinical and environmental samples for the presence of multiple viral and bacterial pathogens rapidly.

  4. Analysis of sensitivity and rapid hybridization of a multiplexed Microbial Detection Microarray

    DOE PAGES

    Thissen, James B.; McLoughlin, Kevin; Gardner, Shea; Gu, Pauline; Mabery, Shalini; Slezak, Tom; Jaing, Crystal

    2014-06-01

    Microarrays have proven to be useful in rapid detection of many viruses and bacteria. Pathogen detection microarrays have been used to diagnose viral and bacterial infections in clinical samples and to evaluate the safety of biological drug materials. A multiplexed version of the Lawrence Livermore Microbial Detection Array (LLMDA) was developed and evaluated with minimum detectable concentrations for pure unamplified DNA viruses, along with mixtures of viral and bacterial DNA subjected to different whole genome amplification protocols. In addition the performance of the array was tested when hybridization time was reduced from 17 h to 1 h. The LLMDA wasmore » able to detect unamplified vaccinia virus DNA at a concentration of 14 fM, or 100,000 genome copies in 12 μL of sample. With amplification, positive identification was made with only 100 genome copies of input material. When tested against human stool samples from patients with acute gastroenteritis, the microarray detected common gastroenteritis viral and bacterial infections such as rotavirus and E. coli. Accurate detection was found but with a 4-fold drop in sensitivity for a 1 h compared to a 17 h hybridization. The array detected 2 ng (equivalent concentration of 15.6 fM) of labeled DNA from a virus with 1 h hybridization without any amplification, and was able to identify the components of a mixture of viruses and bacteria at species and in some cases strain level resolution. Sensitivity improved by three orders of magnitude with random whole genome amplification prior to hybridization; for instance, the array detected a DNA virus with only 20 fg or 100 genome copies as input. This multiplexed microarray is an efficient tool to analyze clinical and environmental samples for the presence of multiple viral and bacterial pathogens rapidly.« less

  5. SNOMAD (Standardization and NOrmalization of MicroArray Data): web-accessible gene expression data analysis.

    PubMed

    Colantuoni, Carlo; Henry, George; Zeger, Scott; Pevsner, Jonathan

    2002-11-01

    SNOMAD is a collection of algorithms for the normalization and standardization of gene expression datasets derived from diverse biological and technological sources. In addition to conventional transformations and visualization tools, SNOMAD includes two non-linear transformations which correct for bias and variance which are non-uniformly distributed across the range of microarray element signal intensities: (1). Local mean normalization; and (2). Local variance correction (Z-score generation using a locally calculated standard deviation).

  6. Antibody Colocalization Microarray: A Scalable Technology for Multiplex Protein Analysis in Complex Samples*

    PubMed Central

    Pla-Roca, M.; Leulmi, R. F.; Tourekhanova, S.; Bergeron, S.; Laforte, V.; Moreau, E.; Gosline, S. J. C.; Bertos, N.; Hallett, M.; Park, M.; Juncker, D.

    2012-01-01

    DNA microarrays were rapidly scaled up from 256 to 6.5 million targets, and although antibody microarrays were proposed earlier, sensitive multiplex sandwich assays have only been scaled up to a few tens of targets. Cross-reactivity, arising because detection antibodies are mixed, is a known weakness of multiplex sandwich assays that is mitigated by lengthy optimization. Here, we introduce (1) vulnerability as a metric for assays. The vulnerability of multiplex sandwich assays to cross-reactivity increases quadratically with the number of targets, and together with experimental results, substantiates that scaling up of multiplex sandwich assays is unfeasible. We propose (2) a novel concept for multiplexing without mixing named antibody colocalization microarray (ACM). In ACMs, both capture and detection antibodies are physically colocalized by spotting to the same two-dimensional coordinate. Following spotting of the capture antibodies, the chip is removed from the arrayer, incubated with the sample, placed back onto the arrayer and then spotted with the detection antibodies. ACMs with up to 50 targets were produced, along with a binding curve for each protein. The ACM was validated by comparing it to ELISA and to a small-scale, conventional multiplex sandwich assay (MSA). Using ACMs, proteins in the serum of breast cancer patients and healthy controls were quantified, and six candidate biomarkers identified. Our results indicate that ACMs are sensitive, robust, and scalable. PMID:22171321

  7. Microarray analysis of gene expression in disk abalone Haliotis discus discus after bacterial challenge.

    PubMed

    De Zoysa, Mahanama; Nikapitiya, Chamilani; Oh, Chulhong; Lee, Youngdeuk; Whang, Ilson; Lee, Jae-Seong; Choi, Cheol Young; Lee, Jehee

    2011-02-01

    In this study, we investigated the gene expression profiling of disk abalone, Haliotis discus discus challenged by a mixture of three pathogenic bacteria Vibrio alginolyticus, Vibrio parahemolyticus, and Listeria monocytogenes using a cDNA microarray. Upon bacteria challenge, 68 (1.6%) and 112 (2.7%) gene transcripts changed their expression levels ≥2 or ≤2 -fold in gills and digestive tract, respectively. There were 46 tissue-specific transcripts that up-regulated specifically in the digestive tract. In contrast, only 13 transcripts showed gill-specific up-regulation. Quantitative real-time PCR was performed to verify microarray data and results revealed that candidate genes namely Krüppell-like factor (KLF), lachesin, muscle lim protein, thioredoxin-2 (TRx-2), nuclear factor interleukin 3 (NFIL-3) and abalone protein 38 were up-regulated. Also, our results further indicated that bacteria challenge may activate the transcription factors or their activators (Krüppell-like factor, inhibitor of NF-κB or Ik-B), inflammatory cytokines (IL-3 regulated protein, allograft inflammatory factor), other cytokines (IFN-44-like protein, SOCS-2), antioxidant enzymes (glutathione-S-transferase, thioredoxin-2 and thioredoxin peroxidase), and apoptosis-related proteins (TNF-α, archeron) in abalone. The identification of immune and stress response genes and their expression profiles in this microarray will permit detailed investigation of the stress and immune responses of abalone genes.

  8. Comparison of L1000 and Affymetrix Microarray for In Vitro Concentration-Response Gene Expression Profiling (SOT)

    EPA Science Inventory

    Advances in high-throughput screening technologies and in vitro systems have opened doors for cost-efficient evaluation of chemical effects on a diversity of biological endpoints. However, toxicogenomics platforms remain too costly to evaluate large libraries of chemicals in conc...

  9. Diagnostic Yield of Chromosomal Microarray Analysis in a Cohort of Patients with Autism Spectrum Disorders from a Highly Consanguineous Population.

    PubMed

    Al-Mamari, Watfa; Al-Saegh, Abeer; Al-Kindy, Adila; Bruwer, Zandre; Al-Murshedi, Fathiya; Al-Thihli, Khalid

    2015-08-01

    Autism Spectrum Disorders are a complicated group of disorders characterized with heterogeneous genetic etiologies. The genetic investigations for this group of disorders have expanded considerably over the past decade. In our study we designed a tired approach and studied the diagnostic yield of chromosomal microarray analysis on patients referred to the Genetic and Developmental Medicine clinic in Sultan Qaboos University in Oman for autism spectrum disorders in a highly consanguineous population. Copy number variants were seen in 27% of our studied cohort of patients and it was strongly associated with dysmorphic features and congenital anomalies. PMID:25703031

  10. Identification of hypoxia-responsive genes in a dopaminergic cell line by subtractive cDNA libraries and microarray analysis.

    PubMed

    Beitner-Johnson, D; Seta, K; Yuan, Y; Kim, H -W.; Rust, R T.; Conrad, P W.; Kobayashi, S; Millhorn, D E.

    2001-07-01

    Transplantation of dopamine-secreting cells harvested from fetal mesencephalon directly into the striatum has had limited success as a therapy for Parkinson's disease. A major problem is that the majority of the cells die during the first 3 weeks following transplantation. Hypoxia in the tissue surrounding the graft is a potential cause of the cell death. We have used subtractive cDNA libraries and microarray analysis to identify the gene expression profile that regulates tolerance to hypoxia. An improved understanding of the molecular basis of hypoxia-tolerance may allow investigators to engineer cells that can survive in the hypoxic environment of the brain parenchyma following transplantation. PMID:11331199

  11. BR 07-1 DEVELOPMENT OF THE CELL MICROARRAY FOR HIGH-THROUGHPUT ANALYSIS OF GUT MICROBIOTA.

    PubMed

    Hong, Seong-Tshool

    2016-09-01

    The human intestine contains a massive and complex microbial community called gut microbiota. A typical human carries 100 trillion microbes in his/her body which is 10 times greater than the number of their host cells, i.e. whole number of human cells. A combined microbial genome constituting gut microbiota is well excess our own human genome. The microbial composition of gut microbiotata and its role on diseases became a booming area of research, presenting a new paradigm of opportunities for modern medicines. Recent evidences showed that gut microbiota acts as a very important determining factor for the development of almost all complex diseases such as primary hypertension, obesity, depression, diabetes, autism, asthma, bowl diseases, rheumatic arthritis, systemic lupus erythematosus, Crohn's disease, Parkinson's disease, Alzheimer's disease, epilepsy, schizophrenia, etc. In spite of the significant role of gut microbiota in the development of complex diseases, the elucidation of the mechanistic pathway on the development of complex diseases by gut microbiota is not moving forward as expected. Current methods to identify alteration of gut microbiota in patients and healthy controls are basically based on the metagenomic sequencings of DNA samples extracted from feces by using next-generation sequencing machines. Although the metagenomic sequencing approaches proved association of gut microbiota with various complex diseases, those methods failed to accurately pinpoint the etiological agents in gut microbiota for complex diseases. The metagenomic sequencing approaches are not only difficult to identify the etiological agent of complex diseases at species level but also difficult to use, requiring complex bioinformatic analyses, and expensive. To overcome the current challenges in analysis of gut microbiota, we developed a novel cell microarray to analyze the constituent microbial organisms of gut microbiota very accurately and fast by using a drop of blood. The

  12. BR 07-1 DEVELOPMENT OF THE CELL MICROARRAY FOR HIGH-THROUGHPUT ANALYSIS OF GUT MICROBIOTA.

    PubMed

    Hong, Seong-Tshool

    2016-09-01

    The human intestine contains a massive and complex microbial community called gut microbiota. A typical human carries 100 trillion microbes in his/her body which is 10 times greater than the number of their host cells, i.e. whole number of human cells. A combined microbial genome constituting gut microbiota is well excess our own human genome. The microbial composition of gut microbiotata and its role on diseases became a booming area of research, presenting a new paradigm of opportunities for modern medicines. Recent evidences showed that gut microbiota acts as a very important determining factor for the development of almost all complex diseases such as primary hypertension, obesity, depression, diabetes, autism, asthma, bowl diseases, rheumatic arthritis, systemic lupus erythematosus, Crohn's disease, Parkinson's disease, Alzheimer's disease, epilepsy, schizophrenia, etc. In spite of the significant role of gut microbiota in the development of complex diseases, the elucidation of the mechanistic pathway on the development of complex diseases by gut microbiota is not moving forward as expected. Current methods to identify alteration of gut microbiota in patients and healthy controls are basically based on the metagenomic sequencings of DNA samples extracted from feces by using next-generation sequencing machines. Although the metagenomic sequencing approaches proved association of gut microbiota with various complex diseases, those methods failed to accurately pinpoint the etiological agents in gut microbiota for complex diseases. The metagenomic sequencing approaches are not only difficult to identify the etiological agent of complex diseases at species level but also difficult to use, requiring complex bioinformatic analyses, and expensive. To overcome the current challenges in analysis of gut microbiota, we developed a novel cell microarray to analyze the constituent microbial organisms of gut microbiota very accurately and fast by using a drop of blood. The

  13. Functional microarray analysis of nitrogen and carbon cycling genes across an Antarctic latitudinal transect.

    PubMed

    Yergeau, Etienne; Kang, Sanghoon; He, Zhili; Zhou, Jizhong; Kowalchuk, George A

    2007-06-01

    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 families were studied for soil-borne microbial communities inhabiting a range of environments from 51 degrees S (cool temperate-Falkland Islands) to 72 degrees S (cold rock desert-Coal Nunatak). The recently designed functional gene array used contains 24,243 oligonucleotide probes and covers >10,000 genes in >150 functional groups involved in nitrogen, carbon, sulfur and phosphorus cycling, metal reduction and resistance and organic contaminant degradation (He et al. 2007). The detected N- and C-cycle genes were significantly different across different sampling locations and vegetation types. A number of significant trends were observed regarding the distribution of key gene families across the environments examined. For example, the relative detection of cellulose degradation genes was correlated with temperature, and microbial C-fixation genes were more present in plots principally lacking vegetation. With respect to the N-cycle, denitrification genes were linked to higher soil temperatures, and N2-fixation genes were linked to plots mainly vegetated by lichens. These microarray-based results were confirmed for a number of gene families using specific real-time PCR, enzymatic assays and process rate measurements. The results presented demonstrate the utility of an integrated functional gene microarray approach in detecting shifts in functional community properties in environmental samples and provide insight into the forces driving important processes of terrestrial Antarctic nutrient cycling. PMID:18043626

  14. Functional microarray analysis of nitrogen and carbon cycling genes across an Antarctic latitudinal transect.

    PubMed

    Yergeau, Etienne; Kang, Sanghoon; He, Zhili; Zhou, Jizhong; Kowalchuk, George A

    2007-06-01

    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 families were studied for soil-borne microbial communities inhabiting a range of environments from 51 degrees S (cool temperate-Falkland Islands) to 72 degrees S (cold rock desert-Coal Nunatak). The recently designed functional gene array used contains 24,243 oligonucleotide probes and covers >10,000 genes in >150 functional groups involved in nitrogen, carbon, sulfur and phosphorus cycling, metal reduction and resistance and organic contaminant degradation (He et al. 2007). The detected N- and C-cycle genes were significantly different across different sampling locations and vegetation types. A number of significant trends were observed regarding the distribution of key gene families across the environments examined. For example, the relative detection of cellulose degradation genes was correlated with temperature, and microbial C-fixation genes were more present in plots principally lacking vegetation. With respect to the N-cycle, denitrification genes were linked to higher soil temperatures, and N2-fixation genes were linked to plots mainly vegetated by lichens. These microarray-based results were confirmed for a number of gene families using specific real-time PCR, enzymatic assays and process rate measurements. The results presented demonstrate the utility of an integrated functional gene microarray approach in detecting shifts in functional community properties in environmental samples and provide insight into the forces driving important processes of terrestrial Antarctic nutrient cycling.

  15. Global analysis of carbohydrate utilization by Lactobacillus acidophilus using cDNA microarrays

    PubMed Central

    Barrangou, Rodolphe; Azcarate-Peril, M. Andrea; Duong, Tri; Conners, Shannon B.; Kelly, Robert M.; Klaenhammer, Todd R.

    2006-01-01

    The transport and catabolic machinery involved in carbohydrate utilization by Lactobacillus acidophilus was characterized genetically by using whole-genome cDNA microarrays. Global transcriptional profiles were determined for growth on glucose, fructose, sucrose, lactose, galactose, trehalose, raffinose, and fructooligosaccharides. Hybridizations were carried out by using a round-robin design, and microarray data were analyzed with a two-stage mixed model ANOVA. Differentially expressed genes were visualized by hierarchical clustering, volcano plots, and contour plots. Overall, only 63 genes (3% of the genome) showed a >4-fold induction. Specifically, transporters of the phosphoenolpyruvate:sugar transferase system were identified for uptake of glucose, fructose, sucrose, and trehalose, whereas ATP-binding cassette transporters were identified for uptake of raffinose and fructooligosaccharides. A member of the LacS subfamily of galactoside-pentose hexuronide translocators was identified for uptake of galactose and lactose. Saccharolytic enzymes likely involved in the metabolism of monosaccharides, disaccharides, and polysaccharides into substrates of glycolysis were also found, including enzymatic machinery of the Leloir pathway. The transcriptome appeared to be regulated by carbon catabolite repression. Although substrate-specific carbohydrate transporters and hydrolases were regulated at the transcriptional level, genes encoding regulatory proteins CcpA, Hpr, HprK/P, and EI were consistently highly expressed. Genes central to glycolysis were among the most highly expressed in the genome. Collectively, microarray data revealed that coordinated and regulated transcription of genes involved in sugar uptake and metabolism is based on the specific carbohydrate provided. L. acidophilus's adaptability to environmental conditions likely contributes to its competitive ability for limited carbohydrate sources available in the human gastrointestinal tract. PMID:16505367

  16. Microarray Analysis of Rat Sensory Ganglia after Local Inflammation Implicates Novel Cytokines in Pain

    PubMed Central

    Strong, Judith A.; Xie, Wenrui; Coyle, Dennis E.; Zhang, Jun-Ming

    2012-01-01

    Inflammation plays a role in neuropathic pain conditions as well as in pain induced solely by an inflammatory stimulus. Robust mechanical hyperalgesia and allodynia can be induced by locally inflaming the L5 dorsal root ganglion (DRG) in rat. This model allows investigation of the contribution of inflammation per se to chronic pain conditions. Most previous microarray studies of DRG gene expression have investigated neuropathic pain models. To examine the role of inflammation, we used microarray methods to examine gene expression 3 days after local inflammation of the L5 DRG in rat. We observed significant regulation in a large number of genes (23% of observed transcripts), and examined 221 (3%) with a fold-change of 1.5-fold or more in more detail. Immune-related genes were the largest category in this group and included members of the complement system as well as several pro-inflammatory cytokines. However, these upregulated cytokines had no prior links to peripheral pain in the literature other than through microarray studies, though most had previously described roles in CNS (especially neuroinflammatory conditions) as well as in immune responses. To confirm an association to pain, qPCR studies examined these cytokines at a later time (day 14), as well as in two different versions of the spinal nerve ligation pain model including a version without any foreign immunogenic material (suture). Cxcl11, Cxcl13, and Cxcl14 were found to be significantly upregulated in all these conditions, while Cxcl9, Cxcl10, and Cxcl16 were upregulated in at least two of these conditions. PMID:22815815

  17. Microarray Analysis of Fluorescence Activated Cell Sorter-Derived Cells: Creating Harmony between Technologies

    PubMed Central

    Tighe, S.

    2011-01-01

    Although microarray technology is well-established in both the research and clinical fields, it continues to evolve into new areas that require new methods for the successful isolations of nucleic acid from non-traditional sources. Because RNA specifically is a labile molecule, special procedures and considerations must be implemented to avoid degradation from methods such as fluorescence activated cell sorting (FACS) and laser capture microdissection (LCM) to name a few. This presentation will discuss specific methodologies to maximize the success of nucleic acid recovery from these approaches including instrument preparation, extraction methods, and the use of special reagents to deal with problematic samples.

  18. Fine-scaled human genetic structure revealed by SNP microarrays.

    PubMed

    Xing, Jinchuan; Watkins, W Scott; Witherspoon, David J; Zhang, Yuhua; Guthery, Stephen L; Thara, Rangaswamy; Mowry, Bryan J; Bulayeva, Kazima; Weiss, Robert B; Jorde, Lynn B

    2009-05-01

    We report an analysis of more than 240,000 loci genotyped using the Affymetrix SNP microarray in 554 individuals from 27 worldwide populations in Africa, Asia, and Europe. To provide a more extensive and complete sampling of human genetic variation, we have included caste and tribal samples from two states in South India, Daghestanis from eastern Europe, and the Iban from Malaysia. Consistent with observations made by Charles Darwin, our results highlight shared variation among human populations and demonstrate that much genetic variation is geographically continuous. At the same time, principal components analyses reveal discernible genetic differentiation among almost all identified populations in our sample, and in most cases, individuals can be clearly assigned to defined populations on the basis of SNP genotypes. All individuals are accurately classified into continental groups using a model-based clustering algorithm, but between closely related populations, genetic and self-classifications conflict for some individuals. The 250K data permitted high-level resolution of genetic variation among Indian caste and tribal populations and between highland and lowland Daghestani populations. In particular, upper-caste individuals from Tamil Nadu and Andhra Pradesh form one defined group, lower-caste individuals from these two states form another, and the tribal Irula samples form a third. Our results emphasize the correlation of genetic and geographic distances and highlight other elements, including social factors that have contributed to population structure. PMID:19411602

  19. Fine-scaled human genetic structure revealed by SNP microarrays.

    PubMed

    Xing, Jinchuan; Watkins, W Scott; Witherspoon, David J; Zhang, Yuhua; Guthery, Stephen L; Thara, Rangaswamy; Mowry, Bryan J; Bulayeva, Kazima; Weiss, Robert B; Jorde, Lynn B

    2009-05-01

    We report an analysis of more than 240,000 loci genotyped using the Affymetrix SNP microarray in 554 individuals from 27 worldwide populations in Africa, Asia, and Europe. To provide a more extensive and complete sampling of human genetic variation, we have included caste and tribal samples from two states in South India, Daghestanis from eastern Europe, and the Iban from Malaysia. Consistent with observations made by Charles Darwin, our results highlight shared variation among human populations and demonstrate that much genetic variation is geographically continuous. At the same time, principal components analyses reveal discernible genetic differentiation among almost all identified populations in our sample, and in most cases, individuals can be clearly assigned to defined populations on the basis of SNP genotypes. All individuals are accurately classified into continental groups using a model-based clustering algorithm, but between closely related populations, genetic and self-classifications conflict for some individuals. The 250K data permitted high-level resolution of genetic variation among Indian caste and tribal populations and between highland and lowland Daghestani populations. In particular, upper-caste individuals from Tamil Nadu and Andhra Pradesh form one defined group, lower-caste individuals from these two states form another, and the tribal Irula samples form a third. Our results emphasize the correlation of genetic and geographic distances and highlight other elements, including social factors that have contributed to population structure.

  20. Allelic imbalances and microdeletions affecting the PTPRD gene in cutaneous squamous cell carcinomas detected using single nucleotide polymorphism microarray analysis.

    PubMed

    Purdie, Karin J; Lambert, Sally R; Teh, Muy-Teck; Chaplin, Tracy; Molloy, Gael; Raghavan, Manoj; Kelsell, David P; Leigh, Irene M; Harwood, Catherine A; Proby, Charlotte M; Young, Bryan D

    2007-07-01

    Cutaneous squamous cell carcinomas (SCC) are the second most commonly diagnosed cancers in fair-skinned people; yet the genetic mechanisms involved in SCC tumorigenesis remain poorly understood. We have used single nucleotide polymorphism (SNP) microarray analysis to examine genome-wide allelic imbalance in 16 primary and 2 lymph node metastatic SCC using paired non-tumour samples to counteract normal copy number variation. The most common genetic change was loss of heterozygosity (LOH) on 9p, observed in 13 of 16 primary SCC. Other recurrent events included LOH on 3p (9 tumors), 2q, 8p, and 13 (each in 8 SCC) and allelic gain on 3q and 8q (each in 6 tumors). Copy number-neutral LOH was observed in a proportion of samples, implying that somatic recombination had led to acquired uniparental disomy, an event not previously demonstrated in SCC. As well as recurrent patterns of gross chromosomal changes, SNP microarray analysis revealed, in 2 primary SCC, a homozygous microdeletion on 9p23 within the protein tyrosine phosphatase receptor type D (PTPRD) locus, an emerging frequent target of homozygous deletion in lung cancer and neuroblastoma. A third sample was heterozygously deleted within this locus and PTPRD expression was aberrant. Two of the 3 primary SCC with PTPRD deletion had demonstrated metastatic potential. Our data identify PTPRD as a candidate tumor suppressor gene in cutaneous SCC with a possible association with metastasis.

  1. Suppression subtractive hybridization coupled with microarray analysis to examine differential expression of genes in virus infected cells

    PubMed Central

    Singh, Sushmita; Kaur, Kuljeet; Kapur, Vivek

    2004-01-01

    High throughput detection of differential expression of genes is an efficient means of identifying genes and pathways that may play a role in biological systems under certain experimental conditions. There exist a variety of approaches that could be used to identify groups of genes that change in expression in response to a particular stimulus or environment. We here describe the application of suppression subtractive hybridization (SSH) coupled with cDNA microarray analysis for isolation and identification of chicken transcripts that change in expression on infection of host cells with a paramyxovirus. SSH was used for initial isolation of differentially expressed transcripts, a large-scale validation of which was accomplished by microarray analysis. The data reveals a large group of regulated genes constituting many biochemical pathways that could serve as targets for future investigations to explore their role in paramyxovirus pathogenesis. The detailed methods described herein could be useful and adaptable to any biological system for studying changes in gene expression. PMID:15181476

  2. Identification and expression analysis of salt-responsive genes using a comparative microarray approach in Salix matsudana.

    PubMed

    Liu, Mingying; Qiao, Guirong; Jiang, Jing; Han, Xiaojiao; Sang, Jian; Zhuo, Renying

    2014-10-01

    Salt stress exerts negative effects on plant growth, development and yields, with roots being the primary site of both perception and damage. Salix matsudana (Chinese willow) is tolerant of high salinity. However, genes associated with this trait were rarely characterized. Therefore, we first performed salt-stress treatment on S. matsudana plants, then identified differentially expressed genes by comparison of salt-treated roots and untreated controls using microarray analysis. A total of 403 salt-responsive genes were identified, of which 239 were repressed and 164 were up-regulated. Functional classification analysis revealed that these genes belonged to families encoding proteins involved in metabolism, regulation of transcription, signal transduction, hormone responses, abiotic stress responses, and other processes related to growth and development. This suggested that when S. matsudana was confronted with salt stress, coordinated adjustments are made to physiological and biochemical processes, which would then allow more resources to be allocated to protective mechanisms to avoid salt injury. The expression patterns of representative genes were further validated and the diversity of the temporal profiles indicated that a combination of several genes and the initiation of diverse pathways performed functions in S. matsudana salt tolerance. This work represents the first study employing microarrays to investigate salt tolerance in S. matsudana. The data presented herein enhance our understanding of the molecular mechanisms of S. matsudana responses to salinity stress and lay the groundwork for genetic engineering strategies to improve stress tolerance of agronomically important species.

  3. MOLECULAR METHODS (E.G., MICROARRAYS) APPLIED TO PLANT GENOMES FOR ASSESSING GENETIC CHANGE AND ENVIRONMENTAL STRESS

    EPA Science Inventory

    This is a technical document that presents a detailed sample standard operating procedure (S.O.P.) for preparing plant nucleic acid samples for microarray analyses using commercial ¿chips¿ such as those sold by Affymetrix. It also presents the application of a commercially availa...

  4. Microarray analysis identifies Salmonella genes belonging to the low-shear modeled microgravity regulon

    NASA Technical Reports Server (NTRS)

    Wilson, James W.; Ramamurthy, Rajee; Porwollik, Steffen; McClelland, Michael; Hammond, Timothy; Allen, Pat; Ott, C. Mark; Pierson, Duane L.; Nickerson, Cheryl A.

    2002-01-01

    The low-shear environment of optimized rotation suspension culture allows both eukaryotic and prokaryotic cells to assume physiologically relevant phenotypes that have led to significant advances in fundamental investigations of medical and biological importance. This culture environment has also been used to model microgravity for ground-based studies regarding the impact of space flight on eukaryotic and prokaryotic physiology. We have previously demonstrated that low-shear modeled microgravity (LSMMG) under optimized rotation suspension culture is a novel environmental signal that regulates the virulence, stress resistance, and protein expression levels of Salmonella enterica serovar Typhimurium. However, the mechanisms used by the cells of any species, including Salmonella, to sense and respond to LSMMG and identities of the genes involved are unknown. In this study, we used DNA microarrays to elucidate the global transcriptional response of Salmonella to LSMMG. When compared with identical growth conditions under normal gravity (1 x g), LSMMG differentially regulated the expression of 163 genes distributed throughout the chromosome, representing functionally diverse groups including transcriptional regulators, virulence factors, lipopolysaccharide biosynthetic enzymes, iron-utilization enzymes, and proteins of unknown function. Many of the LSMMG-regulated genes were organized in clusters or operons. The microarray results were further validated by RT-PCR and phenotypic analyses, and they indicate that the ferric uptake regulator is involved in the LSMMG response. The results provide important insight about the Salmonella LSMMG response and could provide clues for the functioning of known Salmonella virulence systems or the identification of uncharacterized bacterial virulence strategies.

  5. The Local Maximum Clustering Method and Its Application in Microarray Gene Expression Data Analysis

    NASA Astrophysics Data System (ADS)

    Wu, Xiongwu; Chen, Yidong; Brooks, Bernard R.; Su, Yan A.

    2004-12-01

    An unsupervised data clustering method, called the local maximum clustering (LMC) method, is proposed for identifying clusters in experiment data sets based on research interest. A magnitude property is defined according to research purposes, and data sets are clustered around each local maximum of the magnitude property. By properly defining a magnitude property, this method can overcome many difficulties in microarray data clustering such as reduced projection in similarities, noises, and arbitrary gene distribution. To critically evaluate the performance of this clustering method in comparison with other methods, we designed three model data sets with known cluster distributions and applied the LMC method as well as the hierarchic clustering method, the[InlineEquation not available: see fulltext.]-mean clustering method, and the self-organized map method to these model data sets. The results show that the LMC method produces the most accurate clustering results. As an example of application, we applied the method to cluster the leukemia samples reported in the microarray study of Golub et al. (1999).

  6. Four-copy number intervals in SNP microarray analysis: unique patterns and positions.

    PubMed

    Papenhausen, Peter R; Kelly, Carla A; Zvereff, Val; Schwartz, Stuart

    2014-01-01

    Over the past several years, the utility of microarray technology in delineating copy number changes has become well established. In the past 4 years, we have used the SNP array to detect and analyze allele ratios in 150 cases with 4-copy intervals, confirmed by FISH, offering insight into the underlying mechanisms of formation. These cases may be divided into 5 allele patterns--the first 4 of which involve a single homologue--as detected by the genotyping aspects of the microarray: (1) triplications combining homozygous and heterozygous alleles, with a 3:1 ratio of heterozygotes; (2) triplications with allele patterns combining homozygous and heterozygous alleles, with heterozygote ratios of both 3:1 and 2:2; (3) triplications that have homozygous alleles combined with only 2:2 heterozygous alleles; (4) triplications that are completely homozygous; and (5) homozygous duplications on each homologue with no heterozygous alleles. The implications of copy number variants with diverse allelic segregations are presented in this study. PMID:25401283

  7. A lesson for cancer research: placental microarray gene analysis in preeclampsia

    PubMed Central

    Louwen, Frank; Muschol-Steinmetz, Cornelia; Reinhard, Joscha; Reitter, Anke; Yuan, Juping

    2012-01-01

    Tumor progression and pregnancy share many common features, such as immune tolerance and invasion. The invasion of trophoblasts in the placenta into the uterine wall is essential for fetal development, and is thus precisely regulated. Its deregulation has been implicated in preeclampsia, a leading cause for maternal and perinatal mortality and morbidity. Pathogenesis of preeclampsia remains to be defined. Microarray-based gene profiling has been widely used for identifying genes responsible for preeclampsia. In this review, we have summarized the recent data from the microarray studies with preeclamptic placentas. Despite the complex of gene signatures, suggestive of the heterogeneity of preeclampsia, these studies identified a number of differentially expressed genes associated with preeclampsia. Interestingly, most of them have been reported to be tightly involved in tumor progression. We have discussed these interesting genes and analyzed their potential molecular functions in preeclampsia, compared with their roles in malignancy development. Further investigations are warranted to explore the involvement in molecular network of each identified gene, which may provide not only novel strategies for prevention and therapy for preeclampsia but also a better understanding of cancer cells. The trophoblastic cells, with their capacity for proliferation and differentiation, apoptosis and survival, migration, angiogenesis and immune modulation by exploiting similar molecular pathways, make them a compelling model for cancer research. PMID:22929622

  8. Variable selection for discriminant analysis with Markov random field priors for the analysis of microarray data

    PubMed Central

    Stingo, Francesco C.; Vannucci, Marina

    2011-01-01

    Motivation: Discriminant analysis is an effective tool for the classification of experimental units into groups. Here, we consider the typical problem of classifying subjects according to phenotypes via gene expression data and propose a method that incorporates variable selection into the inferential procedure, for the identification of the important biomarkers. To achieve this goal, we build upon a conjugate normal discriminant model, both linear and quadratic, and include a stochastic search variable selection procedure via an MCMC algorithm. Furthermore, we incorporate into the model prior information on the relationships among the genes as described by a gene–gene network. We use a Markov random field (MRF) prior to map the network connections among genes. Our prior model assumes that neighboring genes in the network are more likely to have a joint effect on the relevant biological processes. Results: We use simulated data to assess performances of our method. In particular, we compare the MRF prior to a situation where independent Bernoulli priors are chosen for the individual predictors. We also illustrate the method on benchmark datasets for gene expression. Our simulation studies show that employing the MRF prior improves on selection accuracy. In real data applications, in addition to identifying markers and improving prediction accuracy, we show how the integration of existing biological knowledge into the prior model results in an increased ability to identify genes with strong discriminatory power and also aids the interpretation of the results. Contact: marina@rice.edu PMID:21159623

  9. Analysis of tear inflammatory mediators: A comparison between the microarray and Luminex methods

    PubMed Central

    Dionne, Karen; Nichols, Jason J.; Nichols, Kelly K.

    2016-01-01

    Purpose Inflammatory mediators have been shown to modulate dry eye (DE) disease and may correlate with disease severity, yet the methods used and the associated findings vary significantly in the literature. The goal of this research was to compare two methods, the quantitative microarray and the magnetic bead assay, for detecting cytokine levels in extracted tear samples across three subject groups. Methods Tears were collected from Schirmer strips of the right and left eyes of 20 soft contact lens wearers (CL), 20 normal non-contact lens wearers (NOR), and 20 DE subjects and stored at −80 °C. Tear proteins were eluted and precipitated using ammonium bicarbonate and acetone. The right and left eye samples were combined for each subject. Following the Bradford protein quantitation method, 10 µg of total protein was used for each of the two analyses, Quantibody® Human Inflammation Array 3 (RayBiotech) and High Sensitivity Human Cytokine Magnetic Bead Kit (Millipore). The assays were run using the GenePix® 4000B Scanner (Molecular Devices) or the Luminex MagPix® plate reader (Luminex), respectively. The data were then compared between the two instruments and the three subject groups Results Of the 40 proteins on the Quantibody® microarray, seven had average expression levels above the lower limit of detection: ICAM-1, MCP-1, MIG, MCSF, TIMP-1, TIMP-2, and TNF-RI. Significant differences in expression levels (p<0.05) were detected between the CL and DE groups for MCSF, TIMP-1, and TNF R1, between the NOR and DE groups for ICAM-1, and between the CL and NOR groups for ICAM-1, MCP-1, MCSF, TIMP-1, TIMP-2, and TNF-R1 when using the Student t test. Of the 13 proteins tested with Luminex, IL-1β, IL-4, IL-6, IL-7, and IL-8 had expression levels above the minimum detectable level, and these were most often detected using the Luminex assay compared to the Quantibody® microarray. Contrarily, IL-2, IL-12, IL-13, INF-g, and GM-CSF were detected more frequently using

  10. Genetic Counseling for a Prenatal Diagnosis of Structural Chromosomal Abnormality with High-Resolution Analysis Using a Single Nucleotide Polymorphism Microarray

    PubMed Central

    Takashima, Akiko; Takeshita, Naoki; Kinoshita, Toshihiko

    2016-01-01

    A 41-year old pregnant woman underwent amniocentesis to conduct a conventional karyotyping analysis; the analysis reported an abnormal karyotype: 46, XY, add(9)(p24). Chromosomal microarray analysis (CMA) is utilized in prenatal diagnoses. A single nucleotide polymorphism microarray revealed a male fetus with balanced chromosomal translocations on 9p and balanced chromosomal rearrangements, but another chromosomal abnormality was detected. The fetus had microduplication. The child was born as a phenotypically normal male. CMA is a simple and informative procedure for prenatal genetic diagnosis. CMA is the detection of chromosomal variants of unknown clinical significance; therefore, genetic counseling is important during prenatal genetic testing. PMID:27777709

  11. Identification of Chromosome Abnormalities in Subtelomeric Regions by Microarray Analysis: A Study of 5,380 Cases

    PubMed Central

    Shao, Lina; Shaw, Chad A.; Lu, Xin-Yan; Sahoo, Trilochan; Bacino, Carlos A.; Lalani, Seema R.; Stankiewicz, Pawel; Yatsenko, Svetlana A.; Li, Yinfeng; Neill, Sarah; Pursley, Amber N.; Chinault, A. Craig; Patel, Ankita; Beaudet, Arthur L.; Lupski, James R.; Cheung, Sau W.

    2009-01-01

    Subtelomeric imbalances are a significant cause of congenital disorders. Screening for these abnormalities has traditionally utilized GTG-banding analysis, fluorescence in situ hybridization (FISH) assays, and multiplex ligation-dependent probe amplification. Microarray-based comparative genomic hybridization (array-CGH) is a relatively new technology that can identify microscopic and submicroscopic chromosomal imbalances. It has been proposed that an array with extended coverage at subtelomeric regions could characterize subtelomeric aberrations more efficiently in a single experiment. The targeted arrays for chromosome microarray analysis (CMA), developed by Baylor College of Medicine, have on average 12 BAC/PAC clones covering 10 Mb of each of the 41 subtelomeric regions. We screened 5,380 consecutive clinical patients using CMA. The most common reasons for referral included developmental delay (DD), and/or mental retardation (MR), dysmorphic features (DF), multiple congenital anomalies (MCA), seizure disorders (SD), and autistic, or other behavioral abnormalities. We found pathogenic rearrangements at subtelomeric regions in 236 patients (4.4%). Among these patients, 103 had a deletion, 58 had a duplication, 44 had an unbalanced translocation, and 31 had a complex rearrangement. The detection rates varied among patients with a normal karyotype analysis (2.98%), with an abnormal karyotype analysis (43.4%), and with an unavailable or no karyotype analysis (3.16%). Six patients out of 278 with a prior normal subtelomere-FISH analysis showed an abnormality including an interstitial deletion, two terminal deletions, two interstitial duplications, and a terminal duplication. In conclusion, genomic imbalances at subtelomeric regions contribute significantly to congenital disorders. Targeted array-CGH with extended coverage (up to 10 Mb) of subtelomeric regions will enhance the detection of subtelomeric imbalances, especially for submicroscopic imbalances. PMID

  12. Microarray analysis of E9.5 reduced folate carrier (RFC1; Slc19a1) knockout embryos reveals altered expression of genes in the cubilin-megalin multiligand endocytic receptor complex

    PubMed Central

    Gelineau-van Waes, Janee; Maddox, Joyce R; Smith, Lynette M; van Waes, Michael; Wilberding, Justin; Eudy, James D; Bauer, Linda K; Finnell, Richard H

    2008-01-01

    Background The reduced folate carrier (RFC1) is an integral membrane protein and facilitative anion exchanger that mediates delivery of 5-methyltetrahydrofolate into mammalian cells. Adequate maternal-fetal transport of folate is necessary for normal embryogenesis. Targeted inactivation of the murine RFC1 gene results in post-implantation embryolethality, but daily folic acid supplementation of pregnant dams prolongs survival of homozygous embryos until mid-gestation. At E10.5 RFC1-/- embryos are developmentally delayed relative to wildtype littermates, have multiple malformations, including neural tube defects, and die due to failure of chorioallantoic fusion. The mesoderm is sparse and disorganized, and there is a marked absence of erythrocytes in yolk sac blood islands. The identification of alterations in gene expression and signaling pathways involved in the observed dysmorphology following inactivation of RFC1-mediated folate transport are the focus of this investigation. Results Affymetrix microarray analysis of the relative gene expression profiles in whole E9.5 RFC1-/- vs. RFC1+/+ embryos identified 200 known genes that were differentially expressed. Major ontology groups included transcription factors (13.04%), and genes involved in transport functions (ion, lipid, carbohydrate) (11.37%). Genes that code for receptors, ligands and interacting proteins in the cubilin-megalin multiligand endocytic receptor complex accounted for 9.36% of the total, followed closely by several genes involved in hematopoiesis (8.03%). The most highly significant gene network identified by Ingenuity™ Pathway analysis included 12 genes in the cubilin-megalin multiligand endocytic receptor complex. Altered expression of these genes was validated by quantitative RT-PCR, and immunohistochemical analysis demonstrated that megalin protein expression disappeared from the visceral yolk sac of RFC1-/- embryos, while cubilin protein was widely misexpressed. Conclusion Inactivation of

  13. Use of reverse phase protein microarrays and reference standard development for molecular network analysis of metastatic ovarian carcinoma.

    PubMed

    Sheehan, Katherine M; Calvert, Valerie S; Kay, Elaine W; Lu, Yiling; Fishman, David; Espina, Virginia; Aquino, Joy; Speer, Runa; Araujo, Robyn; Mills, Gordon B; Liotta, Lance A; Petricoin, Emanuel F; Wulfkuhle, Julia D

    2005-04-01

    Cancer can be defined as a deregulation or hyperactivity in the ongoing network of intracellular and extracellular signaling events. Reverse phase protein microarray technology may offer a new opportunity to measure and profile these signaling pathways, providing data on post-translational phosphorylation events not obtainable by gene microarray analysis. Treatment of ovarian epithelial carcinoma almost always takes place in a metastatic setting since unfortunately the disease is often not detected until later stages. Thus, in addition to elucidation of the molecular network within a tumor specimen, critical questions are to what extent do signaling changes occur upon metastasis and are there common pathway elements that arise in the metastatic microenvironment. For individualized combinatorial therapy, ideal therapeutic selection based on proteomic mapping of phosphorylation end points may require evaluation of the patient's metastatic tissue. Extending these findings to the bedside will require the development of optimized protocols and reference standards. We have developed a reference standard based on a mixture of phosphorylated peptides to begin to address this challenge.

  14. CDNA microarray analysis of nerve growth factor-regulated gene expression profile in rat PC12 cells.

    PubMed

    Lee, Kyung-Hee; Ryu, Chun Jeih; Hong, Hyo Jeong; Kim, Jiyoung; Lee, Eunjoo H

    2005-04-01

    Nerve growth factor (NGF)-driven differentiation of PC12 cells into neuronal-like cells provides a representative model system for studying neuronal differentiation processes. Despite of extensive research, gene regulation associated with the differentiation program in PC12 cells still needs to be elucidated. We used cDNA microarray analysis to characterize the response of PC12 cells to NGF at mRNA expression. Forty-six genes were reproducibly influenced by 2-fold or more after NGF treatment for 5 days. Twenty-five of the regulated transcripts were matched to genes which have known functions. Among the microarray results confirmed with real-time reverse transcriptase assay, several genes have not previously known to be modulated by NGF. The results mostly reflected changes in molecules regulating neural plasticity, cytoskeletal organization, and lipid metabolism, which include neuritin, PDZ protein Mrt1, lipoprotein lipase, tropomodulin 1 and rhoB. These observed genetic changes may provide new information about molecular mechanisms underlying NGF-promoted differentiation of PC12 cells. PMID:16076023

  15. Immunoassay, DNA Analysis, and Other Ligand Binding Assay Techniques: From Electropherograms to Multiplexed, Ultrasensitive Microarrays on a Chip

    NASA Astrophysics Data System (ADS)

    Ekins, Roger P.

    1999-06-01

    "Ligand" or "binding" assays have made a major impact on biomedical research and clinical diagnosis since their development in the late 1950s. Immunoassay techniques (relying on specific antibodies to bind the target analyte) represent the best-known example, but analogous DNA and RNA analysis methods (using oligonucleotides to recognize defined polynucleotide sequences) are rapidly gaining in importance and are likely to exert profound effects on human society. The evolution of these methods may be divided into three phases: (i) the initial development and widespread use of sensitive "competitive" assays relying on radioisotopically labeled analyte to monitor the binding reaction; (ii) the introduction in the 1980s of "ultrasensitive", "noncompetitive", labeled antibody methods relying on high-specific-activity nonisotopic labels, leading to the emergence of the automatic analyzers that now dominate the field, and (iii) the present development of "microarray"methods based on antibody or oligonucleotide microspots (each recognizing an individual analyte) arrayed on a solid support and relying on observation (typically by confocal microscopy) of fluorescent signals emitted from each spot. Miniaturized microarray methods permitting ultrasensitive measurement of hundreds of different analytes in a minute sample are likely to revolutionize medicine and related fields within the next decade.

  16. Gene expression microarray analysis of heat stress in the soil invertebrate Folsomia candida.

    PubMed

    Nota, B; van Straalen, N M; Ylstra, B; Roelofs, D

    2010-06-01

    Sudden temperature changes in soil can induce stress in soil-dwelling invertebrates. Hyperthermic conditions have an impact on gene expression as one of the first steps. We use a transcriptomics approach using microarrays to identify expression changes in response to heat in the springtail Folsomia candida. An elevation of temperature (Delta 10 degrees C) altered the expression of 142 genes (116 up-, 26 down-regulated). Many up-regulated genes encoded heat shock proteins, enzymes involved in ATP synthesis, oxidative stress responsive enzymes and anion-transporting ATPases. Down-regulated were glycoside hydrolases, involved in catalysis of disaccharides. The small number of altered transcripts suggest a mild response to heat in this soil invertebrate, but further research is needed to confirm this. This study presents candidate genes for future functional studies concerning thermal stress in soil-dwelling invertebrates. PMID:20074298

  17. Fluorescence in situ hybridization analysis of formalin fixed paraffin embedded tissues, including tissue microarrays.

    PubMed

    Summersgill, Brenda M; Shipley, Janet M

    2010-01-01

    Formalin fixed paraffin embedded (FFPE) material is frequently the most convenient readily available source of diseased tissue, including tumors. Multiple cores of FFPE material are being used increasingly to construct tissue microarrays (TMAs) that enable simultaneous analyses of many archival samples. Fluorescence in situ hybridization (FISH) is an important approach to analyze FFPE material for specific genetic aberrations that may be associated with tumor types or subtypes, cellular morphology, and disease prognosis. Annealing, or hybridization of labeled nucleic acid sequences, or probes, to detect and locate one or more complementary nucleic acid sequences within fixed tissue sections allows the detection of structural (translocation/inversion) and numerical (deletion/gain) aberrations and their localization within tissues. The robust protocols described include probe preparation, hybridization, and detection and take 2-3 days to complete. A protocol is also described for the stripping of probes for repeat FISH in order to maximize the use of scarce tissue resources.

  18. The Mechanisms Underlying α-Amanitin Resistance in Drosophila melanogaster: A Microarray Analysis

    PubMed Central

    Mitchell, Chelsea L.; Saul, Michael C.; Lei, Liang; Wei, Hairong; Werner, Thomas

    2014-01-01

    The rapid evolution of toxin resistance in animals has important consequences for the ecology of species and our economy. Pesticide resistance in insects has been a subject of intensive study; however, very little is known about how Drosophila species became resistant to natural toxins with ecological relevance, such as α-amanitin that is produced in deadly poisonous mushrooms. Here we performed a microarray study to elucidate the genes, chromosomal loci, molecular functions, biological processes, and cellular components that contribute to the α-amanitin resistance phenotype in Drosophila melanogaster. We suggest that toxin entry blockage through the cuticle, phase I and II detoxification, sequestration in lipid particles, and proteolytic cleavage of α-amanitin contribute in concert to this quantitative trait. We speculate that the resistance to mushroom toxins in D. melanogaster and perhaps in mycophagous Drosophila species has evolved as cross-resistance to pesticides, other xenobiotic substances, or environmental stress factors. PMID:24695618

  19. Genome-wide microarray analysis of gene expression profiling in major depression and antidepressant therapy.

    PubMed

    Lin, Eugene; Tsai, Shih-Jen

    2016-01-01

    Major depressive disorder (MDD) is a serious health concern worldwide. Currently there are no predictive tests for the effectiveness of any particular antidepressant in an individual patient. Thus, doctors must prescribe antidepressants based on educated guesses. With the recent advent of scientific research, genome-wide gene expression microarray studies are widely utilized to analyze hundreds of thousands of biomarkers by high-throughput technologies. In addition to the candidate-gene approach, the genome-wide approach has recently been employed to investigate the determinants of MDD as well as antidepressant response to therapy. In this review, we mainly focused on gene expression studies with genome-wide approaches using RNA derived from peripheral blood cells. Furthermore, we reviewed their limitations and future directions with respect to the genome-wide gene expression profiling in MDD pathogenesis as well as in antidepressant therapy.

  20. Identification of Hub Genes Related to the Recovery Phase of Irradiation Injury by Microarray and Integrated Gene Network Analysis

    PubMed Central

    Zhang, Jing; Yang, Yue; Wang, Yin; Zhang, Jinyuan; Wang, Zejian; Yin, Ming; Shen, Xudong

    2011-01-01

    Background Irradiation commonly causes long-term bone marrow injury charactertized by defective HSC self-renewal and a decrease in HSC reserve. However, the effect of high-dose IR on global gene expression during bone marrow recovery remains unknown. Methodology Microarray analysis was used to identify differentially expressed genes that are likely to be critical for bone marrow recovery. Multiple bioinformatics analyses were conducted to identify key hub genes, pathways and biological processes. Principal Findings 1) We identified 1302 differentially expressed genes in murine bone marrow at 3, 7, 11 and 21 days after irradiation. Eleven of these genes are known to be HSC self-renewal associated genes, including Adipoq, Ccl3, Ccnd1, Ccnd2, Cdkn1a, Cxcl12, Junb, Pten, Tal1, Thy1 and Tnf; 2) These 1302 differentially expressed genes function in multiple biological processes of immunity, including hematopoiesis and response to stimuli, and cellular processes including cell proliferation, differentiation, adhesion and signaling; 3) Dynamic Gene Network analysis identified a subgroup of 25 core genes that participate in immune response, regulation of transcription and nucleosome assembly; 4) A comparison of our data with known irradiation-related genes extracted from literature showed 42 genes that matched the results of our microarray analysis, thus demonstrated consistency between studies; 5) Protein-protein interaction network and pathway analyses indicated several essential protein-protein interactions and signaling pathways, including focal adhesion and several immune-related signaling pathways. Conclusions Comparisons to other gene array datasets indicate that global gene expression profiles of irradiation damaged bone marrow show significant differences between injury and recovery phases. Our data suggest that immune response (including hematopoiesis) can be considered as a critical biological process in bone marrow recovery. Several critical hub genes that are

  1. Contributions to Statistical Problems Related to Microarray Data

    ERIC Educational Resources Information Center

    Hong, Feng

    2009-01-01

    Microarray is a high throughput technology to measure the gene expression. Analysis of microarray data brings many interesting and challenging problems. This thesis consists three studies related to microarray data. First, we propose a Bayesian model for microarray data and use Bayes Factors to identify differentially expressed genes. Second, we…

  2. Genome-wide microarray expression and genomic alterations by array-CGH analysis in neuroblastoma stem-like cells.

    PubMed

    Ordóñez, Raquel; Gallo-Oller, Gabriel; Martínez-Soto, Soledad; Legarra, Sheila; Pata-Merci, Noémie; Guegan, Justine; Danglot, Giselle; Bernheim, Alain; Meléndez, Bárbara; Rey, Juan A; Castresana, Javier S

    2014-01-01

    Neuroblastoma has a very diverse clinical behaviour: from spontaneous regression to a very aggressive malignant progression and resistance to chemotherapy. This heterogeneous clinical behaviour might be due to the existence of Cancer Stem Cells (CSC), a subpopulation within the tumor with stem-like cell properties: a significant proliferation capacity, a unique self-renewal capacity, and therefore, a higher ability to form new tumors. We enriched the CSC-like cell population content of two commercial neuroblastoma cell lines by the use of conditioned cell culture media for neurospheres, and compared genomic gains and losses and genome expression by array-CGH and microarray analysis, respectively (in CSC-like versus standard tumor cells culture). Despite the array-CGH did not show significant differences between standard and CSC-like in both analyzed cell lines, the microarray expression analysis highlighted some of the most relevant biological processes and molecular functions that might be responsible for the CSC-like phenotype. Some signalling pathways detected seem to be involved in self-renewal of normal tissues (Wnt, Notch, Hh and TGF-β) and contribute to CSC phenotype. We focused on the aberrant activation of TGF-β and Hh signalling pathways, confirming the inhibition of repressors of TGF-β pathway, as SMAD6 and SMAD7 by RT-qPCR. The analysis of the Sonic Hedgehog pathway showed overexpression of PTCH1, GLI1 and SMO. We found overexpression of CD133 and CD15 in SIMA neurospheres, confirming that this cell line was particularly enriched in stem-like cells. This work shows a cross-talk among different pathways in neuroblastoma and its importance in CSC-like cells. PMID:25392930

  3. Gametogenesis in the Pacific Oyster Crassostrea gigas: A Microarrays-Based Analysis Identifies Sex and Stage Specific Genes

    PubMed Central

    Dheilly, Nolwenn M.; Lelong, Christophe; Huvet, Arnaud; Kellner, Kristell; Dubos, Marie-Pierre; Riviere, Guillaume; Boudry, Pierre; Favrel, Pascal

    2012-01-01

    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. Conclusions

  4. Microarray analysis of ox-LDL (oxidized low-density lipoprotein)-regulated genes in human coronary artery smooth muscle cells.

    PubMed

    Minta, Joe; Jungwon Yun, James; St Bernard, Rosanne

    2010-01-01

    Recent studies suggest that circulating LDL (low-density lipoproteins) play a central role in the pathogenesis of atherosclerosis, and the oxidized form (ox-LDL) is highly atherogenic. Deposits of ox-LDL have been found in atherosclerotic plaques, and ox-LDL has been shown to promote monocyte recruitment, foam cell formation and the transition of quiescent and contractile vascular SMCs (smooth muscle cells) to the migratory and proliferative phenotype. SMC phenotype transition and hyperplasia are the pivotal events in the pathogenesis of atherosclerosis. To comprehend the complex molecular mechanisms involved in ox-LDL-mediated SMC phenotype transition, we have compared the differential gene expression profiles of cultured quiescent human coronary artery SMCs with cells induced with ox-LDL for 3 and 21 h using Affymetrix HG-133UA cDNA microarray chips. Assignment of the regulated genes into functional groups indicated that several genes involved in metabolism, membrane transport, cell-cell interactions, signal transduction, transcription, translation, cell migration, proliferation and apoptosis were differentially expressed. Our data suggests that the interaction of ox-LDL with its cognate receptors on SMCs modulates the induction of several growth factors and cytokines, which activate a variety of intracellular signalling mechanisms (including PI3K, MAPK, Jak/STAT, sphingosine, Rho kinase pathways) that contribute to SMC transition from the quiescent and contractile phenotype to the proliferative and migratory phenotype. Our study has also identified several genes (including CDC27, cyclin A1, cyclin G2, glypican 1, MINOR, p15 and apolipoprotein) not previously implicated in ox-LDL-induced SMC phenotype transition and substantially extends the list of potential candidate genes involved in atherogenesis.

  5. Aptamer Microarrays

    SciTech Connect

    Angel-Syrett, Heather; Collett, Jim; Ellington, Andrew D.

    2009-01-02

    In vitro selection can yield specific, high-affinity aptamers. We and others have devised methods for the automated selection of aptamers, and have begun to use these reagents for the construction of arrays. Arrayed aptamers have proven to be almost as sensitive as their solution phase counterparts, and when ganged together can provide both specific and general diagnostic signals for proteins and other analytes. We describe here technical details regarding the production and processing of aptamer microarrays, including blocking, washing, drying, and scanning. We will also discuss the challenges involved in developing standardized and reproducible methods for binding and quantitating protein targets. While signals from fluorescent analytes or sandwiches are typically captured, it has proven possible for immobilized aptamers to be uniquely coupled to amplification methods not available to protein reagents, thus allowing for protein-binding signals to be greatly amplified. Into the future, many of the biosensor methods described in this book can potentially be adapted to array formats, thus further expanding the utility of and applications for aptamer arrays.

  6. Integrating data from heterogeneous DNA microarray platforms.

    PubMed

    Valente, Eduardo; Rocha, Miguel

    2015-01-01

    DNA microarrays are one of the most used technologies for gene expression measurement. However, there are several distinct microarray platforms, from different manufacturers, each with its own measurement protocol, resulting in data that can hardly be compared or directly integrated. Data integration from multiple sources aims to improve the assertiveness of statistical tests, reducing the data dimensionality problem. The integration of heterogeneous DNA microarray platforms comprehends a set of tasks that range from the re-annotation of the features used on gene expression, to data normalization and batch effect elimination. In this work, a complete methodology for gene expression data integration and application is proposed, which comprehends a transcript-based re-annotation process and several methods for batch effect attenuation. The integrated data will be used to select the best feature set and learning algorithm for a brain tumor classification case study. The integration will consider data from heterogeneous Agilent and Affymetrix platforms, collected from public gene expression databases, such as The Cancer Genome Atlas and Gene Expression Omnibus. PMID:26673932

  7. Optical and surface analysis of DNA microarrays to assess printed spot heterogeneity

    NASA Astrophysics Data System (ADS)

    Nagaraja Rao, Archana

    DNA microarrays have been plagued with analytical problems with quantitation, metrics, figures of merit, and reliability and reproducibility issues, hindering their acceptance in clinical and diagnostic settings. The main deficiency in the printed DNA format is the microspot heterogeneity occurring during array fabrication and further amplified during target hybridization. Work described in this dissertation focuses on assessment of DNA microarray spots generated with conventional pin-type contact printing of fluorescently labeled DNA probes, on industry-standard commercial polymer-coated array slides and their hybridization with complementary oligomer DNA target. Printing of probe DNA microspots shares many features of commonly reported droplet evaporation dynamics that lead to different drying patterns and spot morphologies. This study directly identifies and analyzes different DNA probe chemical and spatial microenvironments within spots, analyzed with high-resolution time-of-flight secondary ion mass spectrometry (TOF-SIMS) chemical imaging, confocal epifluorescence, and probe microscopy force imaging methods. Drying of DNA probe spots shows Marangoni flow effects with high densities of probe DNA-Cy3 located in spot centers and nonhomogeneous DNA distributed radially within printed spots with both TOF-SIMS imaging and epifluorescence microscopy. Target hybridization kinetics and duplex formation were assessed using real-time in situ confocal imaging, and confirmed radial hemispherical diffusion-mediated distribution of target capture from spot edge to its interior. Kinetic modeling indicates pseudo-first order kinetics due to transport limitations and local density-dependent probe interactions with diffusing target. Fluorescence resonance energy transfer (FRET) and photobleaching results show that the high- density probe overcrowding in spots facilitates a broad range of target binding interactions regardless of dye orientations. Moreover, lateral probe density

  8. Global Gene Expression Patterns in Clostridium thermocellum as Determined by Microarray Analysis of Chemostat Cultures on Cellulose or Cellobiose▿ †

    PubMed Central

    Riederer, Allison; Takasuka, Taichi E.; Makino, Shin-ichi; Stevenson, David M.; Bukhman, Yury V.; Elsen, Nathaniel L.; Fox, Brian G.

    2011-01-01

    A microarray study of chemostat growth on insoluble cellulose or soluble cellobiose has provided substantial new information on Clostridium thermocellum gene expression. This is the first comprehensive examination of gene expression in C. thermocellum under defined growth conditions. Expression was detected from 2,846 of 3,189 genes, and regression analysis revealed 348 genes whose changes in expression patterns were growth rate and/or substrate dependent. Successfully modeled genes included those for scaffoldin and cellulosomal enzymes, intracellular metabolic enzymes, transcriptional regulators, sigma factors, signal transducers, transporters, and hypothetical proteins. Unique genes encoding glycolytic pathway and ethanol fermentation enzymes expressed at high levels simultaneously with previously established maximal ethanol production were also identified. Ranking of normalized expression intensities revealed significant changes in transcriptional levels of these genes. The pattern of expression of transcriptional regulators, sigma factors, and signal transducers indicates that response to growth rate is the dominant global mechanism used for control of gene expression in C. thermocellum. PMID:21169455

  9. The manufacture and assessment of tissue microarrays: suggestions and criteria for analysis, with breast cancer as an example.

    PubMed

    Pinder, Sarah E; Brown, John P; Gillett, Cheryl; Purdie, Colin A; Speirs, Valerie; Thompson, Alastair M; Shaaban, Abeer M

    2013-03-01

    Tissue microarray (TMA) is an established and valuable tool, particularly in translational research and clinical trials, allowing resource-efficient use, and high-throughput profiling, of large numbers of tumours. Despite this, there is little evidence, or guidance, on the optimum manufacture, use and assessment of TMAs. Here we review some of the literature, using breast cancer as an example, to highlight good practice and pitfalls in the design and manufacture of TMAs. Issues, such as the size, number, spacing and layout of cores, as well as the assessment and reporting of studies using TMAs are addressed. We make some suggestions regarding these challenges, and propose a checklist of features that should be considered in order to stimulate debate and improve the quality of data produced by TMA analysis. PMID:23087330

  10. Analysis of differentially expressed genes in placental tissues of preeclampsia patients using microarray combined with the Connectivity Map database.

    PubMed

    Song, Y; Liu, J; Huang, S; Zhang, L

    2013-12-01

    Preeclampsia (PE), which affects 2-7% of human pregnancies, causes significant maternal and neonatal morbidity and mortality. To better understand the pathophysiology of PE, the gene expression profiles of placental tissue from 5 controls and 5 PE patients were assessed using microarray. A total of 224 transcripts were significantly differentially expressed (>2-fold change and q value <0.05, SAM software). Gene Ontology (GO) enrichment analysis indicated that genes involved in hypoxia and oxidative and reductive processes were significantly changed. Three differentially expressed genes (DEGs) involved in these biological processes were further verified by quantitative real-time PCR. Finally, the potential therapeutic agents for PE were explored via the Connectivity Map database. In conclusion, the data obtained in this study might provide clues to better understand the pathophysiology of PE and to identify potential therapeutic agents for PE patients.

  11. Microarrays under the microscope

    PubMed Central

    Wildsmith, S E; Elcock, F J

    2001-01-01

    Microarray technology is a rapidly advancing area, which is gaining popularity in many biological disciplines from drug target identification to predictive toxicology. Over the past few years, there has been a dramatic increase in the number of methods and techniques available for carrying out this form of gene expression analysis. The techniques and associated peripherals, such as slide types, deposition methods, robotics, and scanning equipment, are undergoing constant improvement, helping to drive the technology forward in terms of robustness and ease of use. These rapid developments, combined with the number of options available and the associated hyperbole, can prove daunting for the new user. This review aims to guide the researcher through the various steps of conducting microarray experiments, from initial strategy to analysing the data, with critical examination of the benefits and disadvantages along the way. PMID:11212888

  12. Navigating public microarray databases.

    PubMed

    Penkett, Christopher J; Bähler, Jürg

    2004-01-01

    With the ever-escalating amount of data being produced by genome-wide microarray studies, it is of increasing importance that these data are captured in public databases so that researchers can use this information to complement and enhance their own studies. Many groups have set up databases of expression data, ranging from large repositories, which are designed to comprehensively capture all published data, through to more specialized databases. The public repositories, such as ArrayExpress at the European Bioinformatics Institute contain complete datasets in raw format in addition to processed data, whilst the specialist databases tend to provide downstream analysis of normalized data from more focused studies and data sources. Here we provide a guide to the use of these public microarray resources.

  13. Self-directed student research through analysis of microarray datasets: a computer-based functional genomics practical class for masters-level students.

    PubMed

    Grenville-Briggs, Laura J; Stansfield, Ian

    2011-01-01

    This report describes a linked series of Masters-level computer practical workshops. They comprise an advanced functional genomics investigation, based upon analysis of a microarray dataset probing yeast DNA damage responses. The workshops require the students to analyse highly complex transcriptomics datasets, and were designed to stimulate active learning through experience of current research methods in bioinformatics and functional genomics. They seek to closely mimic a realistic research environment, and require the students first to propose research hypotheses, then test those hypotheses using specific sections of the microarray dataset. The complexity of the microarray data provides students with the freedom to propose their own unique hypotheses, tested using appropriate sections of the microarray data. This research latitude was highly regarded by students and is a strength of this practical. In addition, the focus on DNA damage by radiation and mutagenic chemicals allows them to place their results in a human medical context, and successfully sparks broad interest in the subject material. In evaluation, 79% of students scored the practical workshops on a five-point scale as 4 or 5 (totally effective) for student learning. More broadly, the general use of microarray data as a "student research playground" is also discussed.

  14. Lectin-based protein microarray analysis of differences in serum alpha-2-macroglobulin glycosylation between patients with colorectal cancer and persons without cancer.

    PubMed

    Šunderić, Miloš; Šedivá, Alena; Robajac, Dragana; Miljuš, Goran; Gemeiner, Peter; Nedić, Olgica; Katrlík, Jaroslav

    2016-07-01

    Glycosylation is co- and posttranslational modifications affecting proteins. The glycopattern changes are associated with changes in biological function and are involved in many diseases including cancer. We present the lectin-based protein microarray method enabling determination of differences in protein glycosylation. The method involves isolation of targeted protein from samples by immunoprecipitation, spotting of protein from multiple samples into arrays on a microarray slide, incubation with set of biotinylated lectins, the reaction with fluorescent conjugate of streptavidin, and detection of fluorescent intensities by microarray scanner. Lectin-based protein microarray was applied in investigation of differences in alpha-2-macroglobulin (α2M) glycosylation isolated from sera samples of healthy persons and patients with colorectal cancer (CC). From 14 lectins used in analysis, statistically significant differences (Student's t-test, P < 0.05) between two groups of samples (persons without cancer and CC patients) were found for 5 of them. α2M molecules isolated from sera of CC patients have higher content of α2,6 sialic acid, N-acetylglucosamine and mannose residues, and tri-/tetraantennary complex type high-mannose N-glycans. A novel lectin-based protein microarray developed and described can serve as a suitable analytical technique for sensitive, simple, fast, and high-throughput determination of differences in protein glycosylation isolated from serum or other samples.

  15. Effect of Lactobacillus brevis KB290 on the cell-mediated cytotoxic activity of mouse splenocytes: a DNA microarray analysis.

    PubMed

    Fukui, Yuichiro; Sasaki, Erika; Fuke, Nobuo; Nakai, Yuji; Ishijima, Tomoko; Abe, Keiko; Yajima, Nobuhiro

    2013-11-14

    Lactic acid bacteria confer a variety of health benefits. Here, we investigate the mechanisms by which Lactobacillus brevis KB290 (KB290) enhances cell-mediated cytotoxic activity. Female BALB/c mice aged 9 weeks were fed a diet containing KB290 (3 × 10(9) colony-forming units/g) or starch for 1 d. The resulting cytotoxic activity of splenocytes against YAC-1 cells was measured using flow cytometry and analysed for gene expression using DNA microarray technology. KB290 enhanced the cell-mediated cytotoxic activity of splenocytes. DNA microarray analysis identified 327 up-regulated and 347 down-regulated genes that characterised the KB290 diet group. The up-regulated genes were significantly enriched in Gene Ontology terms related to immunity, and, especially, a positive regulation of T-cell-mediated cytotoxicity existed among these terms. Almost all the genes included in the term encoded major histocompatibility complex (MHC) class I molecules involved in the presentation of antigen to CD8(+) cytotoxic T cells. Marco and Signr1 specific to marginal zone macrophages (MZM), antigen-presenting cells, were also up-regulated. Flow cytometric analysis confirmed that the proportion of MZM was significantly increased by KB290 ingestion. Additionally, the over-represented Kyoto Encyclopedia of Genes and Genomes pathways among the up-regulated genes were those for natural killer (NK) cell-mediated cytotoxicity and antigen processing and presentation. The results for the selected genes associated with NK cells and CD8(+) cytotoxic T cells were confirmed by quantitative RT-PCR. These results suggest that enhanced cytotoxic activity could be caused by the activation of NK cells and/or of CD8(+) cytotoxic T cells stimulated via MHC class I presentation.

  16. Perinatal increases in TGF-{alpha} disrupt the saccular phase of lung morphogenesis and cause remodeling: microarray analysis.

    PubMed

    Kramer, Elizabeth L; Deutsch, Gail H; Sartor, Maureen A; Hardie, William D; Ikegami, Machiko; Korfhagen, Thomas R; Le Cras, Timothy D

    2007-08-01

    Transforming growth factor-alpha (TGF-alpha) and its receptor, the epithelial growth factor receptor (EGFR), have been associated with lung remodeling in premature infants with bronchopulmonary dysplasia (BPD). The goal of this study was to target TGF-alpha overexpression to the saccular phase of lung morphogenesis and determine early alterations in gene expression. Conditional lung-specific TGF-alpha bitransgenic mice and single-transgene control mice were generated. TGF-alpha overexpression was induced by doxycycline (Dox) treatment from embryonic day 16.5 (E16.5) to E18.5. After birth, all bitransgenic pups died by postnatal day 7 (P7). Lung histology at E18.5 and P1 showed abnormal lung morphogenesis in bitransgenic mice, characterized by mesenchymal thickening, vascular remodeling, and poor apposition of capillaries to distal air spaces. Surfactant levels (saturated phosphatidylcholine) were not reduced in bitransgenic mice. Microarray analysis was performed after 1 or 2 days of Dox treatment during the saccular (E17.5, E18.5) and alveolar phases (P4, P5) to identify genes induced by EGFR signaling that were shared or unique to each phase. We found 196 genes to be altered (>1.5-fold change; P < 0.01 for at least 2 time points), with only 32% similarly altered in both saccular and alveolar phases. Western blot analysis and immunostaining showed that five genes selected from the microarrays (egr-1, SP-B, SP-D, S100A4, and pleiotrophin) were also increased at the protein level. Pathological changes in TGF-alpha-overexpressing mice bore similarities to premature infants born in the saccular phase who develop BPD, including remodeling of the distal lung septae and arteries.

  17. Peptide-MHC Cellular Microarray with Innovative Data Analysis System for Simultaneously Detecting Multiple CD4 T-Cell Responses

    PubMed Central

    Ge, Xinhui; Gebe, John A.; Bollyky, Paul L.; James, Eddie A.; Yang, Junbao; Stern, Lawrence J.; Kwok, William W.

    2010-01-01

    Background Peptide:MHC cellular microarrays have been proposed to simultaneously characterize multiple Ag-specific populations of T cells. The practice of studying immune responses to complicated pathogens with this tool demands extensive knowledge of T cell epitopes and the availability of peptide:MHC complexes for array fabrication as well as a specialized data analysis approach for result interpretation. Methodology/Principal Findings We co-immobilized peptide:DR0401 complexes, anti-CD28, anti-CD11a and cytokine capture antibodies on the surface of chamber slides to generate a functional array that was able to detect rare Ag-specific T cell populations from previously primed in vitro T cell cultures. A novel statistical methodology was also developed to facilitate batch processing of raw array-like data into standardized endpoint scores, which linearly correlated with total Ag-specific T cell inputs. Applying these methods to analyze Influenza A viral antigen-specific T cell responses, we not only revealed the most prominent viral epitopes, but also demonstrated the heterogeneity of anti-viral cellular responses in healthy individuals. Applying these methods to examine the insulin producing beta-cell autoantigen specific T cell responses, we observed little difference between autoimmune diabetic patients and healthy individuals, suggesting a more subtle association between diabetes status and peripheral autoreactive T cells. Conclusions/Significance The data analysis system is reliable for T cell specificity and functional testing. Peptide:MHC cellular microarrays can be used to obtain multi-parametric results using limited blood samples in a variety of translational settings. PMID:20634998

  18. Global Microarray Analysis of Alkaliphilic Halotolerant Bacterium Bacillus sp. N16-5 Salt Stress Adaptation

    PubMed Central

    Yin, Liang; Xue, Yanfen; Ma, Yanhe

    2015-01-01

    The alkaliphilic halotolerant bacterium Bacillus sp. N16-5 is often exposed to salt stress in its natural habitats. In this study, we used one-colour microarrays to investigate adaptive responses of Bacillus sp. N16-5 transcriptome to long-term growth at different salinity levels (0%, 2%, 8%, and 15% NaCl) and to a sudden salt increase from 0% to 8% NaCl. The common strategies used by bacteria to survive and grow at high salt conditions, such as K+ uptake, Na+ efflux, and the accumulation of organic compatible solutes (glycine betaine and ectoine), were observed in Bacillus sp. N16-5. The genes of SigB regulon involved in general stress responses and chaperone-encoding genes were also induced by high salt concentration. Moreover, the genes regulating swarming ability and the composition of the cytoplasmic membrane and cell wall were also differentially expressed. The genes involved in iron uptake were down-regulated, whereas the iron homeostasis regulator Fur was up-regulated, suggesting that Fur may play a role in the salt adaption of Bacillus sp. N16-5. In summary, we present a comprehensive gene expression profiling of alkaliphilic Bacillus sp. N16-5 cells exposed to high salt stress, which would help elucidate the mechanisms underlying alkaliphilic Bacillus spp. survival in and adaptation to salt stress. PMID:26030352

  19. Exploring host-pathogen interactions through genome wide protein microarray analysis.

    PubMed

    Scietti, Luigi; Sampieri, Katia; Pinzuti, Irene; Bartolini, Erika; Benucci, Barbara; Liguori, Alessia; Haag, Andreas F; Lo Surdo, Paola; Pansegrau, Werner; Nardi-Dei, Vincenzo; Santini, Laura; Arora, Seguinde; Leber, Xavier; Rindi, Simonetta; Savino, Silvana; Costantino, Paolo; Maione, Domenico; Merola, Marcello; Speziale, Pietro; Bottomley, Matthew J; Bagnoli, Fabio; Masignani, Vega; Pizza, Mariagrazia; Scharenberg, Meike; Schlaeppi, Jean-Marc; Nissum, Mikkel; Liberatori, Sabrina

    2016-01-01

    During bacterial pathogenesis extensive contacts between the human and the bacterial extracellular proteomes take place. The identification of novel host-pathogen interactions by standard methods using a case-by-case approach is laborious and time consuming. To overcome this limitation, we took advantage of large libraries of human and bacterial recombinant proteins. We applied a large-scale protein microarray-based screening on two important human pathogens using two different approaches: (I) 75 human extracellular proteins were tested on 159 spotted Staphylococcus aureus recombinant proteins and (II) Neisseria meningitidis adhesin (NadA), an important vaccine component against serogroup B meningococcus, was screened against ≈2300 spotted human recombinant proteins. The approach presented here allowed the identification of the interaction between the S. aureus immune evasion protein FLIPr (formyl-peptide receptor like-1 inhibitory protein) and the human complement component C1q, key players of the offense-defense fighting; and of the interaction between meningococcal NadA and human LOX-1 (low-density oxidized lipoprotein receptor), an endothelial receptor. The novel interactions between bacterial and human extracellular proteins here presented might provide a better understanding of the molecular events underlying S. aureus and N. meningitidis pathogenesis. PMID:27302108

  20. Analysis of the genome content of Lactococcus garvieae by genomic interspecies microarray hybridization

    PubMed Central

    2010-01-01

    Background Lactococcus garvieae is a bacterial pathogen that affects different animal species in addition to humans. Despite the widespread distribution and emerging clinical significance of L. garvieae in both veterinary and human medicine, there is almost a complete lack of knowledge about the genetic content of this microorganism. In the present study, the genomic content of L. garvieae CECT 4531 was analysed using bioinformatics tools and microarray-based comparative genomic hybridization (CGH) experiments. Lactococcus lactis subsp. lactis IL1403 and Streptococcus pneumoniae TIGR4 were used as reference microorganisms. Results The combination and integration of in silico analyses and in vitro CGH experiments, performed in comparison with the reference microorganisms, allowed establishment of an inter-species hybridization framework with a detection threshold based on a sequence similarity of ≥ 70%. With this threshold value, 267 genes were identified as having an analogue in L. garvieae, most of which (n = 258) have been documented for the first time in this pathogen. Most of the genes are related to ribosomal, sugar metabolism or energy conversion systems. Some of the identified genes, such as als and mycA, could be involved in the pathogenesis of L. garvieae infections. Conclusions In this study, we identified 267 genes that were potentially present in L. garvieae CECT 4531. Some of the identified genes could be involved in the pathogenesis of L. garvieae infections. These results provide the first insight into the genome content of L. garvieae. PMID:20233401

  1. Identification of FHL2-regulated genes in liver by microarray and bioinformatics analysis.

    PubMed

    Ng, Chor-Fung; Xu, Jia-Ying; Li, Man-Shan; Tsui, Stephen Kwok-Wing

    2014-04-01

    FHL2 is a LIM domain protein that is able to form various protein complexes and regulate gene transcription. Recent findings showed that FHL2 is a potential tumor suppressor gene that was down-regulated in hepatocellular carcinoma. In the present study, microarray profiling of gene expression was performed to identify the genes regulated by FHL2 in mouse livers. The differentially expressed genes were further analyzed by bioinformatics tools including DAVID, KEGG, and STRING. Our data illustrate that FHL2 affects genes involved in various functions including signal transduction, responses to external stimulus, cancer-related pathways, cardiovascular function and regulation of actin cytoskeleton. Moreover, a network of differentially expressed genes identified in this study and known FHL2-interacting proteins was constructed. Then, genes identified by bioinformatics tools and most functional relevant to FHL2 were selected for further validation. Finally, the differential expression of Ar, Id3, Inhbe, Alas1, Bcl6, Pparδ, Angptl4, and Erbb4 were confirmed by quantitative real-time PCR. In summary, we have established a database of genes that are potentially regulated by FHL2 and these genes should be future targets for the elucidation of functional roles of FHL2.

  2. Hazard characterization and identification of a former ammunition site using microarrays, bioassays, and chemical analysis.

    PubMed

    Eisentraeger, Adolf; Reifferscheid, Georg; Dardenne, Freddy; Blust, Ronny; Schofer, Andrea

    2007-04-01

    More than 100,000 tons of 2,4,6-trinitrotoluene were produced at the former ammunition site Werk Tanne in Clausthal-Zellerfeld, Germany. The production of explosives and consequent detonation in approximately 1944 by the Allies caused great pollution in this area. Four soil samples and three water samples were taken from this site and characterized by applying chemical-analytical methods and several bioassays. Ecotoxicological test systems, such as the algal growth inhibition assay with Desmodesmus subspicatus, and genotoxicity tests, such as the umu and NM2009 tests, were performed. Also applied were the Ames test, according to International Organization for Standardization 16240, and an Ames fluctuation test. The toxic mode of action was examined using bacterial gene profiling assays with a battery of Escherichia coli strains and with the human liver cell line hepG2 using the PIQOR Toxicology cDNA microarray. Additionally, the molecular mechanism of 2,4,6-trinitrotoluene in hepG2 cells was analyzed. The present assessment indicates a danger of pollutant leaching for the soil-groundwater path. A possible impact for human health is discussed, because the groundwater in this area serves as drinking water. PMID:17447547

  3. Microarray Analysis of Gene Expression at the Tumor Front of Colon Cancer.

    PubMed

    Kobayashi, Takaaki; Masaki, Tadahiko; Nozaki, Eriko; Sugiyama, Masanori; Nagashima, Fumio; Furuse, Junji; Onishi, Hiroaki; Watanabe, Takashi; Ohkura, Yasuo

    2015-12-01

    Budding or the presence poorly differentiated clusters at the boundary of cancer tissue is a pathologically important finding and serves as a prognostic factor in colorectal cancer. However, few studies have examined the cancer tissue boundary in clinical samples. The purpose of the present study was to examine gene expression at the tumor front of colon cancer in surgically resected samples. Cancer tissues were obtained by laser microdissection of 20 surgically resected specimens. Genes with significantly different microarray signals between the tumor front and the tumor center were identified. Among genes showing significant up-regulation at the tumor front were six chemokines [chemokine c-c motif ligand (CCL)2 and -18, chemokine (C-X-C motif) ligand (CXCL)9-11, and interleukin 8 (IL8)], and two apoptosis-related molecules [ubiquitin D (UBD) and baculoviral iap repeat-containing 3 (BIRC3)]. Expression of laminin gamma 2 (LAMC2), matrix metallopeptidase 7 (MMP7) and epithelial-mesenchymal transition (EMT)-related molecules were elevated in the tumor front, but their fold changes were smaller than those of the aforementioned genes. These results suggest that chemokines, in addition to EMT-related molecules, may play important roles in invasion of colon cancer. PMID:26637872

  4. Global Microarray Analysis of Alkaliphilic Halotolerant Bacterium Bacillus sp. N16-5 Salt Stress Adaptation.

    PubMed

    Yin, Liang; Xue, Yanfen; Ma, Yanhe

    2015-01-01

    The alkaliphilic halotolerant bacterium Bacillus sp. N16-5 is often exposed to salt stress in its natural habitats. In this study, we used one-colour microarrays to investigate adaptive responses of Bacillus sp. N16-5 transcriptome to long-term growth at different salinity levels (0%, 2%, 8%, and 15% NaCl) and to a sudden salt increase from 0% to 8% NaCl. The common strategies used by bacteria to survive and grow at high salt conditions, such as K+ uptake, Na+ efflux, and the accumulation of organic compatible solutes (glycine betaine and ectoine), were observed in Bacillus sp. N16-5. The genes of SigB regulon involved in general stress responses and chaperone-encoding genes were also induced by high salt concentration. Moreover, the genes regulating swarming ability and the composition of the cytoplasmic membrane and cell wall were also differentially expressed. The genes involved in iron uptake were down-regulated, whereas the iron homeostasis regulator Fur was up-regulated, suggesting that Fur may play a role in the salt adaption of Bacillus sp. N16-5. In summary, we present a comprehensive gene expression profiling of alkaliphilic Bacillus sp. N16-5 cells exposed to high salt stress, which would help elucidate the mechanisms underlying alkaliphilic Bacillus spp. survival in and adaptation to salt stress.

  5. Spatio-Temporal Analysis of Cell-Cell Signaling in a Living Cell Microarray

    NASA Astrophysics Data System (ADS)

    Mirsaidov, Utkur; Timp, Winston; Timp, Kaethe; Matsudaira, Paul; Timp, Greg

    2007-03-01

    Cell-cell signaling plays a central role in biology, enabling individual cells to coordinate their activities. For example, bacteria show evidence of intercellular signaling through quorum sensing, a regulatory mechanism that launches a coordinated response, depending on the population density. To explore the spatio-temporal development of cell-to-cell signaling, we have created regular, heterotypic microarrays of living cells in hydrogel using time-multiplexed optical traps for submicron positional control of the cell orientation and location without loss of viability. We studied the Lux system for quorum sensing; splitting it into sender and receiver plasmids, which were subsequently introduced into E. Coli. Induced by IPTG, the sender cells express a fluorescent reporter (mRFP1) and the LuxI enzyme that catalyzes the synthesis of a molecular signal AHL that diffuses through the cell membrane and the extra-cellular scaffold. The receiver cells collect the AHL signal that binds to the LuxR regulator and reports it through GFP production. We have measured the time-delay between the onset of mRFP1 and GFP dependence on intercellular spacing in the array.

  6. Genome-wide prediction and analysis of human tissue-selective genes using microarray expression data

    PubMed Central

    2013-01-01

    Background Understanding how genes are expressed specifically in particular tissues is a fundamental question in developmental biology. Many tissue-specific genes are involved in the pathogenesis of complex human diseases. However, experimental identification of tissue-specific genes is time consuming and difficult. The accurate predictions of tissue-specific gene targets could provide useful information for biomarker development and drug target identification. Results In this study, we have developed a machine learning approach for predicting the human tissue-specific genes using microarray expression data. The lists of known tissue-specific genes for different tissues were collected from UniProt database, and the expression data retrieved from the previously compiled dataset according to the lists were used for input vector encoding. Random Forests (RFs) and Support Vector Machines (SVMs) were used to construct accurate classifiers. The RF classifiers were found to outperform SVM models for tissue-specific gene prediction. The results suggest that the candidate genes for brain or liver specific expression can provide valuable information for further experimental studies. Our approach was also applied for identifying tissue-selective gene targets for different types of tissues. Conclusions A machine learning approach has been developed for accurately identifying the candidate genes for tissue specific/selective expression. The approach provides an efficient way to select some interesting genes for developing new biomedical markers and improve our knowledge of tissue-specific expression. PMID:23369200

  7. Hazard characterization and identification of a former ammunition site using microarrays, bioassays, and chemical analysis.

    PubMed

    Eisentraeger, Adolf; Reifferscheid, Georg; Dardenne, Freddy; Blust, Ronny; Schofer, Andrea

    2007-04-01

    More than 100,000 tons of 2,4,6-trinitrotoluene were produced at the former ammunition site Werk Tanne in Clausthal-Zellerfeld, Germany. The production of explosives and consequent detonation in approximately 1944 by the Allies caused great pollution in this area. Four soil samples and three water samples were taken from this site and characterized by applying chemical-analytical methods and several bioassays. Ecotoxicological test systems, such as the algal growth inhibition assay with Desmodesmus subspicatus, and genotoxicity tests, such as the umu and NM2009 tests, were performed. Also applied were the Ames test, according to International Organization for Standardization 16240, and an Ames fluctuation test. The toxic mode of action was examined using bacterial gene profiling assays with a battery of Escherichia coli strains and with the human liver cell line hepG2 using the PIQOR Toxicology cDNA microarray. Additionally, the molecular mechanism of 2,4,6-trinitrotoluene in hepG2 cells was analyzed. The present assessment indicates a danger of pollutant leaching for the soil-groundwater path. A possible impact for human health is discussed, because the groundwater in this area serves as drinking water.

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

    PubMed Central

    Efferth, Thomas; Greten, Henry Johannes

    2012-01-01

    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.

  9. Profiling candidate genes involved in wax biosynthesis in Arabidopsis thaliana by microarray analysis.

    PubMed

    Costaglioli, Patricia; Joubès, Jérôme; Garcia, Christel; Stef, Marianne; Arveiler, Benoît; Lessire, René; Garbay, Bertrand

    2005-06-01

    Plant epidermal wax forms a hydrophobic layer covering aerial plant organs which constitutes a barrier against uncontrolled water loss and biotic stresses. Wax biosynthesis requires the coordinated activity of a large number of enzymes for the formation of saturated very-long-chain fatty acids and their further transformation in several aliphatic compounds. We found in the available database 282 candidate genes that may play a role in wax synthesis, regulation and transport. To identify the most interesting candidates, we measured the level of expression of 204 genes in the aerial parts of 15-day-old Arabidopsis seedlings by performing microarray experiments. We showed that only 25% of the putative candidates were expressed to significant levels in our samples, thus significantly reducing the number of genes which will be worth studying using reverse genetics to demonstrate their involvement in wax accumulation. We identified a beta-keto acyl-CoA synthase gene, At5g43760, which is co-regulated with the wax gene CER6 in a number of conditions and organs. By contrast, we showed that neither the fatty acyl-CoA reductase genes nor the wax synthase genes were expressed in 15-day-old leaves and stems, raising questions about the identity of the enzymes involved in the acyl-reduction pathway that accounts for 20% of the total wax amount. PMID:15914083

  10. Exploring host-pathogen interactions through genome wide protein microarray analysis

    PubMed Central

    Scietti, Luigi; Sampieri, Katia; Pinzuti, Irene; Bartolini, Erika; Benucci, Barbara; Liguori, Alessia; Haag, Andreas F.; Lo Surdo, Paola; Pansegrau, Werner; Nardi-Dei, Vincenzo; Santini, Laura; Arora, Seguinde; Leber, Xavier; Rindi, Simonetta; Savino, Silvana; Costantino, Paolo; Maione, Domenico; Merola, Marcello; Speziale, Pietro; Bottomley, Matthew J.; Bagnoli, Fabio; Masignani, Vega; Pizza, Mariagrazia; Scharenberg, Meike; Schlaeppi, Jean-Marc; Nissum, Mikkel; Liberatori, Sabrina

    2016-01-01

    During bacterial pathogenesis extensive contacts between the human and the bacterial extracellular proteomes take place. The identification of novel host-pathogen interactions by standard methods using a case-by-case approach is laborious and time consuming. To overcome this limitation, we took advantage of large libraries of human and bacterial recombinant proteins. We applied a large-scale protein microarray-based screening on two important human pathogens using two different approaches: (I) 75 human extracellular proteins were tested on 159 spotted Staphylococcus aureus recombinant proteins and (II) Neisseria meningitidis adhesin (NadA), an important vaccine component against serogroup B meningococcus, was screened against ≈2300 spotted human recombinant proteins. The approach presented here allowed the identification of the interaction between the S. aureus immune evasion protein FLIPr (formyl-peptide receptor like-1 inhibitory protein) and the human complement component C1q, key players of the offense-defense fighting; and of the interaction between meningococcal NadA and human LOX-1 (low-density oxidized lipoprotein receptor), an endothelial receptor. The novel interactions between bacterial and human extracellular proteins here presented might provide a better understanding of the molecular events underlying S. aureus and N. meningitidis pathogenesis. PMID:27302108

  11. Exploring host-pathogen interactions through genome wide protein microarray analysis.

    PubMed

    Scietti, Luigi; Sampieri, Katia; Pinzuti, Irene; Bartolini, Erika; Benucci, Barbara; Liguori, Alessia; Haag, Andreas F; Lo Surdo, Paola; Pansegrau, Werner; Nardi-Dei, Vincenzo; Santini, Laura; Arora, Seguinde; Leber, Xavier; Rindi, Simonetta; Savino, Silvana; Costantino, Paolo; Maione, Domenico; Merola, Marcello; Speziale, Pietro; Bottomley, Matthew J; Bagnoli, Fabio; Masignani, Vega; Pizza, Mariagrazia; Scharenberg, Meike; Schlaeppi, Jean-Marc; Nissum, Mikkel; Liberatori, Sabrina

    2016-06-15

    During bacterial pathogenesis extensive contacts between the human and the bacterial extracellular proteomes take place. The identification of novel host-pathogen interactions by standard methods using a case-by-case approach is laborious and time consuming. To overcome this limitation, we took advantage of large libraries of human and bacterial recombinant proteins. We applied a large-scale protein microarray-based screening on two important human pathogens using two different approaches: (I) 75 human extracellular proteins were tested on 159 spotted Staphylococcus aureus recombinant proteins and (II) Neisseria meningitidis adhesin (NadA), an important vaccine component against serogroup B meningococcus, was screened against ≈2300 spotted human recombinant proteins. The approach presented here allowed the identification of the interaction between the S. aureus immune evasion protein FLIPr (formyl-peptide receptor like-1 inhibitory protein) and the human complement component C1q, key players of the offense-defense fighting; and of the interaction between meningococcal NadA and human LOX-1 (low-density oxidized lipoprotein receptor), an endothelial receptor. The novel interactions between bacterial and human extracellular proteins here presented might provide a better understanding of the molecular events underlying S. aureus and N. meningitidis pathogenesis.

  12. Site-specific immobilization of biotinylated proteins for protein microarray analysis.

    PubMed

    Lue, Rina Y P; Chen, Grace Y J; Zhu, Qing; Lesaicherre, Marie-Laure; Yao, Shao Q

    2004-01-01

    The postgenome era has led to a new frontier of proteomics that requires the development of protein microarray, which enables us to unravel the biological function of proteins in a massively parallel fashion. Several ways of immobilizing proteins onto surfaces have been reported, but many of these attachments are unspecific, resulting in the unfavorable orientation of the immobilized proteins. His6 tag has been used to site-specifically immobilize proteins onto nickel-coated slides, which presumably oriented proteins uniformly on the surface of the slide. However, the binding between Ni-NTA and His tag proteins is not strong, causing the immobilized proteins to dissociate from the slide even under simple wash conditions. The authors have developed a novel strategy of using an intein-mediated expression system to generate biotinylated proteins suitable for immobilization onto avidin-functionalized glass slides. Array-scan results not only show successful immobilization of proteins onto slides by antibody detection method but also full retention of biological activities of the immobilized proteins. The strong and specific interaction between biotin and avidin also permits the use of stringent incubation and washing conditions on the protein microchip, thus making it a highly robust method for array studies.

  13. Function analysis of proteins encoded by ORFs 1 to 8 of porcine circovirus-like virus P1 by microarray assay.

    PubMed

    Wen, Libin; Wang, Fengzhi; Zhang, Dan; He, Kongwang

    2015-12-01

    Porcine circovirus-like agent P1 is a newly discovered virus containing a single-strand circular genome. The genome of P1 is a DNA molecule of 648 nucleotides which contains eight open reading frames (ORFs) that probably encode potential proteins or polypeptides. Thus it is very important to clarify these proteins' function. Here we provide the methods and analysis of microarray data in detail to characterize the transcriptome profile of P1 with and without the ORF. The relevant microarray data sets have been deposited in Gene Expression Omnibus (GEO) database under accession number GSE71945. PMID:26697373

  14. Analyzing gene expression data from microarray and next-generation dna sequencing transcriptome profiling assays using GeneSifter analysis edition.

    PubMed

    Porter, Sandra; Olson, N Eric; Smith, Todd

    2009-09-01

    Transcription profiling with microarrays has become a standard procedure for comparing the levels of gene expression between pairs of samples, or multiple samples following different experimental treatments. New technologies, collectively known as next-generation DNA sequencing methods, are also starting to be used for transcriptome analysis. These technologies, with their low background, large capacity for data collection, and dynamic range, provide a powerful and complementary tool to the assays that formerly relied on microarrays. In this chapter, we describe two protocols for working with microarray data from pairs of samples and samples treated with multiple conditions, and discuss alternative protocols for carrying out similar analyses with next-generation DNA sequencing data from two different instrument platforms (Illumina GA and Applied Biosystems SOLiD).

  15. A multi-parametric microarray for protein profiling: simultaneous analysis of 8 different cytochromes via differentially element tagged antibodies and laser ablation ICP-MS.

    PubMed

    Waentig, Larissa; Techritz, Sandra; Jakubowski, Norbert; Roos, Peter H

    2013-11-01

    The paper presents a new multi-parametric protein microarray embracing the multi-analyte capabilities of laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). The combination of high throughput reverse phase protein microarrays with element tagged antibodies and LA-ICP-MS makes it possible to detect and quantify many proteins or biomarkers in multiple samples simultaneously. A proof of concept experiment is performed for the analysis of cytochromes particularly of cytochrome P450 enzymes, which play an important role in the metabolism of xenobiotics such as toxicants and drugs. With the aid of the LA-ICP-MS based multi-parametric reverse phase protein microarray it was possible to analyse 8 cytochromes in 14 different proteomes in one run. The methodology shows excellent detection limits in the lower amol range and a very good linearity of R(2) ≥ 0.9996 which is a prerequisite for the development of further quantification strategies.

  16. Self-Directed Student Research through Analysis of Microarray Datasets: A Computer-Based Functional Genomics Practical Class for Masters-Level Students

    ERIC Educational Resources Information Center

    Grenville-Briggs, Laura J.; Stansfield, Ian

    2011-01-01

    This report describes a linked series of Masters-level computer practical workshops. They comprise an advanced functional genomics investigation, based upon analysis of a microarray dataset probing yeast DNA damage responses. The workshops require the students to analyse highly complex transcriptomics datasets, and were designed to stimulate…

  17. Microarray analysis of active cardiac remodeling genes in a familial hypertrophic cardiomyopathy mouse model rescued by a phospholamban knockout

    PubMed Central

    Rajan, Sudarsan; Pena, James R.; Jegga, Anil G.; Aronow, Bruce J.; Wolska, Beata M.

    2013-01-01

    Familial hypertrophic cardiomyopathy (FHC) is a disease characterized by ventricular hypertrophy, fibrosis, and aberrant systolic and/or diastolic function. Our laboratories have previously developed two mouse models that affect cardiac performance. One mouse model encodes an FHC-associated mutation in α-tropomyosin: Glu → Gly at amino acid 180, designated as Tm180. These mice display a phenotype that is characteristic of FHC, including severe cardiac hypertrophy with fibrosis and impaired physiological performance. The other model was a gene knockout of phospholamban (PLN KO), a regulator of calcium uptake in the sarcoplasmic reticulum of cardiomyocytes; these hearts exhibit hypercontractility with no pathological abnormalities. Previous work in our laboratories shows that when mice were genetically crossed between the PLN KO and Tm180, the progeny (PLN KO/Tm180) display a rescued hypertrophic phenotype with improved morphology and cardiac function. To understand the changes in gene expression that occur in these models undergoing cardiac remodeling (Tm180, PLN KO, PLN KO/Tm180, and nontransgenic control mice), we conducted microarray analyses of left ventricular tissue at 4 and 12 mo of age. Expression profiling reveals that 1,187 genes changed expression in direct response to the three genetic models. With these 1,187 genes, 11 clusters emerged showing normalization of transcript expression in the PLN KO/Tm180 hearts. In addition, 62 transcripts are highly involved in suppression of the hypertrophic phenotype. Confirmation of the microarray analysis was conducted by quantitative RT-PCR. These results provide insight into genes that alter expression during cardiac remodeling and are active during modulation of the cardiomyopathic phenotype. PMID:23800848

  18. Not proper ROC curves as new tool for the analysis of differentially expressed genes in microarray experiments

    PubMed Central

    Parodi, Stefano; Pistoia, Vito; Muselli, Marco

    2008-01-01

    Background Most microarray experiments are carried out with the purpose of identifying genes whose expression varies in relation with specific conditions or in response to environmental stimuli. In such studies, genes showing similar mean expression values between two or more groups are considered as not differentially expressed, even if hidden subclasses with different expression values may exist. In this paper we propose a new method for identifying differentially expressed genes, based on the area between the ROC curve and the rising diagonal (ABCR). ABCR represents a more general approach than the standard area under the ROC curve (AUC), because it can identify both proper (i.e., concave) and not proper ROC curves (NPRC). In particular, NPRC may correspond to those genes that tend to escape standard selection methods. Results We assessed the performance of our method using data from a publicly available database of 4026 genes, including 14 normal B cell samples (NBC) and 20 heterogeneous lymphomas (namely: 9 follicular lymphomas and 11 chronic lymphocytic leukemias). Moreover, NBC also included two sub-classes, i.e., 6 heavily stimulated and 8 slightly or not stimulated samples. We identified 1607 differentially expressed genes with an estimated False Discovery Rate of 15%. Among them, 16 corresponded to NPRC and all escaped standard selection procedures based on AUC and t statistics. Moreover, a simple inspection to the shape of such plots allowed to identify the two subclasses in either one class in 13 cases (81%). Conclusion NPRC represent a new useful tool for the analysis of microarray data. PMID:18834513

  19. Microarray analysis of tomato plants exposed to the nonviruliferous or viruliferous whitefly vector harboring Pepper golden mosaic virus.

    PubMed

    Musser, Richard O; Hum-Musser, Sue M; Gallucci, Matthew; DesRochers, Brittany; Brown, Judith K

    2014-01-01

    Plants are routinely exposed to biotic and abiotic stresses to which they have evolved by synthesizing constitutive and induced defense compounds. Induced defense compounds are usually made, initially, at low levels; however, following further stimulation by specific kinds of biotic and abiotic stresses, they can be synthesized in relatively large amounts to abate the particular stress. cDNA microarray hybridization was used to identify an array of genes that were differentially expressed in tomato plants 15 d after they were exposed to feeding by nonviruliferous whiteflies or by viruliferous whiteflies carrying Pepper golden mosaic virus (PepGMV) (Begomovirus, Geminiviridae). Tomato plants inoculated by viruliferous whiteflies developed symptoms characteristic of PepGMV, whereas plants exposed to nonviruliferous whitefly feeding or nonwounded (negative) control plants exhibited no disease symptoms. The microarray analysis yielded over 290 spotted probes, with significantly altered expression of 161 putative annotated gene targets, and 129 spotted probes of unknown identities. The majority of the differentially regulated "known" genes were associated with the plants exposed to viruliferous compared with nonviruliferous whitefly feeding. Overall, significant differences in gene expression were represented by major physiological functions including defense-, pathogen-, photosynthesis-, and signaling-related responses and were similar to genes identified for other insect-plant systems. Viruliferous whitefly-stimulated gene expression was validated by real-time quantitative polymerase chain reaction of selected, representative candidate genes (messenger RNA): arginase, dehydrin, pathogenesis-related proteins 1 and -4, polyphenol oxidase, and several protease inhibitors. This is the first comparative profiling of the expression of tomato plants portraying different responses to biotic stress induced by viruliferous whitefly feeding (with resultant virus infection

  20. Microarray analysis of natural socially regulated plasticity in circadian rhythms of honey bees.

    PubMed

    Rodriguez-Zas, Sandra L; Southey, Bruce R; Shemesh, Yair; Rubin, Elad B; Cohen, Mira; Robinson, Gene E; Bloch, Guy

    2012-02-01

    Honey bee workers care for ("nurse") the brood around the clock without circadian rhythmicity, but then they forage outside with strong circadian rhythms and a consolidated nightly rest. This chronobiological plasticity is associated with variation in the expression of the canonical "clock genes" that regulate the circadian clock: nurse bees show no brain rhythms of expression, while foragers do. These results suggest that the circadian system is organized differently in nurses and foragers. Nurses switch to activity with circadian rhythms shortly after being removed from the hive, suggesting that at least some clock cells in their brain continue to measure time while in the hive. We performed a microarray genome-wide survey to determine general patterns of brain gene expression in nurses and foragers sampled around the clock. We found 160 and 541 transcripts that exhibited significant sinusoidal oscillations in nurses and foragers, respectively, with peaks of expression distributed throughout the day in both task groups. Consistent with earlier studies, transcripts of genes involved in circadian rhythms, including Clockwork Orange that has not been studied before in bees, oscillated in foragers but not in nurses. The oscillating transcripts also were enriched for genes involved in the visual system, "development" and "response to stimuli" (foragers), "muscle contraction" and "microfilament motor gene expression" (nurses), and "generation of precursor metabolites" and "energy" (both). Transcripts of genes encoding P450 enzymes oscillated in both nurses and foragers but with a different phase. This study identified new putative clock-controlled genes in the honey bee and suggests that some brain functions show circadian rhythmicity even in nurse bees that are active around the clock.

  1. Gene expression microarray analysis of the sciatic nerve of mice with diabetic neuropathy.

    PubMed

    Zhang, Lei; Qu, Shen; Liang, Aibin; Jiang, Hong; Wang, Hao

    2015-02-01

    The present study aimed to explore novel target genes that regulate the development of diabetic neuropathy (DN) by analyzing gene expression profiles in the sciatic nerve of infected mice. The GSE11343 microarray dataset, which was downloaded from Gene Expression Omnibus, included data on 4 control samples and 5 samples from mice with diabetes induced by streptozotocin (STZ), 5 samples from normal mice treated with rosiglitazone (Rosi) and 5 samples from mice with diabetes induced by STZ and treated with Rosi. Differentially expressed genes (DEGs) between the different groups were identified using the substitution augmentation modification redefinition (SAMR) model. The Gene Ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID). Regulatory and protein‑protein interaction networks were searched using BioCarta and STRING, respectively. The protein structures of potential regulatory genes were predicted using the SYBYL program. Compared with the controls, 1,384 DEGs were identified in the mice with STZ-induced diabetes and 7 DEGs were identified in the mice treated with Rosi. There were 518 DEGs identified between the mice in the STZ + Rosi and STZ groups. We identified 45 GO items, and the calmodulin nerve phosphatase and chemokine signaling pathways were identified as the main pathways. Three genes [myristoylated alanine-rich protein kinase C substrate (Marcks), GLI pathogenesis-related 2 (Glipr2) and centrosomal protein 170 kDa (Cep170)] were found to be co-regulated by both STZ and Rosi, the protein structure of which was predicted and certain binding activity to Rosi was docked. Our study demonstrates that the Marcks, Glipr2 and Cep170 genes may be underlying drug targets in the treatment of DN. PMID:25435094

  2. Analysis of Liquid Bead Microarray Antibody Assay Data for Epidemiologic Studies of Pathogen-Cancer Associations

    PubMed Central

    Colombara, Danny V.; Hughes, James P.; Burnett-Hartman, Andrea N.; Hawes, Stephen E.; Galloway, Denise A.; Schwartz, Stephen M.; Bostick, Roberd M.; Potter, John D.; Manhart, Lisa E.

    2015-01-01

    Background Liquid bead microarray antibody (LBMA) assays are used to assess pathogen-cancer associations. However, studies analyze LBMA data differently, limiting comparability. Methods We generated 10,000 Monte Carlo-type simulations of log-normal antibody distributions (exposure) with 200 cases and 200 controls (outcome). We estimated type I error rates, statistical power, and bias associated with t-tests, logistic regression with a linear exposure and with the exposure dichotomized at 200 units, 400 units, the mean among controls plus two standard deviations, and the value corresponding to the optimal sensitivity and specificity. We also applied these models, and data visualizations (kernel density plots, receiver operating characteristic (ROC) curves, predicted probability plots, and Q-Q plots), to two empirical datasets to assess the consistency of the exposure-outcome relationship. Results All strategies had acceptable type I error rates (0.03≤P≤0.048), except for the dichotomization according to optimal sensitivity and specificity, which had a type I error rate of 0.27. Among the remaining methods, logistic regression with a linear predictor (Power=1.00) and t-tests (Power=1.00) had the highest power to detect a mean difference of 1.0 MFI (median fluorescence intensity) on the log scale and were unbiased. Dichotomization methods upwardly biased the risk estimates. Conclusion These results indicate that logistic regression with linear predictors and unpaired t-tests are superior to logistic regression with dichotomized predictors for assessing disease associations with LBMA data. Logistic regression with continuous linear predictors and t-tests are preferable to commonly used LBMA dichotomization methods. PMID:26071614

  3. DNA Microarray Analysis of Anaerobic Methanosarcina Barkeri Reveals Responses to Heat Shock and Air Exposure

    SciTech Connect

    Zhang, Weiwen; Culley, David E.; Nie, Lei; Brockman, Fred J.

    2006-04-08

    Summary Methanosarcina barkeri can grow only under strictly anoxic conditions because enzymes in methane formation pathways of are very oxygen sensitive. However, it has been determined that M. barkeri can survive oxidative stress. To obtain further knowledge of cellular changes in M. barkeri in responsive to oxidative and other environmental stress, a first whole-genome M. barkeri oligonucleotide microarray was constructed according to the draft genome sequence that contains 5072 open reading frames (ORFs) and was used to investigate the global transcriptomic response of M. barkeri to oxidative stress and heat shock. The result showed that 552 genes in the M. barkeri genome were responsive to oxidative stress, while 177 genes responsive to heat-shock, respectively using a cut off of 2.5 fold change. Among them, 101 genes were commonly responsive to both environmental stimuli. In addition to various house-keeping genes, large number of functionally unknown genes (38-57% of total responsive genes) was regulated by both stress conditions. The result showed that the Hsp60 (GroEL) system, which was previously thought not present in archaea, was up-regulated and may play important roles in protein biogenesis in responsive to heat shock in M. barkeri. No gene encoding superoxide dismutase, catalase, nonspecific peroxidases or thioredoxin reductase was differentially expressed when subjected to oxidative stress. Instead, significant downregulation of house-keeping genes and up-regulation of genes encoding transposase was found in responsive to oxidative stress, suggesting that M. barkeri may be adopting a passive protective mechanism by slowing down cellular activities to survive the stress rather than activating a means against oxidative stress.

  4. Effect of leucine uptake on hepatic and skeletal muscle gene expression in rats: a microarray analysis

    PubMed Central

    Cheon, Wookwang

    2015-01-01

    [Purpose] This study was performed to explore the physiological functions of leucine by exploring genes with leucine-dependent variability using DNA microarray. [Methods] Sprague-Dawley rats (n = 20) were separated into a HPD (30% High Protein Diet, n = 10) group and a NPD (0% Non Protein Diet, n = 10) group and fed a protein diet for 2 weeks. At the end of the 2-week period, the rats were fasted for 12-16 hours, further separated into subgroups within the HPD (Saline, n = 5, Leucine, n = 5) and NPD (Saline, n = 5, Leucine, n = 5) groups and administered with a leucine solution. The liver and muscles were harvested after 2 hours for RNA extraction. RNA purification from the isolated muscles and target gene identification using DNA chip were performed. The target gene was determined based on the results of the DNA chip experiment, and mRNA expression of the target gene was analyzed using Real-Time PCR. [Results] In the skeletal muscle, 27 genes were upregulated while 52 genes were down regulated after leucine administration in the NPD group. In the liver, 160 genes were up-regulated while 126 were down-regulated. The per2 gene was one of the genes with leucine-dependent induction in muscles and liver. [Conclusion] This study was performed to explore the physiological functions of leucine, however, a large number of genes showed variability. Therefore, it was difficult to definitively identify the genes linked with a particular physiological function. Various nutritional effects of leucine were observed. High variability in cytokines, receptors, and various membrane proteins were observed, which suggests that leucine functions as more than a nutrient. The interpretation may depend on investigators’ perspectives, therefore, discussion with relevant experts and the BCAA (Branched-Chain Amino Acids) society may be needed for effective utilization of this data. PMID:26244133

  5. Gene expression microarray analysis of the sciatic nerve of mice with diabetic neuropathy

    PubMed Central

    ZHANG, LEI; QU, SHEN; LIANG, AIBIN; JIANG, HONG; WANG, HAO

    2015-01-01

    The present study aimed to explore novel target genes that regulate the development of diabetic neuropathy (DN) by analyzing gene expression profiles in the sciatic nerve of infected mice. The GSE11343 microarray dataset, which was downloaded from Gene Expression Omnibus, included data on 4 control samples and 5 samples from mice with diabetes induced by streptozotocin (STZ), 5 samples from normal mice treated with rosiglitazone (Rosi) and 5 samples from mice with diabetes induced by STZ and treated with Rosi. Differentially expressed genes (DEGs) between the different groups were identified using the substitution augmentation modification redefinition (SAMR) model. The Gene Ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID). Regulatory and protein-protein interaction networks were searched using BioCarta and STRING, respectively. The protein structures of potential regulatory genes were predicted using the SYBYL program. Compared with the controls, 1,384 DEGs were identified in the mice with STZ-induced diabetes and 7 DEGs were identified in the mice treated with Rosi. There were 518 DEGs identified between the mice in the STZ + Rosi and STZ groups. We identified 45 GO items, and the calmodulin nerve phosphatase and chemokine signaling pathways were identified as the main pathways. Three genes [myristoylated alanine-rich protein kinase C substrate (Marcks), GLI pathogenesis-related 2 (Glipr2) and centrosomal protein 170 kDa (Cep170)] were found to be co-regulated by both STZ and Rosi, the protein structure of which was predicted and certain binding activity to Rosi was docked. Our study demonstrates that the Marcks, Glipr2 and Cep170 genes may be underlying drug targets in the treatment of DN. PMID:25435094