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Sample records for functional gene microarray

  1. Sediment denitrifier community composition and nirS gene expression investigated with functional gene microarrays

    DEFF Research Database (Denmark)

    Francis, C.A.; Jackson, G.A.; Ward, B.B.

    2008-01-01

    A functional gene microarray was used to investigate denitrifier community composition and nitrite reductase (nirS) gene expression in sediments along the estuarine gradient in Chesapeake Bay, USA. The nirS oligonucleotide probe set was designed to represent a sequence database containing 539...... Chesapeake Bay clones, as well as sequences from many other environments. Greatest nirS diversity was detected at the freshwater station at the head of the bay and least diversity at the higher salinity station near the mouth of the Bay. The most common OTUs from the sequence database were detected...... on the array with high signal strength in most samples. One of the most abundant OTUs, CB2-S-138, was identified as dominant at the mid-bay site by both microarray and quantitative PCR assays, but it comprised a much smaller fraction of the assemblage in the north and south bay samples. cDNA (transcribed from...

  2. Functional microarray analysis of nitrogen and carbon cycling genes across an Antarctic latitudinal transect.

    NARCIS (Netherlands)

    Yergeau, E.; Kang, S.; He, Z.; Zhou, J.; Kowalchuk, G.A.

    2007-01-01

    Soil-borne microbial communities were examined via a functional gene microarray approach across a southern polar latitudinal gradient to gain insight into the environmental factors steering soil N- and C-cycling in terrestrial Antarctic ecosystems. The abundance and diversity of functional gene

  3. Array2BIO: from microarray expression data to functional annotation of co-regulated genes

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    Rasley Amy

    2006-06-01

    Full Text Available Abstract Background There are several isolated tools for partial analysis of microarray expression data. To provide an integrative, easy-to-use and automated toolkit for the analysis of Affymetrix microarray expression data we have developed Array2BIO, an application that couples several analytical methods into a single web based utility. Results Array2BIO converts raw intensities into probe expression values, automatically maps those to genes, and subsequently identifies groups of co-expressed genes using two complementary approaches: (1 comparative analysis of signal versus control and (2 clustering analysis of gene expression across different conditions. The identified genes are assigned to functional categories based on Gene Ontology classification and KEGG protein interaction pathways. Array2BIO reliably handles low-expressor genes and provides a set of statistical methods for quantifying expression levels, including Benjamini-Hochberg and Bonferroni multiple testing corrections. An automated interface with the ECR Browser provides evolutionary conservation analysis for the identified gene loci while the interconnection with Crème allows prediction of gene regulatory elements that underlie observed expression patterns. Conclusion We have developed Array2BIO – a web based tool for rapid comprehensive analysis of Affymetrix microarray expression data, which also allows users to link expression data to Dcode.org comparative genomics tools and integrates a system for translating co-expression data into mechanisms of gene co-regulation. Array2BIO is publicly available at http://array2bio.dcode.org.

  4. Rough-fuzzy clustering for grouping functionally similar genes from microarray data.

    Science.gov (United States)

    Maji, Pradipta; Paul, Sushmita

    2013-01-01

    Gene expression data clustering is one of the important tasks of functional genomics as it provides a powerful tool for studying functional relationships of genes in a biological process. Identifying coexpressed groups of genes represents the basic challenge in gene clustering problem. In this regard, a gene clustering algorithm, termed as robust rough-fuzzy c-means, is proposed judiciously integrating the merits of rough sets and fuzzy sets. While the concept of lower and upper approximations of rough sets deals with uncertainty, vagueness, and incompleteness in cluster definition, the integration of probabilistic and possibilistic memberships of fuzzy sets enables efficient handling of overlapping partitions in noisy environment. The concept of possibilistic lower bound and probabilistic boundary of a cluster, introduced in robust rough-fuzzy c-means, enables efficient selection of gene clusters. An efficient method is proposed to select initial prototypes of different gene clusters, which enables the proposed c-means algorithm to converge to an optimum or near optimum solutions and helps to discover coexpressed gene clusters. The effectiveness of the algorithm, along with a comparison with other algorithms, is demonstrated both qualitatively and quantitatively on 14 yeast microarray data sets.

  5. Pineal function: impact of microarray analysis

    DEFF Research Database (Denmark)

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

    2009-01-01

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

  6. Application of a novel functional gene microarray to probe the functional ecology of ammonia oxidation in nitrifying activated sludge.

    Directory of Open Access Journals (Sweden)

    Michael D Short

    Full Text Available We report on the first study trialling a newly-developed, functional gene microarray (FGA for characterising bacterial and archaeal ammonia oxidisers in activated sludge. Mixed liquor (ML and media biofilm samples from a full-scale integrated fixed-film activated sludge (IFAS plant were analysed with the FGA to profile the diversity and relative abundance of ammonia-oxidising archaea and bacteria (AOA and AOB respectively. FGA analyses of AOA and AOB communities revealed ubiquitous distribution of AOA across all samples - an important finding for these newly-discovered and poorly characterised organisms. Results also revealed striking differences in the functional ecology of attached versus suspended communities within the IFAS reactor. Quantitative assessment of AOB and AOA functional gene abundance revealed a dominance of AOB in the ML and approximately equal distribution of AOA and AOB in the media-attached biofilm. Subsequent correlations of functional gene abundance data with key water quality parameters suggested an important functional role for media-attached AOB in particular for IFAS reactor nitrification performance and indicate possible functional redundancy in some IFAS ammonia oxidiser communities. Results from this investigation demonstrate the capacity of the FGA to resolve subtle ecological shifts in key microbial communities in nitrifying activated sludge and indicate its value as a tool for better understanding the linkages between the ecology and performance of these engineered systems.

  7. Facilitating functional annotation of chicken microarray data

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    Gresham Cathy R

    2009-10-01

    Full Text Available Abstract 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

  8. Prosecutor: parameter-free inference of gene function for prokaryotes using DNA microarray data, genomic context and multiple gene annotation sources

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    van Hijum Sacha AFT

    2008-10-01

    Full Text Available Abstract Background Despite a plethora of functional genomic efforts, the function of many genes in sequenced genomes remains unknown. The increasing amount of microarray data for many species allows employing the guilt-by-association principle to predict function on a large scale: genes exhibiting similar expression patterns are more likely to participate in shared biological processes. Results We developed Prosecutor, an application that enables researchers to rapidly infer gene function based on available gene expression data and functional annotations. Our parameter-free functional prediction method uses a sensitive algorithm to achieve a high association rate of linking genes with unknown function to annotated genes. Furthermore, Prosecutor utilizes additional biological information such as genomic context and known regulatory mechanisms that are specific for prokaryotes. We analyzed publicly available transcriptome data sets and used literature sources to validate putative functions suggested by Prosecutor. We supply the complete results of our analysis for 11 prokaryotic organisms on a dedicated website. Conclusion The Prosecutor software and supplementary datasets available at http://www.prosecutor.nl allow researchers working on any of the analyzed organisms to quickly identify the putative functions of their genes of interest. A de novo analysis allows new organisms to be studied.

  9. Novel approach to select genes from RMA normalized microarray data using functional hearing tests in aging mice

    Science.gov (United States)

    D'Souza, Mary; Zhu, Xiaoxia; Frisina, Robert D.

    2008-01-01

    Presbycusis – age-related hearing loss – is the number one communicative disorder and one of the top three chronic medical condition of our aged population. High-throughput technologies potentially can be used to identify differentially expressed genes that may be better diagnostic and therapeutic targets for sensory and neural disorders. Here we analyzed gene expression for a set of GABA receptors in the cochlea of aging CBA mice using the Affymetrix GeneChip MOE430A. Functional phenotypic hearing measures were made, including auditory brainstem response (ABR) thresholds and distortion-product otoacoustic emission (DPOAE) amplitudes (four age groups). Four specific criteria were used to assess gene expression changes from RMA normalized microarray data (40 replicates). Linear regression models were used to fit the neurophysiological hearing measurements to probe-set expression profiles. These data were first subjected to one-way ANOVA, and then linear regression was performed. In addition, the log signal ratio was converted to fold change, and selected gene expression changes were confirmed by relative real-time PCR. Major findings: expression of GABA-A receptor subunit α6 was upregulated with age and hearing loss, whereas subunit α1 was repressed. In addition, GABA-A receptor associated protein like-1 and GABA-A receptor associated protein like-2 were strongly downregulated with age and hearing impairment. Lastly, gene expression measures were correlated with pathway/network relationships relevant to the inner ear using Pathway Architect, to identify key pathways consistent with the gene expression changes observed. PMID:18455804

  10. Functional clustering and lineage markers: insights into cellular differentiation and gene function from large-scale microarray studies of purified primary cell populations.

    Science.gov (United States)

    Hume, David A; Summers, Kim M; Raza, Sobia; Baillie, J Kenneth; Freeman, Thomas C

    2010-06-01

    Very large microarray datasets showing gene expression across multiple tissues and cell populations provide a window on the transcriptional networks that underpin the differences in functional activity between biological systems. Clusters of co-expressed genes provide lineage markers, candidate regulators of cell function and, by applying the principle of guilt by association, candidate functions for genes of currently unknown function. We have analysed a dataset comprising pure cell populations from hemopoietic and non-hemopoietic cell types (http://biogps.gnf.org). Using a novel network visualisation and clustering approach, we demonstrate that it is possible to identify very tight expression signatures associated specifically with embryonic stem cells, mesenchymal cells and hematopoietic lineages. Selected examples validate the prediction that gene function can be inferred by co-expression. One expression cluster was enriched in phagocytes, which, alongside endosome-lysosome constituents, contains genes that may make up a 'pathway' for phagocyte differentiation. Promoters of these genes are enriched for binding sites for the ETS/PU.1 and MITF families. Another cluster was associated with the production of a specific extracellular matrix, with high levels of gene expression shared by cells of mesenchymal origin (fibroblasts, adipocytes, osteoblasts and myoblasts). We discuss the limitations placed upon such data by the presence of alternative promoters with distinct tissue specificity within many protein-coding genes. Copyright 2010 Elsevier Inc. All rights reserved.

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

    African Journals Online (AJOL)

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

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

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    Ile Kristina E

    2003-07-01

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

  13. Integrated olfactory receptor and microarray gene expression databases

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    Crasto Chiquito J

    2007-06-01

    Full Text Available Abstract Background Gene expression patterns of olfactory receptors (ORs are an important component of the signal encoding mechanism in the olfactory system since they determine the interactions between odorant ligands and sensory neurons. We have developed the Olfactory Receptor Microarray Database (ORMD to house OR gene expression data. ORMD is integrated with the Olfactory Receptor Database (ORDB, which is a key repository of OR gene information. Both databases aim to aid experimental research related to olfaction. Description ORMD is a Web-accessible database that provides a secure data repository for OR microarray experiments. It contains both publicly available and private data; accessing the latter requires authenticated login. The ORMD is designed to allow users to not only deposit gene expression data but also manage their projects/experiments. For example, contributors can choose whether to make their datasets public. For each experiment, users can download the raw data files and view and export the gene expression data. For each OR gene being probed in a microarray experiment, a hyperlink to that gene in ORDB provides access to genomic and proteomic information related to the corresponding olfactory receptor. Individual ORs archived in ORDB are also linked to ORMD, allowing users access to the related microarray gene expression data. Conclusion ORMD serves as a data repository and project management system. It facilitates the study of microarray experiments of gene expression in the olfactory system. In conjunction with ORDB, ORMD integrates gene expression data with the genomic and functional data of ORs, and is thus a useful resource for both olfactory researchers and the public.

  14. Identification of bovine leukemia virus tax function associated with host cell transcription, signaling, stress response and immune response pathway by microarray-based gene expression analysis

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    Arainga Mariluz

    2012-03-01

    Full Text Available Abstract Background Bovine leukemia virus (BLV is associated with enzootic bovine leukosis and is closely related to human T-cell leukemia virus type I. The Tax protein of BLV is a transcriptional activator of viral replication and a key contributor to oncogenic potential. We previously identified interesting mutant forms of Tax with elevated (TaxD247G or reduced (TaxS240P transactivation effects on BLV replication and propagation. However, the effects of these mutations on functions other than transcriptional activation are unknown. In this study, to identify genes that play a role in the cascade of signal events regulated by wild-type and mutant Tax proteins, we used a large-scale host cell gene-profiling approach. Results Using a microarray containing approximately 18,400 human mRNA transcripts, we found several alterations after the expression of Tax proteins in genes involved in many cellular functions such as transcription, signal transduction, cell growth, apoptosis, stress response, and immune response, indicating that Tax protein has multiple biological effects on various cellular environments. We also found that TaxD247G strongly regulated more genes involved in transcription, signal transduction, and cell growth functions, contrary to TaxS240P, which regulated fewer genes. In addition, the expression of genes related to stress response significantly increased in the presence of TaxS240P as compared to wild-type Tax and TaxD247G. By contrast, the largest group of downregulated genes was related to immune response, and the majority of these genes belonged to the interferon family. However, no significant difference in the expression level of downregulated genes was observed among the Tax proteins. Finally, the expression of important cellular factors obtained from the human microarray results were validated at the RNA and protein levels by real-time quantitative reverse transcription-polymerase chain reaction and western blotting

  15. Improving missing value estimation in microarray data with gene ontology.

    Science.gov (United States)

    Tuikkala, Johannes; Elo, Laura; Nevalainen, Olli S; Aittokallio, Tero

    2006-03-01

    Gene expression microarray experiments produce datasets with frequent missing expression values. Accurate estimation of missing values is an important prerequisite for efficient data analysis as many statistical and machine learning techniques either require a complete dataset or their results are significantly dependent on the quality of such estimates. A limitation of the existing estimation methods for microarray data is that they use no external information but the estimation is based solely on the expression data. We hypothesized that utilizing a priori information on functional similarities available from public databases facilitates the missing value estimation. We investigated whether semantic similarity originating from gene ontology (GO) annotations could improve the selection of relevant genes for missing value estimation. The relative contribution of each information source was automatically estimated from the data using an adaptive weight selection procedure. Our experimental results in yeast cDNA microarray datasets indicated that by considering GO information in the k-nearest neighbor algorithm we can enhance its performance considerably, especially when the number of experimental conditions is small and the percentage of missing values is high. The increase of performance was less evident with a more sophisticated estimation method. We conclude that even a small proportion of annotated genes can provide improvements in data quality significant for the eventual interpretation of the microarray experiments. Java and Matlab codes are available on request from the authors. Available online at http://users.utu.fi/jotatu/GOImpute.html.

  16. Classification across gene expression microarray studies

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    Kuner Ruprecht

    2009-12-01

    Full Text Available Abstract Background The increasing number of gene expression microarray studies represents an important resource in biomedical research. As a result, gene expression based diagnosis has entered clinical practice for patient stratification in breast cancer. However, the integration and combined analysis of microarray studies remains still a challenge. We assessed the potential benefit of data integration on the classification accuracy and systematically evaluated the generalization performance of selected methods on four breast cancer studies comprising almost 1000 independent samples. To this end, we introduced an evaluation framework which aims to establish good statistical practice and a graphical way to monitor differences. The classification goal was to correctly predict estrogen receptor status (negative/positive and histological grade (low/high of each tumor sample in an independent study which was not used for the training. For the classification we chose support vector machines (SVM, predictive analysis of microarrays (PAM, random forest (RF and k-top scoring pairs (kTSP. Guided by considerations relevant for classification across studies we developed a generalization of kTSP which we evaluated in addition. Our derived version (DV aims to improve the robustness of the intrinsic invariance of kTSP with respect to technologies and preprocessing. Results For each individual study the generalization error was benchmarked via complete cross-validation and was found to be similar for all classification methods. The misclassification rates were substantially higher in classification across studies, when each single study was used as an independent test set while all remaining studies were combined for the training of the classifier. However, with increasing number of independent microarray studies used in the training, the overall classification performance improved. DV performed better than the average and showed slightly less variance. In

  17. Microarray Assisted Gene Discovery in Ulcerative Colitis

    DEFF Research Database (Denmark)

    Brusgaard, Klaus

    ), and microarray based expression studies. In IBD the increased production of chemo attractants from the inflamed microenvironment results in recruitment of activated CD4+ T lymphocytes which results in tissue damage. Where Th1 cell-derived cytokines has been reported to be essential mediators in CD with high (IFN...... on the activation of different downstream pathways. Thus it seems that different genetic backgrounds can lead to similar clinical manifestations, and as well determines the susceptibility to IBD. In the previous micro array based expression studies on UC the main target has been to point to new candidate genes...... based on analysis of the main up or down regulated genes in the dataset. The majority of the studies are hampered by a relatively shortcoming of the numbers of genes analysed on the particular array. In this study the main target has been to point to clusters of genes involved in biochemical pathways...

  18. Development of a cell-defined siRNA microarray for analysis of gene function in human bone marrow stromal cells

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    Hi Chul Kim

    2016-03-01

    The efficiency of this CDSM was verified using three siRNAs (targeting p65, Slug, and N-cadherin, with persistent gene silencing for 5 days. We obtained the significant and reliable data with effective knock-down in our condition, and suggested our method as the qualitatively improved siRNA microarray screening method for hBMSCs.

  19. Washing scaling of GeneChip microarray expression

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    Krohn Knut

    2010-05-01

    Full Text Available Abstract Background Post-hybridization washing is an essential part of microarray experiments. Both the quality of the experimental washing protocol and adequate consideration of washing in intensity calibration ultimately affect the quality of the expression estimates extracted from the microarray intensities. Results We conducted experiments on GeneChip microarrays with altered protocols for washing, scanning and staining to study the probe-level intensity changes as a function of the number of washing cycles. For calibration and analysis of the intensity data we make use of the 'hook' method which allows intensity contributions due to non-specific and specific hybridization of perfect match (PM and mismatch (MM probes to be disentangled in a sequence specific manner. On average, washing according to the standard protocol removes about 90% of the non-specific background and about 30-50% and less than 10% of the specific targets from the MM and PM, respectively. Analysis of the washing kinetics shows that the signal-to-noise ratio doubles roughly every ten stringent washing cycles. Washing can be characterized by time-dependent rate constants which reflect the heterogeneous character of target binding to microarray probes. We propose an empirical washing function which estimates the survival of probe bound targets. It depends on the intensity contribution due to specific and non-specific hybridization per probe which can be estimated for each probe using existing methods. The washing function allows probe intensities to be calibrated for the effect of washing. On a relative scale, proper calibration for washing markedly increases expression measures, especially in the limit of small and large values. Conclusions Washing is among the factors which potentially distort expression measures. The proposed first-order correction method allows direct implementation in existing calibration algorithms for microarray data. We provide an experimental

  20. Microarray-based Detection of Antibiotic Resisteance Genes in Salmonella

    NARCIS (Netherlands)

    Hoek, van A.H.A.M.; Aarts, H.J.M.

    2008-01-01

    In the presented study, 143 Salmonella isolates belonging to 26 different serovars were screened for the presence of antibiotic resistance genes by microarray analysis. The microarray contained a total of 223 oligonucleotides representing genes encoding for resistance to the following antibiotic

  1. A Critical Perspective On Microarray Breast Cancer Gene Expression Profiling

    NARCIS (Netherlands)

    Sontrop, H.M.J.

    2015-01-01

    Microarrays offer biologists an exciting tool that allows the simultaneous assessment of gene expression levels for thousands of genes at once. At the time of their inception, microarrays were hailed as the new dawn in cancer biology and oncology practice with the hope that within a decade diseases

  2. Gene-Expression Profiles in Generalized Aggressive Periodontitis: A Gene Network-Based Microarray Analysis.

    Science.gov (United States)

    Guzeldemir-Akcakanat, Esra; Sunnetci-Akkoyunlu, Deniz; Orucguney, Begum; Cine, Naci; Kan, Bahadır; Yılmaz, Elif Büsra; Gümüşlü, Esen; Savli, Hakan

    2016-01-01

    In this study, molecular biomarkers that play a role in the development of generalized aggressive periodontitis (GAgP) are investigated using gingival tissue samples through omics-based whole-genome transcriptomics while using healthy individuals as background controls. Gingival tissue biopsies from 23 patients with GAgP and 25 healthy individuals were analyzed using gene-expression microarrays with network and pathway analyses to identify gene-expression patterns. To substantiate the results of the microarray studies, real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was performed to assess the messenger RNA (mRNA) expression of MZB1 and DSC1. The microarrays and qRT-PCR resulted in similar gene-expression changes, confirming the reliability of the microarray results at the mRNA level. As a result of the gene-expression microarray studies, four significant gene networks were identified. The most upregulated genes were found as MZB1, TNFRSF17, PNOC, FCRL5, LAX1, BMS1P20, IGLL5, MMP7, SPAG4, and MEI1; the most downregulated genes were found as LOR, LAMB4, AADACL2, MAPT, ARG1, NPR3, AADAC, DSC1, LRRC4, and CHP2. Functions of the identified genes that were involved in gene networks were cellular development, cell growth and proliferation, cellular movement, cell-cell signaling and interaction, humoral immune response, protein synthesis, cell death and survival, cell population and organization, organismal injury and abnormalities, molecular transport, and small-molecule biochemistry. The data suggest new networks that have important functions as humoral immune response and organismal injury/abnormalities. Future analyses may facilitate proteomic profiling analyses to identify gene-expression patterns related to clinical outcome.

  3. Gene Expression and Microarray Investigation of Dendrobium ...

    African Journals Online (AJOL)

    Result: Between the diabetic rat group and the wild-type group, 1339 functional genes showed differences in expression levels (p < 0.05). ... Genes whose expression normalized were mainly those affected by the disease state and associated with glucose and lipid metabolism, cell growth, apoptosis, biosynthesis, olfactory ...

  4. Antigen microarrays: descriptive chemistry or functional immunomics?

    Science.gov (United States)

    Prechl, József; Papp, Krisztián; Erdei, Anna

    2010-04-01

    Advances in protein microarray technology allow the generation of high content, reliable information about complex, multilevel protein interaction networks. Yet antigen arrays are used mostly only as devices for parallel immune assays describing multitudes of individual binding events. We propose here that the huge amount of immunological information hidden in the plasma of an individual could be better revealed by combining the characterization of antibody binding to target epitopes with improved estimation of effector functions triggered by these binding events. Furthermore, we could generate functional immune profiles characterizing general immune responsiveness of the individual by designing arrays incorporating epitope collections from diverse subsets of antibody targets. Copyright 2010 Elsevier Ltd. All rights reserved.

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

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    Gadea Jose

    2008-07-01

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

  6. Comparison of gene expression microarray data with count-based RNA measurements informs microarray interpretation.

    Science.gov (United States)

    Richard, Arianne C; Lyons, Paul A; Peters, James E; Biasci, Daniele; Flint, Shaun M; Lee, James C; McKinney, Eoin F; Siegel, Richard M; Smith, Kenneth G C

    2014-08-04

    Although numerous investigations have compared gene expression microarray platforms, preprocessing methods and batch correction algorithms using constructed spike-in or dilution datasets, there remains a paucity of studies examining the properties of microarray data using diverse biological samples. Most microarray experiments seek to identify subtle differences between samples with variable background noise, a scenario poorly represented by constructed datasets. Thus, microarray users lack important information regarding the complexities introduced in real-world experimental settings. The recent development of a multiplexed, digital technology for nucleic acid measurement enables counting of individual RNA molecules without amplification and, for the first time, permits such a study. Using a set of human leukocyte subset RNA samples, we compared previously acquired microarray expression values with RNA molecule counts determined by the nCounter Analysis System (NanoString Technologies) in selected genes. We found that gene measurements across samples correlated well between the two platforms, particularly for high-variance genes, while genes deemed unexpressed by the nCounter generally had both low expression and low variance on the microarray. Confirming previous findings from spike-in and dilution datasets, this "gold-standard" comparison demonstrated signal compression that varied dramatically by expression level and, to a lesser extent, by dataset. Most importantly, examination of three different cell types revealed that noise levels differed across tissues. Microarray measurements generally correlate with relative RNA molecule counts within optimal ranges but suffer from expression-dependent accuracy bias and precision that varies across datasets. We urge microarray users to consider expression-level effects in signal interpretation and to evaluate noise properties in each dataset independently.

  7. The monitoring of gene functions on a cell-defined siRNA microarray in human bone marrow stromal and U2OS cells

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    Hi Chul Kim

    2016-06-01

    Full Text Available Here, we developed a cell defined siRNA microarray (CDSM for human bone marrow stromal cells (hBMSCs designed to control the culture of cells inside the spot area without reducing the efficiency of siRNA silencing, “Development of a cell-defined siRNA microarray for analysis of gene functionin human bone marrow stromal cells” (Kim et al., 2016 [1]. First, we confirmed that p65 protein inhibition efficiency was maintained when hBMSCs were culture for 7 days on the siRNA spot, and siRNA spot activity remained in spite of long term storage (10 days and 2 months. Additionally, we confirmed p65 protein inhibition in U2OS cells after 48 h reverse transfection.

  8. Emerging use of gene expression microarrays in plant physiology.

    Science.gov (United States)

    Wullschleger, Stan D; Difazio, Stephen P

    2003-01-01

    Microarrays have become an important technology for the global analysis of gene expression in humans, animals, plants, and microbes. Implemented in the context of a well-designed experiment, cDNA and oligonucleotide arrays can provide highthroughput, simultaneous analysis of transcript abundance for hundreds, if not thousands, of genes. However, despite widespread acceptance, the use of microarrays as a tool to better understand processes of interest to the plant physiologist is still being explored. To help illustrate current uses of microarrays in the plant sciences, several case studies that we believe demonstrate the emerging application of gene expression arrays in plant physiology were selected from among the many posters and presentations at the 2003 Plant and Animal Genome XI Conference. Based on this survey, microarrays are being used to assess gene expression in plants exposed to the experimental manipulation of air temperature, soil water content and aluminium concentration in the root zone. Analysis often includes characterizing transcript profiles for multiple post-treatment sampling periods and categorizing genes with common patterns of response using hierarchical clustering techniques. In addition, microarrays are also providing insights into developmental changes in gene expression associated with fibre and root elongation in cotton and maize, respectively. Technical and analytical limitations of microarrays are discussed and projects attempting to advance areas of microarray design and data analysis are highlighted. Finally, although much work remains, we conclude that microarrays are a valuable tool for the plant physiologist interested in the characterization and identification of individual genes and gene families with potential application in the fields of agriculture, horticulture and forestry.

  9. Microarray analysis of gene expression during bacteriophage T4 infection.

    Science.gov (United States)

    Luke, Kimberly; Radek, Agnes; Liu, XiuPing; Campbell, John; Uzan, Marc; Haselkorn, Robert; Kogan, Yakov

    2002-08-01

    Genomic microarrays were used to examine the complex temporal program of gene expression exhibited by bacteriophage T4 during the course of development. The microarray data confirm the existence of distinct early, middle, and late transcriptional classes during the bacteriophage replicative cycle. This approach allows assignment of previously uncharacterized genes to specific temporal classes. The genomic expression data verify many promoter assignments and predict the existence of previously unidentified promoters.

  10. Functional profiling of microarray experiments using text-mining derived bioentities.

    Science.gov (United States)

    Minguez, Pablo; Al-Shahrour, Fátima; Montaner, David; Dopazo, Joaquín

    2007-11-15

    The increasing use of microarray technologies brought about a parallel demand in methods for the functional interpretation of the results. Beyond the conventional functional annotations for genes, such as gene ontology, pathways, etc. other sources of information are still to be exploited. Text-mining methods allow extracting informative terms (bioentities) with different functional, chemical, clinical, etc. meanings, that can be associated to genes. We show how to use these associations within an appropriate statistical framework and how to apply them through easy-to-use, web-based environments to the functional interpretation of microarray experiments. Functional enrichment and gene set enrichment tests using bioentities are presented.

  11. DNA microarray analysis of genes differentially expressed in ...

    Indian Academy of Sciences (India)

    These genes may play a major role in promoting excessive proliferation and accumulation of lipid droplets, which contribute to the development of obesity. By using microarray-based technology, we examined differential gene expression in early differentiated adipocytes and late differentiated adipocytes. Validated genes ...

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

    Science.gov (United States)

    Yang, Jianji; Cohen, Aaron; Hersh, William

    2009-02-05

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

  13. Gene Expression Analysis Using Agilent DNA Microarrays

    DEFF Research Database (Denmark)

    Stangegaard, Michael

    2009-01-01

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

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

    Science.gov (United States)

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

    2016-01-10

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

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

    Directory of Open Access Journals (Sweden)

    Bordoni Roberta

    2007-11-01

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

  16. Gene ordering in partitive clustering using microarray expressions

    Indian Academy of Sciences (India)

    PRAKASH KUMAR

    the new hybrid approach, finds comparable or sometimes superior biological gene order in less computation time than those obtained by optimal leaf ordering in hierarchical clustering solution. Ray S S, Bandyopadhyay S and Pal S K 2007 Gene ordering in partitive clustering using microarray expressions; J. Biosci.

  17. Microarray analysis of adipose tissue gene expression profiles ...

    Indian Academy of Sciences (India)

    Excessive accumulation of lipids in the adipose tissue is one of the main problems faced by the broiler industry nowadays. In order to visualize the mechanisms involved in the gene expression and regulation of lipid metabolism in adipose tissue, cDNA microarray containing 9 024 cDNA was used to construct gene ...

  18. Handling gene redundancy in microarray data using Grey Relational Analysis.

    Science.gov (United States)

    Zhang, Li-Juan; Li, Zhou-Jun; Chen, Huo-Wang

    2008-01-01

    Gene selection is one of the important and frequently used techniques for microarray data classification. In this paper, we introduce a new metric to measure gene-class relevance and gene-gene redundancy. The new metric is based on Grey Relational Analysis (GRA), called Grey Relational Grade (GRG), and never used in gene selection before. Based on the GRG, we develop a new gene selection method, which uses GRG to group similar genes to clusters, and then select informative genes from each cluster to avoid redundancy. Experiments on public data sets demonstrate the effectiveness of the proposed method.

  19. Sample size for detecting differentially expressed genes in microarray experiments

    Directory of Open Access Journals (Sweden)

    Li Jiangning

    2004-11-01

    Full Text Available Abstract Background Microarray experiments are often performed with a small number of biological replicates, resulting in low statistical power for detecting differentially expressed genes and concomitant high false positive rates. While increasing sample size can increase statistical power and decrease error rates, with too many samples, valuable resources are not used efficiently. The issue of how many replicates are required in a typical experimental system needs to be addressed. Of particular interest is the difference in required sample sizes for similar experiments in inbred vs. outbred populations (e.g. mouse and rat vs. human. Results We hypothesize that if all other factors (assay protocol, microarray platform, data pre-processing were equal, fewer individuals would be needed for the same statistical power using inbred animals as opposed to unrelated human subjects, as genetic effects on gene expression will be removed in the inbred populations. We apply the same normalization algorithm and estimate the variance of gene expression for a variety of cDNA data sets (humans, inbred mice and rats comparing two conditions. Using one sample, paired sample or two independent sample t-tests, we calculate the sample sizes required to detect a 1.5-, 2-, and 4-fold changes in expression level as a function of false positive rate, power and percentage of genes that have a standard deviation below a given percentile. Conclusions Factors that affect power and sample size calculations include variability of the population, the desired detectable differences, the power to detect the differences, and an acceptable error rate. In addition, experimental design, technical variability and data pre-processing play a role in the power of the statistical tests in microarrays. We show that the number of samples required for detecting a 2-fold change with 90% probability and a p-value of 0.01 in humans is much larger than the number of samples commonly used in

  20. Identification of Human Housekeeping Genes and Tissue-Selective Genes by Microarray Meta-Analysis

    Science.gov (United States)

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

    2011-01-01

    Background Categorizing protein-encoding transcriptomes of normal tissues into housekeeping genes and tissue-selective genes is a fundamental step toward studies of genetic functions and genetic associations to tissue-specific diseases. Previous studies have been mainly based on a few data sets with limited samples in each tissue, which restrained the representativeness of their identified genes, and resulted in low consensus among them. Results This study compiled 1,431 samples in 43 normal human tissues from 104 microarray data sets. We developed a new method to improve gene expression assessment, and showed that more than ten samples are needed to robustly identify the protein-encoding transcriptome of a tissue. We identified 2,064 housekeeping genes and 2,293 tissue-selective genes, and analyzed gene lists by functional enrichment analysis. The housekeeping genes are mainly involved in fundamental cellular functions, and the tissue-selective genes are strikingly related to functions and diseases corresponding to tissue-origin. We also compared agreements and related functions among our housekeeping genes and those of previous studies, and pointed out some reasons for the low consensuses. Conclusions The results indicate that sufficient samples have improved the identification of protein-encoding transcriptome of a tissue. Comprehensive meta-analysis has proved the high quality of our identified HK and TS genes. These results could offer a useful resource for future research on functional and genomic features of HK and TS genes. PMID:21818400

  1. Gene expression profiling in cluster headache: a pilot microarray study.

    Science.gov (United States)

    Sjöstrand, Christina; Duvefelt, Kristina; Steinberg, Anna; Remahl, Ingela Nilsson; Waldenlind, Elisabet; Hillert, Jan

    2006-01-01

    Cluster headache (CH) is a primary neurovascular headache disorder characterized by attacks of excruciating pain accompanied by ipsilateral autonomic symptoms. CH pathophysiology is presumed to involve an activation of hypothalamic and trigeminovascular systems, but inflammation and immunological mechanisms have also been hypothesized to be of importance. To identify differentially expressed genes during different clinical phases of CH, assuming that changes of pathophysiological importance would also be seen in peripheral venous blood. Blood samples were drawn at 3 consecutive occasions from 3 episodic CH patients: during attacks, between attacks and in remission, and at 1 occasion from 3 matched controls. Global gene expression was analyzed with microarray tehnology using the Affymetrix Human Genome U133 2.0 Plus GeneChip Set, covering more than 54,000 gene transcripts, corresponding to almost 22,000 genes. Quantitative RT-PCR on S100P gene expression was analyzed in 6 patients and 14 controls. Overall, quite small differences were seen intraindividually and large differences interindividually. However, pairwise comparisons of signal values showed upregulation of several S100 calcium binding proteins; S100A8 (calgranulin A), S100A12 (calgranulin C), and S100P during active phase of the disease compared to remission. Also, annexin A3 (calcium-binding) and ICAM3 showed upregulation. BIRC1 (neuronal apoptosis inhibitory protein), CREB5, HLA-DQA1, and HLA-DQB1 were upregulated in patients compared to controls. The upregulation of S100P during attack versus remission was confirmed by quantitative RT-PCR analysis. The S100A8 and S100A12 proteins are considered markers of non-infectious inflammatory disease, while the function of S100P is still largely unknown. Furthermore, upregulation of HLA-DQ genes in CH patients may also indicate an inflammatory response. Upregulation of these pro-inflammatory genes during the active phase of CH has not formerly been reported. Data

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

    Science.gov (United States)

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

    2012-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Vanderburg Charles R

    2009-01-01

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

  4. A Fisheye Viewer for microarray-based gene expression data.

    Science.gov (United States)

    Wu, Min; Thao, Cheng; Mu, Xiangming; Munson, Ethan V

    2006-10-13

    Microarray has been widely used to measure the relative amounts of every mRNA transcript from the genome in a single scan. Biologists have been accustomed to reading their experimental data directly from tables. However, microarray data are quite large and are stored in a series of files in a machine-readable format, so direct reading of the full data set is not feasible. The challenge is to design a user interface that allows biologists to usefully view large tables of raw microarray-based gene expression data. This paper presents one such interface--an electronic table (E-table) that uses fisheye distortion technology. The Fisheye Viewer for microarray-based gene expression data has been successfully developed to view MIAME data stored in the MAGE-ML format. The viewer can be downloaded from the project web site http://polaris.imt.uwm.edu:7777/fisheye/. The fisheye viewer was implemented in Java so that it could run on multiple platforms. We implemented the E-table by adapting JTable, a default table implementation in the Java Swing user interface library. Fisheye views use variable magnification to balance magnification for easy viewing and compression for maximizing the amount of data on the screen. This Fisheye Viewer is a lightweight but useful tool for biologists to quickly overview the raw microarray-based gene expression data in an E-table.

  5. A fisheye viewer for microarray-based gene expression data

    Directory of Open Access Journals (Sweden)

    Munson Ethan V

    2006-10-01

    Full Text Available Abstract Background Microarray has been widely used to measure the relative amounts of every mRNA transcript from the genome in a single scan. Biologists have been accustomed to reading their experimental data directly from tables. However, microarray data are quite large and are stored in a series of files in a machine-readable format, so direct reading of the full data set is not feasible. The challenge is to design a user interface that allows biologists to usefully view large tables of raw microarray-based gene expression data. This paper presents one such interface – an electronic table (E-table that uses fisheye distortion technology. Results The Fisheye Viewer for microarray-based gene expression data has been successfully developed to view MIAME data stored in the MAGE-ML format. The viewer can be downloaded from the project web site http://polaris.imt.uwm.edu:7777/fisheye/. The fisheye viewer was implemented in Java so that it could run on multiple platforms. We implemented the E-table by adapting JTable, a default table implementation in the Java Swing user interface library. Fisheye views use variable magnification to balance magnification for easy viewing and compression for maximizing the amount of data on the screen. Conclusion This Fisheye Viewer is a lightweight but useful tool for biologists to quickly overview the raw microarray-based gene expression data in an E-table.

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

    International Nuclear Information System (INIS)

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

    2003-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2003-07-01

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

  8. Evaluation of gene importance in microarray data based upon probability of selection

    Directory of Open Access Journals (Sweden)

    Fu Li M

    2005-03-01

    Full Text Available Abstract Background Microarray devices permit a genome-scale evaluation of gene function. This technology has catalyzed biomedical research and development in recent years. As many important diseases can be traced down to the gene level, a long-standing research problem is to identify specific gene expression patterns linking to metabolic characteristics that contribute to disease development and progression. The microarray approach offers an expedited solution to this problem. However, it has posed a challenging issue to recognize disease-related genes expression patterns embedded in the microarray data. In selecting a small set of biologically significant genes for classifier design, the nature of high data dimensionality inherent in this problem creates substantial amount of uncertainty. Results Here we present a model for probability analysis of selected genes in order to determine their importance. Our contribution is that we show how to derive the P value of each selected gene in multiple gene selection trials based on different combinations of data samples and how to conduct a reliability analysis accordingly. The importance of a gene is indicated by its associated P value in that a smaller value implies higher information content from information theory. On the microarray data concerning the subtype classification of small round blue cell tumors, we demonstrate that the method is capable of finding the smallest set of genes (19 genes with optimal classification performance, compared with results reported in the literature. Conclusion In classifier design based on microarray data, the probability value derived from gene selection based on multiple combinations of data samples enables an effective mechanism for reducing the tendency of fitting local data particularities.

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

    Directory of Open Access Journals (Sweden)

    Paula Fernandez

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

  10. Spotted cotton oligonucleotide microarrays for gene expression analysis

    Directory of Open Access Journals (Sweden)

    Nettleton Dan

    2007-03-01

    Full Text Available Abstract Background Microarrays offer a powerful tool for diverse applications plant biology and crop improvement. Recently, two comprehensive assemblies of cotton ESTs were constructed based on three Gossypium species. Using these assemblies as templates, we describe the design and creation and of a publicly available oligonucleotide array for cotton, useful for all four of the cultivated species. Results Synthetic oligonucleotide probes were generated from exemplar sequences of a global assembly of 211,397 cotton ESTs derived from >50 different cDNA libraries representing many different tissue types and tissue treatments. A total of 22,787 oligonucleotide probes are included on the arrays, optimized to target the diversity of the transcriptome and previously studied cotton genes, transcription factors, and genes with homology to Arabidopsis. A small portion of the oligonucleotides target unidentified protein coding sequences, thereby providing an element of gene discovery. Because many oligonucleotides were based on ESTs from fiber-specific cDNA libraries, the microarray has direct application for analysis of the fiber transcriptome. To illustrate the utility of the microarray, we hybridized labeled bud and leaf cDNAs from G. hirsutum and demonstrate technical consistency of results. Conclusion The cotton oligonucleotide microarray provides a reproducible platform for transcription profiling in cotton, and is made publicly available through http://cottonevolution.info.

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

    Science.gov (United States)

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

    2014-06-01

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

  12. Gene expression profiling by DNA microarrays and its application to dental research.

    Science.gov (United States)

    Kuo, Winston Patrick; Whipple, Mark E; Sonis, Stephen T; Ohno-Machado, Lucila; Jenssen, Tor-Kristian

    2002-10-01

    DNA microarray technology has been used for genome-wide gene expression studies that incorporate molecular genetics and computer science skills on massive levels. The technology permits the simultaneous analysis of tens of thousands of genes for the purposes of gene discovery, disease diagnosis. improved drug development, and therapeutics tailored to specific disease processes. In this review, the two most common microarray technologies and their potential application to dental research will be discussed. The authors review current articles pertaining to the technologies and analysis of mRNA expression using DNA micro-arrays and its application to dental research. Since many genes contribute to normal functioning, research efforts are moving from the search for a disease specific gene to the understanding of the biochemical and molecular functioning of a variety of genes and how complicated networks of interaction can lead to a disease state, such as oral cancer. With the incorporation of DNA micro-array based research, we can look forward to more accurate diagnosis and surgical treatment/drug-delivery therapy based on an individual patient's genetic profile.

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

    Directory of Open Access Journals (Sweden)

    Angel Chao

    2007-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Cohen Aaron

    2009-02-01

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

  15. Gene Expression and Microarray Investigation of Dendrobium ...

    African Journals Online (AJOL)

    diet. The rats were continuously fed for 16 months, and blood glucose monitored by a glucose meter. One wild-type rat and 4 high- fat/high-glucose rats died during ..... therapy not only changed gene expression patterns in type 2 diabetes but also improved immune activity and reduced the likelihood of cancer development.

  16. A gene expression microarray for Nicotiana benthamiana based on de novo transcriptome sequence assembly.

    Science.gov (United States)

    Goralski, Michal; Sobieszczanska, Paula; Obrepalska-Steplowska, Aleksandra; Swiercz, Aleksandra; Zmienko, Agnieszka; Figlerowicz, Marek

    2016-01-01

    microarray capabilities for studying gene expression in this plant. Additionally, by defining the sense orientation of over 106,000 contigs, we substantially improved the functional information on the N. benthamiana transcriptome. The simple hybridization-based approach for detecting the sense orientation of computationally assembled sequences can be used for updating the transcriptomes of other non-model organisms, including cases where no significant homology to known proteins exists.

  17. In search of functional association from time-series microarray data based on the change trend and level of gene expression

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    Zeng An-Ping

    2006-02-01

    Full Text Available Abstract Background The increasing availability of time-series expression data opens up new possibilities to study functional linkages of genes. Present methods used to infer functional linkages between genes from expression data are mainly based on a point-to-point comparison. Change trends between consecutive time points in time-series data have been so far not well explored. Results In this work we present a new method based on extracting main features of the change trend and level of gene expression between consecutive time points. The method, termed as trend correlation (TC, includes two major steps: 1, calculating a maximal local alignment of change trend score by dynamic programming and a change trend correlation coefficient between the maximal matched change levels of each gene pair; 2, inferring relationships of gene pairs based on two statistical extraction procedures. The new method considers time shifts and inverted relationships in a similar way as the local clustering (LC method but the latter is merely based on a point-to-point comparison. The TC method is demonstrated with data from yeast cell cycle and compared with the LC method and the widely used Pearson correlation coefficient (PCC based clustering method. The biological significance of the gene pairs is examined with several large-scale yeast databases. Although the TC method predicts an overall lower number of gene pairs than the other two methods at a same p-value threshold, the additional number of gene pairs inferred by the TC method is considerable: e.g. 20.5% compared with the LC method and 49.6% with the PCC method for a p-value threshold of 2.7E-3. Moreover, the percentage of the inferred gene pairs consistent with databases by our method is generally higher than the LC method and similar to the PCC method. A significant number of the gene pairs only inferred by the TC method are process-identity or function-similarity pairs or have well-documented biological

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

    Directory of Open Access Journals (Sweden)

    Dai Yilin

    2012-06-01

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

  19. Evaluation of artificial time series microarray data for dynamic gene regulatory network inference.

    Science.gov (United States)

    Xenitidis, P; Seimenis, I; Kakolyris, S; Adamopoulos, A

    2017-08-07

    High-throughput technology like microarrays is widely used in the inference of gene regulatory networks (GRNs). We focused on time series data since we are interested in the dynamics of GRNs and the identification of dynamic networks. We evaluated the amount of information that exists in artificial time series microarray data and the ability of an inference process to produce accurate models based on them. We used dynamic artificial gene regulatory networks in order to create artificial microarray data. Key features that characterize microarray data such as the time separation of directly triggered genes, the percentage of directly triggered genes and the triggering function type were altered in order to reveal the limits that are imposed by the nature of microarray data on the inference process. We examined the effect of various factors on the inference performance such as the network size, the presence of noise in microarray data, and the network sparseness. We used a system theory approach and examined the relationship between the pole placement of the inferred system and the inference performance. We examined the relationship between the inference performance in the time domain and the true system parameter identification. Simulation results indicated that time separation and the percentage of directly triggered genes are crucial factors. Also, network sparseness, the triggering function type and noise in input data affect the inference performance. When two factors were simultaneously varied, it was found that variation of one parameter significantly affects the dynamic response of the other. Crucial factors were also examined using a real GRN and acquired results confirmed simulation findings with artificial data. Different initial conditions were also used as an alternative triggering approach. Relevant results confirmed that the number of datasets constitutes the most significant parameter with regard to the inference performance. Copyright © 2017 Elsevier

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

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    Maija Wolf

    2005-01-01

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

  1. A novel parametric approach to mine gene regulatory relationship from microarray datasets

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    Zhu Yunping

    2010-12-01

    Full Text Available Abstract Background Microarray has been widely used to measure the gene expression level on the genome scale in the current decade. Many algorithms have been developed to reconstruct gene regulatory networks based on microarray data. Unfortunately, most of these models and algorithms focus on global properties of the expression of genes in regulatory networks. And few of them are able to offer intuitive parameters. We wonder whether some simple but basic characteristics of microarray datasets can be found to identify the potential gene regulatory relationship. Results Based on expression correlation, expression level variation and vectors derived from microarray expression levels, we first introduced several novel parameters to measure the characters of regulating gene pairs. Subsequently, we used the naïve Bayesian network to integrate these features as well as the functional co-annotation between transcription factors and their target genes. Then, based on the character of time-delay from the expression profile, we were able to predict the existence and direction of the regulatory relationship respectively. Conclusions Several novel parameters have been proposed and integrated to identify the regulatory relationship. This new model is proved to be of higher efficacy than that of individual features. It is believed that our parametric approach can serve as a fast approach for regulatory relationship mining.

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

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    Kolisis Fragiskos N

    2009-10-01

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

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

    Science.gov (United States)

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

    2009-10-27

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

  4. GenePublisher: automated analysis of DNA microarray data

    DEFF Research Database (Denmark)

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

    2003-01-01

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

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

    Science.gov (United States)

    Beyer, Sasha J; Zhang, Xiaoli; Jimenez, Rafael E; Lee, Mei-Ling T; Richardson, Andrea L; Huang, Kun; Jhiang, Sissy M

    2011-10-11

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

  6. Optimization models for cancer classification: extracting gene interaction information from microarray expression data.

    Science.gov (United States)

    Antonov, Alexey V; Tetko, Igor V; Mader, Michael T; Budczies, Jan; Mewes, Hans W

    2004-03-22

    Microarray data appear particularly useful to investigate mechanisms in cancer biology and represent one of the most powerful tools to uncover the genetic mechanisms causing loss of cell cycle control. Recently, several different methods to employ microarray data as a diagnostic tool in cancer classification have been proposed. These procedures take changes in the expression of particular genes into account but do not consider disruptions in certain gene interactions caused by the tumor. It is probable that some genes participating in tumor development do not change their expression level dramatically. Thus, they cannot be detected by simple classification approaches used previously. For these reasons, a classification procedure exploiting information related to changes in gene interactions is needed. We propose a MAximal MArgin Linear Programming (MAMA) method for the classification of tumor samples based on microarray data. This procedure detects groups of genes and constructs models (features) that strongly correlate with particular tumor types. The detected features include genes whose functional relations are changed for particular cancer types. The proposed method was tested on two publicly available datasets and demonstrated a prediction ability superior to previously employed classification schemes. The MAMA system was developed using the linear programming system LINDO http://www.lindo.com. A Perl script that specifies the optimization problem for this software is available upon request from the authors.

  7. Meta-analysis of gene expression microarrays with missing replicates

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    Leckie Christopher

    2011-03-01

    Full Text Available Abstract Background Many different microarray experiments are publicly available today. It is natural to ask whether different experiments for the same phenotypic conditions can be combined using meta-analysis, in order to increase the overall sample size. However, some genes are not measured in all experiments, hence they cannot be included or their statistical significance cannot be appropriately estimated in traditional meta-analysis. Nonetheless, these genes, which we refer to as incomplete genes, may also be informative and useful. Results We propose a meta-analysis framework, called "Incomplete Gene Meta-analysis", which can include incomplete genes by imputing the significance of missing replicates, and computing a meta-score for every gene across all datasets. We demonstrate that the incomplete genes are worthy of being included and our method is able to appropriately estimate their significance in two groups of experiments. We first apply the Incomplete Gene Meta-analysis and several comparable methods to five breast cancer datasets with an identical set of probes. We simulate incomplete genes by randomly removing a subset of probes from each dataset and demonstrate that our method consistently outperforms two other methods in terms of their false discovery rate. We also apply the methods to three gastric cancer datasets for the purpose of discriminating diffuse and intestinal subtypes. Conclusions Meta-analysis is an effective approach that identifies more robust sets of differentially expressed genes from multiple studies. The incomplete genes that mainly arise from the use of different platforms may also have statistical and biological importance but are ignored or are not appropriately involved by previous studies. Our Incomplete Gene Meta-analysis is able to incorporate the incomplete genes by estimating their significance. The results on both breast and gastric cancer datasets suggest that the highly ranked genes and associated GO

  8. Data Integration for Microarrays: Enhanced Inference for Gene Regulatory Networks

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    Alina Sîrbu

    2015-05-01

    Full Text Available Microarray technologies have been the basis of numerous important findings regarding gene expression in the few last decades. Studies have generated large amounts of data describing various processes, which, due to the existence of public databases, are widely available for further analysis. Given their lower cost and higher maturity compared to newer sequencing technologies, these data continue to be produced, even though data quality has been the subject of some debate. However, given the large volume of data generated, integration can help overcome some issues related, e.g., to noise or reduced time resolution, while providing additional insight on features not directly addressed by sequencing methods. Here, we present an integration test case based on public Drosophila melanogaster datasets (gene expression, binding site affinities, known interactions. Using an evolutionary computation framework, we show how integration can enhance the ability to recover transcriptional gene regulatory networks from these data, as well as indicating which data types are more important for quantitative and qualitative network inference. Our results show a clear improvement in performance when multiple datasets are integrated, indicating that microarray data will remain a valuable and viable resource for some time to come.

  9. Transcriptional regulatory network refinement and quantification through kinetic modeling, gene expression microarray data and information theory

    Science.gov (United States)

    Sayyed-Ahmad, Abdallah; Tuncay, Kagan; Ortoleva, Peter J

    2007-01-01

    Background Gene expression microarray and other multiplex data hold promise for addressing the challenges of cellular complexity, refined diagnoses and the discovery of well-targeted treatments. A new approach to the construction and quantification of transcriptional regulatory networks (TRNs) is presented that integrates gene expression microarray data and cell modeling through information theory. Given a partial TRN and time series data, a probability density is constructed that is a functional of the time course of transcription factor (TF) thermodynamic activities at the site of gene control, and is a function of mRNA degradation and transcription rate coefficients, and equilibrium constants for TF/gene binding. Results Our approach yields more physicochemical information that compliments the results of network structure delineation methods, and thereby can serve as an element of a comprehensive TRN discovery/quantification system. The most probable TF time courses and values of the aforementioned parameters are obtained by maximizing the probability obtained through entropy maximization. Observed time delays between mRNA expression and activity are accounted for implicitly since the time course of the activity of a TF is coupled by probability functional maximization, and is not assumed to be proportional to expression level of the mRNA type that translates into the TF. This allows one to investigate post-translational and TF activation mechanisms of gene regulation. Accuracy and robustness of the method are evaluated. A kinetic formulation is used to facilitate the analysis of phenomena with a strongly dynamical character while a physically-motivated regularization of the TF time course is found to overcome difficulties due to omnipresent noise and data sparsity that plague other methods of gene expression data analysis. An application to Escherichia coli is presented. Conclusion Multiplex time series data can be used for the construction of the network of

  10. GeneRank: Using search engine technology for the analysis of microarray experiments

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    Breitling Rainer

    2005-09-01

    Full Text Available Abstract Background Interpretation of simple microarray experiments is usually based on the fold-change of gene expression between a reference and a "treated" sample where the treatment can be of many types from drug exposure to genetic variation. Interpretation of the results usually combines lists of differentially expressed genes with previous knowledge about their biological function. Here we evaluate a method – based on the PageRank algorithm employed by the popular search engine Google – that tries to automate some of this procedure to generate prioritized gene lists by exploiting biological background information. Results GeneRank is an intuitive modification of PageRank that maintains many of its mathematical properties. It combines gene expression information with a network structure derived from gene annotations (gene ontologies or expression profile correlations. Using both simulated and real data we find that the algorithm offers an improved ranking of genes compared to pure expression change rankings. Conclusion Our modification of the PageRank algorithm provides an alternative method of evaluating microarray experimental results which combines prior knowledge about the underlying network. GeneRank offers an improvement compared to assessing the importance of a gene based on its experimentally observed fold-change alone and may be used as a basis for further analytical developments.

  11. GeneRank: using search engine technology for the analysis of microarray experiments.

    Science.gov (United States)

    Morrison, Julie L; Breitling, Rainer; Higham, Desmond J; Gilbert, David R

    2005-09-21

    Interpretation of simple microarray experiments is usually based on the fold-change of gene expression between a reference and a "treated" sample where the treatment can be of many types from drug exposure to genetic variation. Interpretation of the results usually combines lists of differentially expressed genes with previous knowledge about their biological function. Here we evaluate a method--based on the PageRank algorithm employed by the popular search engine Google--that tries to automate some of this procedure to generate prioritized gene lists by exploiting biological background information. GeneRank is an intuitive modification of PageRank that maintains many of its mathematical properties. It combines gene expression information with a network structure derived from gene annotations (gene ontologies) or expression profile correlations. Using both simulated and real data we find that the algorithm offers an improved ranking of genes compared to pure expression change rankings. Our modification of the PageRank algorithm provides an alternative method of evaluating microarray experimental results which combines prior knowledge about the underlying network. GeneRank offers an improvement compared to assessing the importance of a gene based on its experimentally observed fold-change alone and may be used as a basis for further analytical developments.

  12. Stability of gene contributions and identification of outliers in multivariate analysis of microarray data

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    Schumacher Martin M

    2008-06-01

    Full Text Available Abstract Background Multivariate ordination methods are powerful tools for the exploration of complex data structures present in microarray data. These methods have several advantages compared to common gene-by-gene approaches. However, due to their exploratory nature, multivariate ordination methods do not allow direct statistical testing of the stability of genes. Results In this study, we developed a computationally efficient algorithm for: i the assessment of the significance of gene contributions and ii the identification of sample outliers in multivariate analysis of microarray data. The approach is based on the use of resampling methods including bootstrapping and jackknifing. A statistical package of R functions was developed. This package includes tools for both inferring the statistical significance of gene contributions and identifying outliers among samples. Conclusion The methodology was successfully applied to three published data sets with varying levels of signal intensities. Its relevance was compared with alternative methods. Overall, it proved to be particularly effective for the evaluation of the stability of microarray data.

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

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    Peng Zhao

    2015-01-01

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

  14. A salmonid EST genomic study: genes, duplications, phylogeny and microarrays

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    Brahmbhatt Sonal

    2008-11-01

    Full Text Available Abstract Background Salmonids are of interest because of their relatively recent genome duplication, and their extensive use in wild fisheries and aquaculture. A comprehensive gene list and a comparison of genes in some of the different species provide valuable genomic information for one of the most widely studied groups of fish. Results 298,304 expressed sequence tags (ESTs from Atlantic salmon (69% of the total, 11,664 chinook, 10,813 sockeye, 10,051 brook trout, 10,975 grayling, 8,630 lake whitefish, and 3,624 northern pike ESTs were obtained in this study and have been deposited into the public databases. Contigs were built and putative full-length Atlantic salmon clones have been identified. A database containing ESTs, assemblies, consensus sequences, open reading frames, gene predictions and putative annotation is available. The overall similarity between Atlantic salmon ESTs and those of rainbow trout, chinook, sockeye, brook trout, grayling, lake whitefish, northern pike and rainbow smelt is 93.4, 94.2, 94.6, 94.4, 92.5, 91.7, 89.6, and 86.2% respectively. An analysis of 78 transcript sets show Salmo as a sister group to Oncorhynchus and Salvelinus within Salmoninae, and Thymallinae as a sister group to Salmoninae and Coregoninae within Salmonidae. Extensive gene duplication is consistent with a genome duplication in the common ancestor of salmonids. Using all of the available EST data, a new expanded salmonid cDNA microarray of 32,000 features was created. Cross-species hybridizations to this cDNA microarray indicate that this resource will be useful for studies of all 68 salmonid species. Conclusion An extensive collection and analysis of salmonid RNA putative transcripts indicate that Pacific salmon, Atlantic salmon and charr are 94–96% similar while the more distant whitefish, grayling, pike and smelt are 93, 92, 89 and 86% similar to salmon. The salmonid transcriptome reveals a complex history of gene duplication that is

  15. Reproducibility of gene expression across generations of Affymetrix microarrays

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    Haslett Judith N

    2003-06-01

    Full Text Available Abstract Background The development of large-scale gene expression profiling technologies is rapidly changing the norms of biological investigation. But the rapid pace of change itself presents challenges. Commercial microarrays are regularly modified to incorporate new genes and improved target sequences. Although the ability to compare datasets across generations is crucial for any long-term research project, to date no means to allow such comparisons have been developed. In this study the reproducibility of gene expression levels across two generations of Affymetrix GeneChips® (HuGeneFL and HG-U95A was measured. Results Correlation coefficients were computed for gene expression values across chip generations based on different measures of similarity. Comparing the absolute calls assigned to the individual probe sets across the generations found them to be largely unchanged. Conclusion We show that experimental replicates are highly reproducible, but that reproducibility across generations depends on the degree of similarity of the probe sets and the expression level of the corresponding transcript.

  16. A Gene Selection Method for Microarray Data Based on Binary PSO Encoding Gene-to-Class Sensitivity Information.

    Science.gov (United States)

    Han, Fei; Yang, Chun; Wu, Ya-Qi; Zhu, Jian-Sheng; Ling, Qing-Hua; Song, Yu-Qing; Huang, De-Shuang

    2017-01-01

    Traditional gene selection methods for microarray data mainly considered the features' relevance by evaluating their utility for achieving accurate predication or exploiting data variance and distribution, and the selected genes were usually poorly explicable. To improve the interpretability of the selected genes as well as prediction accuracy, an improved gene selection method based on binary particle swarm optimization (BPSO) and prior information is proposed in this paper. In the proposed method, BPSO encoding gene-to-class sensitivity (GCS) information is used to perform gene selection. The gene-to-class sensitivity information, extracted from the samples by extreme learning machine (ELM), is encoded into the selection process in four aspects: initializing particles, updating the particles, modifying maximum velocity, and adopting mutation operation adaptively. Constrained by the gene-to-class sensitivity information, the new method can select functional gene subsets which are significantly sensitive to the samples' classes. With the few discriminative genes selected by the proposed method, ELM, K-nearest neighbor and support vector machine classifiers achieve much high prediction accuracy on five public microarray data, which in turn verifies the efficiency and effectiveness of the proposed gene selection method.

  17. Common target genes of palatal and gingival fibroblasts for EMD: the microarray approach.

    Science.gov (United States)

    Gruber, R; Stähli, A; Miron, R J; Bosshardt, D D; Sculean, A

    2015-02-01

    Connective tissue grafts are frequently applied, together with Emdogain(®) , for root coverage. However, it is unknown whether fibroblasts from the gingiva and from the palate respond similarly to Emdogain. The aim of this study was therefore to evaluate the effect of Emdogain(®) on fibroblasts from palatal and gingival connective tissue using a genome-wide microarray approach. Human palatal and gingival fibroblasts were exposed to Emdogain(®) and RNA was subjected to microarray analysis followed by gene ontology screening with Database for Annotation, Visualization and Integrated Discovery functional annotation clustering, Kyoto Encyclopedia of Genes and Genomes pathway analysis and the Search Tool for the Retrieval of Interacting Genes/Proteins functional protein association network. Microarray results were confirmed by quantitative RT-PCR analysis. The transcription levels of 106 genes were up-/down-regulated by at least five-fold in both gingival and palatal fibroblasts upon exposure to Emdogain(®) . Gene ontology screening assigned the respective genes into 118 biological processes, six cellular components, eight molecular functions and five pathways. Among the striking patterns observed were the changing expression of ligands targeting the transforming growth factor-beta and gp130 receptor family as well as the transition of mesenchymal epithelial cells. Moreover, Emdogain(®) caused changes in expression of receptors for chemokines, lipids and hormones, and for transcription factors such as SMAD3, peroxisome proliferator-activated receptor gamma and those of the ETS family. The present data suggest that Emdogain(®) causes substantial alterations in gene expression, with similar patterns observed in palatal and gingival fibroblasts. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  18. Probabilistic estimation of microarray data reliability and underlying gene expression

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    Sigvardsson Mikael

    2003-09-01

    Full Text Available Abstract Background The availability of high throughput methods for measurement of mRNA concentrations makes the reliability of conclusions drawn from the data and global quality control of samples and hybridization important issues. We address these issues by an information theoretic approach, applied to discretized expression values in replicated gene expression data. Results Our approach yields a quantitative measure of two important parameter classes: First, the probability P(σ|S that a gene is in the biological state σ in a certain variety, given its observed expression S in the samples of that variety. Second, sample specific error probabilities which serve as consistency indicators of the measured samples of each variety. The method and its limitations are tested on gene expression data for developing murine B-cells and a t-test is used as reference. On a set of known genes it performs better than the t-test despite the crude discretization into only two expression levels. The consistency indicators, i.e. the error probabilities, correlate well with variations in the biological material and thus prove efficient. Conclusions The proposed method is effective in determining differential gene expression and sample reliability in replicated microarray data. Already at two discrete expression levels in each sample, it gives a good explanation of the data and is comparable to standard techniques.

  19. Application of four dyes in gene expression analyses by microarrays

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    van Schooten Frederik J

    2005-07-01

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

  20. An Efficient Ensemble Learning Method for Gene Microarray Classification

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    Alireza Osareh

    2013-01-01

    Full Text Available The gene microarray analysis and classification have demonstrated an effective way for the effective diagnosis of diseases and cancers. However, it has been also revealed that the basic classification techniques have intrinsic drawbacks in achieving accurate gene classification and cancer diagnosis. On the other hand, classifier ensembles have received increasing attention in various applications. Here, we address the gene classification issue using RotBoost ensemble methodology. This method is a combination of Rotation Forest and AdaBoost techniques which in turn preserve both desirable features of an ensemble architecture, that is, accuracy and diversity. To select a concise subset of informative genes, 5 different feature selection algorithms are considered. To assess the efficiency of the RotBoost, other nonensemble/ensemble techniques including Decision Trees, Support Vector Machines, Rotation Forest, AdaBoost, and Bagging are also deployed. Experimental results have revealed that the combination of the fast correlation-based feature selection method with ICA-based RotBoost ensemble is highly effective for gene classification. In fact, the proposed method can create ensemble classifiers which outperform not only the classifiers produced by the conventional machine learning but also the classifiers generated by two widely used conventional ensemble learning methods, that is, Bagging and AdaBoost.

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

    Science.gov (United States)

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

    2013-05-01

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

  2. Microarray Analysis of Differential Gene Expression Profile Between Human Fetal and Adult Heart.

    Science.gov (United States)

    Geng, Zhimin; Wang, Jue; Pan, Lulu; Li, Ming; Zhang, Jitai; Cai, Xueli; Chu, Maoping

    2017-04-01

    Although many changes have been discovered during heart maturation, the genetic mechanisms involved in the changes between immature and mature myocardium have only been partially elucidated. Here, gene expression profile changed between the human fetal and adult heart was characterized. A human microarray was applied to define the gene expression signatures of the fetal (13-17 weeks of gestation, n = 4) and adult hearts (30-40 years old, n = 4). Gene ontology analyses, pathway analyses, gene set enrichment analyses, and signal transduction network were performed to predict the function of the differentially expressed genes. Ten mRNAs were confirmed by quantificational real-time polymerase chain reaction. 5547 mRNAs were found to be significantly differentially expressed. "Cell cycle" was the most enriched pathway in the down-regulated genes. EFGR, IGF1R, and ITGB1 play a central role in the regulation of heart development. EGFR, IGF1R, and FGFR2 were the core genes regulating cardiac cell proliferation. The quantificational real-time polymerase chain reaction results were concordant with the microarray data. Our data identified the transcriptional regulation of heart development in the second trimester and the potential regulators that play a prominent role in the regulation of heart development and cardiac cells proliferation.

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

    Directory of Open Access Journals (Sweden)

    Richardson Andrea L

    2011-10-01

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

  4. Gene ordering in partitive clustering using microarray expressions

    Indian Academy of Sciences (India)

    PRAKASH KUMAR

    fibroblast data and showed that our approach improves the result quality of partitive clustering solution, by identifying subclusters within big clusters, grouping functionally correlated genes within clusters, minimization of summation of gene expression distances, and the maximization of biological gene ordering using MIPS ...

  5. The limit fold change model: A practical approach for selecting differentially expressed genes from microarray data

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    Rytz Andreas

    2002-06-01

    Full Text Available Abstract Background The biomedical community is developing new methods of data analysis to more efficiently process the massive data sets produced by microarray experiments. Systematic and global mathematical approaches that can be readily applied to a large number of experimental designs become fundamental to correctly handle the otherwise overwhelming data sets. Results The gene selection model presented herein is based on the observation that: (1 variance of gene expression is a function of absolute expression; (2 one can model this relationship in order to set an appropriate lower fold change limit of significance; and (3 this relationship defines a function that can be used to select differentially expressed genes. The model first evaluates fold change (FC across the entire range of absolute expression levels for any number of experimental conditions. Genes are systematically binned, and those genes within the top X% of highest FCs for each bin are evaluated both with and without the use of replicates. A function is fitted through the top X% of each bin, thereby defining a limit fold change. All genes selected by the 5% FC model lie above measurement variability using a within standard deviation (SDwithin confidence level of 99.9%. Real time-PCR (RT-PCR analysis demonstrated 85.7% concordance with microarray data selected by the limit function. Conclusion The FC model can confidently select differentially expressed genes as corroborated by variance data and RT-PCR. The simplicity of the overall process permits selecting model limits that best describe experimental data by extracting information on gene expression patterns across the range of expression levels. Genes selected by this process can be consistently compared between experiments and enables the user to globally extract information with a high degree of confidence.

  6. Investigating the effect of paralogs on microarray gene-set analysis

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    Seoighe Cathal

    2011-01-01

    Full Text Available Abstract Background In order to interpret the results obtained from a microarray experiment, researchers often shift focus from analysis of individual differentially expressed genes to analyses of sets of genes. These gene-set analysis (GSA methods use previously accumulated biological knowledge to group genes into sets and then aim to rank these gene sets in a way that reflects their relative importance in the experimental situation in question. We suspect that the presence of paralogs affects the ability of GSA methods to accurately identify the most important sets of genes for subsequent research. Results We show that paralogs, which typically have high sequence identity and similar molecular functions, also exhibit high correlation in their expression patterns. We investigate this correlation as a potential confounding factor common to current GSA methods using Indygene http://www.cbio.uct.ac.za/indygene, a web tool that reduces a supplied list of genes so that it includes no pairwise paralogy relationships above a specified sequence similarity threshold. We use the tool to reanalyse previously published microarray datasets and determine the potential utility of accounting for the presence of paralogs. Conclusions The Indygene tool efficiently removes paralogy relationships from a given dataset and we found that such a reduction, performed prior to GSA, has the ability to generate significantly different results that often represent novel and plausible biological hypotheses. This was demonstrated for three different GSA approaches when applied to the reanalysis of previously published microarray datasets and suggests that the redundancy and non-independence of paralogs is an important consideration when dealing with GSA methodologies.

  7. Investigating the effect of paralogs on microarray gene-set analysis

    LENUS (Irish Health Repository)

    Faure, Andre J

    2011-01-24

    Abstract Background In order to interpret the results obtained from a microarray experiment, researchers often shift focus from analysis of individual differentially expressed genes to analyses of sets of genes. These gene-set analysis (GSA) methods use previously accumulated biological knowledge to group genes into sets and then aim to rank these gene sets in a way that reflects their relative importance in the experimental situation in question. We suspect that the presence of paralogs affects the ability of GSA methods to accurately identify the most important sets of genes for subsequent research. Results We show that paralogs, which typically have high sequence identity and similar molecular functions, also exhibit high correlation in their expression patterns. We investigate this correlation as a potential confounding factor common to current GSA methods using Indygene http:\\/\\/www.cbio.uct.ac.za\\/indygene, a web tool that reduces a supplied list of genes so that it includes no pairwise paralogy relationships above a specified sequence similarity threshold. We use the tool to reanalyse previously published microarray datasets and determine the potential utility of accounting for the presence of paralogs. Conclusions The Indygene tool efficiently removes paralogy relationships from a given dataset and we found that such a reduction, performed prior to GSA, has the ability to generate significantly different results that often represent novel and plausible biological hypotheses. This was demonstrated for three different GSA approaches when applied to the reanalysis of previously published microarray datasets and suggests that the redundancy and non-independence of paralogs is an important consideration when dealing with GSA methodologies.

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

    Directory of Open Access Journals (Sweden)

    Gravelat Fabrice

    2010-09-01

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

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

    Science.gov (United States)

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

    2013-01-01

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

  10. Computational analysis of microarray gene expression profiles of lung cancer

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    Babichev S. A.

    2016-02-01

    Full Text Available Aim. The article presents the researches on the optimization of the DNA microarray data processing, which is aimed at improving the quality of object clustering. Methods. Data preprocessing was performed with program R using Bioconductor package. Modelling the clustering process was made in the software environment KNIME using the program WEKA functions. Results. The data preprocessing is shown to be optimal while using such techniques as the background correction rma method, quantile normalization, mas PM correction and summarization by mas method. The simulation results have demonstrated a high effectiveness of the clustering algorithm Sota for this category of data. Conclusion. The results of the research have shown that improving the quality of biological object clustering is possible by means of hybridization and optimization of the methods and algorithms at different stages of data processing.

  11. Microarray analysis reveals key genes and pathways in Tetralogy of Fallot

    Science.gov (United States)

    He, Yue-E; Qiu, Hui-Xian; Jiang, Jian-Bing; Wu, Rong-Zhou; Xiang, Ru-Lian; Zhang, Yuan-Hai

    2017-01-01

    The aim of the present study was to identify key genes that may be involved in the pathogenesis of Tetralogy of Fallot (TOF) using bioinformatics methods. The GSE26125 microarray dataset, which includes cardiovascular tissue samples derived from 16 children with TOF and five healthy age-matched control infants, was downloaded from the Gene Expression Omnibus database. Differential expression analysis was performed between TOF and control samples to identify differentially expressed genes (DEGs) using Student's t-test, and the R/limma package, with a log2 fold-change of >2 and a false discovery rate of <0.01 set as thresholds. The biological functions of DEGs were analyzed using the ToppGene database. The ReactomeFIViz application was used to construct functional interaction (FI) networks, and the genes in each module were subjected to pathway enrichment analysis. The iRegulon plugin was used to identify transcription factors predicted to regulate the DEGs in the FI network, and the gene-transcription factor pairs were then visualized using Cytoscape software. A total of 878 DEGs were identified, including 848 upregulated genes and 30 downregulated genes. The gene FI network contained seven function modules, which were all comprised of upregulated genes. Genes enriched in Module 1 were enriched in the following three neurological disorder-associated signaling pathways: Parkinson's disease, Alzheimer's disease and Huntington's disease. Genes in Modules 0, 3 and 5 were dominantly enriched in pathways associated with ribosomes and protein translation. The Xbox binding protein 1 transcription factor was demonstrated to be involved in the regulation of genes encoding the subunits of cytoplasmic and mitochondrial ribosomes, as well as genes involved in neurodegenerative disorders. Therefore, dysfunction of genes involved in signaling pathways associated with neurodegenerative disorders, ribosome function and protein translation may contribute to the pathogenesis of TOF

  12. Gene expression profile analysis of genes in rat hippocampus from antidepressant treated rats using DNA microarray

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    Shin Minkyu

    2010-11-01

    Full Text Available Abstract Background The molecular and biological mechanisms by which many antidepressants function are based on the monoamine depletion hypothesis. However, the entire cascade of mechanisms responsible for the therapeutic effect of antidepressants has not yet been elucidated. Results We used a genome-wide microarray system containing 30,000 clones to evaluate total RNA that had been isolated from the brains of treated rats to identify the genes involved in the therapeutic mechanisms of various antidepressants, a tricyclic antidepressant (imipramine. a selective serotonin reuptake inhibitor (fluoxetine, a monoamine oxidase inhibitor (phenelzine and psychoactive herbal extracts of Nelumbinis Semen (NS. To confirm the differential expression of the identified genes, we analyzed the amount of mRNA that was isolated from the hippocampus of rats that had been treated with antidepressants by real-time RT-PCR using primers specific for selected genes of interest. These data demonstrate that antidepressants interfere with the expression of a large array of genes involved in signaling, survival and protein metabolism, suggesting that the therapeutic effect of these antidepressants is very complex. Surprisingly, unlike other antidepressants, we found that the standardized herbal medicine, Nelumbinis Semen, is free of factors that can induce neurodegenerative diseases such as caspase 8, α-synuclein, and amyloid precursor protein. In addition, the production of the inflammatory cytokine, IFNγ, was significantly decreased in rat hippocampus in response to treatment with antidepressants, while the inhibitory cytokine, TGFβ, was significantly enhanced. Conclusions These results suggest that antidepressants function by regulating neurotransmission as well as suppressing immunoreactivity in the central nervous system.

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

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    Sadhukhan Provash

    2004-06-01

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

  14. Gene expression risk signatures maintain prognostic power in multiple myeloma despite microarray probe set translation

    DEFF Research Database (Denmark)

    Hermansen, N E U; Borup, R; Andersen, M K

    2016-01-01

    INTRODUCTION: Gene expression profiling (GEP) risk models in multiple myeloma are based on 3'-end microarrays. We hypothesized that GEP risk signatures could retain prognostic power despite being translated and applied to whole-transcript microarray data. METHODS: We studied CD138-positive bone...... signatures maintain significant prognostic power in HDT myeloma patients. We suggest probe set matching for GEP risk signature translation as part of the efforts towards a microarray-independent GEP risk standard. (ClicinalTrials.gov identifier: NCT00639054)....

  15. Gene expression profiling of HCV genotype 3a initial liver fibrosis and cirrhosis patients using microarray

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    Ahmad Waqar

    2012-03-01

    Full Text Available Abstract Background Hepatitis C virus (HCV causes liver fibrosis that may lead to liver cirrhosis or hepatocellular carcinoma (HCC, and may partially depend on infecting viral genotype. HCV genotype 3a is being more common in Asian population, especially Pakistan; the detail mechanism of infection still needs to be explored. In this study, we investigated and compared the gene expression profile between initial fibrosis stage and cirrhotic 3a genotype patients. Methods Gene expression profiling of human liver tissues was performed containing more than 22000 known genes. Using Oparray protocol, preparation and hybridization of slides was carried out and followed by scanning with GeneTAC integrator 4.0 software. Normalization of the data was obtained using MIDAS software and Significant Microarray Analysis (SAM was performed to obtain differentially expressed candidate genes. Results Out of 22000 genes studied, 219 differentially regulated genes found with P ≤ 0.05 between both groups; 107 among those were up-regulated and 112 were down-regulated. These genes were classified into 31 categories according to their biological functions. The main categories included: apoptosis, immune response, cell signaling, kinase activity, lipid metabolism, protein metabolism, protein modulation, metabolism, vision, cell structure, cytoskeleton, nervous system, protein metabolism, protein modulation, signal transduction, transcriptional regulation and transport activity. Conclusion This is the first study on gene expression profiling in patients associated with genotype 3a using microarray analysis. These findings represent a broad portrait of genomic changes in early HCV associated fibrosis and cirrhosis. We hope that identified genes in this study will help in future to act as prognostic and diagnostic markers to differentiate fibrotic patients from cirrhotic ones.

  16. Microarray Analysis on Gene Regulation by Estrogen, Progesterone and Tamoxifen in Human Endometrial Stromal Cells

    Science.gov (United States)

    Ren, Chun-E; Zhu, Xueqiong; Li, Jinping; Lyle, Christian; Dowdy, Sean; Podratz, Karl C.; Byck, David; Chen, Hai-Bin; Jiang, Shi-Wen

    2015-01-01

    Epithelial stromal cells represent a major cellular component of human uterine endometrium that is subject to tight hormonal regulation. Through cell-cell contacts and/or paracrine mechanisms, stromal cells play a significant role in the malignant transformation of epithelial cells. We isolated stromal cells from normal human endometrium and investigated the morphological and transcriptional changes induced by estrogen, progesterone and tamoxifen. We demonstrated that stromal cells express appreciable levels of estrogen and progesterone receptors and undergo different morphological changes upon hormonal stimulation. Microarray analysis indicated that both estrogen and progesterone induced dramatic alterations in a variety of genes associated with cell structure, transcription, cell cycle, and signaling. However, divergent patterns of changes, and in some genes opposite effects, were observed for the two hormones. A large number of genes are identified as novel targets for hormonal regulation. These hormone-responsive genes may be involved in normal uterine function and the development of endometrial malignancies. PMID:25782154

  17. Microarray Analysis on Gene Regulation by Estrogen, Progesterone and Tamoxifen in Human Endometrial Stromal Cells

    Directory of Open Access Journals (Sweden)

    Chun-E Ren

    2015-03-01

    Full Text Available Epithelial stromal cells represent a major cellular component of human uterine endometrium that is subject to tight hormonal regulation. Through cell-cell contacts and/or paracrine mechanisms, stromal cells play a significant role in the malignant transformation of epithelial cells. We isolated stromal cells from normal human endometrium and investigated the morphological and transcriptional changes induced by estrogen, progesterone and tamoxifen. We demonstrated that stromal cells express appreciable levels of estrogen and progesterone receptors and undergo different morphological changes upon hormonal stimulation. Microarray analysis indicated that both estrogen and progesterone induced dramatic alterations in a variety of genes associated with cell structure, transcription, cell cycle, and signaling. However, divergent patterns of changes, and in some genes opposite effects, were observed for the two hormones. A large number of genes are identified as novel targets for hormonal regulation. These hormone-responsive genes may be involved in normal uterine function and the development of endometrial malignancies.

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

    Energy Technology Data Exchange (ETDEWEB)

    William Grundy; Manuel Ares, Jr.; David Haussler

    2001-06-18

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

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

    Science.gov (United States)

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

    2015-01-01

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

  20. Gene selection for microarray data classification via subspace learning and manifold regularization.

    Science.gov (United States)

    Tang, Chang; Cao, Lijuan; Zheng, Xiao; Wang, Minhui

    2017-12-19

    With the rapid development of DNA microarray technology, large amount of genomic data has been generated. Classification of these microarray data is a challenge task since gene expression data are often with thousands of genes but a small number of samples. In this paper, an effective gene selection method is proposed to select the best subset of genes for microarray data with the irrelevant and redundant genes removed. Compared with original data, the selected gene subset can benefit the classification task. We formulate the gene selection task as a manifold regularized subspace learning problem. In detail, a projection matrix is used to project the original high dimensional microarray data into a lower dimensional subspace, with the constraint that the original genes can be well represented by the selected genes. Meanwhile, the local manifold structure of original data is preserved by a Laplacian graph regularization term on the low-dimensional data space. The projection matrix can serve as an importance indicator of different genes. An iterative update algorithm is developed for solving the problem. Experimental results on six publicly available microarray datasets and one clinical dataset demonstrate that the proposed method performs better when compared with other state-of-the-art methods in terms of microarray data classification. Graphical Abstract The graphical abstract of this work.

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

    Science.gov (United States)

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

    2015-01-01

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

  2. Gene Expression Browser: Large-Scale and Cross-Experiment Microarray Data Management, Search & Visualization

    Science.gov (United States)

    The amount of microarray gene expression data in public repositories has been increasing exponentially for the last couple of decades. High-throughput microarray data integration and analysis has become a critical step in exploring the large amount of expression data for biological discovery. Howeve...

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

    Directory of Open Access Journals (Sweden)

    Eils Roland

    2005-11-01

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

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

    Directory of Open Access Journals (Sweden)

    Nalin C W Goonesekere

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

  5. Microarray analysis identifies a common set of cellular genes modulated by different HCV replicon clones

    Directory of Open Access Journals (Sweden)

    Gerosolimo Germano

    2008-06-01

    Full Text Available Abstract Background Hepatitis C virus (HCV RNA synthesis and protein expression affect cell homeostasis by modulation of gene expression. The impact of HCV replication on global cell transcription has not been fully evaluated. Thus, we analysed the expression profiles of different clones of human hepatoma-derived Huh-7 cells carrying a self-replicating HCV RNA which express all viral proteins (HCV replicon system. Results First, we compared the expression profile of HCV replicon clone 21-5 with both the Huh-7 parental cells and the 21-5 cured (21-5c cells. In these latter, the HCV RNA has been eliminated by IFN-α treatment. To confirm data, we also analyzed microarray results from both the 21-5 and two other HCV replicon clones, 22-6 and 21-7, compared to the Huh-7 cells. The study was carried out by using the Applied Biosystems (AB Human Genome Survey Microarray v1.0 which provides 31,700 probes that correspond to 27,868 human genes. Microarray analysis revealed a specific transcriptional program induced by HCV in replicon cells respect to both IFN-α-cured and Huh-7 cells. From the original datasets of differentially expressed genes, we selected by Venn diagrams a final list of 38 genes modulated by HCV in all clones. Most of the 38 genes have never been described before and showed high fold-change associated with significant p-value, strongly supporting data reliability. Classification of the 38 genes by Panther System identified functional categories that were significantly enriched in this gene set, such as histones and ribosomal proteins as well as extracellular matrix and intracellular protein traffic. The dataset also included new genes involved in lipid metabolism, extracellular matrix and cytoskeletal network, which may be critical for HCV replication and pathogenesis. Conclusion Our data provide a comprehensive analysis of alterations in gene expression induced by HCV replication and reveal modulation of new genes potentially useful

  6. Observation of intermittency in gene expression on cDNA microarrays

    CERN Document Server

    Peterson, L E

    2002-01-01

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

  7. Application of Gene Shaving and Mixture Models to Cluster Microarray Gene Expression Data

    Directory of Open Access Journals (Sweden)

    S. Wen

    2007-01-01

    Full Text Available Researchers are frequently faced with the analysis of microarray data of a relatively large number of genes using a small number of tissue samples. We examine the application of two statistical methods for clustering such microarray expression data: EMMIX-GENE and GeneClust. EMMIX-GENE is a mixture-model based clustering approach, designed primarily to cluster tissue samples on the basis of the genes. GeneClust is an implementation of the gene shaving methodology, motivated by research to identify distinct sets of genes for which variation in expression could be related to a biological property of the tissue samples. We illustrate the use of these two methods in the analysis of Affymetrix oligonucleotide arrays of well-known data sets from colon tissue samples with and without tumors, and of tumor tissue samples from patients with leukemia. Although the two approaches have been developed from different perspectives, the results demonstrate a clear correspondence between gene clusters produced by GeneClust and EMMIX-GENE for the colon tissue data. It is demonstrated, for the case of ribosomal proteins and smooth muscle genes in the colon data set, that both methods can classify genes into co-regulated families. It is further demonstrated that tissue types (tumor and normal can be separated on the basis of subtle distributed patterns of genes. Application to the leukemia tissue data produces a division of tissues corresponding closely to the external classification, acute myeloid leukemia (AML and acute lymphoblastic leukaemia (ALL, for both methods. In addition, we also identify genes specifi c for the subgroup of ALL-T cell samples. Overall, we find that the gene shaving method produces gene clusters at great speed; allows variable cluster sizes and can incorporate partial or full supervision; and finds clusters of genes in which the gene expression varies greatly over the tissue samples while maintaining a high level of coherence between the

  8. Microarray analysis of gene expression on herbal glycoside recipes improving deficient ability of spatial learning memory in ischemic mice.

    Science.gov (United States)

    Wang, Zhong; Du, Qingyou; Wang, Fusheng; Liu, Zhongrong; Li, Baigang; Wang, Anmin; Wang, Yongyan

    2004-03-01

    In order to reveal the mechanism of herbal glycoside recipes retrieving deficient ability of spatial learning memory in mice suffering from cerebral ischemia/reperfusion, a microarray system was used to analyze gene expression in those groups with increasing ability of spatial learning memory who were different from ischemic mice. In this work, we reported a comprehensive characterization of gene expression profiles of mouse hippocampus by the use of cDNA microarray system containing 1176 known genes in middle cerebral artery occlusion (MCAO) ischemic mice after treating with different dosage recipes of glycoside herbs (30, 90, and 270 mg/kg). The ability of spatial learning memory in ischemic mice was found to be decreased. The pathological process in ischemic mouse brain showed that a complex related to 100 genes' expression yielded 1.8-fold. Dose-dependent effects showed an improvement in the deficient ability and reduction in infarct volume when treated with glycoside recipes. Many genes (38-46) in expression were found greater than 1.8-fold in those effective recipes groups, including genes in cell cycle regulation, signal transduction, nerve system transcription factors, DNA binding protein, etc. Nine genes related to retrieving deficient ability of spatial learning memory treated with glycoside recipes were also found in this study. These results suggest that microarray analysis of gene expression might be useful for elucidating the mechanisms of pharmacological function of recipes.

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

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    Yu-Juan Xiang

    2015-06-01

    Full Text Available Objective: The aim of this study was to reveal the exact changes during the occurrence of breast cancer to explore significant new and promising genes or factors related to this disease. Methods: We compared the gene expression profiles of breast cancer tissues with its uninvolved normal breast tissues as controls using the cDNA microarray analysis in seven breast cancer patients. Further, one representative gene, named IFI30, was quantitatively analyzed by real-time PCR to confirm the result of the cDNA microarray analysis. Results: A total of 427 genes were identified with significantly differential expression, 221 genes were up-regulated and 206 genes were down-regulated. And the result of cDNA microarray analysis was validated by detection of IFI30 mRNA level changes by real-time PCR. Genes for cell proliferation, cell cycle, cell division, mitosis, apoptosis, and immune response were enriched in the up-regulated genes, while genes for cell adhesion, proteolysis, and transport were significantly enriched in the down-regulated genes in breast cancer tissues compared with normal breast tissues by a gene ontology analysis. Conclusion: Our present study revealed a range of differentially expressed genes between breast cancer tissues and normal breast tissues, and provide candidate genes for further study focusing on the pathogenesis and new biomarkers for breast cancer. Keywords: Breast neoplasms, Candidate genes, Microarray

  10. mRNA expression in rabbit experimental aneurysms: a study using gene chip microarrays.

    Science.gov (United States)

    Mangrum, W I; Farassati, F; Kadirvel, R; Kolbert, C P; Raghavakaimal, S; Dai, D; Ding, Y H; Grill, D; Khurana, V G; Kallmes, D F

    2007-05-01

    The molecular characteristics of intracranial aneurysms are still poorly documented. A rabbit elastase aneurysm model has been helpful in the evaluation of devices and strategies involved in endovascular treatment of aneurysms. The goal of this project was to document the molecular changes, assessed by gene chip microarrays, associated with the creation of aneurysms in this model compared with the contralateral carotid artery. A microarray of rabbit genes of interest was constructed using rabbit nucleotide sequences from GenBank. Elastase-induced saccular aneurysms were created at the origin of the right common carotid artery in 4 rabbits. Twelve weeks after aneurysm creation, RNA was isolated from the aneurysm as well as the contralateral common carotid artery and used for microarray experiments. Reverse transcription-polymerase chain reaction (RT-PCR) was performed on 1 animal as a confirmatory test. Ninety-six (46%) of 209 genes in the microarray were differentially expressed in the rabbit aneurysm compared with the contralateral common carotid artery. In general, differential gene expression followed specific molecular pathways. Similarities were found between rabbit aneurysms and human intracranial aneurysms, including increased metalloproteinase activity and decreased production of the extracellular matrix. RT-PCR results confirmed the differential expression found by the gene chip microarray. The molecular characteristics of the rabbit elastase-induced saccular aneurysm are described. The rabbit aneurysm model shares some molecular features with human intracranial aneurysms. Future studies can use the rabbit model and the new rabbit gene chip microarray to study the molecular aspects of saccular aneurysms.

  11. Feature selection and classification of MAQC-II breast cancer and multiple myeloma microarray gene expression data.

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    Qingzhong Liu

    Full Text Available Microarray data has a high dimension of variables but available datasets usually have only a small number of samples, thereby making the study of such datasets interesting and challenging. In the task of analyzing microarray data for the purpose of, e.g., predicting gene-disease association, feature selection is very important because it provides a way to handle the high dimensionality by exploiting information redundancy induced by associations among genetic markers. Judicious feature selection in microarray data analysis can result in significant reduction of cost while maintaining or improving the classification or prediction accuracy of learning machines that are employed to sort out the datasets. In this paper, we propose a gene selection method called Recursive Feature Addition (RFA, which combines supervised learning and statistical similarity measures. We compare our method with the following gene selection methods: Support Vector Machine Recursive Feature Elimination (SVMRFE, Leave-One-Out Calculation Sequential Forward Selection (LOOCSFS, Gradient based Leave-one-out Gene Selection (GLGS. To evaluate the performance of these gene selection methods, we employ several popular learning classifiers on the MicroArray Quality Control phase II on predictive modeling (MAQC-II breast cancer dataset and the MAQC-II multiple myeloma dataset. Experimental results show that gene selection is strictly paired with learning classifier. Overall, our approach outperforms other compared methods. The biological functional analysis based on the MAQC-II breast cancer dataset convinced us to apply our method for phenotype prediction. Additionally, learning classifiers also play important roles in the classification of microarray data and our experimental results indicate that the Nearest Mean Scale Classifier (NMSC is a good choice due to its prediction reliability and its stability across the three performance measurements: Testing accuracy, MCC values, and

  12. Discrimination of phytoplasmas using an oligonucleotide microarray targeting rps3, rpl22, and rps19 genes

    Czech Academy of Sciences Publication Activity Database

    Lenz, Ondřej; Marková, J.; Sarkisova, Tatiana; Fránová, Jana; Přibylová, Jaroslava

    2015-01-01

    Roč. 70, January 2015 (2015), s. 47-52 ISSN 0261-2194 Institutional support: RVO:60077344 Keywords : DNA microarray * rpl22 gene * rps19 gene * rps3 gene Subject RIV: EE - Microbiology, Virology Impact factor: 1.652, year: 2015

  13. Microarray Expression Profiles of 20.000 Genes across 23 Healthy Porcine Tissues

    DEFF Research Database (Denmark)

    Hornshøj, Henrik; Conley, Lene Nagstrup; Hedegaard, Jakob

    2007-01-01

    Gene expression microarrays have been intensively applied to screen for genes involved in specific biological processes of interest such as diseases or responses to environmental stimuli. For mammalian species, cataloging of the global gene expression profiles in large tissue collections under...

  14. FiGS: a filter-based gene selection workbench for microarray data

    Directory of Open Access Journals (Sweden)

    Yun Taegyun

    2010-01-01

    Full Text Available Abstract Background The selection of genes that discriminate disease classes from microarray data is widely used for the identification of diagnostic biomarkers. Although various gene selection methods are currently available and some of them have shown excellent performance, no single method can retain the best performance for all types of microarray datasets. It is desirable to use a comparative approach to find the best gene selection result after rigorous test of different methodological strategies for a given microarray dataset. Results FiGS is a web-based workbench that automatically compares various gene selection procedures and provides the optimal gene selection result for an input microarray dataset. FiGS builds up diverse gene selection procedures by aligning different feature selection techniques and classifiers. In addition to the highly reputed techniques, FiGS diversifies the gene selection procedures by incorporating gene clustering options in the feature selection step and different data pre-processing options in classifier training step. All candidate gene selection procedures are evaluated by the .632+ bootstrap errors and listed with their classification accuracies and selected gene sets. FiGS runs on parallelized computing nodes that capacitate heavy computations. FiGS is freely accessible at http://gexp.kaist.ac.kr/figs. Conclusion FiGS is an web-based application that automates an extensive search for the optimized gene selection analysis for a microarray dataset in a parallel computing environment. FiGS will provide both an efficient and comprehensive means of acquiring optimal gene sets that discriminate disease states from microarray datasets.

  15. Microarray-Based Analysis of Differential Gene Expression between Infective and Noninfective Larvae of Strongyloides stercoralis

    Science.gov (United States)

    Ramanathan, Roshan; Varma, Sudhir; Ribeiro, José M. C.; Myers, Timothy G.; Nolan, Thomas J.; Abraham, David; Lok, James B.; Nutman, Thomas B.

    2011-01-01

    Background Differences between noninfective first-stage (L1) and infective third-stage (L3i) larvae of parasitic nematode Strongyloides stercoralis at the molecular level are relatively uncharacterized. DNA microarrays were developed and utilized for this purpose. Methods and Findings Oligonucleotide hybridization probes for the array were designed to bind 3,571 putative mRNA transcripts predicted by analysis of 11,335 expressed sequence tags (ESTs) obtained as part of the Nematode EST project. RNA obtained from S. stercoralis L3i and L1 was co-hybridized to each array after labeling the individual samples with different fluorescent tags. Bioinformatic predictions of gene function were developed using a novel cDNA Annotation System software. We identified 935 differentially expressed genes (469 L3i-biased; 466 L1-biased) having two-fold expression differences or greater and microarray signals with a p valuemicroarray tool for the examination of S. stercoralis biology has been developed and provides new and valuable insights regarding differences between infective and noninfective S. stercoralis larvae. Potential therapeutic and vaccine targets were identified for further study. PMID:21572524

  16. Identification of human metapneumovirus-induced gene networks in airway epithelial cells by microarray analysis

    International Nuclear Information System (INIS)

    Bao, X.; Sinha, M.; Liu, T.; Hong, C.; Luxon, B.A.; Garofalo, R.P.; Casola, A.

    2008-01-01

    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

  17. Fusion gene microarray reveals cancer type-specificity among fusion genes.

    Science.gov (United States)

    Løvf, Marthe; Thomassen, Gard O S; Bakken, Anne Cathrine; Celestino, Ricardo; Fioretos, Thoas; Lind, Guro E; Lothe, Ragnhild A; Skotheim, Rolf I

    2011-05-01

    Detection of fusion genes for diagnostic purposes and as a guide to treatment is well-established in hematological malignancies, and the prevalence of fusion genes in epithelial cancers is also increasingly appreciated. To study whether established fusion genes are present within additional cancer types, we have used an updated version of our fusion gene microarray in a systematic survey of reported fusion genes in multiple cancer types. We assembled a comprehensive database of published fusion genes, including those reported only in individual studies and samples, and fusion genes resulting from deep sequencing of cancer genomes and transcriptomes. From the total set of 548 fusion genes, we designed 599,839 oligonucleotides, targeting both chimeric transcript junctions as well as sequences internal to each of the fusion gene partners. We investigated the presence of fusion genes in a series of 67 cell lines representing 15 different cancer types. Data from ten leukemia cell lines with known fusion gene status were used to develop an automated scoring algorithm, and in five cell lines the correct fusion gene was the top scoring hit, and one came second. Two additional fusion genes, BCAS4-BCAS3 in the MCF-7 breast cancer cell line and CCDC6-RET in the TPC-1 thyroid cancer cell line were validated as true positive fusion transcripts. However, these fusion genes were not new to these cancer types, and none of 548 fusion genes were identified from a novel cancer type. We therefore find it unlikely that the assayed fusion genes are commonly present across multiple cancer types. 2011 Wiley-Liss, Inc.

  18. Supplementing High-Density SNP Microarrays for Additional Coverage of Disease-Related Genes: Addiction as a Paradigm

    Energy Technology Data Exchange (ETDEWEB)

    SacconePhD, Scott F [Washington University, St. Louis; Chesler, Elissa J [ORNL; Bierut, Laura J [Washington University, St. Louis; Kalivas, Peter J [Medical College of South Carolina, Charleston; Lerman, Caryn [University of Pennsylvania; Saccone, Nancy L [Washington University, St. Louis; Uhl, George R [Johns Hopkins University; Li, Chuan-Yun [Peking University; Philip, Vivek M [ORNL; Edenberg, Howard [Indiana University; Sherry, Steven [National Center for Biotechnology Information; Feolo, Michael [National Center for Biotechnology Information; Moyzis, Robert K [Johns Hopkins University; Rutter, Joni L [National Institute of Drug Abuse

    2009-01-01

    Commercial SNP microarrays now provide comprehensive and affordable coverage of the human genome. However, some diseases have biologically relevant genomic regions that may require additional coverage. Addiction, for example, is thought to be influenced by complex interactions among many relevant genes and pathways. We have assembled a list of 486 biologically relevant genes nominated by a panel of experts on addiction. We then added 424 genes that showed evidence of association with addiction phenotypes through mouse QTL mappings and gene co-expression analysis. We demonstrate that there are a substantial number of SNPs in these genes that are not well represented by commercial SNP platforms. We address this problem by introducing a publicly available SNP database for addiction. The database is annotated using numeric prioritization scores indicating the extent of biological relevance. The scores incorporate a number of factors such as SNP/gene functional properties (including synonymy and promoter regions), data from mouse systems genetics and measures of human/mouse evolutionary conservation. We then used HapMap genotyping data to determine if a SNP is tagged by a commercial microarray through linkage disequilibrium. This combination of biological prioritization scores and LD tagging annotation will enable addiction researchers to supplement commercial SNP microarrays to ensure comprehensive coverage of biologically relevant regions.

  19. Oligonucleotide-based microarray analysis of retinoic acid target genes in the protochordate, Ciona intestinalis.

    Science.gov (United States)

    Ishibashi, Tomoko; Usami, Takeshi; Fujie, Manabu; Azumi, Kaoru; Satoh, Nori; Fujiwara, Shigeki

    2005-08-01

    Oligonucleotide-based microarray analyses were carried out to identify retinoic acid target genes in embryos of the ascidian Ciona intestinalis. Of 21,938 spots, 50 (corresponding to 43 genes) showed over twofold up-regulation in retinoic acid-treated tail bud embryos. In situ hybridization verified retinoic acid-induced up-regulation of 23 genes. Many of them were expressed in the anterior tail region, where a retinaldehyde dehydrogenase homolog is expressed. Homologs of vertebrate genes involved in neurogenesis and/or neuronal functions (e.g., COUP-TF, Ci-Hox1, and SCO-spondin) were expressed in the central nervous system of Ciona embryos, and activated by retinoic acid. Genes encoding transcription factors (e.g., Ci-lmx1.2, vitamin D receptor, and Hox proteins) and apoptosis-related proteins (e.g., transglutaminase and an apoptosis-inducing factor homolog) were also activated by retinoic acid. Simultaneous treatment of embryos with retinoic acid and puromycin revealed a few direct targets, including genes encoding Ci-Hox1, Ci-Cyp26, and an Rnf126-like ring finger protein. (c) 2005 Wiley-Liss, Inc.

  20. A microarray gene expressions with classification using extreme learning machine

    Directory of Open Access Journals (Sweden)

    Yasodha M.

    2015-01-01

    Full Text Available In the present scenario, one of the dangerous disease is cancer. It spreads through blood or lymph to other location of the body, it is a set of cells display uncontrolled growth, attack and destroy nearby tissues, and occasionally metastasis. In cancer diagnosis and molecular biology, a utilized effective tool is DNA microarrays. The dominance of this technique is recognized, so several open doubt arise regarding proper examination of microarray data. In the field of medical sciences, multicategory cancer classification plays very important role. The need for cancer classification has become essential because the number of cancer sufferers is increasing. In this research work, to overcome problems of multicategory cancer classification an improved Extreme Learning Machine (ELM classifier is used. It rectify problems faced by iterative learning methods such as local minima, improper learning rate and over fitting and the training completes with high speed.

  1. A Combinatory Approach for Selecting Prognostic Genes in Microarray Studies of Tumour Survivals

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    Qihua Tan

    2009-01-01

    Full Text Available Different from significant gene expression analysis which looks for genes that are differentially regulated, feature selection in the microarray-based prognostic gene expression analysis aims at finding a subset of marker genes that are not only differentially expressed but also informative for prediction. Unfortunately feature selection in literature of microarray study is predominated by the simple heuristic univariate gene filter paradigm that selects differentially expressed genes according to their statistical significances. We introduce a combinatory feature selection strategy that integrates differential gene expression analysis with the Gram-Schmidt process to identify prognostic genes that are both statistically significant and highly informative for predicting tumour survival outcomes. Empirical application to leukemia and ovarian cancer survival data through-within- and cross-study validations shows that the feature space can be largely reduced while achieving improved testing performances.

  2. Microarray analysis of pancreatic gene expression during biotin repletion in biotin-deficient rats.

    Science.gov (United States)

    Dakshinamurti, Krishnamurti; Bagchi, Rushita A; Abrenica, Bernard; Czubryt, Michael P

    2015-12-01

    Biotin is a B vitamin involved in multiple metabolic pathways. In humans, biotin deficiency is relatively rare but can cause dermatitis, alopecia, and perosis. Low biotin levels occur in individuals with type-2 diabetes, and supplementation with biotin plus chromium may improve blood sugar control. The acute effect on pancreatic gene expression of biotin repletion following chronic deficiency is unclear, therefore we induced biotin deficiency in adult male rats by feeding them a 20% raw egg white diet for 6 weeks. Animals were then randomized into 2 groups: one group received a single biotin supplement and returned to normal chow lacking egg white, while the second group remained on the depletion diet. After 1 week, pancreata were removed from biotin-deficient (BD) and biotin-repleted (BR) animals and RNA was isolated for microarray analysis. Biotin depletion altered gene expression in a manner indicative of inflammation, fibrosis, and defective pancreatic function. Conversely, biotin repletion activated numerous repair and anti-inflammatory pathways, reduced fibrotic gene expression, and induced multiple genes involved in pancreatic endocrine and exocrine function. A subset of the results was confirmed by quantitative real-time PCR analysis, as well as by treatment of pancreatic AR42J cells with biotin. The results indicate that biotin repletion, even after lengthy deficiency, results in the rapid induction of repair processes in the pancreas.

  3. A 588-gene microarray analysis of the peripheral blood mononuclear cells of spondyloarthropathy patients

    NARCIS (Netherlands)

    Gu, J.; Märker-Hermann, E.; Baeten, D.; Tsai, W. C.; Gladman, D.; Xiong, M.; Deister, H.; Kuipers, J. G.; Huang, F.; Song, Y. W.; Maksymowych, W.; Kalsi, J.; Bannai, M.; Seta, N.; Rihl, M.; Crofford, L. J.; Veys, E.; de Keyser, F.; Yu, D. T. Y.

    2002-01-01

    OBJECTIVES: To identify genes which are more highly expressed in the peripheral blood mononuclear cells (PBMC) of patients with spondyloarthropathy (SpA), rheumatoid arthritis (RA) and psoriatic arthritis (PsA), in comparison to normal subjects. METHODS: A 588-gene microarray was used as a screening

  4. Statistical Redundancy Testing for Improved Gene Selection in Cancer Classification Using Microarray Data

    Directory of Open Access Journals (Sweden)

    J. Sunil Rao

    2007-01-01

    Full Text Available In gene selection for cancer classifi cation using microarray data, we define an eigenvalue-ratio statistic to measure a gene’s contribution to the joint discriminability when this gene is included into a set of genes. Based on this eigenvalueratio statistic, we define a novel hypothesis testing for gene statistical redundancy and propose two gene selection methods. Simulation studies illustrate the agreement between statistical redundancy testing and gene selection methods. Real data examples show the proposed gene selection methods can select a compact gene subset which can not only be used to build high quality cancer classifiers but also show biological relevance.

  5. An improved procedure for gene selection from microarray experiments using false discovery rate criterion

    Directory of Open Access Journals (Sweden)

    Yang Mark CK

    2006-01-01

    Full Text Available Abstract Background A large number of genes usually show differential expressions in a microarray experiment with two types of tissues, and the p-values of a proper statistical test are often used to quantify the significance of these differences. The genes with small p-values are then picked as the genes responsible for the differences in the tissue RNA expressions. One key question is what should be the threshold to consider the p-values small. There is always a trade off between this threshold and the rate of false claims. Recent statistical literature shows that the false discovery rate (FDR criterion is a powerful and reasonable criterion to pick those genes with differential expression. Moreover, the power of detection can be increased by knowing the number of non-differential expression genes. While this number is unknown in practice, there are methods to estimate it from data. The purpose of this paper is to present a new method of estimating this number and use it for the FDR procedure construction. Results A combination of test functions is used to estimate the number of differentially expressed genes. Simulation study shows that the proposed method has a higher power to detect these genes than other existing methods, while still keeping the FDR under control. The improvement can be substantial if the proportion of true differentially expressed genes is large. This procedure has also been tested with good results using a real dataset. Conclusion For a given expected FDR, the method proposed in this paper has better power to pick genes that show differentiation in their expression than two other well known methods.

  6. Detection bias in microarray and sequencing transcriptomic analysis identified by housekeeping genes.

    Science.gov (United States)

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

    2016-03-01

    This work includes the original data used to discover the gene ontology bias in transcriptomic analysis conducted by microarray and high throughput sequencing (Zhang et al., 2015) [1]. In the analysis, housekeeping genes were used to examine the differential detection ability by microarray and sequencing because these genes are probably the most reliably detected. The genes included here were compiled from 15 human housekeeping gene studies. The provided tables here comprise of detailed chromosomal location, detection breadth, normalized expression level, exon count, total exon length, and total intron length of each concerned gene and their related transcripts. We hope this information can help researchers better understand the differences in gene ontology-bias we discussed (Zhang et al., 2015) [1] and can encourage further improvement on these two technology platforms.

  7. An Emulsion Based Microarray Method to Detect the Toxin Genes of Toxin-Producing Organisms

    Directory of Open Access Journals (Sweden)

    Yunfei Bai

    2011-08-01

    Full Text Available Toxins produced by bacteria and fungi are one of the most important factors which may cause food contamination. The study of detection methods with high sensitivity and throughput is significant for the protection of food safety. In the present study, we coupled microarray with emulsion PCR and developed a high throughput detection method. Thirteen different gene sites which encode the common toxins of several bacteria and fungi were assayed in parallel in positive and maize samples. Conventional PCR assays were carried out for comparison. The results showed that the developed microarray method had high specificity and sensitivity. Two zearalenone-related genes were investigated in one of the ten maize samples obtained with this present method. The results indicated that the emulsion based microarray detection method was developed successfully and suggested its potential application in multiple gene site detection.

  8. Serious limitations of the QTL/Microarray approach for QTL gene discovery

    Directory of Open Access Journals (Sweden)

    Warden Craig H

    2010-07-01

    Full Text Available Abstract Background It has been proposed that the use of gene expression microarrays in nonrecombinant parental or congenic strains can accelerate the process of isolating individual genes underlying quantitative trait loci (QTL. However, the effectiveness of this approach has not been assessed. Results Thirty-seven studies that have implemented the QTL/microarray approach in rodents were reviewed. About 30% of studies showed enrichment for QTL candidates, mostly in comparisons between congenic and background strains. Three studies led to the identification of an underlying QTL gene. To complement the literature results, a microarray experiment was performed using three mouse congenic strains isolating the effects of at least 25 biometric QTL. Results show that genes in the congenic donor regions were preferentially selected. However, within donor regions, the distribution of differentially expressed genes was homogeneous once gene density was accounted for. Genes within identical-by-descent (IBD regions were less likely to be differentially expressed in chromosome 2, but not in chromosomes 11 and 17. Furthermore, expression of QTL regulated in cis (cis eQTL showed higher expression in the background genotype, which was partially explained by the presence of single nucleotide polymorphisms (SNP. Conclusions The literature shows limited successes from the QTL/microarray approach to identify QTL genes. Our own results from microarray profiling of three congenic strains revealed a strong tendency to select cis-eQTL over trans-eQTL. IBD regions had little effect on rate of differential expression, and we provide several reasons why IBD should not be used to discard eQTL candidates. In addition, mismatch probes produced false cis-eQTL that could not be completely removed with the current strains genotypes and low probe density microarrays. The reviewed studies did not account for lack of coverage from the platforms used and therefore removed genes

  9. A standardized fold change method for microarray differential expression analysis used to reveal genes involved in acute rejection in murine allograft models.

    Science.gov (United States)

    Zhou, Weichen; Wang, Yi; Fujino, Masayuki; Shi, Leming; Jin, Li; Li, Xiao-Kang; Wang, Jiucun

    2018-03-01

    Murine transplantation models are used extensively to research immunological rejection and tolerance. Here we studied both murine heart and liver allograft models using microarray technology. We had difficulty in identifying genes related to acute rejections expressed in both heart and liver transplantation models using two standard methodologies: Student's t test and linear models for microarray data (Limma). Here we describe a new method, standardized fold change (SFC), for differential analysis of microarray data. We estimated the performance of SFC, the t test and Limma by generating simulated microarray data 100 times. SFC performed better than the t test and showed a higher sensitivity than Limma where there is a larger value for fold change of expression. SFC gave better reproducibility than Limma and the t test with real experimental data from the MicroArray Quality Control platform and expression data from a mouse cardiac allograft. Eventually, a group of significant overlapping genes was detected by SFC in the expression data of mouse cardiac and hepatic allografts and further validated with the quantitative RT-PCR assay. The group included genes for important reactions of transplantation rejection and revealed functional changes of the immune system in both heart and liver of the mouse model. We suggest that SFC can be utilized to stably and effectively detect differential gene expression and to explore microarray data in further studies.

  10. Screening and further analyzing differentially expressed genes in acute idiopathic pulmonary fibrosis with DNA microarray.

    Science.gov (United States)

    Min, F; Gao, F; Liu, Z

    2013-10-01

    Acute idiopathic pulmonary fibrosis (IPF) is a serious and progressive form of lung disease, and millions of people suffer from this disease in the world. To provide clues for getting a better understanding of the mechanism of this disease, we identified and further analyzed the differential expressed genes in IPF. In this study, we downloaded the gene expression microarray (GSE10667) from Gene Expression Omnibus (GEO) database. The dataset contained a total of 23 samples, including 15 normal controls and 8 diseases samples (IPF). Then, we identified the differentially expressed genes between normal and disease samples with packages in R language. Consequently, the PPI network was also constructed for the products of these DEGs, and modules in the network were analyzed by Cytoscape's plug-in Mcode and Bingo. Furthermore, enrichment analysis was performed by DAVID to illustrate the altered pathways in IPF. The drug compounds for PLK1 were screened in DrugBank. Atotal of 349 genes were identified as differentially expressed genes between normal and disease samples, and we constructed a protein-protein interaction network which included 200 pairs of proteins. Then three modules were identified in our network. Function of these modules were predicted to be related to protein kinase binding, extracellular matrix structural and structural constituent of cytoskeleton, respectively. Finally, we focused on module A including 18 DEGs. PLK1 (Polo like kinge-1) in this module was predicted as a marker gene in IPF, which was related to cell cycle pathway. Several compounds were found which may be the potential drug for IPF.

  11. Macrophage gene expression associated with remodeling of the prepartum rat cervix: microarray and pathway analyses.

    Directory of Open Access Journals (Sweden)

    Abigail E Dobyns

    Full Text Available As the critical gatekeeper for birth, prepartum remodeling of the cervix is associated with increased resident macrophages (Mφ, proinflammatory processes, and extracellular matrix degradation. This study tested the hypothesis that expression of genes unique to Mφs characterizes the prepartum from unremodeled nonpregnant cervix. Perfused cervix from prepartum day 21 postbreeding (D21 or nonpregnant (NP rats, with or without Mφs, had RNA extracted and whole genome microarray analysis performed. By subtractive analyses, expression of 194 and 120 genes related to Mφs in the cervix from D21 rats were increased and decreased, respectively. In both D21 and NP groups, 158 and 57 Mφ genes were also more or less up- or down-regulated, respectively. Mφ gene expression patterns were most strongly correlated within groups and in 5 major clustering patterns. In the cervix from D21 rats, functional categories and canonical pathways of increased expression by Mφ gene related to extracellular matrix, cell proliferation, differentiation, as well as cell signaling. Pathways were characteristic of inflammation and wound healing, e.g., CD163, CD206, and CCR2. Signatures of only inflammation pathways, e.g., CSF1R, EMR1, and MMP12 were common to both D21 and NP groups. Thus, a novel and complex balance of Mφ genes and clusters differentiated the degraded extracellular matrix and cellular genomic activities in the cervix before birth from the unremodeled state. Predicted Mφ activities, pathways, and networks raise the possibility that expression patterns of specific genes characterize and promote prepartum remodeling of the cervix for parturition at term and with preterm labor.

  12. Macrophage gene expression associated with remodeling of the prepartum rat cervix: microarray and pathway analyses.

    Science.gov (United States)

    Dobyns, Abigail E; Goyal, Ravi; Carpenter, Lauren Grisham; Freeman, Tom C; Longo, Lawrence D; Yellon, Steven M

    2015-01-01

    As the critical gatekeeper for birth, prepartum remodeling of the cervix is associated with increased resident macrophages (Mφ), proinflammatory processes, and extracellular matrix degradation. This study tested the hypothesis that expression of genes unique to Mφs characterizes the prepartum from unremodeled nonpregnant cervix. Perfused cervix from prepartum day 21 postbreeding (D21) or nonpregnant (NP) rats, with or without Mφs, had RNA extracted and whole genome microarray analysis performed. By subtractive analyses, expression of 194 and 120 genes related to Mφs in the cervix from D21 rats were increased and decreased, respectively. In both D21 and NP groups, 158 and 57 Mφ genes were also more or less up- or down-regulated, respectively. Mφ gene expression patterns were most strongly correlated within groups and in 5 major clustering patterns. In the cervix from D21 rats, functional categories and canonical pathways of increased expression by Mφ gene related to extracellular matrix, cell proliferation, differentiation, as well as cell signaling. Pathways were characteristic of inflammation and wound healing, e.g., CD163, CD206, and CCR2. Signatures of only inflammation pathways, e.g., CSF1R, EMR1, and MMP12 were common to both D21 and NP groups. Thus, a novel and complex balance of Mφ genes and clusters differentiated the degraded extracellular matrix and cellular genomic activities in the cervix before birth from the unremodeled state. Predicted Mφ activities, pathways, and networks raise the possibility that expression patterns of specific genes characterize and promote prepartum remodeling of the cervix for parturition at term and with preterm labor.

  13. Macrophage Gene Expression Associated with Remodeling of the Prepartum Rat Cervix: Microarray and Pathway Analyses

    Science.gov (United States)

    Dobyns, Abigail E.; Goyal, Ravi; Carpenter, Lauren Grisham; Freeman, Tom C.; Longo, Lawrence D.; Yellon, Steven M.

    2015-01-01

    As the critical gatekeeper for birth, prepartum remodeling of the cervix is associated with increased resident macrophages (Mφ), proinflammatory processes, and extracellular matrix degradation. This study tested the hypothesis that expression of genes unique to Mφs characterizes the prepartum from unremodeled nonpregnant cervix. Perfused cervix from prepartum day 21 postbreeding (D21) or nonpregnant (NP) rats, with or without Mφs, had RNA extracted and whole genome microarray analysis performed. By subtractive analyses, expression of 194 and 120 genes related to Mφs in the cervix from D21 rats were increased and decreased, respectively. In both D21 and NP groups, 158 and 57 Mφ genes were also more or less up- or down-regulated, respectively. Mφ gene expression patterns were most strongly correlated within groups and in 5 major clustering patterns. In the cervix from D21 rats, functional categories and canonical pathways of increased expression by Mφ gene related to extracellular matrix, cell proliferation, differentiation, as well as cell signaling. Pathways were characteristic of inflammation and wound healing, e.g., CD163, CD206, and CCR2. Signatures of only inflammation pathways, e.g., CSF1R, EMR1, and MMP12 were common to both D21 and NP groups. Thus, a novel and complex balance of Mφ genes and clusters differentiated the degraded extracellular matrix and cellular genomic activities in the cervix before birth from the unremodeled state. Predicted Mφ activities, pathways, and networks raise the possibility that expression patterns of specific genes characterize and promote prepartum remodeling of the cervix for parturition at term and with preterm labor. PMID:25811906

  14. Use of non-amplified RNA samples for microarray analysis of gene expression.

    Directory of Open Access Journals (Sweden)

    Hiroko Sudo

    Full Text Available Demand for high quality gene expression data has driven the development of revolutionary microarray technologies. The quality of the data is affected by the performance of the microarray platform as well as how the nucleic acid targets are prepared. The most common method for target nucleic acid preparation includes in vitro transcription amplification of the sample RNA. Although this method requires a small amount of starting material and is reported to have high reproducibility, there are also technical disadvantages such as amplification bias and the long, laborious protocol. Using RNA derived from human brain, breast and colon, we demonstrate that a non-amplification method, which was previously shown to be inferior, could be transformed to a highly quantitative method with a dynamic range of five orders of magnitude. Furthermore, the correlation coefficient calculated by comparing microarray assays using non-amplified samples with qRT-PCR assays was approximately 0.9, a value much higher than when samples were prepared using amplification methods. Our results were also compared with data from various microarray platforms studied in the MicroArray Quality Control (MAQC project. In combination with micro-columnar 3D-Gene™ microarray, this non-amplification method is applicable to a variety of genetic analyses, including biomarker screening and diagnostic tests for cancer.

  15. Microarray analysis of gene expression in the cyclooxygenase knockout mice - a connection to autism spectrum disorder.

    Science.gov (United States)

    Rai-Bhogal, Ravneet; Ahmad, Eizaaz; Li, Hongyan; Crawford, Dorota A

    2017-11-21

    The cellular and molecular events that take place during brain development play an important role in governing function of the mature brain. Lipid-signalling molecules such as prostaglandin E 2 (PGE 2 ) play an important role in healthy brain development. Abnormalities along the COX-PGE 2 signalling pathway due to genetic or environmental causes have been linked to autism spectrum disorder (ASD). This study aims to evaluate the effect of altered COX-PGE 2 signalling on development and function of the prenatal brain using male mice lacking cyclooxygenase-1 and cyclooxygenase-2 (COX-1 -/- and COX-2 -/- ) as potential model systems of ASD. Microarray analysis was used to determine global changes in gene expression during embryonic days 16 (E16) and 19 (E19). Gene Ontology: Biological Process (GO:BP) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were implemented to identify affected developmental genes and cellular processes. We found that in both knockouts the brain at E16 had nearly twice as many differentially expressed genes, and affected biological pathways containing various ASD-associated genes important in neuronal function. Interestingly, using GeneMANIA and Cytoscape we also show that the ASD-risk genes identified in both COX-1 -/- and COX-2 -/- models belong to protein-interaction networks important for brain development despite of different cellular localization of these enzymes. Lastly, we identified eight genes that belong to the Wnt signalling pathways exclusively in the COX-2 -/- mice at E16. The level of PKA-phosphorylated β-catenin (S552), a major activator of the Wnt pathway, was increased in this model, suggesting crosstalk between the COX-2-PGE 2 and Wnt pathways during early brain development. Overall, these results provide further molecular insight into the contribution of the COX-PGE 2 pathways to ASD and demonstrate that COX-1 -/- and COX-2 -/- animals might be suitable new model systems for studying the disorders. © 2017 Federation of

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

    International Nuclear Information System (INIS)

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

    2005-01-01

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

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

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    Regiane de Fátima Travensolo

    2009-06-01

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

  18. Changes in gene expression linked with adult reproductive diapause in a northern malt fly species: a candidate gene microarray study

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    Hoikkala Anneli

    2010-02-01

    Full Text Available Abstract Background Insect diapause is an important biological process which involves many life-history parameters important for survival and reproductive fitness at both individual and population level. Drosophila montana, a species of D. virilis group, has a profound photoperiodic reproductive diapause that enables the adult flies to survive through the harsh winter conditions of high latitudes and altitudes. We created a custom-made microarray for D. montana with 101 genes known to affect traits important in diapause, photoperiodism, reproductive behaviour, circadian clock and stress tolerance in model Drosophila species. This array gave us a chance to filter out genes showing expression changes during photoperiodic reproductive diapause in a species adapted to live in northern latitudes with high seasonal changes in environmental conditions. Results Comparisons among diapausing, reproducing and young D. montana females revealed expression changes in 24 genes on microarray; for example in comparison between diapausing and reproducing females one gene (Drosophila cold acclimation gene, Dca showed up-regulation and 15 genes showed down-regulation in diapausing females. Down-regulation of seven of these genes was specific to diapause state while in five genes the expression changes were linked with the age of the females rather than with their reproductive status. Also, qRT-PCR experiments confirmed couch potato (cpo gene to be involved in diapause of D. montana. Conclusions A candidate gene microarray proved to offer a practical and cost-effective way to trace genes that are likely to play an important role in photoperiodic reproductive diapause and further in adaptation to seasonally varying environmental conditions. The present study revealed two genes, Dca and cpo, whose role in photoperiodic diapause in D. montana is worth of studying in more details. Also, further studies using the candidate gene microarray with more specific experimental

  19. Troubleshooting methods for microarray gene expression analysis in the onset of diabetic kidney disease

    NARCIS (Netherlands)

    Mazagova, Magdalena; Henning, Robert H.; Duin, Marry; van Buiten, Azuwerus; Buikema, Hendrik; Deelman, Leo E.

    2013-01-01

    Introduction: Microarrays have become the standard technique for discovering new genes involved in the development of (kidney) disease. Diabetic nephropathy is a frequent complication of diabetes and is characterized by renal fibrosis. As the pathways leading to fibrosis are initiated early in

  20. Optimal Design of Genetic Studies of Gene Expression With Two-Color Microarrays in Outbred Crosses

    NARCIS (Netherlands)

    Lam, Alex C.; Fu, Jingyuan; Jansen, Ritsert C.; Haley, Chris S.; de Koning, Dirk-Jan

    2008-01-01

    Combining global gene-expression profiling and genetic analysis of natural allelic variation (genetical genomics) has great potential in dissecting the genetic pathways underlying complex phenotypes. Efficient use of microarrays is paramount in experimental design as the cost. of conducting this

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

    Science.gov (United States)

    Sarkar, Anasua; Maulik, Ujjwal

    2015-01-01

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

  2. GENE EXPRESSION IN THE TESTES OF NORMOSPERMIC VERSUS TERATOSPERMIC DOMESTIC CATS USING HUMAN CDNA MICROARRAY ANALYSES

    Science.gov (United States)

    GENE EXPRESSION IN THE TESTES OF NORMOSPERMIC VERSUS TERATOSPERMIC DOMESTIC CATS USING HUMAN cDNA MICROARRAY ANALYSESB.S. Pukazhenthi1, J. C. Rockett2, M. Ouyang3, D.J. Dix2, J.G. Howard1, P. Georgopoulos4, W.J. J. Welsh3 and D. E. Wildt11Department of Reproductiv...

  3. A unified framework for finding differentially expressed genes from microarray experiments

    Directory of Open Access Journals (Sweden)

    Yeasin Mohammed

    2007-09-01

    Full Text Available Abstract Background This paper presents a unified framework for finding differentially expressed genes (DEGs from the microarray data. The proposed framework has three interrelated modules: (i gene ranking, ii significance analysis of genes and (iii validation. The first module uses two gene selection algorithms, namely, a two-way clustering and b combined adaptive ranking to rank the genes. The second module converts the gene ranks into p-values using an R-test and fuses the two sets of p-values using the Fisher's omnibus criterion. The DEGs are selected using the FDR analysis. The third module performs three fold validations of the obtained DEGs. The robustness of the proposed unified framework in gene selection is first illustrated using false discovery rate analysis. In addition, the clustering-based validation of the DEGs is performed by employing an adaptive subspace-based clustering algorithm on the training and the test datasets. Finally, a projection-based visualization is performed to validate the DEGs obtained using the unified framework. Results The performance of the unified framework is compared with well-known ranking algorithms such as t-statistics, Significance Analysis of Microarrays (SAM, Adaptive Ranking, Combined Adaptive Ranking and Two-way Clustering. The performance curves obtained using 50 simulated microarray datasets each following two different distributions indicate the superiority of the unified framework over the other reported algorithms. Further analyses on 3 real cancer datasets and 3 Parkinson's datasets show the similar improvement in performance. First, a 3 fold validation process is provided for the two-sample cancer datasets. In addition, the analysis on 3 sets of Parkinson's data is performed to demonstrate the scalability of the proposed method to multi-sample microarray datasets. Conclusion This paper presents a unified framework for the robust selection of genes from the two-sample as well as multi

  4. Density based pruning for identification of differentially expressed genes from microarray data

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    Xu Jia

    2010-11-01

    Full Text Available Abstract Motivation Identification of differentially expressed genes from microarray datasets is one of the most important analyses for microarray data mining. Popular algorithms such as statistical t-test rank genes based on a single statistics. The false positive rate of these methods can be improved by considering other features of differentially expressed genes. Results We proposed a pattern recognition strategy for identifying differentially expressed genes. Genes are mapped to a two dimension feature space composed of average difference of gene expression and average expression levels. A density based pruning algorithm (DB Pruning is developed to screen out potential differentially expressed genes usually located in the sparse boundary region. Biases of popular algorithms for identifying differentially expressed genes are visually characterized. Experiments on 17 datasets from Gene Omnibus Database (GEO with experimentally verified differentially expressed genes showed that DB pruning can significantly improve the prediction accuracy of popular identification algorithms such as t-test, rank product, and fold change. Conclusions Density based pruning of non-differentially expressed genes is an effective method for enhancing statistical testing based algorithms for identifying differentially expressed genes. It improves t-test, rank product, and fold change by 11% to 50% in the numbers of identified true differentially expressed genes. The source code of DB pruning is freely available on our website http://mleg.cse.sc.edu/degprune

  5. Microarray analysis of the gene expression profile in triethylene glycol dimethacrylate-treated human dental pulp cells.

    Science.gov (United States)

    Torun, D; Torun, Z Ö; Demirkaya, K; Sarper, M; Elçi, M P; Avcu, F

    2017-11-01

    Triethylene glycol dimethacrylate (TEGDMA) is an important resin monomer commonly used in the structure of dental restorative materials. Recent studies have shown that unpolymerized resin monomers may be released into the oral environment and cause harmful biological effects. We investigated changes in the gene expression profiles of TEGDMA-treated human dental pulp cells (hDPCs) following short- (1-day) and long-term (7-days) exposure. HDPCs were exposed to a noncytotoxic concentration of TEGDMA, and gene expression profiles were evaluated by microarray analysis. The results were confirmed by quantitative reverse-transcriptase PCR (qRT PCR). In total, 1282 and 1319 genes (up- or down-regulated) were differentially expressed compared with control group after the 1- and 7-day incubation periods, respectively. Biological ontology-based analyses revealed that metabolic, cellular, and developmental processes constituted the largest groups of biological functional processes. qRT-PCR analysis on bone morphogenetic protein-2 (BMP-2), BMP-4, secreted protein, acidic, cysteine-rich, collagen type I alpha 1, oxidative stress-induced growth inhibitor 1, MMP3, interleukin-6, and heme oxygenase-1 genes confirmed the changes in expression observed in the microarray analysis. Our results suggest that TEGDMA can change the many functions of hDPCs through large changes in gene expression levels and complex interactions with different signaling pathways.

  6. Gene selection and classification for cancer microarray data based on machine learning and similarity measures

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    Liu Qingzhong

    2011-12-01

    Full Text Available Abstract Background Microarray data have a high dimension of variables and a small sample size. In microarray data analyses, two important issues are how to choose genes, which provide reliable and good prediction for disease status, and how to determine the final gene set that is best for classification. Associations among genetic markers mean one can exploit information redundancy to potentially reduce classification cost in terms of time and money. Results To deal with redundant information and improve classification, we propose a gene selection method, Recursive Feature Addition, which combines supervised learning and statistical similarity measures. To determine the final optimal gene set for prediction and classification, we propose an algorithm, Lagging Prediction Peephole Optimization. By using six benchmark microarray gene expression data sets, we compared Recursive Feature Addition with recently developed gene selection methods: Support Vector Machine Recursive Feature Elimination, Leave-One-Out Calculation Sequential Forward Selection and several others. Conclusions On average, with the use of popular learning machines including Nearest Mean Scaled Classifier, Support Vector Machine, Naive Bayes Classifier and Random Forest, Recursive Feature Addition outperformed other methods. Our studies also showed that Lagging Prediction Peephole Optimization is superior to random strategy; Recursive Feature Addition with Lagging Prediction Peephole Optimization obtained better testing accuracies than the gene selection method varSelRF.

  7. An evolutionary approach for gene selection and classification of microarray data based on SVM error-bound theories.

    Science.gov (United States)

    Debnath, Rameswar; Kurita, Takio

    2010-04-01

    Microarrays have thousands to tens-of-thousands of gene features, but only a few hundred patient samples are available. The fundamental problem in microarray data analysis is identifying genes whose disruption causes congenital or acquired disease in humans. In this paper, we propose a new evolutionary method that can efficiently select a subset of potentially informative genes for support vector machine (SVM) classifiers. The proposed evolutionary method uses SVM with a given subset of gene features to evaluate the fitness function, and new subsets of features are selected based on the estimates of generalization error of SVMs and frequency of occurrence of the features in the evolutionary approach. Thus, in theory, selected genes reflect to some extent the generalization performance of SVM classifiers. We compare our proposed method with several existing methods and find that the proposed method can obtain better classification accuracy with a smaller number of selected genes than the existing methods. Copyright (c) 2010 Elsevier Ireland Ltd. All rights reserved.

  8. Gene expression profile analysis in human hepatocellular carcinoma by cDNA microarray.

    Science.gov (United States)

    Chung, Eun Jung; Sung, Young Kwan; Farooq, Mohammad; Kim, Younghee; Im, Sanguk; Tak, Won Young; Hwang, Yoon Jin; Kim, Yang Il; Han, Hyung Soo; Kim, Jung-Chul; Kim, Moon Kyu

    2002-12-31

    We performed gene expression profiling of normal and hepatocellular carcinoma (HCC) liver tissues using a high-density microarray that contained 3,063 human cDNA. The results of a microarray hybridization experiment from eight different HCC tissues were analyzed and classified by the Cluster program. Among these differentially-expressed genes, the galectin-3, serine/threonine kinase SGK, translation factor eIF-4A, -4B, -3, fibroblast growth factor receptor, and ribosomal protein L35A were up-regulated; the mRNAs of Nip3, decorin, and the insulin-like growth factor binding protein-3 were down-regulated in HCC. The differential expression of these genes was further confirmed by an RT-PCR analysis. In addition, our data suggest that the gene expression profile of HCC varies according to the histological types.

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

    Science.gov (United States)

    Kang, Suyeon; Song, Jongwoo

    2017-09-02

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

  10. Microarray-Based Gene Expression Profiling to Elucidate Effectiveness of Fermented Codonopsis lanceolata in Mice

    Science.gov (United States)

    Choi, Woon Yong; Kim, Ji Seon; Park, Sung Jin; Ma, Choong Je; Lee, Hyeon Yong

    2014-01-01

    In this study, the effect of Codonopsis lanceolata fermented by lactic acid on controlling gene expression levels related to obesity was observed in an oligonucleotide chip microarray. Among 8170 genes, 393 genes were up regulated and 760 genes were down regulated in feeding the fermented C. lanceolata (FCL). Another 374 genes were up regulated and 527 genes down regulated without feeding the sample. The genes were not affected by the FCL sample. It was interesting that among those genes, Chytochrome P450, Dmbt1, LOC76487, and thyroid hormones, etc., were mostly up or down regulated. These genes are more related to lipid synthesis. We could conclude that the FCL possibly controlled the gene expression levels related to lipid synthesis, which resulted in reducing obesity. However, more detailed protein expression experiments should be carried out. PMID:24717412

  11. Microarray-Based Gene Expression Profiling to Elucidate Effectiveness of Fermented Codonopsis lanceolata in Mice

    Directory of Open Access Journals (Sweden)

    Woon Yong Choi

    2014-04-01

    Full Text Available In this study, the effect of Codonopsis lanceolata fermented by lactic acid on controlling gene expression levels related to obesity was observed in an oligonucleotide chip microarray. Among 8170 genes, 393 genes were up regulated and 760 genes were down regulated in feeding the fermented C. lanceolata (FCL. Another 374 genes were up regulated and 527 genes down regulated without feeding the sample. The genes were not affected by the FCL sample. It was interesting that among those genes, Chytochrome P450, Dmbt1, LOC76487, and thyroid hormones, etc., were mostly up or down regulated. These genes are more related to lipid synthesis. We could conclude that the FCL possibly controlled the gene expression levels related to lipid synthesis, which resulted in reducing obesity. However, more detailed protein expression experiments should be carried out.

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

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    Gress Thomas M

    2008-01-01

    Full Text Available Abstract 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.

  13. Evaluation of differential gene expression during behavioral development in the honeybee using microarrays and northern blots

    Science.gov (United States)

    Kucharski, Robert; Maleszka, Ryszard

    2002-01-01

    Background The honeybee (Apis mellifera) has been used with great success in a variety of behavioral studies. The lack of genomic tools in this species has, however, hampered efforts to provide genome-based explanations for behavioral data. We have combined the power of DNA arrays and the availability of distinct behavioral stages in honeybees to explore the dynamics of gene expression during adult development in this insect. In addition, we used caffeine treatment, a procedure that accelerates learning abilities in honeybees, to examine changes in gene expression underlying drug-induced behavioral modifications. Results Spotted microarrays containing several thousand cDNAs were interrogated with RNAs extracted from newly emerged worker bees, experienced foragers and caffeine-treated bees. Thirty-six differentially expressed cDNAs were verified by northern blot hybridization and characterized in silico by sequencing and database searches. Experienced foragers overexpressed royal jelly proteins, a putative imaginal disc growth factor, a transcriptional regulator (Stck) and several enzymes, including α-glucosidases, aminopeptidases and glucose dehydrogenase. Naive workers showed increased expression of members of the SPARC and lectin families, heat-shock cognate proteins and several proteins related to RNA translation and mitochondrial function. A number of novel genes overexpressed in both naive and experienced bees, and genes induced by caffeine, have also been identified. Conclusions We have shown the usefulness of this transcriptome-based approach for gene discovery, in particular in the context of the efficacy of drug treatment, in a model organism in which routine genetic techniques cannot be applied easily. PMID:11864369

  14. Identification of genes differentially expressed in a resistant reaction to Mycosphaerella pinodes in pea using microarray technology

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    Cubero José I

    2011-01-01

    Full Text Available Abstract Background Ascochyta blight, caused by Mycosphaerella pinodes is one of the most important pea pathogens. However, little is known about the genes and mechanisms of resistance acting against M. pinodes in pea. Resistance identified so far to this pathogen is incomplete, polygenic and scarce in pea, being most common in Pisum relatives. The identification of the genes underlying resistance would increase our knowledge about M. pinodes-pea interaction and would facilitate the introgression of resistance into pea varieties. In the present study differentially expressed genes in the resistant P. sativum ssp. syriacum accession P665 comparing to the susceptible pea cv. Messire after inoculation with M. pinodes have been identified using a M. truncatula microarray. Results Of the 16,470 sequences analysed, 346 were differentially regulated. Differentially regulated genes belonged to almost all functional categories and included genes involved in defense such as genes involved in cell wall reinforcement, phenylpropanoid and phytoalexins metabolism, pathogenesis- related (PR proteins and detoxification processes. Genes associated with jasmonic acid (JA and ethylene signal transduction pathways were induced suggesting that the response to M. pinodes in pea is regulated via JA and ET pathways. Expression levels of ten differentially regulated genes were validated in inoculated and control plants using qRT-PCR showing that the P665 accession shows constitutively an increased expression of the defense related genes as peroxidases, disease resistance response protein 39 (DRR230-b, glutathione S-transferase (GST and 6a-hydroxymaackiain methyltransferase. Conclusions Through this study a global view of genes expressed during resistance to M. pinodes has been obtained, giving relevant information about the mechanisms and pathways conferring resistance to this important disease. In addition, the M. truncatula microarray represents an efficient tool to

  15. Identification of genes differentially expressed in a resistant reaction to Mycosphaerella pinodes in pea using microarray technology.

    Science.gov (United States)

    Fondevilla, Sara; Küster, Helge; Krajinski, Franziska; Cubero, José I; Rubiales, Diego

    2011-01-13

    Ascochyta blight, caused by Mycosphaerella pinodes is one of the most important pea pathogens. However, little is known about the genes and mechanisms of resistance acting against M. pinodes in pea. Resistance identified so far to this pathogen is incomplete, polygenic and scarce in pea, being most common in Pisum relatives. The identification of the genes underlying resistance would increase our knowledge about M. pinodes-pea interaction and would facilitate the introgression of resistance into pea varieties. In the present study differentially expressed genes in the resistant P. sativum ssp. syriacum accession P665 comparing to the susceptible pea cv. Messire after inoculation with M. pinodes have been identified using a M. truncatula microarray. Of the 16,470 sequences analysed, 346 were differentially regulated. Differentially regulated genes belonged to almost all functional categories and included genes involved in defense such as genes involved in cell wall reinforcement, phenylpropanoid and phytoalexins metabolism, pathogenesis- related (PR) proteins and detoxification processes. Genes associated with jasmonic acid (JA) and ethylene signal transduction pathways were induced suggesting that the response to M. pinodes in pea is regulated via JA and ET pathways. Expression levels of ten differentially regulated genes were validated in inoculated and control plants using qRT-PCR showing that the P665 accession shows constitutively an increased expression of the defense related genes as peroxidases, disease resistance response protein 39 (DRR230-b), glutathione S-transferase (GST) and 6a-hydroxymaackiain methyltransferase. Through this study a global view of genes expressed during resistance to M. pinodes has been obtained, giving relevant information about the mechanisms and pathways conferring resistance to this important disease. In addition, the M. truncatula microarray represents an efficient tool to identify candidate genes controlling resistance to M

  16. Normalization and gene p-value estimation: issues in microarray data processing.

    Science.gov (United States)

    Fundel, Katrin; Küffner, Robert; Aigner, Thomas; Zimmer, Ralf

    2008-05-28

    Numerous methods exist for basic processing, e.g. normalization, of microarray gene expression data. These methods have an important effect on the final analysis outcome. Therefore, it is crucial to select methods appropriate for a given dataset in order to assure the validity and reliability of expression data analysis. Furthermore, biological interpretation requires expression values for genes, which are often represented by several spots or probe sets on a microarray. How to best integrate spot/probe set values into gene values has so far been a somewhat neglected problem. We present a case study comparing different between-array normalization methods with respect to the identification of differentially expressed genes. Our results show that it is feasible and necessary to use prior knowledge on gene expression measurements to select an adequate normalization method for the given data. Furthermore, we provide evidence that combining spot/probe set p-values into gene p-values for detecting differentially expressed genes has advantages compared to combining expression values for spots/probe sets into gene expression values. The comparison of different methods suggests to use Stouffer's method for this purpose. The study has been conducted on gene expression experiments investigating human joint cartilage samples of osteoarthritis related groups: a cDNA microarray (83 samples, four groups) and an Affymetrix (26 samples, two groups) data set. The apparently straight forward steps of gene expression data analysis, e.g. between-array normalization and detection of differentially regulated genes, can be accomplished by numerous different methods. We analyzed multiple methods and the possible effects and thereby demonstrate the importance of the single decisions taken during data processing. We give guidelines for evaluating normalization outcomes. An overview of these effects via appropriate measures and plots compared to prior knowledge is essential for the biological

  17. Multi-Gene Detection and Identification of Mosquito-Borne RNA Viruses Using an Oligonucleotide Microarray

    Science.gov (United States)

    Grubaugh, Nathan D.; McMenamy, Scott S.; Turell, Michael J.; Lee, John S.

    2013-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Nathan D Grubaugh

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

  19. Exploring matrix factorization techniques for significant genes identification of Alzheimer’s disease microarray gene expression data

    Directory of Open Access Journals (Sweden)

    Hu Xiaohua

    2011-07-01

    Full Text Available Abstract Background The wide use of high-throughput DNA microarray technology provide an increasingly detailed view of human transcriptome from hundreds to thousands of genes. Although biomedical researchers typically design microarray experiments to explore specific biological contexts, the relationships between genes are hard to identified because they are complex and noisy high-dimensional data and are often hindered by low statistical power. The main challenge now is to extract valuable biological information from the colossal amount of data to gain insight into biological processes and the mechanisms of human disease. To overcome the challenge requires mathematical and computational methods that are versatile enough to capture the underlying biological features and simple enough to be applied efficiently to large datasets. Methods Unsupervised machine learning approaches provide new and efficient analysis of gene expression profiles. In our study, two unsupervised knowledge-based matrix factorization methods, independent component analysis (ICA and nonnegative matrix factorization (NMF are integrated to identify significant genes and related pathways in microarray gene expression dataset of Alzheimer’s disease. The advantage of these two approaches is they can be performed as a biclustering method by which genes and conditions can be clustered simultaneously. Furthermore, they can group genes into different categories for identifying related diagnostic pathways and regulatory networks. The difference between these two method lies in ICA assume statistical independence of the expression modes, while NMF need positivity constrains to generate localized gene expression profiles. Results In our work, we performed FastICA and non-smooth NMF methods on DNA microarray gene expression data of Alzheimer’s disease respectively. The simulation results shows that both of the methods can clearly classify severe AD samples from control samples, and

  20. A new approach to species determination for yeast strains: DNA microarray-based comparative genomic hybridization using a yeast DNA microarray with 6000 genes.

    Science.gov (United States)

    Watanabe, Takahito; Murata, Yoshinori; Oka, Syuichi; Iwahashi, Hitoshi

    2004-03-01

    DNA-DNA hybridization is known as the superior method in the elucidation of relationships between closely related taxa, such as species and strain. For species determination we propose a new DNA-DNA hybridization method: the DNA microarray-based comparative genomic hybridization (CGH) method, using a yeast DNA microarray with approximately 6000 genes. The genome from a yeast strain as a sample strain (Sample) was labelled with Cy3-dye and hybridized to a single DNA microarray, together with the Cy5-labelled genome of S. cerevisiae S288C as a reference strain (Reference). The log2 ratio values [log2[Cy3(Sample)/Cy5(Reference)]: Ratio] of signal intensities of all the gene spots were estimated and divided into the following groups: Ratio < or = -1; -1 < Ratio < 1; 1 < or = Ratio. The hybridization profiles of the genomes of type strains belonging to the genus Saccharomyces were significantly different from that of S. cerevisiae S288C. The Ratio-based grouping allowed us to discriminate between some species from S. cerevisiae more clearly. Furthermore, cluster analysis discriminated between closely related species and strains. Using this method, we were able to not only perform species determination but also to obtain information on alternation in gene copy number of such gene amplifications and deletions with single-gene resolution. These observations indicated that DNA microarray-based CGH is a powerful system for species determination and comparative genome analysis. Copyright 2004 John Wiley & Sons, Ltd.

  1. Gene ordering in partitive clustering using microarray expressions

    Indian Academy of Sciences (India)

    2007-06-28

    Jun 28, 2007 ... Two existing algorithms for optimally ordering cities in travelling salesman problem (TSP), namely, FRAG_GALK and Concorde, are hybridized individually with self organizing MAP to show the importance of gene ordering in partitive clustering framework. We validated our hybrid approach using yeast and ...

  2. Interaction of pseudomonas aeruginosa with epithelial cells: identification of differentially regulated genes by expression microarray analysis of human cDNAs

    NARCIS (Netherlands)

    Ichikawa, J. K.; Norris, A.; Bangera, M. G.; Geiss, G. K.; van 't Wout, A. B.; Bumgarner, R. E.; Lory, S.

    2000-01-01

    Pseudomonas aeruginosa is an opportunistic pathogen that plays a major role in lung function deterioration in cystic fibrosis patients. To identify critical host responses during infection, we have used high-density DNA microarrays, consisting of 1,506 human cDNA clones, to monitor gene expression

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

    Science.gov (United States)

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

    2007-05-01

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

  4. Microarray analysis of gene expression in disk abalone Haliotis discus discus after bacterial challenge.

    Science.gov (United States)

    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. Copyright © 2010 Elsevier Ltd. All rights reserved.

  5. Implementation of plaid model biclustering method on microarray of carcinoma and adenoma tumor gene expression data

    Science.gov (United States)

    Ardaneswari, Gianinna; Bustamam, Alhadi; Sarwinda, Devvi

    2017-10-01

    A Tumor is an abnormal growth of cells that serves no purpose. Carcinoma is a tumor that grows from the top of the cell membrane and the organ adenoma is a benign tumor of the gland-like cells or epithelial tissue. In the field of molecular biology, the development of microarray technology is used in the data store of disease genetic expression. For each of microarray gene, an amount of information is stored for each trait or condition. In gene expression data clustering can be done with a bicluster algorithm, thats clustering method which not only the objects to be clustered, but also the properties or condition of the object. This research proposed Plaid Model Biclustering as one of biclustering method. In this study, we discuss the implementation of Plaid Model Biclustering Method on microarray of Carcinoma and Adenoma tumor gene expression data. From the experimental results, we found three biclusters are formed by Carcinoma gene expression data and four biclusters are formed by Adenoma gene expression data.

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

    Directory of Open Access Journals (Sweden)

    Robert T Gaeta

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

  7. DNA Microarrays

    Science.gov (United States)

    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.

  8. SSHscreen and SSHdb, generic software for microarray based gene discovery: application to the stress response in cowpea.

    Science.gov (United States)

    Coetzer, Nanette; Gazendam, Inge; Oelofse, Dean; Berger, Dave K

    2010-04-01

    Suppression subtractive hybridization is a popular technique for gene discovery from non-model organisms without an annotated genome sequence, such as cowpea (Vigna unguiculata (L.) Walp). We aimed to use this method to enrich for genes expressed during drought stress in a drought tolerant cowpea line. However, current methods were inefficient in screening libraries and management of the sequence data, and thus there was a need to develop software tools to facilitate the process. Forward and reverse cDNA libraries enriched for cowpea drought response genes were screened on microarrays, and the R software package SSHscreen 2.0.1 was developed (i) to normalize the data effectively using spike-in control spot normalization, and (ii) to select clones for sequencing based on the calculation of enrichment ratios with associated statistics. Enrichment ratio 3 values for each clone showed that 62% of the forward library and 34% of the reverse library clones were significantly differentially expressed by drought stress (adjusted p value 88% of the clones in both libraries were derived from rare transcripts in the original tester samples, thus supporting the notion that suppression subtractive hybridization enriches for rare transcripts. A set of 118 clones were chosen for sequencing, and drought-induced cowpea genes were identified, the most interesting encoding a late embryogenesis abundant Lea5 protein, a glutathione S-transferase, a thaumatin, a universal stress protein, and a wound induced protein. A lipid transfer protein and several components of photosynthesis were down-regulated by the drought stress. Reverse transcriptase quantitative PCR confirmed the enrichment ratio values for the selected cowpea genes. SSHdb, a web-accessible database, was developed to manage the clone sequences and combine the SSHscreen data with sequence annotations derived from BLAST and Blast2GO. The self-BLAST function within SSHdb grouped redundant clones together and illustrated that the

  9. GeneX Va: VBC open source microarray database and analysis software.

    Science.gov (United States)

    Lee, Jae K; Laudeman, Tom; Kanter, Jodi; James, Teela; Siadaty, Mir S; Knaus, William A; Prorok, Alyson; Bao, Yongde; Freeman, Brad; Puiu, Daniela; Wen, Li Min; Buck, Gregory A; Schlauch, Karen; Weller, Jennifer; Fox, Jay W

    2004-04-01

    Developed by the Virginia Bioinformatics Consortium (VBC), GeneX Va is an open source, freeware database and bioinformatics analysis software for archiving and analyzing Affymetrix GeneChip data. It provides an integrated framework for management, documentation, and analysis of microarray experiments and data to support a range of users, from individual research laboratories to institutional microarray facilities. GeneX Va also provides web-based access to a PostgreSQL relational database system with a comprehensive security system. Data can be extracted from the database and delivered to interactive or scriptable statistical analysis protocols. The security system allows each investigator to manage their own array data and analysis output files and also provides custom access privileges for other users, groups, and internal/external collaborators. The analysis interface uses "Analysis Trees," an innovative user interface that allows researchers to interactively create a tree-structured flow chart of analysis routines. The latest GeneX Va software is available from and can be freely downloaded at the Sourceforge web site http://va-genex.sourceforge.net. To allow researchers to access the database and analysis capabilities of the GeneX Va system, microarray data from many VBC GeneChip experiments have been deposited into a public section of the GeneX Va system at the University of Virginia. The VBC GeneX Va sites, which include documentation, are at http://genes.med.virginia.edu/ of the University of Virginia and at http://genex.csbc.vcu.edu/ of the Virginia Commonwealth University.

  10. Gametogenesis in the Pacific Oyster Crassostrea gigas: A Microarrays-Based Analysis Identifies Sex and Stage Specific Genes

    Science.gov (United States)

    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

  11. Interpretable gene expression classifier with an accurate and compact fuzzy rule base for microarray data analysis.

    Science.gov (United States)

    Ho, Shinn-Ying; Hsieh, Chih-Hung; Chen, Hung-Ming; Huang, Hui-Ling

    2006-09-01

    An accurate classifier with linguistic interpretability using a small number of relevant genes is beneficial to microarray data analysis and development of inexpensive diagnostic tests. Several frequently used techniques for designing classifiers of microarray data, such as support vector machine, neural networks, k-nearest neighbor, and logistic regression model, suffer from low interpretabilities. This paper proposes an interpretable gene expression classifier (named iGEC) with an accurate and compact fuzzy rule base for microarray data analysis. The design of iGEC has three objectives to be simultaneously optimized: maximal classification accuracy, minimal number of rules, and minimal number of used genes. An "intelligent" genetic algorithm IGA is used to efficiently solve the design problem with a large number of tuning parameters. The performance of iGEC is evaluated using eight commonly-used data sets. It is shown that iGEC has an accurate, concise, and interpretable rule base (1.1 rules per class) on average in terms of test classification accuracy (87.9%), rule number (3.9), and used gene number (5.0). Moreover, iGEC not only has better performance than the existing fuzzy rule-based classifier in terms of the above-mentioned objectives, but also is more accurate than some existing non-rule-based classifiers.

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

    International Nuclear Information System (INIS)

    Rabbani, M.A.

    2005-01-01

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

  13. Evaluation of the gene-specific dye bias in cDNA microarray experiments.

    Science.gov (United States)

    Martin-Magniette, Marie-Laure; Aubert, Julie; Cabannes, Eric; Daudin, Jean-Jacques

    2005-05-01

    In cDNA microarray experiments all samples are labeled with either Cy3 or Cy5. Systematic and gene-specific dye bias effects have been observed in dual-color experiments. In contrast to systematic effects which can be corrected by a normalization method, the gene-specific dye bias is not completely suppressed and may alter the conclusions about the differentially expressed genes. The gene-specific dye bias is taken into account using an analysis of variance model. We propose an index, named label bias index, to measure the gene-specific dye bias. It requires at least two self-self hybridization cDNA microarrays. After lowess normalization we have found that the gene-specific dye bias is the major source of experimental variability between replicates. The ratio (R/G) may exceed 2. As a consequence false positive genes may be found in direct comparison without dye-swap. The stability of this artifact and its consequences on gene variance and on direct or indirect comparisons are addressed. http://www.inapg.inra.fr/ens_rech/mathinfo/recherche/mathematique

  14. mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling.

    Science.gov (United States)

    Alshamlan, Hala; Badr, Ghada; Alohali, Yousef

    2015-01-01

    An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.

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

    Science.gov (United States)

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

    2017-12-01

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

  16. Microarray Analysis of the Gene Expression Profile in Triethylene ...

    African Journals Online (AJOL)

    2018-01-24

    Jan 24, 2018 ... Metabolic, cellular, and developmental processes were the most affected biological functional annotations in both up‑ and down‑regulated transcripts. However, cell‑cell signaling, cell‑cell adhesion, cell cycle, induction of apoptosis, cell death, macrophage activation, ion transport, and responses to stress ...

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

    Science.gov (United States)

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

    2004-09-01

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

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

    Directory of Open Access Journals (Sweden)

    Hedegaard Jakob

    2009-07-01

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

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

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    Thomas Efferth

    2012-05-01

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

  20. Screening of FGF target genes in Xenopus by microarray: temporal dissection of the signalling pathway using a chemical inhibitor.

    Science.gov (United States)

    Chung, Hyeyoung A; Hyodo-Miura, Junko; Kitayama, Atsushi; Terasaka, Chie; Nagamune, Teruyuki; Ueno, Naoto

    2004-08-01

    Microarray is a powerful tool for analysing gene expression patterns in genome-wide view and has greatly contributed to our understanding of spatiotemporal embryonic development at the molecular level. Members of FGF (fibroblast growth factor) family play important roles in embryogenesis, e.g. in organogenesis, proliferation, differentiation, cell migration, angiogenesis, and wound healing. To dissect spatiotemporally the versatile roles of FGF during embryogenesis, we profiled gene expression in Xenopus embryo explants treated with SU5402, a chemical inhibitor specific to FGF receptor 1 (FGFR1), by microarray. We identified 38 genes that were down-regulated and 5 that were up-regulated in response to SU5402 treatment from stage 10.5-11.5 and confirmed their FGF-dependent transcription with RT-PCR analysis and whole-mount in situ hybridization (WISH). Among the 43 genes, we identified 26 as encoding novel proteins and investigated their spatial expression pattern by WISH. Genes whose expression patterns were similar to FGFR1 were further analysed to test whether any of them represented functional FGF target molecules. Here, we report two interesting genes: one is a component of the canonical Ras-MAPK pathway, similar to mammalian mig6 (mitogen-inducible gene 6) acting in muscle differentiation; the other, similar to GPCR4 (G-protein coupled receptor 4), is a promising candidate for a gastrulation movement regulator. These results demonstrate that our approach is a promising strategy for scanning the genes that are essential for the regulation of a diverse array of developmental processes.

  1. Informative Gene Selection for Cancer Classification with Microarray Data Using a Metaheuristic Framework

    Science.gov (United States)

    M, Pyingkodi; R, Thangarajan

    2018-02-26

    Objective: Cancer diagnosis is one of the most vital emerging clinical applications of microarray data. Due to the high dimensionality, gene selection is an important step for improving expression data classification performance. There is therefore a need for effective methods to select informative genes for prediction and diagnosis of cancer. The main objective of this research was to derive a heuristic approach to select highly informative genes. Methods: A metaheuristic approach with a Genetic Algorithm with Levy Flight (GA-LV) was applied for classification of cancer genes in microarrays. The experimental results were analyzed with five major cancer gene expression benchmark datasets. Result: GA-LV proved superior to GA and statistical approaches, with 100% accuracy for the dataset for Leukemia, Lung and Lymphoma. For Prostate and Colon datasets the GA-LV was 99.5% and 99.2% accurate, respectively. Conclusion: The experimental results show that the proposed approach is suitable for effective gene selection with all benchmark datasets, removing irrelevant and redundant genes to improve classification accuracy. Creative Commons Attribution License

  2. Quality control in microarray assessment of gene expression in human airway epithelium

    Directory of Open Access Journals (Sweden)

    Attiyeh Marc A

    2009-10-01

    Full Text Available Abstract Background Microarray technology provides a powerful tool for defining gene expression profiles of airway epithelium that lend insight into the pathogenesis of human airway disorders. The focus of this study was to establish rigorous quality control parameters to ensure that microarray assessment of the airway epithelium is not confounded by experimental artifact. Samples (total n = 223 of trachea, large and small airway epithelium were collected by fiberoptic bronchoscopy of 144 individuals and hybridized to Affymetrix microarrays. The pre- and post-chip quality control (QC criteria established, included: (1 RNA quality, assessed by RNA Integrity Number (RIN ≥ 7.0; (2 cRNA transcript integrity, assessed by signal intensity ratio of GAPDH 3' to 5' probe sets ≤ 3.0; and (3 the multi-chip normalization scaling factor ≤ 10.0. Results Of the 223 samples, all three criteria were assessed in 191; of these 184 (96.3% passed all three criteria. For the remaining 32 samples, the RIN was not available, and only the other two criteria were used; of these 29 (90.6% passed these two criteria. Correlation coefficients for pairwise comparisons of expression levels for 100 maintenance genes in which at least one array failed the QC criteria (average Pearson r = 0.90 ± 0.04 were significantly lower (p Conclusion Based on the aberrant maintenance gene data generated from samples failing the established QC criteria, we propose that the QC criteria outlined in this study can accurately distinguish high quality from low quality data, and can be used to delete poor quality microarray samples before proceeding to higher-order biological analyses and interpretation.

  3. DNA microarray-based experimental strategy for trustworthy expression profiling of the hippocampal genes by astaxanthin supplementation in adult mouse.

    Science.gov (United States)

    Yook, Jang Soo; Shibato, Junko; Rakwal, Randeep; Soya, Hideaki

    2016-03-01

    Naturally occurring astaxantin (ASX) is one of the noticeable carotenoid and dietary supplement, which has strong antioxidant and anti-inflammatory properties, and neuroprotective effects in the brain through crossing the blood-brain barrier. Specially, we are interested in the role of ASX as a brain food. Although ASX has been suggested to have potential benefit to the brain function, the underlying molecular mechanisms and events mediating such effect remain unknown. Here we examined molecular factors in the hippocampus of adult mouse fed ASX diets (0.1% and 0.5% doses) using DNA microarray (Agilent 4 × 44 K whole mouse genome chip) analysis. In this study, we described in detail our experimental workflow and protocol, and validated quality controls with the housekeeping gene expression (Gapdh and Beta-actin) on the dye-swap based approach to advocate our microarray data, which have been uploaded to Gene Expression Omnibus (accession number GSE62197) as a gene resource for the scientific community. This data will also form an important basis for further detailed experiments and bioinformatics analysis with an aim to unravel the potential molecular pathways or mechanisms underlying the positive effects of ASX supplementation on the brain, in particular the hippocampus.

  4. DNA microarray-based experimental strategy for trustworthy expression profiling of the hippocampal genes by astaxanthin supplementation in adult mouse

    Directory of Open Access Journals (Sweden)

    Jang Soo Yook

    2016-03-01

    Full Text Available Naturally occurring astaxantin (ASX is one of the noticeable carotenoid and dietary supplement, which has strong antioxidant and anti-inflammatory properties, and neuroprotective effects in the brain through crossing the blood–brain barrier. Specially, we are interested in the role of ASX as a brain food. Although ASX has been suggested to have potential benefit to the brain function, the underlying molecular mechanisms and events mediating such effect remain unknown. Here we examined molecular factors in the hippocampus of adult mouse fed ASX diets (0.1% and 0.5% doses using DNA microarray (Agilent 4 × 44 K whole mouse genome chip analysis. In this study, we described in detail our experimental workflow and protocol, and validated quality controls with the housekeeping gene expression (Gapdh and Beta-actin on the dye-swap based approach to advocate our microarray data, which have been uploaded to Gene Expression Omnibus (accession number GSE62197 as a gene resource for the scientific community. This data will also form an important basis for further detailed experiments and bioinformatics analysis with an aim to unravel the potential molecular pathways or mechanisms underlying the positive effects of ASX supplementation on the brain, in particular the hippocampus.

  5. GeneChip microarrays facilitate identification of Protease Nexin-1 as a target gene of the Prx2 (S8) homeoprotein.

    Science.gov (United States)

    Scott, Karen K; Norris, Russell A; Potter, S Steven; Norrington, David W; Baybo, Mary Ann; Hicklin, David M; Kern, Michael J

    2003-02-01

    The paired-related homeobox genes, Prx1 and Prx2, are important for normal skeletal and cardiovascular development as well as adult vascular remodeling. The identification and characterization of Prx downstream targets is crucial to understanding their function in normal developmental processes and congenital malformations. To identify Prx2 regulated genes, stably transfected NIH3T3 clones expressing Prx2 sense or antisense transcripts were generated. Expression profiles initially were established for two of the clones using Affymetrix GeneChip arrays. Over 6,400 genes were screened by the microarray approach, and approximately 500 genes differed in expression by a factor of two or more. Fifteen genes were chosen for further analysis. RT-PCR of the two transfectants used in the GeneChip analysis demonstrated that five out of the 15 genes were differentially expressed. However, after screening additional stable transfectant clones only one of the 15 genes, Protease Nexin-1 (PN-1), was differentially expressed. Subsequent Northern blot, RT-PCR, and further GeneChip analysis of additional stable transfectants confirmed that PN-1 expression is increased at least fivefold when Prx2 is overexpressed. It was demonstrated that Prx2 directly regulates PN-1 because (1) Prx2 binds to a cis element in the PN-1 promoter in vitro, and (2) Prx2 regulates the PN-1 promoter in transient transfection assays. The GeneChip analysis generated a prioritized list of other potential targets. The utility and limitations of cell culture models combined with microarray analysis for elucidating complex regulatory cascades are discussed.

  6. Growth hormone regulation of rat liver gene expression assessed by SSH and microarray.

    Science.gov (United States)

    Gardmo, Cissi; Swerdlow, Harold; Mode, Agneta

    2002-04-25

    The sexually dimorphic secretion of growth hormone (GH) that prevails in the rat leads to a sex-differentiated expression of GH target genes, particularly in the liver. We have used subtractive suppressive hybridization (SSH) to search for new target genes induced by the female-characteristic, near continuous, pattern of GH secretion. Microarrays and dot-blot hybridizations were used in an attempt to confirm differential ratios of expression of obtained SSH clones. Out of 173 unique SSH clones, 41 could be verified as differentially expressed. Among these, we identified 17 known genes not previously recognized as differentially regulated by the sex-specific GH pattern. Additional SSH clones may also represent genes subjected to sex-specific GH regulation since only transcripts abundantly expressed could be verified. Optimized analyses, specific for each gene, are required to fully characterize the degree of differential expression.

  7. Identification of differential expression of genes in hepatocellular carcinoma by suppression subtractive hybridization combined cDNA microarray.

    Science.gov (United States)

    Liu, Yuefang; Zhu, Xiaojing; Zhu, Jin; Liao, Shibing; Tang, Qi; Liu, Kaikun; Guan, Xiaohong; Zhang, Jianping; Feng, Zhenqing

    2007-10-01

    The genetic background of hepatocellular carcinoma (HCC) has yet to be completely understood. Here, we describe the application of suppression subtractive hybridization (SSH) coupled with cDNA microarray analysis for the isolation and identification of differential expression of genes in HCC. Twenty-six known genes were validated as up-regulated and 19 known genes as down-regulated in HCC. The known genes identified were found to have diverse functions. In addition to the overexpression of AFP, these genes (increased in the presence of HCC) are involved in many processes, such as transcription and protein biosynthesis (HNRPDL, PABPC1, POLR2K, SRP9, SNRPA, and six ribosomal protein genes including RPL8, RPL14, RPL41, RPS5, RPS17, RPS24), the metabolism of lipids and proteins (FADS1, ApoA-II, ApoM, FTL), cell proliferation (Syndecan-2, and Annexin A2), and signal transduction (LRRC28 and FMR1). Additionally, a glutathione-binding protein involved in the detoxification of methylglyoxal known as GLO1 and an enzyme which increases the formation of prostaglandin E(2) known as PLA2G10 were up-regulated in HCC. Among the underexpressed genes discovered in HCC, most were responsible for liver-synthesized proteins (fibrinogen, complement species, amyloid, albumin, haptoglobin, hemopexin and orosomucoid). The enzyme implicated in the biotransformation of CYP family members (LOC644587) was decreased. The genes coding enzymes ADH1C, ALDH6A1, ALDOB, Arginase and CES1 were also found. Additionally, we isolated a zinc transporter (Zip14) and a function-unknown gene named ZBTB11 (Zinc finger and BTB domain containing 11) which were underexpressed, and seven expression sequence tags deregulated in HCC without significant homology reported in the public database. Essentially, by using SSH combined with a cDNA microarray we have identified a number of genes associated with HCC, most of which have not been previously reported. Further characterization of these differentially expressed

  8. Genetic Bee Colony (GBC) algorithm: A new gene selection method for microarray cancer classification.

    Science.gov (United States)

    Alshamlan, Hala M; Badr, Ghada H; Alohali, Yousef A

    2015-06-01

    Naturally inspired evolutionary algorithms prove effectiveness when used for solving feature selection and classification problems. Artificial Bee Colony (ABC) is a relatively new swarm intelligence method. In this paper, we propose a new hybrid gene selection method, namely Genetic Bee Colony (GBC) algorithm. The proposed algorithm combines the used of a Genetic Algorithm (GA) along with Artificial Bee Colony (ABC) algorithm. The goal is to integrate the advantages of both algorithms. The proposed algorithm is applied to a microarray gene expression profile in order to select the most predictive and informative genes for cancer classification. In order to test the accuracy performance of the proposed algorithm, extensive experiments were conducted. Three binary microarray datasets are use, which include: colon, leukemia, and lung. In addition, another three multi-class microarray datasets are used, which are: SRBCT, lymphoma, and leukemia. Results of the GBC algorithm are compared with our recently proposed technique: mRMR when combined with the Artificial Bee Colony algorithm (mRMR-ABC). We also compared the combination of mRMR with GA (mRMR-GA) and Particle Swarm Optimization (mRMR-PSO) algorithms. In addition, we compared the GBC algorithm with other related algorithms that have been recently published in the literature, using all benchmark datasets. The GBC algorithm shows superior performance as it achieved the highest classification accuracy along with the lowest average number of selected genes. This proves that the GBC algorithm is a promising approach for solving the gene selection problem in both binary and multi-class cancer classification. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    Raftery Adrian E

    2005-07-01

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

  10. Analysis of ripening-related gene expression in papaya using an Arabidopsis-based microarray

    Science.gov (United States)

    2012-01-01

    Background Papaya (Carica papaya L.) is a commercially important crop that produces climacteric fruits with a soft and sweet pulp that contain a wide range of health promoting phytochemicals. Despite its importance, little is known about transcriptional modifications during papaya fruit ripening and their control. In this study we report the analysis of ripe papaya transcriptome by using a cross-species (XSpecies) microarray technique based on the phylogenetic proximity between papaya and Arabidopsis thaliana. Results Papaya transcriptome analyses resulted in the identification of 414 ripening-related genes with some having their expression validated by qPCR. The transcription profile was compared with that from ripening tomato and grape. There were many similarities between papaya and tomato especially with respect to the expression of genes encoding proteins involved in primary metabolism, regulation of transcription, biotic and abiotic stress and cell wall metabolism. XSpecies microarray data indicated that transcription factors (TFs) of the MADS-box, NAC and AP2/ERF gene families were involved in the control of papaya ripening and revealed that cell wall-related gene expression in papaya had similarities to the expression profiles seen in Arabidopsis during hypocotyl development. Conclusion The cross-species array experiment identified a ripening-related set of genes in papaya allowing the comparison of transcription control between papaya and other fruit bearing taxa during the ripening process. PMID:23256600

  11. Validation and characterization of DNA microarray gene expression data distribution and associated moments

    Directory of Open Access Journals (Sweden)

    Chang Xiaoqing

    2010-11-01

    Full Text Available Abstract Background The data from DNA microarrays are increasingly being used in order to understand effects of different conditions, exposures or diseases on the modulation of the expression of various genes in a biological system. This knowledge is then further used in order to generate molecular mechanistic hypotheses for an organism when it is exposed to different conditions. Several different methods have been proposed to analyze these data under different distributional assumptions on gene expression. However, the empirical validation of these assumptions is lacking. Results Best fit hypotheses tests, moment-ratio diagrams and relationships between the different moments of the distribution of the gene expression was used to characterize the observed distributions. The data are obtained from the publicly available gene expression database, Gene Expression Omnibus (GEO to characterize the empirical distributions of gene expressions obtained under varying experimental situations each of which providing relatively large number of samples for hypothesis testing. All data were obtained from either of two microarray platforms - the commercial Affymetrix mouse 430.2 platform and a non-commercial Rosetta/Merck one. The data from each platform were preprocessed in the same manner. Conclusions The null hypotheses for goodness of fit for all considered univariate theoretical probability distributions (including the Normal distribution are rejected for more than 50% of probe sets on the Affymetrix microarray platform at a 95% confidence level, suggesting that under the tested conditions a priori assumption of any of these distributions across all probe sets is not valid. The pattern of null hypotheses rejection was different for the data from Rosetta/Merck platform with only around 20% of the probe sets failing the logistic distribution goodness-of-fit test. We find that there are statistically significant (at 95% confidence level based on the F

  12. Performance comparison of two microarray platforms to assess differential gene expression in human monocyte and macrophage cells

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    Montalescot Gilles

    2008-06-01

    Full Text Available Abstract Background In this study we assessed the respective ability of Affymetrix and Illumina microarray methodologies to answer a relevant biological question, namely the change in gene expression between resting monocytes and macrophages derived from these monocytes. Five RNA samples for each type of cell were hybridized to the two platforms in parallel. In addition, a reference list of differentially expressed genes (DEG was generated from a larger number of hybridizations (mRNA from 86 individuals using the RNG/MRC two-color platform. Results Our results show an important overlap of the Illumina and Affymetrix DEG lists. In addition, more than 70% of the genes in these lists were also present in the reference list. Overall the two platforms had very similar performance in terms of biological significance, evaluated by the presence in the DEG lists of an excess of genes belonging to Gene Ontology (GO categories relevant for the biology of monocytes and macrophages. Our results support the conclusion of the MicroArray Quality Control (MAQC project that the criteria used to constitute the DEG lists strongly influence the degree of concordance among platforms. However the importance of prioritizing genes by magnitude of effect (fold change rather than statistical significance (p-value to enhance cross-platform reproducibility recommended by the MAQC authors was not supported by our data. Conclusion Functional analysis based on GO enrichment demonstrates that the 2 compared technologies delivered very similar results and identified most of the relevant GO categories enriched in the reference list.

  13. Evaluation of an expanded microarray for detecting antibiotic resistance genes in a broad range of gram-negative bacterial pathogens.

    Science.gov (United States)

    Card, Roderick; Zhang, Jiancheng; Das, Priya; Cook, Charlotte; Woodford, Neil; Anjum, Muna F

    2013-01-01

    A microarray capable of detecting genes for resistance to 75 clinically relevant antibiotics encompassing 19 different antimicrobial classes was tested on 132 Gram-negative bacteria. Microarray-positive results correlated >91% with antimicrobial resistance phenotypes, assessed using British Society for Antimicrobial Chemotherapy clinical breakpoints; the overall test specificity was >83%. Microarray-positive results without a corresponding resistance phenotype matched 94% with PCR results, indicating accurate detection of genes present in the respective bacteria by microarray when expression was low or absent and, hence, undetectable by susceptibility testing. The low sensitivity and negative predictive values of the microarray results for identifying resistance to some antimicrobial resistance classes are likely due to the limited number of resistance genes present on the current microarray for those antimicrobial agents or to mutation-based resistance mechanisms. With regular updates, this microarray can be used for clinical diagnostics to help accurate therapeutic options to be taken following infection with multiple-antibiotic-resistant Gram-negative bacteria and prevent treatment failure.

  14. Genes expression by using cDNA Microarray in Whallak-tang

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    Cheol-kyung Sin

    2008-12-01

    Full Text Available Objective : This study was undertaken to determine the effect of Whallak-tang on expression of CD/cytokine Genes. Methods : The expression of CD/Cytokine Genes were examined by cDNA microarray using the human mast cell line(HMC-l. Results : The expression of ATP5F1, FLJ20671, unknown, KIAA0342, OAS2, unknown genes were increased in 200~300% range. The expression of unknown, MDS006, IFITM1, MRPL3, ZNF207, FTH1, FBP1, NRGN, NR1H2, KIAA0747 genes were decreased in 0~33% range. Conclusion : These results would provide important basic data on the possibility of the clinical treatment of Whallaktang in musculoskeletal disease.

  15. Specific mutation screening of TP53 gene by low-density DNA microarray

    Science.gov (United States)

    Rangel-López, Angélica; Méndez-Tenorio, Alfonso; Beattie, Kenneth L; Maldonado, Rogelio; Mendoza, Patricia; Vázquez, Guelaguetza; Pérez-Plasencia, Carlos; Sánchez, Martha; Navarro, Guillermo; Salcedo, Mauricio

    2009-01-01

    TP53 is the most commonly mutated gene in human cancers. Approximately 90% of mutations in this gene are localized between domains encoding exons 5 to 8. The aim of this investigation was to examine the ability of the low density DNA microarray with the assistance of double tandem hybridization platform to characterize TP53 mutational hotspots in exons 5, 7, and 8 of the TP53. Nineteen capture probes specific to each potential mutation site were designed to hybridize to specific site. Virtual hybridization was used to predict the stability of hybridization of each capture probe with the target. Thirty-three DNA samples from different sources were analyzed for mutants in these exons. A total of 32 codon substitutions were found by DNA sequencing. 24 of them a showed a perfect correlation with the hybridization pattern system and DNA sequencing analysis of the regions scanned. Although in this work we directed our attention to some of the most representative mutations of the TP53 gene, the results suggest that this microarray system proved to be a rapid, reliable, and effective method for screening all the mutations in TP53 gene. PMID:24198462

  16. OpWise: Operons aid the identification of differentially expressed genes in bacterial microarray experiments

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    Arkin Adam P

    2006-01-01

    Full Text Available Abstract Background Differentially expressed genes are typically identified by analyzing the variation between replicate measurements. These procedures implicitly assume that there are no systematic errors in the data even though several sources of systematic error are known. Results OpWise estimates the amount of systematic error in bacterial microarray data by assuming that genes in the same operon have matching expression patterns. OpWise then performs a Bayesian analysis of a linear model to estimate significance. In simulations, OpWise corrects for systematic error and is robust to deviations from its assumptions. In several bacterial data sets, significant amounts of systematic error are present, and replicate-based approaches overstate the confidence of the changers dramatically, while OpWise does not. Finally, OpWise can identify additional changers by assigning genes higher confidence if they are consistent with other genes in the same operon. Conclusion Although microarray data can contain large amounts of systematic error, operons provide an external standard and allow for reasonable estimates of significance. OpWise is available at http://microbesonline.org/OpWise.

  17. Determination of the differentially expressed genes in microarray experiments using local FDR

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    Daudin J-J

    2004-09-01

    Full Text Available Abstract Background Thousands of genes in a genomewide data set are tested against some null hypothesis, for detecting differentially expressed genes in microarray experiments. The expected proportion of false positive genes in a set of genes, called the False Discovery Rate (FDR, has been proposed to measure the statistical significance of this set. Various procedures exist for controlling the FDR. However the threshold (generally 5% is arbitrary and a specific measure associated with each gene would be worthwhile. Results Using process intensity estimation methods, we define and give estimates of the local FDR, which may be considered as the probability for a gene to be a false positive. After a global assessment rule controlling the false positive error, the local FDR is a valuable guideline for deciding wether a gene is differentially expressed. The interest of the method is illustrated on three well known data sets. A R routine for computing local FDR estimates from p-values is available at http://www.inapg.fr/ens_rech/mathinfo/recherche/mathematique/outil.html. Conclusions The local FDR associated with each gene measures the probability that it is a false positive. It gives the opportunity to compute the FDR of any given group of clones (of the same gene or genes pertaining to the same regulation network or the same chromosomic region.

  18. Determination of the differentially expressed genes in microarray experiments using local FDR.

    Science.gov (United States)

    Aubert, J; Bar-Hen, A; Daudin, J J; Robin, S

    2004-09-06

    Thousands of genes in a genomewide data set are tested against some null hypothesis, for detecting differentially expressed genes in microarray experiments. The expected proportion of false positive genes in a set of genes, called the False Discovery Rate (FDR), has been proposed to measure the statistical significance of this set. Various procedures exist for controlling the FDR. However the threshold (generally 5%) is arbitrary and a specific measure associated with each gene would be worthwhile. Using process intensity estimation methods, we define and give estimates of the local FDR, which may be considered as the probability for a gene to be a false positive. After a global assessment rule controlling the false positive error, the local FDR is a valuable guideline for deciding wether a gene is differentially expressed. The interest of the method is illustrated on three well known data sets. A R routine for computing local FDR estimates from p-values is available at http://www.inapg.fr/ens_rech/mathinfo/recherche/mathematique/outil.html. The local FDR associated with each gene measures the probability that it is a false positive. It gives the opportunity to compute the FDR of any given group of clones (of the same gene) or genes pertaining to the same regulation network or the same chromosomic region.

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

    Science.gov (United States)

    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.

  20. Incorporating gene ontology into fuzzy relational clustering of microarray gene expression data.

    Science.gov (United States)

    Paul, Animesh Kumar; Shill, Pintu Chandra

    2018-01-01

    The product of gene expression works together in the cell for each living organism in order to achieve different biological processes. Many proteins are involved in different roles depending on the environment of the organism for the functioning of the cell. In this paper, we propose gene ontology (GO) annotations based semi-supervised clustering algorithm called GO fuzzy relational clustering (GO-FRC) where one gene is allowed to be assigned to multiple clusters which are the most biologically relevant behavior of genes. In the clustering process, GO-FRC utilizes useful biological knowledge which is available in the form of a gene ontology, as a prior knowledge along with the gene expression data. The prior knowledge helps to improve the coherence of the groups concerning the knowledge field. The proposed GO-FRC has been tested on the two yeast (Saccharomyces cerevisiae) expression profiles datasets (Eisen and Dream5 yeast datasets) and compared with other state-of-the-art clustering algorithms. Experimental results imply that GO-FRC is able to produce more biologically relevant clusters with the use of the small amount of GO annotations. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Identification of Putative Ortholog Gene Blocks Involved in Gestant and Lactating Mammary Gland Development: A Rodent Cross-Species Microarray Transcriptomics Approach

    Science.gov (United States)

    Rodríguez-Cruz, Maricela; Coral-Vázquez, Ramón M.; Hernández-Stengele, Gabriel; Sánchez, Raúl; Salazar, Emmanuel; Sanchez-Muñoz, Fausto; Encarnación-Guevara, Sergio; Ramírez-Salcedo, Jorge

    2013-01-01

    The mammary gland (MG) undergoes functional and metabolic changes during the transition from pregnancy to lactation, possibly by regulation of conserved genes. The objective was to elucidate orthologous genes, chromosome clusters and putative conserved transcriptional modules during MG development. We analyzed expression of 22,000 transcripts using murine microarrays and RNA samples of MG from virgin, pregnant, and lactating rats by cross-species hybridization. We identified 521 transcripts differentially expressed; upregulated in early (78%) and midpregnancy (89%) and early lactation (64%), but downregulated in mid-lactation (61%). Putative orthologous genes were identified. We mapped the altered genes to orthologous chromosomal locations in human and mouse. Eighteen sets of conserved genes associated with key cellular functions were revealed and conserved transcription factor binding site search entailed possible coregulation among all eight block sets of genes. This study demonstrates that the use of heterologous array hybridization for screening of orthologous gene expression from rat revealed sets of conserved genes arranged in chromosomal order implicated in signaling pathways and functional ontology. Results demonstrate the utilization power of comparative genomics and prove the feasibility of using rodent microarrays to identification of putative coexpressed orthologous genes involved in the control of human mammary gland development. PMID:24288657

  2. Functionalization of Poly- (methyl methacrylate) (PMMA) as a substrate for DNA microarrays

    DEFF Research Database (Denmark)

    Fixe, A.F.; Dufva, Hans Martin; Telleman, Pieter

    2004-01-01

    A chemical procedure was developed to functionalize poly(methyl methacrylate) (PMMA) substrates. PMMA is reacted with hexamethylene diamine to yield an aminated surface for immobilizing DNA in microarrays. The density of primary NH2 groups was 0.29 nmol/cm(2). The availability of these primary...

  3. The prediction of interferon treatment effects based on time series microarray gene expression profiles

    Directory of Open Access Journals (Sweden)

    Wei Chao-Chun

    2008-08-01

    Full Text Available Abstract Background The status of a disease can be reflected by specific transcriptional profiles resulting from the induction or repression activity of a number of genes. Here, we proposed a time-dependent diagnostic model to predict the treatment effects of interferon and ribavirin to HCV infected patients by using time series microarray gene expression profiles of a published study. Methods In the published study, 33 African-American (AA and 36 Caucasian American (CA patients with chronic HCV genotype 1 infection received pegylated interferon and ribavirin therapy for 28 days. HG-U133A GeneChip containing 22283 probes was used to analyze the global gene expression in peripheral blood mononuclear cells (PBMC of all the patients on day 0 (pretreatment, 1, 2, 7, 14, and 28. According to the decrease of HCV RNA levels on day 28, two categories of responses were defined: good and poor. A voting method based on Student's t test, Wilcoxon test, empirical Bayes test and significance analysis of microarray was used to identify differentially expressed genes. A time-dependent diagnostic model based on C4.5 decision tree was constructed to predict the treatment outcome. This model not only utilized the gene expression profiles before the treatment, but also during the treatment. Leave-one-out cross validation was used to evaluate the performance of the model. Results The model could correctly predict all Caucasian American patients' treatment effects at very early time point. The prediction accuracy of African-American patients achieved 85.7%. In addition, thirty potential biomarkers which may play important roles in response to interferon and ribavirin were identified. Conclusion Our method provides a way of using time series gene expression profiling to predict the treatment effect of pegylated interferon and ribavirin therapy on HCV infected patients. Similar experimental and bioinformatical strategies may be used to improve treatment decisions for

  4. An Entropy-based gene selection method for cancer classification using microarray data

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    Krishnan Arun

    2005-03-01

    Full Text Available Abstract Background Accurate diagnosis of cancer subtypes remains a challenging problem. Building classifiers based on gene expression data is a promising approach; yet the selection of non-redundant but relevant genes is difficult. The selected gene set should be small enough to allow diagnosis even in regular clinical laboratories and ideally identify genes involved in cancer-specific regulatory pathways. Here an entropy-based method is proposed that selects genes related to the different cancer classes while at the same time reducing the redundancy among the genes. Results The present study identifies a subset of features by maximizing the relevance and minimizing the redundancy of the selected genes. A merit called normalized mutual information is employed to measure the relevance and the redundancy of the genes. In order to find a more representative subset of features, an iterative procedure is adopted that incorporates an initial clustering followed by data partitioning and the application of the algorithm to each of the partitions. A leave-one-out approach then selects the most commonly selected genes across all the different runs and the gene selection algorithm is applied again to pare down the list of selected genes until a minimal subset is obtained that gives a satisfactory accuracy of classification. The algorithm was applied to three different data sets and the results obtained were compared to work done by others using the same data sets Conclusion This study presents an entropy-based iterative algorithm for selecting genes from microarray data that are able to classify various cancer sub-types with high accuracy. In addition, the feature set obtained is very compact, that is, the redundancy between genes is reduced to a large extent. This implies that classifiers can be built with a smaller subset of genes.

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

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    Pablo Moscato

    2013-05-01

    Full Text Available 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.

  6. [Combining SSH and cDNA microarray for identification of lung cancer related genes].

    Science.gov (United States)

    Fan, Baoxing; Zhang, Kaitai; Da, Jiping; Xie, Ling; Wang, Shengqi; Wu, Dechang

    2003-04-20

    To screen and identify differentially expressed genes among lung cancer tissues, paracancerous pulmonary tissues and some other kinds of tumor tissues using suppression subtractive hybridization (SSH) and cDNA Microarray. One cDNA chip was made by gathering clones of three differentially expressed cDNA libraries which came from BEP2D cell lines during three different malignant transformed phases. Then the clones were hybridizated with cDNA probes which extracted from 15 cases of lung cancer tissues, 5 cases of paracancerous pulmonary tissues and 24 cases of other 8 kinds of tumor tissues respectively. Twenty-six cDNAs were obtained which expressed higher in lung cancer tissues than that in paracancerous pulmonary tissues. Thirty-one cDNAs expressed remarkably higher in paracancerous tissues than those in cancer tissues. Compared with other 8 kinds of tumors, paracancerous tissues had 63 overexpressed cDNAs and lung cancer tissues had 87 overexpressed cDNAs. The combination of SSH and cDNA microarray is rapid and effective for screening and identification of differentially expressed genes in different samples. It may be potentially useful for diagnosis of lung cancer to further study the differentially expressed genes among lung cancer tissues, paracancerous pulmonary tissues and other tumor tissues.

  7. Microarray Analysis Reveals Altered Lipid and Glucose Metabolism Genes in Differentiated, Ritonavir-Treated 3T3-L1 Adipocytes.

    Science.gov (United States)

    Loonam, Cathriona R; O'Dell, Sandra D; Sharp, Paul A; Mullen, Anne

    2016-01-01

    HIV lipodystrophy is characterised by abnormal adipose tissue distribution and metabolism, as a result of altered adipocyte function and gene expression. The protease inhibitor ritonavir is associated with the development of lipodystrophy. Quantifying changes in adipogenic gene expression in the presence of ritonavir may help to identify therapeutic targets for HIV lipodystrophy. Affymetrix Mouse Genome 430 2.0 oligonucleotide microarray was used to investigate gene expression in 3T3-L1 adipocytes treated with 20 µmol/l ritonavir or vehicle control (ethanol). Pparg, Adipoq, Retn and Il6 expression were validated by real time RT-PCR. Transcriptional signalling through PPAR-γ was investigated using a DNA-binding ELISA. Changes in adipocyte function were investigated through secreted adiponectin quantification using ELISA and Oil Red O staining for triglyceride storage. Expression of 389 genes was altered by more than 5-fold in the presence of ritonavir (all P Gene ontology analysis revealed down-regulation of genes responsible for adipocyte triglyceride accumulation including complement factor D (Cfd; 238.42-fold), Cidec (73.75-fold) and Pparg (5.63-fold). Glucose transport genes were also down-regulated including Adipoq (24.42-fold) and Glut4 (13.36-fold), while Il6 was up-regulated (10.39-fold). PPAR-γ regulatory genes Cebpa (11.33-fold) and liver-X-receptor α (Nr1h3) were down-regulated. Changes in Pparg, Adipoq and Il6 were confirmed by RT-PCR. PPAR-γ binding to its nuclear consensus site, adiponectin secretion and triglyceride accumulation were all reduced by ritonavir. Ritonavir had a significant effect on expression of genes involved in adipocyte differentiation, lipid accumulation and glucose metabolism. Down-regulation of Pparg may be mediated by changes in Cebpa, Lcn2 and Nr1h3.

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

    Hu, Wenchao; Liu, Yuting; Yan, Jun

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Feldman Mark

    2008-12-01

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

  11. Functional interaction analysis of GM1-related carbohydrates and Vibrio cholerae toxins using carbohydrate microarray.

    Science.gov (United States)

    Kim, Chang Sup; Seo, Jeong Hyun; Cha, Hyung Joon

    2012-08-07

    The development of analytical tools is important for understanding the infection mechanisms of pathogenic bacteria or viruses. In the present work, a functional carbohydrate microarray combined with a fluorescence immunoassay was developed to analyze the interactions of Vibrio cholerae toxin (ctx) proteins and GM1-related carbohydrates. Ctx proteins were loaded onto the surface-immobilized GM1 pentasaccharide and six related carbohydrates, and their binding affinities were detected immunologically. The analysis of the ctx-carbohydrate interactions revealed that the intrinsic selectivity of ctx was GM1 pentasaccharide ≫ GM2 tetrasaccharide > asialo GM1 tetrasaccharide ≥ GM3trisaccharide, indicating that a two-finger grip formation and the terminal monosaccharides play important roles in the ctx-GM1 interaction. In addition, whole cholera toxin (ctxAB(5)) had a stricter substrate specificity and a stronger binding affinity than only the cholera toxin B subunit (ctxB). On the basis of the quantitative analysis, the carbohydrate microarray showed the sensitivity of detection of the ctxAB(5)-GM1 interaction with a limit-of-detection (LOD) of 2 ng mL(-1) (23 pM), which is comparable to other reported high sensitivity assay tools. In addition, the carbohydrate microarray successfully detected the actual toxin directly secreted from V. cholerae, without showing cross-reactivity to other bacteria. Collectively, these results demonstrate that the functional carbohydrate microarray is suitable for analyzing toxin protein-carbohydrate interactions and can be applied as a biosensor for toxin detection.

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

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    Nolwenn M Dheilly

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

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

    International Nuclear Information System (INIS)

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

    2001-01-01

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

  14. [Research on the relevance between the virulent genes differential expression and pathogenecity of Leptospira with microarray].

    Science.gov (United States)

    Yu, De-li; Bao, Lang

    2015-01-01

    To find the change of virulent gene expression and to analyze the relevance between the virulent change and the gene expression. Grouped guinea pigs were inoculated with 1 mL Leptospira cultured in vivo, Leptospira cultured in vitro and the Leptospira culture medium through abdominal subcutaneous respectively. The survival rate, body mass and temperature change of guinea pigs in different groups were measured within 15 d after the inoculation, then the survived guinea pigs were scarified, and the organ coefficient was also measured to know the virulence of Leptospira cultured in different environment. The amplified gene segments from Leptospira were used as probes and wrote the microarray. The total RNA was extracted from Leptospira standard strain cultured in culture medium and guinea pigs. After reverse transcription to cDNA, they were labeled with Cy3 and Cy5 respectively. Labeled cDNA was mixed and hybridized with the microarray. The hybridized mircroarray was scanned and analysed. The survival rate of inoculated guinea pig was different from group to group (in vivo group: 0%; in vitro group: 88.9%; culture medium group: 100%). The guinea pigs in vivo group had a higher temperature (PLeptospira: LA1027, LA1029, LA4004, LA3050, LA3540, LA0327, LA0378, LA1650, LA3937, LA2089, LA2144, LA3576, LA0011 and gene of Loa22 were up regulation after continuously cultured in guinea pigs. The pathogenic ability of Leptospira cultured in different environment is different and the gene expression of Leptospira is different between in vivo and in vitro as well. The understanding of the meaning of this change might help to know the pathogenecity of Leptospira.

  15. Microarray-based approach identifies microRNAs and their target functional patterns in polycystic kidney disease

    Directory of Open Access Journals (Sweden)

    Boehn Susanne NE

    2008-12-01

    Full Text Available Abstract Background MicroRNAs (miRNAs play key roles in mammalian gene expression and several cellular processes, including differentiation, development, apoptosis and cancer pathomechanisms. Recently the biological importance of primary cilia has been recognized in a number of human genetic diseases. Numerous disorders are related to cilia dysfunction, including polycystic kidney disease (PKD. Although involvement of certain genes and transcriptional networks in PKD development has been shown, not much is known how they are regulated molecularly. Results Given the emerging role of miRNAs in gene expression, we explored the possibilities of miRNA-based regulations in PKD. Here, we analyzed the simultaneous expression changes of miRNAs and mRNAs by microarrays. 935 genes, classified into 24 functional categories, were differentially regulated between PKD and control animals. In parallel, 30 miRNAs were differentially regulated in PKD rats: our results suggest that several miRNAs might be involved in regulating genetic switches in PKD. Furthermore, we describe some newly detected miRNAs, miR-31 and miR-217, in the kidney which have not been reported previously. We determine functionally related gene sets, or pathways to reveal the functional correlation between differentially expressed mRNAs and miRNAs. Conclusion We find that the functional patterns of predicted miRNA targets and differentially expressed mRNAs are similar. Our results suggest an important role of miRNAs in specific pathways underlying PKD.

  16. Association Study between BDNF Gene Polymorphisms and Autism by Three-Dimensional Gel-Based Microarray

    Directory of Open Access Journals (Sweden)

    Zuhong Lu

    2009-06-01

    Full Text Available Single nucleotide polymorphisms (SNPs are important markers which can be used in association studies searching for susceptible genes of complex diseases. High-throughput methods are needed for SNP genotyping in a large number of samples. In this study, we applied polyacrylamide gel-based microarray combined with dual-color hybridization for association study of four BDNF polymorphisms with autism. All the SNPs in both patients and controls could be analyzed quickly and correctly. Among four SNPs, only C270T polymorphism showed significant differences in the frequency of the allele (χ2 = 7.809, p = 0.005 and genotype (χ2 = 7.800, p = 0.020. In the haplotype association analysis, there was significant difference in global haplotype distribution between the groups (χ2 = 28.19,p = 3.44e-005. We suggest that BDNF has a possible role in the pathogenesis of autism. The study also show that the polyacrylamide gel-based microarray combined with dual-color hybridization is a rapid, simple and high-throughput method for SNPs genotyping, and can be used for association study of susceptible gene with disorders in large samples.

  17. Tissue-Based Microarray Expression of Genes Predictive of Metastasis in Uveal Melanoma and Differentially Expressed in Metastatic Uveal Melanoma

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    Hakan Demirci

    2013-01-01

    Full Text Available Purpose: To screen the microarray expression of CDH1, ECM1, EIF1B, FXR1, HTR2B, ID2, LMCD1, LTA4H, MTUS1, RAB31, ROBO1, and SATB1 genes which are predictive of primary uveal melanoma metastasis, and NFKB2, PTPN18, MTSS1, GADD45B, SNCG, HHIP, IL12B, CDK4, RPLP0, RPS17, RPS12 genes that are differentially expressed in metastatic uveal melanoma in normal whole human blood and tissues prone to metastatic involvement by uveal melanoma. Methods: We screened the GeneNote and GNF BioGPS databases for microarray analysis of genes predictive of primary uveal melanoma metastasis and those differentially expressed in metastatic uveal melanoma in normal whole blood, liver, lung and skin. Results: Microarray analysis showed expression of all 22 genes in normal whole blood, liver, lung and skin, which are the most common sites of metastases. In the GNF BioGPS database, data for expression of the HHIP gene in normal whole blood and skin was not complete. Conclusions: Microarray analysis of genes predicting systemic metastasis of uveal melanoma and genes differentially expressed in metastatic uveal melanoma may not be used as a biomarker for metastasis in whole blood, liver, lung, and skin. Their expression in tissues prone to metastasis may suggest that they play a role in tropism of uveal melanoma metastasis to these tissues.

  18. Discovering time-lagged rules from microarray data using gene profile classifiers

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    Ponzoni Ignacio

    2011-04-01

    Full Text Available Abstract Background Gene regulatory networks have an essential role in every process of life. In this regard, the amount of genome-wide time series data is becoming increasingly available, providing the opportunity to discover the time-delayed gene regulatory networks that govern the majority of these molecular processes. Results This paper aims at reconstructing gene regulatory networks from multiple genome-wide microarray time series datasets. In this sense, a new model-free algorithm called GRNCOP2 (Gene Regulatory Network inference by Combinatorial OPtimization 2, which is a significant evolution of the GRNCOP algorithm, was developed using combinatorial optimization of gene profile classifiers. The method is capable of inferring potential time-delay relationships with any span of time between genes from various time series datasets given as input. The proposed algorithm was applied to time series data composed of twenty yeast genes that are highly relevant for the cell-cycle study, and the results were compared against several related approaches. The outcomes have shown that GRNCOP2 outperforms the contrasted methods in terms of the proposed metrics, and that the results are consistent with previous biological knowledge. Additionally, a genome-wide study on multiple publicly available time series data was performed. In this case, the experimentation has exhibited the soundness and scalability of the new method which inferred highly-related statistically-significant gene associations. Conclusions A novel method for inferring time-delayed gene regulatory networks from genome-wide time series datasets is proposed in this paper. The method was carefully validated with several publicly available data sets. The results have demonstrated that the algorithm constitutes a usable model-free approach capable of predicting meaningful relationships between genes, revealing the time-trends of gene regulation.

  19. Feature selection and classification for microarray data analysis: Evolutionary methods for identifying predictive genes

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    Aitken Stuart

    2005-06-01

    Full Text Available Abstract Background In the clinical context, samples assayed by microarray are often classified by cell line or tumour type and it is of interest to discover a set of genes that can be used as class predictors. The leukemia dataset of Golub et al. 1 and the NCI60 dataset of Ross et al. 2 present multiclass classification problems where three tumour types and nine cell lines respectively must be identified. We apply an evolutionary algorithm to identify the near-optimal set of predictive genes that classify the data. We also examine the initial gene selection step whereby the most informative genes are selected from the genes assayed. Results In the absence of feature selection, classification accuracy on the training data is typically good, but not replicated on the testing data. Gene selection using the RankGene software 3 is shown to significantly improve performance on the testing data. Further, we show that the choice of feature selection criteria can have a significant effect on accuracy. The evolutionary algorithm is shown to perform stably across the space of possible parameter settings – indicating the robustness of the approach. We assess performance using a low variance estimation technique, and present an analysis of the genes most often selected as predictors. Conclusion The computational methods we have developed perform robustly and accurately, and yield results in accord with clinical knowledge: A Z-score analysis of the genes most frequently selected identifies genes known to discriminate AML and Pre-T ALL leukemia. This study also confirms that significantly different sets of genes are found to be most discriminatory as the sample classes are refined.

  20. Specific mutation screening of TP53 gene by low-density DNA microarray

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    Angélica Rangel-López

    2009-01-01

    Full Text Available Angélica Rangel-López1–3, Alfonso Méndez-Tenorio3, Kenneth L Beattie4, Rogelio Maldonado3, Patricia Mendoza1, Guelaguetza Vázquez1, Carlos Pérez-Plasencia5, Martha Sánchez2, Guillermo Navarro6, Mauricio Salcedo11Laboratorio de Oncología Genómica, Unidad de Investigación Médica en Enfermedades Oncológicas, Hospital de Oncología, CMN Siglo XXI-IMSS, Mexico City, Mexico; 2Unidad de Investigación Médica en Enfermedades Nefrológicas, Hospital de Especialidades, CMN Siglo XXI-IMSS, Mexico City; Mexico; 3Laboratorio de Biotecnología y Bioinformática Genómica, Escuela Nacional de Ciencias Biológicas, IPN Mexico City, Mexico; 4Amerigenics, Inc., Crossville, TN, USA; 5Unidad de Investigación Biomédica en Cáncer, Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México UNAM, Instituto Nacional de Cancerología INCAN, Mexico City, Mexico; 6Laboratorio de Organometálicos UNAM, Mexico City, MexicoAbstract: TP53 is the most commonly mutated gene in human cancers. Approximately 90% of mutations in this gene are localized between domains encoding exons 5 to 8. The aim of this investigation was to examine the ability of the low density DNA microarray with the assistance of double tandem hybridization platform to characterize TP53 mutational hotspots in exons 5, 7, and 8 of the TP53. Nineteen capture probes specific to each potential mutation site were designed to hybridize to specific site. Virtual hybridization was used to predict the stability of hybridization of each capture probe with the target. Thirty-three DNA samples from different sources were analyzed for mutants in these exons. A total of 32 codon substitutions were found by DNA sequencing. 24 of them a showed a perfect correlation with the hybridization pattern system and DNA sequencing analysis of the regions scanned. Although in this work we directed our attention to some of the most representative mutations of the TP503 gene, the results suggest

  1. Ultrafiltration and Microarray for Detection of Microbial Source Tracking Marker and Pathogen Genes in Riverine and Marine Systems.

    Science.gov (United States)

    Li, Xiang; Harwood, Valerie J; Nayak, Bina; Weidhaas, Jennifer L

    2016-01-04

    Pathogen identification and microbial source tracking (MST) to identify sources of fecal pollution improve evaluation of water quality. They contribute to improved assessment of human health risks and remediation of pollution sources. An MST microarray was used to simultaneously detect genes for multiple pathogens and indicators of fecal pollution in freshwater, marine water, sewage-contaminated freshwater and marine water, and treated wastewater. Dead-end ultrafiltration (DEUF) was used to concentrate organisms from water samples, yielding a recovery efficiency of >95% for Escherichia coli and human polyomavirus. Whole-genome amplification (WGA) increased gene copies from ultrafiltered samples and increased the sensitivity of the microarray. Viruses (adenovirus, bocavirus, hepatitis A virus, and human polyomaviruses) were detected in sewage-contaminated samples. Pathogens such as Legionella pneumophila, Shigella flexneri, and Campylobacter fetus were detected along with genes conferring resistance to aminoglycosides, beta-lactams, and tetracycline. Nonmetric dimensional analysis of MST marker genes grouped sewage-spiked freshwater and marine samples with sewage and apart from other fecal sources. The sensitivity (percent true positives) of the microarray probes for gene targets anticipated in sewage was 51 to 57% and was lower than the specificity (percent true negatives; 79 to 81%). A linear relationship between gene copies determined by quantitative PCR and microarray fluorescence was found, indicating the semiquantitative nature of the MST microarray. These results indicate that ultrafiltration coupled with WGA provides sufficient nucleic acids for detection of viruses, bacteria, protozoa, and antibiotic resistance genes by the microarray in applications ranging from beach monitoring to risk assessment. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

  2. Development of peptide-functionalized synthetic hydrogel microarrays for stem cell and tissue engineering applications.

    Science.gov (United States)

    Jia, Jia; Coyle, Robert C; Richards, Dylan J; Berry, Christopher Lloyd; Barrs, Ryan Walker; Biggs, Joshua; James Chou, C; Trusk, Thomas C; Mei, Ying

    2016-11-01

    Synthetic polymer microarray technology holds remarkable promise to rapidly identify suitable biomaterials for stem cell and tissue engineering applications. However, most of previous microarrayed synthetic polymers do not possess biological ligands (e.g., peptides) to directly engage cell surface receptors. Here, we report the development of peptide-functionalized hydrogel microarrays based on light-assisted copolymerization of poly(ethylene glycol) diacrylates (PEGDA) and methacrylated-peptides. Using solid-phase peptide/organic synthesis, we developed an efficient route to synthesize methacrylated-peptides. In parallel, we identified PEG hydrogels that effectively inhibit non-specific cell adhesion by using PEGDA-700 (M. W.=700) as a monomer. The combined use of these chemistries enables the development of a powerful platform to prepare peptide-functionalized PEG hydrogel microarrays. Additionally, we identified a linker composed of 4 glycines to ensure sufficient exposure of the peptide moieties from hydrogel surfaces. Further, we used this system to directly compare cell adhesion abilities of several related RGD peptides: RGD, RGDS, RGDSG and RGDSP. Finally, we combined the peptide-functionalized hydrogel technology with bioinformatics to construct a library composed of 12 different RGD peptides, including 6 unexplored RGD peptides, to develop culture substrates for hiPSC-derived cardiomyocytes (hiPSC-CMs), a cell type known for poor adhesion to synthetic substrates. 2 out of 6 unexplored RGD peptides showed substantial activities to support hiPSC-CMs. Among them, PMQKMRGDVFSP from laminin β4 subunit was found to support the highest adhesion and sarcomere formation of hiPSC-CMs. With bioinformatics, the peptide-functionalized hydrogel microarrays accelerate the discovery of novel biological ligands to develop biomaterials for stem cell and tissue engineering applications. In this manuscript, we described the development of a robust approach to prepare peptide-functionalized

  3. SSHscreen and SSHdb, generic software for microarray based gene discovery: application to the stress response in cowpea

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    Oelofse Dean

    2010-04-01

    Full Text Available Abstract Background Suppression subtractive hybridization is a popular technique for gene discovery from non-model organisms without an annotated genome sequence, such as cowpea (Vigna unguiculata (L. Walp. We aimed to use this method to enrich for genes expressed during drought stress in a drought tolerant cowpea line. However, current methods were inefficient in screening libraries and management of the sequence data, and thus there was a need to develop software tools to facilitate the process. Results Forward and reverse cDNA libraries enriched for cowpea drought response genes were screened on microarrays, and the R software package SSHscreen 2.0.1 was developed (i to normalize the data effectively using spike-in control spot normalization, and (ii to select clones for sequencing based on the calculation of enrichment ratios with associated statistics. Enrichment ratio 3 values for each clone showed that 62% of the forward library and 34% of the reverse library clones were significantly differentially expressed by drought stress (adjusted p value 88% of the clones in both libraries were derived from rare transcripts in the original tester samples, thus supporting the notion that suppression subtractive hybridization enriches for rare transcripts. A set of 118 clones were chosen for sequencing, and drought-induced cowpea genes were identified, the most interesting encoding a late embryogenesis abundant Lea5 protein, a glutathione S-transferase, a thaumatin, a universal stress protein, and a wound induced protein. A lipid transfer protein and several components of photosynthesis were down-regulated by the drought stress. Reverse transcriptase quantitative PCR confirmed the enrichment ratio values for the selected cowpea genes. SSHdb, a web-accessible database, was developed to manage the clone sequences and combine the SSHscreen data with sequence annotations derived from BLAST and Blast2GO. The self-BLAST function within SSHdb grouped

  4. SSHscreen and SSHdb, generic software for microarray based gene discovery: application to the stress response in cowpea

    Science.gov (United States)

    2010-01-01

    Background Suppression subtractive hybridization is a popular technique for gene discovery from non-model organisms without an annotated genome sequence, such as cowpea (Vigna unguiculata (L.) Walp). We aimed to use this method to enrich for genes expressed during drought stress in a drought tolerant cowpea line. However, current methods were inefficient in screening libraries and management of the sequence data, and thus there was a need to develop software tools to facilitate the process. Results Forward and reverse cDNA libraries enriched for cowpea drought response genes were screened on microarrays, and the R software package SSHscreen 2.0.1 was developed (i) to normalize the data effectively using spike-in control spot normalization, and (ii) to select clones for sequencing based on the calculation of enrichment ratios with associated statistics. Enrichment ratio 3 values for each clone showed that 62% of the forward library and 34% of the reverse library clones were significantly differentially expressed by drought stress (adjusted p value 88% of the clones in both libraries were derived from rare transcripts in the original tester samples, thus supporting the notion that suppression subtractive hybridization enriches for rare transcripts. A set of 118 clones were chosen for sequencing, and drought-induced cowpea genes were identified, the most interesting encoding a late embryogenesis abundant Lea5 protein, a glutathione S-transferase, a thaumatin, a universal stress protein, and a wound induced protein. A lipid transfer protein and several components of photosynthesis were down-regulated by the drought stress. Reverse transcriptase quantitative PCR confirmed the enrichment ratio values for the selected cowpea genes. SSHdb, a web-accessible database, was developed to manage the clone sequences and combine the SSHscreen data with sequence annotations derived from BLAST and Blast2GO. The self-BLAST function within SSHdb grouped redundant clones together and

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

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    Pascal Barbry

    2006-04-01

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

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

    Science.gov (United States)

    Dayem, Manal A.; Moreilhon, Chimène; Turchi, Laurent; Magnone, Virginie; Christen, Richard; Ponzio, Gilles

    2003-01-01

    Wound healing involves several steps: spreading of the cells, migration and proliferation. We have profiled gene expression during the early events of wound healing in normal human keratinocytes with a home-made DNA microarray containing about 1000 relevant human probes. An original wounding machine was used, that allows the wounding of up to 40% of the surface of a confluent monolayer of cultured cells grown on a Petri dish (compared with 5% with a classical ‘scratch’ method). The two aims of the present study were: (a) to validate a limited number of genes by comparing the expression levels obtained with this technique with those found in the literature; (b) to combine the use of the wounding machine with DNA microarray analysis for large-scale detection of the molecular events triggered during the early stages of the wound-healing process. The time-courses of RNA expression observed at 0.5, 1.5, 3, 6 and 15 h after wounding for genes such as c-Fos, c-Jun, Egr1, the plasminogen activator PLAU (uPA) and the signal transducer and transcription activator STAT3, were consistent with previously published data. This suggests that our methodologies are able to perform quantitative measurement of gene expression. Transcripts encoding two zinc finger proteins, ZFP36 and ZNF161, and the tumour necrosis factor α-induced protein TNFAIP3, were also overexpressed after wounding. The role of the p38 mitogen-activated protein kinase (p38MAPK) in wound healing was shown after the inhibition of p38 by SB203580, but our results also suggest the existence of surrogate activating pathways. PMID:18629100

  7. Integrated microarray and ChIP analysis identifies multiple Foxa2 dependent target genes in the notochord.

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    Tamplin, Owen J; Cox, Brian J; Rossant, Janet

    2011-12-15

    The node and notochord are key tissues required for patterning of the vertebrate body plan. Understanding the gene regulatory network that drives their formation and function is therefore important. Foxa2 is a key transcription factor at the top of this genetic hierarchy and finding its targets will help us to better understand node and notochord development. We performed an extensive microarray-based gene expression screen using sorted embryonic notochord cells to identify early notochord-enriched genes. We validated their specificity to the node and notochord by whole mount in situ hybridization. This provides the largest available resource of notochord-expressed genes, and therefore candidate Foxa2 target genes in the notochord. Using existing Foxa2 ChIP-seq data from adult liver, we were able to identify a set of genes expressed in the notochord that had associated regions of Foxa2-bound chromatin. Given that Foxa2 is a pioneer transcription factor, we reasoned that these sites might represent notochord-specific enhancers. Candidate Foxa2-bound regions were tested for notochord specific enhancer function in a zebrafish reporter assay and 7 novel notochord enhancers were identified. Importantly, sequence conservation or predictive models could not have readily identified these regions. Mutation of putative Foxa2 binding elements in two of these novel enhancers abrogated reporter expression and confirmed their Foxa2 dependence. The combination of highly specific gene expression profiling and genome-wide ChIP analysis is a powerful means of understanding developmental pathways, even for small cell populations such as the notochord. Copyright © 2011 Elsevier Inc. All rights reserved.

  8. Molecular Signature of Cancer at Gene Level or Pathway Level? Case Studies of Colorectal Cancer and Prostate Cancer Microarray Data

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    Jiajia Chen

    2013-01-01

    Full Text Available With recent advances in microarray technology, there has been a flourish in genome-scale identification of molecular signatures for cancer. However, the differentially expressed genes obtained by different laboratories are highly divergent. The present discrepancy at gene level indicates a need for a novel strategy to obtain more robust signatures for cancer. In this paper we hypothesize that (1 the expression signatures of different cancer microarray datasets are more similar at pathway level than at gene level; (2 the comparability of the cancer molecular mechanisms of different individuals is related to their genetic similarities. In support of the hypotheses, we summarized theoretical and experimental evidences, and conducted case studies on colorectal and prostate cancer microarray datasets. Based on the above assumption, we propose that reliable cancer signatures should be investigated in the context of biological pathways, within a cohort of genetically homogeneous population. It is hoped that the hypotheses can guide future research in cancer mechanism and signature discovery.

  9. Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data

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    Cheung Leo

    2007-02-01

    Full Text Available Abstract Background Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more important for our understanding of diseases at genomic level. Although many machine learning methods have been developed and applied to the area of microarray gene expression data analysis, the majority of them are based on linear models, which however are not necessarily appropriate for the underlying connection between the target disease and its associated explanatory genes. Linear model based methods usually also bring in false positive significant features more easily. Furthermore, linear model based algorithms often involve calculating the inverse of a matrix that is possibly singular when the number of potentially important genes is relatively large. This leads to problems of numerical instability. To overcome these limitations, a few non-linear methods have recently been introduced to the area. Many of the existing non-linear methods have a couple of critical problems, the model selection problem and the model parameter tuning problem, that remain unsolved or even untouched. In general, a unified framework that allows model parameters of both linear and non-linear models to be easily tuned is always preferred in real-world applications. Kernel-induced learning methods form a class of approaches that show promising potentials to achieve this goal. Results A hierarchical statistical model named kernel-imbedded Gaussian process (KIGP is developed under a unified Bayesian framework for binary disease classification problems using microarray gene expression data. In particular, based on a probit regression setting, an adaptive algorithm with a cascading structure is designed to find the appropriate kernel, to discover the potentially significant genes, and to make the optimal class prediction accordingly. A Gibbs sampler is built as the core of the algorithm to make

  10. Transcriptome sequencing and microarray design for functional genomics in the extremophile Arabidopsis relative Thellungiella salsuginea (Eutrema salsugineum).

    Science.gov (United States)

    Lee, Yang Ping; Giorgi, Federico M; Lohse, Marc; Kvederaviciute, Kotryna; Klages, Sven; Usadel, Björn; Meskiene, Irute; Reinhardt, Richard; Hincha, Dirk K

    2013-11-14

    Most molecular studies of plant stress tolerance have been performed with Arabidopsis thaliana, although it is not particularly stress tolerant and may lack protective mechanisms required to survive extreme environmental conditions. Thellungiella salsuginea has attracted interest as an alternative plant model species with high tolerance of various abiotic stresses. While the T. salsuginea genome has recently been sequenced, its annotation is still incomplete and transcriptomic information is scarce. In addition, functional genomics investigations in this species are severely hampered by a lack of affordable tools for genome-wide gene expression studies. Here, we report the results of Thellungiella de novo transcriptome assembly and annotation based on 454 pyrosequencing and development and validation of a T. salsuginea microarray. ESTs were generated from a non-normalized and a normalized library synthesized from RNA pooled from samples covering different tissues and abiotic stress conditions. Both libraries yielded partially unique sequences, indicating their necessity to obtain comprehensive transcriptome coverage. More than 1 million sequence reads were assembled into 42,810 unigenes, approximately 50% of which could be functionally annotated. These unigenes were compared to all available Thellungiella genome sequence information. In addition, the groups of Late Embryogenesis Abundant (LEA) proteins, Mitogen Activated Protein (MAP) kinases and protein phosphatases were annotated in detail. We also predicted the target genes for 384 putative miRNAs. From the sequence information, we constructed a 44 k Agilent oligonucleotide microarray. Comparison of same-species and cross-species hybridization results showed superior performance of the newly designed array for T. salsuginea samples. The developed microarrays were used to investigate transcriptional responses of T. salsuginea and Arabidopsis during cold acclimation using the MapMan software. This study provides

  11. Microarray gene expression profiles from mature gonad tissues of Atlantic bluefin tuna, Thunnus thynnus in the Gulf of Mexico.

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    Gardner, Luke D; Jayasundara, Nishad; Castilho, Pedro C; Block, Barbara

    2012-10-05

    . Gene expression profiles in T. thynnus sexually mature testes and ovaries were characterized with reference to gametogenesis and potential alternative functions. This report is the first application of microarray technology for bluefin tunas and demonstrates the efficacy by which this technique may be used for further characterization of specific biological aspects for this valuable teleost fish.

  12. Microarray gene expression profiles from mature gonad tissues of Atlantic bluefin tuna, Thunnus thynnus in the Gulf of Mexico

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    Gardner Luke D

    2012-10-01

    reproductive biology by using a contemporary transcriptome approach. Gene expression profiles in T. thynnus sexually mature testes and ovaries were characterized with reference to gametogenesis and potential alternative functions. This report is the first application of microarray technology for bluefin tunas and demonstrates the efficacy by which this technique may be used for further characterization of specific biological aspects for this valuable teleost fish.

  13. Protective Effect of Gwakhyangjeonggisan Herbal Acupuncture Solution in Glioblastoma Cells: Microarray Analysis of Gene Expression

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    Hong-Seok Lee

    2005-12-01

    Full Text Available Objectives : Neurological disorders have been one of main therapeutic targets of acupuncture. The present study investigated the protective effects of Gwakhyangjeonggisan herbal acupuncture solution (GHAS. Methods : We performed 3-(4,5-dimethylthiazol-2-yl-2,5-diphenyltetrazolium bromide (MTT assay in glioblastoma cells, and did microarray analysis with cells exposed to reactive oxigen species (ROS of hydrogen peroxide by 8.0 k Human cDNA, with cut-off level of 2-fold changes in gene expression. Results : MTT assay showed protective effect of GHAS on the glioblastoma cells exposed to hydrogen peroxide. When glioblastoma cells were exposed to hydrogen peroxide, 24 genes were downregulated. When the cells were pretreated with GHAS before exposure to hydrogen peroxide, 46 genes were downregulated. Many of the genes downregulated by hydrogen peroxide stimulation were decreased in the amount of downregulation or reversed to upregulation. Conclusions : The gene expression changes observed in the present study are supposed to be related to the protective molecular mechanism of GHAS in the glioblastoma cells exposed to ROS stress.

  14. Carbohydrate Cluster Microarrays Fabricated on 3-Dimensional Dendrimeric Platforms for Functional Glycomics Exploration

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    Zhou, Xichun; Turchi, Craig; Wang, Denong

    2009-01-01

    We reported here a novel, ready-to-use bioarray platform and methodology for construction of sensitive carbohydrate cluster microarrays. This technology utilizes a 3-dimensional (3-D) poly(amidoamine) starburst dendrimer monolayer assembled on glass surface, which is functionalized with terminal aminooxy and hydrazide groups for site-specific coupling of carbohydrates. A wide range of saccharides, including monosaccharides, oligosaccharides and polysaccharides of diverse structures, are applicable for the 3-D bioarray platform without prior chemical derivatization. The process of carbohydrate coupling is effectively accelerated by microwave radiation energy. The carbohydrate concentration required for microarray fabrication is substantially reduced using this technology. Importantly, this bioarray platform presents sugar chains in defined orientation and cluster configurations. It is, thus, uniquely useful for exploration of the structural and conformational diversities of glyco-epitope and their functional properties. PMID:19791771

  15. Gene expression profiling to characterize sediment toxicity – a pilot study using Caenorhabditis elegans whole genome microarrays

    Science.gov (United States)

    Menzel, Ralph; Swain, Suresh C; Hoess, Sebastian; Claus, Evelyn; Menzel, Stefanie; Steinberg, Christian EW; Reifferscheid, Georg; Stürzenbaum, Stephen R

    2009-01-01

    Background Traditionally, toxicity of river sediments is assessed using whole sediment tests with benthic organisms. The challenge, however, is the differentiation between multiple effects caused by complex contaminant mixtures and the unspecific toxicity endpoints such as survival, growth or reproduction. The use of gene expression profiling facilitates the identification of transcriptional changes at the molecular level that are specific to the bio-available fraction of pollutants. Results In this pilot study, we exposed the nematode Caenorhabditis elegans to three sediments of German rivers with varying (low, medium and high) levels of heavy metal and organic contamination. Beside chemical analysis, three standard bioassays were performed: reproduction of C. elegans, genotoxicity (Comet assay) and endocrine disruption (YES test). Gene expression was profiled using a whole genome DNA-microarray approach to identify overrepresented functional gene categories and derived cellular processes. Disaccharide and glycogen metabolism were found to be affected, whereas further functional pathways, such as oxidative phosphorylation, ribosome biogenesis, metabolism of xenobiotics, aging and several developmental processes were found to be differentially regulated only in response to the most contaminated sediment. Conclusion This study demonstrates how ecotoxicogenomics can identify transcriptional responses in complex mixture scenarios to distinguish different samples of river sediments. PMID:19366437

  16. The Local Maximum Clustering Method and Its Application in Microarray Gene Expression Data Analysis

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    Chen Yidong

    2004-01-01

    Full Text Available 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 -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.

  17. Comparing gene discovery from Affymetrix GeneChip microarrays and Clontech PCR-select cDNA subtraction: a case study

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    Cao, Wuxiong; Epstein, Charles; Liu, Hong; DeLoughery, Craig; Ge, Nanxiang; Lin, Jieyi; Diao, Rong; Cao, Hui; Long, Fan; Zhang, Xin; Chen, Yangde; Wright, Paul S; Busch, Steve; Wenck, Michelle; Wong, Karen; Saltzman, Alan G; Tang, Zhihua; Liu, Li; Zilberstein, Asher

    2004-01-01

    Background Several high throughput technologies have been employed to identify differentially regulated genes that may be molecular targets for drug discovery. Here we compared the sets of differentially regulated genes discovered using two experimental approaches: a subtracted suppressive hybridization (SSH) cDNA library methodology and Affymetrix GeneChip® technology. In this "case study" we explored the transcriptional pattern changes during the in vitro differentiation of human monocytes to myeloid dendritic cells (DC), and evaluated the potential for novel gene discovery using the SSH methodology. Results The same RNA samples isolated from peripheral blood monocyte precursors and immature DC (iDC) were used for GeneChip microarray probing and SSH cDNA library construction. 10,000 clones from each of the two-way SSH libraries (iDC-monocytes and monocytes-iDC) were picked for sequencing. About 2000 transcripts were identified for each library from 8000 successful sequences. Only 70% to 75% of these transcripts were represented on the U95 series GeneChip microarrays, implying that 25% to 30% of these transcripts might not have been identified in a study based only on GeneChip microarrays. In addition, about 10% of these transcripts appeared to be "novel", although these have not yet been closely examined. Among the transcripts that are also represented on the chips, about a third were concordantly discovered as differentially regulated between iDC and monocytes by GeneChip microarray transcript profiling. The remaining two thirds were either not inferred as differentially regulated from GeneChip microarray data, or were called differentially regulated but in the opposite direction. This underscores the importance both of generating reciprocal pairs of SSH libraries, and of real-time RT-PCR confirmation of the results. Conclusions This study suggests that SSH could be used as an alternative and complementary transcript profiling tool to GeneChip microarrays

  18. DNA microarray analysis reveals that antibiotic resistance-gene diversity in human gut microbiota is age related.

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    Lu, Na; Hu, Yongfei; Zhu, Liying; Yang, Xi; Yin, Yeshi; Lei, Fang; Zhu, Yongliang; Du, Qin; Wang, Xin; Meng, Zhiqi; Zhu, Baoli

    2014-03-12

    The human gut is a reservoir for antibiotic resistance genes. In this report, we used a DNA microarray chip covering 369 resistance types to investigate the relationship between antibiotic resistance-gene diversity and human age. Metagenomic DNA from fecal samples from 124 healthy volunteers of four different age groups (pre-school-aged children (CH), school-aged children (SC), high school students (HSS) and adults (AD)) were hybridized to the microarray chip. The results showed that 80 different gene types were recovered from the gut microbiota of the 124 individuals: 25 from CH, 37 from SC, 58 from HSS and 72 from AD. Further analysis indicated that the antibiotic resistance genes in the CH, SC and AD groups clustered independently, whereas the gene types in the HSS group were more divergent. Our results indicated that antibiotic resistance genes in the human gut microbiota accumulate from childhood to adulthood and become more complex with age.

  19. DNA microarray analysis reveals that antibiotic resistance-gene diversity in human gut microbiota is age related

    Science.gov (United States)

    Lu, Na; Hu, Yongfei; Zhu, Liying; Yang, Xi; Yin, Yeshi; Lei, Fang; Zhu, Yongliang; Du, Qin; Wang, Xin; Meng, Zhiqi; Zhu, Baoli

    2014-01-01

    The human gut is a reservoir for antibiotic resistance genes. In this report, we used a DNA microarray chip covering 369 resistance types to investigate the relationship between antibiotic resistance-gene diversity and human age. Metagenomic DNA from fecal samples from 124 healthy volunteers of four different age groups (pre-school-aged children (CH), school-aged children (SC), high school students (HSS) and adults (AD)) were hybridized to the microarray chip. The results showed that 80 different gene types were recovered from the gut microbiota of the 124 individuals: 25 from CH, 37 from SC, 58 from HSS and 72 from AD. Further analysis indicated that the antibiotic resistance genes in the CH, SC and AD groups clustered independently, whereas the gene types in the HSS group were more divergent. Our results indicated that antibiotic resistance genes in the human gut microbiota accumulate from childhood to adulthood and become more complex with age. PMID:24618772

  20. Microarray-based identification of differentially expressed genes in intracellular Brucella abortus within RAW264.7 cells.

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    Mingxing Tian

    Full Text Available Brucella spp. is a species of facultative intracellular Gram-negative bacteria that induces abortion and causes sterility in domesticated mammals and chronic undulant fever in humans. Important determinants of Brucella's virulence and potential for chronic infection include the ability to circumvent the host cell's internal surveillance system and the capability to proliferate within dedicated and non-dedicated phagocytes. Hence, identifying genes necessary for intracellular survival may hold the key to understanding Brucella infection. In the present study, microarray analysis reveals that 7.82% (244/3334 of all Brucella abortus genes were up-regulated and 5.4% (180/3334 were down-regulated in RAW264.7 cells, compared to free-living cells in TSB. qRT-PCR verification further confirmed a >5-fold up-regulation for fourteen genes. Functional analysis classified araC, ddp, and eryD as to partake in information storage and processing, alp, flgF and virB9 to be involved in cellular processes, hpcd and aldh to play a role in metabolism, mfs and nikC to be involved in both cellular processes and metabolism, and four hypothetical genes (bruAb1_1814, bruAb1_0475, bruAb1_1926, and bruAb1_0292 had unknown functions. Furthermore, we constructed a B. abortus 2308 mutant Δddp where the ddp gene is deleted in order to evaluate the role of ddp in intracellular survival. Infection assay indicated significantly higher adherence and invasion abilities of the Δddp mutant, however it does not survive well in RAW264.7 cells. Brucella may survive in hostile intracellular environment by modulating gene expression.

  1. Combined analysis of murine and human microarrays and ChIP analysis reveals genes associated with the ability of MYC to maintain tumorigenesis.

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    Chi-Hwa Wu

    2008-06-01

    Full Text Available The MYC oncogene has been implicated in the regulation of up to thousands of genes involved in many cellular programs including proliferation, growth, differentiation, self-renewal, and apoptosis. MYC is thought to induce cancer through an exaggerated effect on these physiologic programs. Which of these genes are responsible for the ability of MYC to initiate and/or maintain tumorigenesis is not clear. Previously, we have shown that upon brief MYC inactivation, some tumors undergo sustained regression. Here we demonstrate that upon MYC inactivation there are global permanent changes in gene expression detected by microarray analysis. By applying StepMiner analysis, we identified genes whose expression most strongly correlated with the ability of MYC to induce a neoplastic state. Notably, genes were identified that exhibited permanent changes in mRNA expression upon MYC inactivation. Importantly, permanent changes in gene expression could be shown by chromatin immunoprecipitation (ChIP to be associated with permanent changes in the ability of MYC to bind to the promoter regions. Our list of candidate genes associated with tumor maintenance was further refined by comparing our analysis with other published results to generate a gene signature associated with MYC-induced tumorigenesis in mice. To validate the role of gene signatures associated with MYC in human tumorigenesis, we examined the expression of human homologs in 273 published human lymphoma microarray datasets in Affymetrix U133A format. One large functional group of these genes included the ribosomal structural proteins. In addition, we identified a group of genes involved in a diverse array of cellular functions including: BZW2, H2AFY, SFRS3, NAP1L1, NOLA2, UBE2D2, CCNG1, LIFR, FABP3, and EDG1. Hence, through our analysis of gene expression in murine tumor models and human lymphomas, we have identified a novel gene signature correlated with the ability of MYC to maintain tumorigenesis.

  2. Biomphalaria glabrata transcriptome: cDNA microarray profiling identifies resistant- and susceptible-specific gene expression in haemocytes from snail strains exposed to Schistosoma mansoni

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    Rollinson David

    2008-12-01

    Full Text Available Abstract Background Biomphalaria glabrata is an intermediate snail host for Schistosoma mansoni, one of the important schistosomes infecting man. B. glabrata/S. mansoni provides a useful model system for investigating the intimate interactions between host and parasite. Examining differential gene expression between S. mansoni-exposed schistosome-resistant and susceptible snail lines will identify genes and pathways that may be involved in snail defences. Results We have developed a 2053 element cDNA microarray for B. glabrata containing clones from ORESTES (Open Reading frame ESTs libraries, suppression subtractive hybridization (SSH libraries and clones identified in previous expression studies. Snail haemocyte RNA, extracted from parasite-challenged resistant and susceptible snails, 2 to 24 h post-exposure to S. mansoni, was hybridized to the custom made cDNA microarray and 98 differentially expressed genes or gene clusters were identified, 94 resistant-associated and 4 susceptible-associated. Quantitative PCR analysis verified the cDNA microarray results for representative transcripts. Differentially expressed genes were annotated and clustered using gene ontology (GO terminology and Kyoto Encyclopaedia of Genes and Genomes (KEGG pathway analysis. 61% of the identified differentially expressed genes have no known function including the 4 susceptible strain-specific transcripts. Resistant strain-specific expression of genes implicated in innate immunity of invertebrates was identified, including hydrolytic enzymes such as cathepsin L, a cysteine proteinase involved in lysis of phagocytosed particles; metabolic enzymes such as ornithine decarboxylase, the rate-limiting enzyme in the production of polyamines, important in inflammation and infection processes, as well as scavenging damaging free radicals produced during production of reactive oxygen species; stress response genes such as HSP70; proteins involved in signalling, such as importin 7

  3. Biomphalaria glabrata transcriptome: cDNA microarray profiling identifies resistant- and susceptible-specific gene expression in haemocytes from snail strains exposed to Schistosoma mansoni

    Science.gov (United States)

    Lockyer, Anne E; Spinks, Jenny; Kane, Richard A; Hoffmann, Karl F; Fitzpatrick, Jennifer M; Rollinson, David; Noble, Leslie R; Jones, Catherine S

    2008-01-01

    Background Biomphalaria glabrata is an intermediate snail host for Schistosoma mansoni, one of the important schistosomes infecting man. B. glabrata/S. mansoni provides a useful model system for investigating the intimate interactions between host and parasite. Examining differential gene expression between S. mansoni-exposed schistosome-resistant and susceptible snail lines will identify genes and pathways that may be involved in snail defences. Results We have developed a 2053 element cDNA microarray for B. glabrata containing clones from ORESTES (Open Reading frame ESTs) libraries, suppression subtractive hybridization (SSH) libraries and clones identified in previous expression studies. Snail haemocyte RNA, extracted from parasite-challenged resistant and susceptible snails, 2 to 24 h post-exposure to S. mansoni, was hybridized to the custom made cDNA microarray and 98 differentially expressed genes or gene clusters were identified, 94 resistant-associated and 4 susceptible-associated. Quantitative PCR analysis verified the cDNA microarray results for representative transcripts. Differentially expressed genes were annotated and clustered using gene ontology (GO) terminology and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analysis. 61% of the identified differentially expressed genes have no known function including the 4 susceptible strain-specific transcripts. Resistant strain-specific expression of genes implicated in innate immunity of invertebrates was identified, including hydrolytic enzymes such as cathepsin L, a cysteine proteinase involved in lysis of phagocytosed particles; metabolic enzymes such as ornithine decarboxylase, the rate-limiting enzyme in the production of polyamines, important in inflammation and infection processes, as well as scavenging damaging free radicals produced during production of reactive oxygen species; stress response genes such as HSP70; proteins involved in signalling, such as importin 7 and copine 1

  4. Microarray analysis reveals altered expression of a large number of nuclear genes in developing cytoplasmic male sterile Brassica napus flowers.

    Science.gov (United States)

    Carlsson, Jenny; Lagercrantz, Ulf; Sundström, Jens; Teixeira, Rita; Wellmer, Frank; Meyerowitz, Elliot M; Glimelius, Kristina

    2007-02-01

    To gain new insights into the mechanism underlying cytoplasmic male sterility (CMS), we compared the nuclear gene expression profiles of flowers of a Brassica napus CMS line with that of the fertile B. napus maintainer line using Arabidopsis thaliana flower-specific cDNA microarrays. The CMS line used has a B. napus nuclear genome, but has a rearranged mitochondrial (mt) genome consisting of both B. napus and A. thaliana DNA. Gene expression profiling revealed that a large number of genes differed in expression between the two lines. For example, nuclear genes coding for proteins that are involved in protein import into organelles, genes expressed in stamens and pollen, as well as genes implicated in either cell-wall remodeling or architecture, were repressed in the CMS line compared with B. napus. These results show that the mt genome of the CMS line strongly influences nuclear gene expression, and thus reveal the importance of retrograde signalling between the mitochondria and the nucleus. Furthermore, flowers of the CMS line are characterized by a replacement of stamens with carpelloid organs, and thus partially resemble the APETALA3 (AP3) and PISTILLATA (PI) mutants. In accordance with this phenotype, AP3 expression was downregulated in the stamens, shortly before these organs developed carpelloid characteristics, even though it was initiated correctly. Repression of PI succeeded that of AP3 and might be a consequence of a loss of AP3 activity. These results suggest that AP3 expression in stamens depends on proper mt function and a correct nuclear-mt interaction, and that mt alterations cause the male sterility phenotype of the CMS line.

  5. Identification of the SAAT Gene Involved in Strawberry Flavor Biogenesis by Use of DNA Microarrays

    Science.gov (United States)

    Aharoni, Asaph; Keizer, Leopold C. P.; Bouwmeester, Harro J.; Sun, Zhongkui; Alvarez-Huerta, Mayte; Verhoeven, Harrie A.; Blaas, Jan; van Houwelingen, Adèle M. M. L.; De Vos, Ric C. H.; van der Voet, Hilko; Jansen, Ritsert C.; Guis, Monique; Mol, Jos; Davis, Ronald W.; Schena, Mark; van Tunen, Arjen J.; O'Connell, Ann P.

    2000-01-01

    Fruit flavor is a result of a complex mixture of numerous compounds. The formation of these compounds is closely correlated with the metabolic changes occurring during fruit maturation. Here, we describe the use of DNA microarrays and appropriate statistical analyses to dissect a complex developmental process. In doing so, we have identified a novel strawberry alcohol acyltransferase (SAAT) gene that plays a crucial role in flavor biogenesis in ripening fruit. Volatile esters are quantitatively and qualitatively the most important compounds providing fruity odors. Biochemical evidence for involvement of the SAAT gene in formation of fruity esters is provided by characterizing the recombinant protein expressed in Escherichia coli. The SAAT enzyme showed maximum activity with aliphatic medium-chain alcohols, whose corresponding esters are major components of strawberry volatiles. The enzyme was capable of utilizing short- and medium-chain, branched, and aromatic acyl-CoA molecules as cosubstrates. The results suggest that the formation of volatile esters in fruit is subject to the availability of acyl-CoA molecules and alcohol substrates and is dictated by the temporal expression pattern of the SAAT gene(s) and substrate specificity of the SAAT enzyme(s). PMID:10810141

  6. Development of a predictor for human brain tumors based on gene expression values obtained from two types of microarray technologies.

    Science.gov (United States)

    Castells, Xavier; Acebes, Juan José; Boluda, Susana; Moreno-Torres, Angel; Pujol, Jesús; Julià-Sapé, Margarida; Candiota, Ana Paula; Ariño, Joaquín; Barceló, Anna; Arús, Carles

    2010-04-01

    Development of molecular diagnostics that can reliably differentiate amongst different subtypes of brain tumors is an important unmet clinical need in postgenomics medicine and clinical oncology. A simple linear formula derived from gene expression values of four genes (GFAP, PTPRZ1, GPM6B, and PRELP) measured from cDNA microarrays (n = 35) have distinguished glioblastoma and meningioma cases in a previous study. We herein extend this work further and report that the above predictor formula showed its robustness when applied to Affymetrix microarray data acquired prospectively in our laboratory (n = 80) as well as publicly available data (n = 98). Importantly, GFAP and GPM6B were both retained as being significant in the predictive model upon using the Affymetrix data obtained in our laboratory, whereas the other two predictor genes were SFRP2 and SLC6A2. These results collectively indicate the importance of the expression values of GFAP and GPM6B genes sampled from the two types of microarray technologies tested. The high prediction accuracy obtained in these instances demonstrates the robustness of the predictors across microarray platforms used. This result would require further validation with a larger population of meningioma and glioblastoma cases. At any rate, this study paves the way for further application of gene signatures to more stringent biopsy discrimination challenges.

  7. Microarray-based screening of differentially expressed genes in glucocorticoid-induced avascular necrosis

    Science.gov (United States)

    Huang, Gangyong; Wei, Yibing; Zhao, Guanglei; Xia, Jun; Wang, Siqun; Wu, Jianguo; Chen, Feiyan; Chen, Jie; Shi, Jingshen

    2017-01-01

    The underlying mechanisms of glucocorticoid (GC)-induced avascular necrosis of the femoral head (ANFH) have yet to be fully understood, in particular the mechanisms associated with the change of gene expression pattern. The present study aimed to identify key genes with a differential expression pattern in GC-induced ANFH. E-MEXP-2751 microarray data were downloaded from the ArrayExpress database. Differentially expressed genes (DEGs) were identified in 5 femoral head samples of steroid-induced ANFH rats compared with 5 placebo-treated rat samples. Gene Ontology (GO) and pathway enrichment analyses were performed upon these DEGs. A total 93 DEGs (46 upregulated and 47 downregulated genes) were identified in GC-induced ANFH samples. These DEGs were enriched in different GO terms and pathways, including chondrocyte differentiation and detection of chemical stimuli. The enrichment map revealed that skeletal system development was interconnected with several other GO terms by gene overlap. The literature mined network analysis revealed that 5 upregulated genes were associated with femoral necrosis, including parathyroid hormone receptor 1 (PTHR1), vitamin D (1,25-Dihydroxyvitamin D3) receptor (VDR), collagen, type II, α1, proprotein convertase subtilisin/kexin type 6 and zinc finger protein 354C (ZFP354C). In addition, ZFP354C and VDR were identified to transcription factors. Furthermore, PTHR1 was revealed to interact with VDR, and α-2-macroglobulin (A2M) interacted with fibronectin 1 (FN1) in the PPI network. PTHR1 may be involved in GC-induced ANFH via interacting with VDR. A2M may also be involved in the development of GC-induced ANFH through interacting with FN1. An improved understanding of the molecular mechanisms underlying GC-induced ANFH may provide novel targets for diagnostics and therapeutic treatment. PMID:28393228

  8. Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering

    Science.gov (United States)

    2010-01-01

    Background Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or sub-classes, of either individuals or genes. Performing a cluster analysis commonly involve decisions on how to; handle missing values, standardize the data and select genes. In addition, pre-processing, involving various types of filtration and normalization procedures, can have an effect on the ability to discover biologically relevant classes. Here we consider cluster analysis in a broad sense and perform a comprehensive evaluation that covers several aspects of cluster analyses, including normalization. Result We evaluated 2780 cluster analysis methods on seven publicly available 2-channel microarray data sets with common reference designs. Each cluster analysis method differed in data normalization (5 normalizations were considered), missing value imputation (2), standardization of data (2), gene selection (19) or clustering method (11). The cluster analyses are evaluated using known classes, such as cancer types, and the adjusted Rand index. The performances of the different analyses vary between the data sets and it is difficult to give general recommendations. However, normalization, gene selection and clustering method are all variables that have a significant impact on the performance. In particular, gene selection is important and it is generally necessary to include a relatively large number of genes in order to get good performance. Selecting genes with high standard deviation or using principal component analysis are shown to be the preferred gene selection methods. Hierarchical clustering using Ward's method, k-means clustering and Mclust are the clustering methods considered in this paper that achieves the highest adjusted Rand. Normalization can have a significant positive impact on the ability to cluster individuals, and there are indications that background correction is

  9. Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering

    Directory of Open Access Journals (Sweden)

    Landfors Mattias

    2010-10-01

    Full Text Available Abstract Background Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or sub-classes, of either individuals or genes. Performing a cluster analysis commonly involve decisions on how to; handle missing values, standardize the data and select genes. In addition, pre-processing, involving various types of filtration and normalization procedures, can have an effect on the ability to discover biologically relevant classes. Here we consider cluster analysis in a broad sense and perform a comprehensive evaluation that covers several aspects of cluster analyses, including normalization. Result We evaluated 2780 cluster analysis methods on seven publicly available 2-channel microarray data sets with common reference designs. Each cluster analysis method differed in data normalization (5 normalizations were considered, missing value imputation (2, standardization of data (2, gene selection (19 or clustering method (11. The cluster analyses are evaluated using known classes, such as cancer types, and the adjusted Rand index. The performances of the different analyses vary between the data sets and it is difficult to give general recommendations. However, normalization, gene selection and clustering method are all variables that have a significant impact on the performance. In particular, gene selection is important and it is generally necessary to include a relatively large number of genes in order to get good performance. Selecting genes with high standard deviation or using principal component analysis are shown to be the preferred gene selection methods. Hierarchical clustering using Ward's method, k-means clustering and Mclust are the clustering methods considered in this paper that achieves the highest adjusted Rand. Normalization can have a significant positive impact on the ability to cluster individuals, and there are indications that

  10. Microarray data and gene expression statistics for Saccharomyces cerevisiae exposed to simulated asbestos mine drainage

    Directory of Open Access Journals (Sweden)

    Heather E. Driscoll

    2017-08-01

    Full Text Available Here we describe microarray expression data (raw and normalized, experimental metadata, and gene-level data with expression statistics from Saccharomyces cerevisiae exposed to simulated asbestos mine drainage from the Vermont Asbestos Group (VAG Mine on Belvidere Mountain in northern Vermont, USA. For nearly 100 years (between the late 1890s and 1993, chrysotile asbestos fibers were extracted from serpentinized ultramafic rock at the VAG Mine for use in construction and manufacturing industries. Studies have shown that water courses and streambeds nearby have become contaminated with asbestos mine tailings runoff, including elevated levels of magnesium, nickel, chromium, and arsenic, elevated pH, and chrysotile asbestos-laden mine tailings, due to leaching and gradual erosion of massive piles of mine waste covering approximately 9 km2. We exposed yeast to simulated VAG Mine tailings leachate to help gain insight on how eukaryotic cells exposed to VAG Mine drainage may respond in the mine environment. Affymetrix GeneChip® Yeast Genome 2.0 Arrays were utilized to assess gene expression after 24-h exposure to simulated VAG Mine tailings runoff. The chemistry of mine-tailings leachate, mine-tailings leachate plus yeast extract peptone dextrose media, and control yeast extract peptone dextrose media is also reported. To our knowledge this is the first dataset to assess global gene expression patterns in a eukaryotic model system simulating asbestos mine tailings runoff exposure. Raw and normalized gene expression data are accessible through the National Center for Biotechnology Information Gene Expression Omnibus (NCBI GEO Database Series GSE89875 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE89875.

  11. Identification of Arabidopsis candidate genes in response to biotic and abiotic stresses using comparative microarrays.

    Directory of Open Access Journals (Sweden)

    Arjun Sham

    Full Text Available Plants have evolved with intricate mechanisms to cope with multiple environmental stresses. To adapt with biotic and abiotic stresses, plant responses involve changes at the cellular and molecular levels. The current study was designed to investigate the effects of combinations of different environmental stresses on the transcriptome level of Arabidopsis genome using public microarray databases. We investigated the role of cyclopentenones in mediating plant responses to environmental stress through TGA (TGACG motif-binding factor transcription factor, independently from jasmonic acid. Candidate genes were identified by comparing plants inoculated with Botrytis cinerea or treated with heat, salt or osmotic stress with non-inoculated or non-treated tissues. About 2.5% heat-, 19% salinity- and 41% osmotic stress-induced genes were commonly upregulated by B. cinerea-treatment; and 7.6%, 19% and 48% of genes were commonly downregulated by B. cinerea-treatment, respectively. Our results indicate that plant responses to biotic and abiotic stresses are mediated by several common regulatory genes. Comparisons between transcriptome data from Arabidopsis stressed-plants support our hypothesis that some molecular and biological processes involved in biotic and abiotic stress response are conserved. Thirteen of the common regulated genes to abiotic and biotic stresses were studied in detail to determine their role in plant resistance to B. cinerea. Moreover, a T-DNA insertion mutant of the Responsive to Dehydration gene (rd20, encoding for a member of the caleosin (lipid surface protein family, showed an enhanced sensitivity to B. cinerea infection and drought. Overall, the overlapping of plant responses to abiotic and biotic stresses, coupled with the sensitivity of the rd20 mutant, may provide new interesting programs for increased plant resistance to multiple environmental stresses, and ultimately increases its chances to survive. Future research

  12. Microarray analysis of changes in bone cell gene expression early after cadmium gavage in mice

    International Nuclear Information System (INIS)

    Regunathan, Akhila; Glesne, David A.; Wilson, Allison K.; Song, Jongwoo; Nicolae, Dan; Flores, Tony; Bhattacharyya, Maryka H.

    2003-01-01

    We developed an in vivo model for cadmium-induced bone loss in which mice excrete bone mineral in feces beginning 8 h after cadmium gavage. Female mice of three strains [CF1, MTN (metallothionein-wild-type), and MT1,2KO (MT1,2-deficient)] were placed on a low-calcium diet for 2 weeks. Each mouse was gavaged with 200 μg Cd or vehicle only. Fecal calcium was monitored daily for 9 days, beginning 4 days before cadmium gavage, to document the bone response. For CF1 mice, bones were taken from four groups: +/- Cd, 2 h after Cd and +/- Cd, 4 h after Cd. MTN and MT1,2KO strains had two groups each: +/-Cd, 4 h after Cd. PolyA+ RNA preparations from marrow-free shafts of femura and tibiae of each +/- Cd pair were submitted to Incyte Genomics for microarray analysis. Fecal Ca results showed that bone calcium excreted after cadmium differed for the three mouse strains: CF1, 0.24 ± 0.08 mg; MTN, 0.92 ± 0.22 mg; and MT1,2KO, 1.7 ± 0.4 mg. Gene array results showed that nearly all arrayed genes were unaffected by cadmium. However, MT1 and MT2 had Cd+/Cd- expression ratios >1 in all four groups, while all ratios for MT3 were essentially 1, showing specificity. Both probes for MAPK 14 (p38 MAPK) had expression ratios >1, while no other MAPK responded to cadmium. Vacuolar proton pump ATPase and integrin alpha v (osteoclast genes), transferrin receptor, and src-like adaptor protein genes were stimulated by Cd; other src-related genes were unaffected. Genes for bone formation, stress response, growth factors, and signaling molecules showed little or no response to cadmium. Results support the hypothesis that Cd stimulates bone demineralization via a p38 MAPK pathway involving osteoclast activation

  13. Identification of Arabidopsis candidate genes in response to biotic and abiotic stresses using comparative microarrays.

    Science.gov (United States)

    Sham, Arjun; Moustafa, Khaled; Al-Ameri, Salma; Al-Azzawi, Ahmed; Iratni, Rabah; AbuQamar, Synan

    2015-01-01

    Plants have evolved with intricate mechanisms to cope with multiple environmental stresses. To adapt with biotic and abiotic stresses, plant responses involve changes at the cellular and molecular levels. The current study was designed to investigate the effects of combinations of different environmental stresses on the transcriptome level of Arabidopsis genome using public microarray databases. We investigated the role of cyclopentenones in mediating plant responses to environmental stress through TGA (TGACG motif-binding factor) transcription factor, independently from jasmonic acid. Candidate genes were identified by comparing plants inoculated with Botrytis cinerea or treated with heat, salt or osmotic stress with non-inoculated or non-treated tissues. About 2.5% heat-, 19% salinity- and 41% osmotic stress-induced genes were commonly upregulated by B. cinerea-treatment; and 7.6%, 19% and 48% of genes were commonly downregulated by B. cinerea-treatment, respectively. Our results indicate that plant responses to biotic and abiotic stresses are mediated by several common regulatory genes. Comparisons between transcriptome data from Arabidopsis stressed-plants support our hypothesis that some molecular and biological processes involved in biotic and abiotic stress response are conserved. Thirteen of the common regulated genes to abiotic and biotic stresses were studied in detail to determine their role in plant resistance to B. cinerea. Moreover, a T-DNA insertion mutant of the Responsive to Dehydration gene (rd20), encoding for a member of the caleosin (lipid surface protein) family, showed an enhanced sensitivity to B. cinerea infection and drought. Overall, the overlapping of plant responses to abiotic and biotic stresses, coupled with the sensitivity of the rd20 mutant, may provide new interesting programs for increased plant resistance to multiple environmental stresses, and ultimately increases its chances to survive. Future research directions towards a

  14. Improving the power to detect differentially expressed genes in comparative microarray experiments by including information from self-self hybridizations

    NARCIS (Netherlands)

    Gusnanto, Arief; Tom, Brian; Burns, Philippa; Macaulay, Iain; Thijssen-Timmer, Daphne C.; Tijssen, Marloes R.; Langford, Cordelia; Watkins, Nicholas; Ouwehand, Willem; Berzuini, Carlo; Dudbridge, Frank

    2007-01-01

    Our ability to detect differentially expressed genes in a microarray experiment can be hampered when the number of biological samples of interest is limited. In this situation, we propose the use of information from self-self hybridizations to acuminate our inference of differential expression. A

  15. Candidate Genes for Testicular Cancer Evaluated by In Situ Protein Expression Analyses on Tissue Microarrays

    Directory of Open Access Journals (Sweden)

    Rolf I. Skotheim

    2003-09-01

    Full Text Available By the use of high-throughput molecular technologies, the number of genes and proteins potentially relevant to testicular germ cell tumor (TGCT and other diseases will increase rapidly. In a recent transcriptional profiling, we demonstrated the overexpression of GRB7 and JUP in TGCTs, confirmed the reported overexpression of CCND2. We also have recent evidences for frequent genetic alterations of FHIT and epigenetic alterations of MGMT. To evaluate whether the expression of these genes is related to any clinicopathological variables, we constructed a tissue microarray with 510 testicular tissue cores from 279 patients diagnosed with TGCT, covering various histological subgroups and clinical stages. By immunohistochemistry, we found that JUP, GRB7, CCND2 proteins were rarely present in normal testis, but frequently expressed at high levels in TGCT. Additionally, all premalignant intratubular germ cell neoplasias were JUP-immunopositive. MGMT and FHIT were expressed by normal testicular tissues, but at significantly lower frequencies in TGCT. Except for CCND2, the expressions of all markers were significantly associated with various TGCT subtypes. In summary, we have developed a high-throughput tool for the evaluation of TGCT markers, utilized this to validate five candidate genes whose protein expressions were indeed deregulated in TGCT.

  16. Microarray study of single nucleotide polymorphisms and expression of ATP-binding cassette genes in breast tumors

    Science.gov (United States)

    Tsyganov, M. M.; Ibragimova, M. K.; Karabut, I. V.; Freydin, M. B.; Choinzonov, E. L.; Litvyakov, N. V.

    2015-11-01

    Our previous research establishes that changes of expression of the ATP-binding cassette genes family is connected with the neoadjuvant chemotherapy effect. However, the mechanism of regulation of resistance gene expression remains unclear. As many researchers believe, single nucleotide polymorphisms can be involved in this process. Thereupon, microarray analysis is used to study polymorphisms in ATP-binding cassette genes. It is thus found that MDR gene expression is connected with 5 polymorphisms, i.e. rs241432, rs241429, rs241430, rs3784867, rs59409230, which participate in the regulation of expression of own genes.

  17. Cross-platform comparison of SYBR® Green real-time PCR with TaqMan PCR, microarrays and other gene expression measurement technologies evaluated in the MicroArray Quality Control (MAQC study

    Directory of Open Access Journals (Sweden)

    Dial Stacey L

    2008-07-01

    Full Text Available Abstract Background The MicroArray Quality Control (MAQC project evaluated the inter- and intra-platform reproducibility of seven microarray platforms and three quantitative gene expression assays in profiling the expression of two commercially available Reference RNA samples (Nat Biotechnol 24:1115-22, 2006. The tested microarrays were the platforms from Affymetrix, Agilent Technologies, Applied Biosystems, GE Healthcare, Illumina, Eppendorf and the National Cancer Institute, and quantitative gene expression assays included TaqMan® Gene Expression PCR Assay, Standardized (Sta RT-PCR™ and QuantiGene®. The data showed great consistency in gene expression measurements across different microarray platforms, different technologies and test sites. However, SYBR® Green real-time PCR, another common technique utilized by half of all real-time PCR users for gene expression measurement, was not addressed in the MAQC study. In the present study, we compared the performance of SYBR Green PCR with TaqMan PCR, microarrays and other quantitative technologies using the same two Reference RNA samples as the MAQC project. We assessed SYBR Green real-time PCR using commercially available RT2 Profiler™ PCR Arrays from SuperArray, containing primer pairs that have been experimentally validated to ensure gene-specificity and high amplification efficiency. Results The SYBR Green PCR Arrays exhibit good reproducibility among different users, PCR instruments and test sites. In addition, the SYBR Green PCR Arrays have the highest concordance with TaqMan PCR, and a high level of concordance with other quantitative methods and microarrays that were evaluated in this study in terms of fold-change correlation and overlap of lists of differentially expressed genes. Conclusion These data demonstrate that SYBR Green real-time PCR delivers highly comparable results in gene expression measurement with TaqMan PCR and other high-density microarrays.

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

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    Rempei Yanagawa

    2001-01-01

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

  19. Chromosomal patterns of gene expression from microarray data: methodology, validation and clinical relevance in gliomas

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    Evrard Annick

    2006-12-01

    Full Text Available Abstract Background Expression microarrays represent a powerful technique for the simultaneous investigation of thousands of genes. The evidence that genes are not randomly distributed in the genome and that their coordinated expression depends on their position on chromosomes has highlighted the need for mathematical approaches to exploit this dependency for the analysis of expression data-sets. Results We have devised a novel mathematical technique (CHROMOWAVE based on the Haar wavelet transform and applied it to a dataset obtained with the Affymetrix® HG-U133_Plus_2 array in 27 gliomas. CHROMOWAVE generated multi-chromosomal pattern featuring low expression in chromosomes 1p, 4, 9q, 13, 18, and 19q. This pattern was not only statistically robust but also clinically relevant as it was predictive of favourable outcome. This finding was replicated on a data-set independently acquired by another laboratory. FISH analysis indicated that monosomy 1p and 19q was a frequent feature of tumours displaying the CHROMOWAVE pattern but that allelic loss on chromosomes 4, 9q, 13 and 18 was much less common. Conclusion The ability to detect expression changes of spatially related genes and to map their position on chromosomes makes CHROMOWAVE a valuable screening method for the identification and display of regional gene expression changes of clinical relevance. In this study, FISH data showed that monosomy was frequently associated with diffuse low gene expression on chromosome 1p and 19q but not on chromosomes 4, 9q, 13 and 18. Comparative genomic hybridisation, allelic polymorphism analysis and methylation studies are in progress in order to identify the various mechanisms involved in this multi-chromosomal expression pattern.

  20. Systematic gene microarray analysis of the lncRNA expression profiles in human uterine cervix carcinoma.

    Science.gov (United States)

    Chen, Jie; Fu, Ziyi; Ji, Chenbo; Gu, Pingqing; Xu, Pengfei; Yu, Ningzhu; Kan, Yansheng; Wu, Xiaowei; Shen, Rong; Shen, Yan

    2015-05-01

    The human uterine cervix carcinoma is one of the most well-known malignancy reproductive system cancers, which threatens women health globally. However, the mechanisms of the oncogenesis and development process of cervix carcinoma are not yet fully understood. Long non-coding RNAs (lncRNAs) have been proved to play key roles in various biological processes, especially development of cancer. The function and mechanism of lncRNAs on cervix carcinoma is still rarely reported. We selected 3 cervix cancer and normal cervix tissues separately, then performed lncRNA microarray to detect the differentially expressed lncRNAs. Subsequently, we explored the potential function of these dysregulated lncRNAs through online bioinformatics databases. Finally, quantity real-time PCR was carried out to confirm the expression levels of these dysregulated lncRNAs in cervix cancer and normal tissues. We uncovered the profiles of differentially expressed lncRNAs between normal and cervix carcinoma tissues by using the microarray techniques, and found 1622 upregulated and 3026 downregulated lncRNAs (fold-change>2.0) in cervix carcinoma compared to the normal cervical tissue. Furthermore, we found HOXA11-AS might participate in cervix carcinogenesis by regulating HOXA11, which is involved in regulating biological processes of cervix cancer. This study afforded expression profiles of lncRNAs between cervix carcinoma tissue and normal cervical tissue, which could provide database for further research about the function and mechanism of key-lncRNAs in cervix carcinoma, and might be helpful to explore potential diagnosis factors and therapeutic targets for cervix carcinoma. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

  1. Microarray Data Analysis of Space Grown Arabidopsis Leaves for Genes Important in Vascular Patterning. Analysis of Space Grown Arabidopsis with Microarray Data from GeneLab: Identification of Genes Important in Vascular Patterning

    Science.gov (United States)

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

    2016-01-01

    Venation patterning in leaves is a major determinant of photosynthesis efficiency because of its dependency on vascular transport of photo-assimilates, water, and minerals. Arabidopsis thaliana grown in microgravity show delayed growth and leaf maturation. Gene expression data from the roots, hypocotyl, and leaves of A. thaliana grown during spaceflight vs. ground control analyzed by Affymetrix microarray are available through NASA's GeneLab (GLDS-7). We analyzed the data for differential expression of genes in leaves resulting from the effects of spaceflight on vascular patterning. Two genes were found by preliminary analysis to be up-regulated during spaceflight that may be related to vascular formation. The genes are responsible for coding an ARGOS (Auxin-Regulated Gene Involved in Organ Size)-like protein (potentially affecting cell elongation in the leaves), and an F-box/kelch-repeat protein (possibly contributing to protoxylem specification). Further analysis that will focus on raw data quality assessment and a moderated t-test may further confirm up-regulation of the two genes and/or identify other gene candidates. Plants defective in these genes will then be assessed for phenotype by the mapping and quantification of leaf vascular patterning by NASA's VESsel GENeration (VESGEN) software to model specific vascular differences of plants grown in spaceflight.

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

    Directory of Open Access Journals (Sweden)

    Niggli Felix K

    2006-06-01

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

  3. Identification of genes related to high royal jelly production in the honey bee (Apis mellifera) using microarray analysis

    OpenAIRE

    Nie, Hongyi; Liu, Xiaoyan; Pan, Jiao; Li, Wenfeng; Li, Zhiguo; Zhang, Shaowu; Chen, Shenglu; Miao, Xiaoqing; Zheng, Nenggan; Su, Songkun

    2017-01-01

    Abstract China is the largest royal jelly producer and exporter in the world, and high royal jelly-yielding strains have been bred in the country for approximately three decades. However, information on the molecular mechanism underlying high royal jelly production is scarce. Here, a cDNA microarray was used to screen and identify differentially expressed genes (DEGs) to obtain an overview on the changes in gene expression levels between high and low royal jelly producing bees. We developed a...

  4. DNA microarray global gene expression analysis of influenza virus-infected chicken and duck cells

    Directory of Open Access Journals (Sweden)

    Suresh V. Kuchipudi

    2015-06-01

    Full Text Available The data described in this article pertain to the article by Kuchipudi et al. (2014 titled “Highly Pathogenic Avian Influenza Virus Infection in Chickens But Not Ducks Is Associated with Elevated Host Immune and Pro-inflammatory Responses” [1]. While infection of chickens with highly pathogenic avian influenza (HPAI H5N1 virus subtypes often leads to 100% mortality within 1 to 2 days, infection of ducks in contrast causes mild or no clinical signs. The rapid onset of fatal disease in chickens, but with no evidence of severe clinical symptoms in ducks, suggests underlying differences in their innate immune mechanisms. We used Chicken Genechip microarrays (Affymetrix to analyse the gene expression profiles of primary chicken and duck lung cells infected with a low pathogenic avian influenza (LPAI H2N3 virus and two HPAI H5N1 virus subtypes to understand the molecular basis of host susceptibility and resistance in chickens and ducks. Here, we described the experimental design, quality control and analysis that were performed on the data set. The data are publicly available through the Gene Expression Omnibus (GEOdatabase with accession number GSE33389, and the analysis and interpretation of these data are included in Kuchipudi et al. (2014 [1].

  5. Microarray analysis of differential gene expression elicited in Trametes versicolor during interspecific mycelial interactions.

    Science.gov (United States)

    Eyre, Catherine; Muftah, Wafa; Hiscox, Jennifer; Hunt, Julie; Kille, Peter; Boddy, Lynne; Rogers, Hilary J

    2010-08-01

    Trametes versicolor is an important white rot fungus of both industrial and ecological interest. Saprotrophic basidiomycetes are the major decomposition agents in woodland ecosystems, and rarely form monospecific populations, therefore interspecific mycelial interactions continually occur. Interactions have different outcomes including replacement of one species by the other or deadlock. We have made subtractive cDNA libraries to enrich for genes that are expressed when T. versicolor interacts with another saprotrophic basidiomycete, Stereum gausapatum, an interaction that results in the replacement of the latter. Expressed sequence tags (ESTs) (1920) were used for microarray analysis, and their expression compared during interaction with three different fungi: S. gausapatum (replaced by T. versicolor), Bjerkandera adusta (deadlock) and Hypholoma fasciculare (replaced T. versicolor). Expression of significantly more probes changed in the interaction between T. versicolor and S. gausapatum or B. adusta compared to H. fasciculare, suggesting a relationship between interaction outcome and changes in gene expression. Copyright © 2010 The British Mycological Society. Published by Elsevier Ltd. All rights reserved.

  6. Analyzing Multiple-Probe Microarray: Estimation and Application of Gene Expression Indexes

    KAUST Repository

    Maadooliat, Mehdi

    2012-07-26

    Gene expression index estimation is an essential step in analyzing multiple probe microarray data. Various modeling methods have been proposed in this area. Amidst all, a popular method proposed in Li and Wong (2001) is based on a multiplicative model, which is similar to the additive model discussed in Irizarry et al. (2003a) at the logarithm scale. Along this line, Hu et al. (2006) proposed data transformation to improve expression index estimation based on an ad hoc entropy criteria and naive grid search approach. In this work, we re-examined this problem using a new profile likelihood-based transformation estimation approach that is more statistically elegant and computationally efficient. We demonstrate the applicability of the proposed method using a benchmark Affymetrix U95A spiked-in experiment. Moreover, We introduced a new multivariate expression index and used the empirical study to shows its promise in terms of improving model fitting and power of detecting differential expression over the commonly used univariate expression index. As the other important content of the work, we discussed two generally encountered practical issues in application of gene expression index: normalization and summary statistic used for detecting differential expression. Our empirical study shows somewhat different findings from the MAQC project (MAQC, 2006).

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

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    M J Pont

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

  8. Characterization of ovine hepatic gene expression profiles in response to Escherichia coli lipopolysaccharide using a bovine cDNA microarray

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    Boermans Herman J

    2006-11-01

    Full Text Available Abstract Background During systemic gram-negative bacterial infections, lipopolysaccharide (LPS ligation to the hepatic Toll-like receptor-4 complex induces the production of hepatic acute phase proteins that are involved in the host response to infection and limit the associated inflammatory process. Identifying the genes that regulate this hepatic response to LPS in ruminants may provide insight into the pathogenesis of bacterial diseases and eventually facilitate breeding of more disease resistant animals. The objective of this research was to profile the expression of ovine hepatic genes in response to Escherichia coli LPS challenge (0, 200, 400 ng/kg using a bovine cDNA microarray and quantitative real-time PCR (qRT-PCR. Results Twelve yearling ewes were challenged iv with E. coli LPS (0, 200, 400 ng/kg and liver biopsies were collected 4–5 hours post-challenge to assess hepatic gene expression profiles by bovine cDNA microarray and qRT-PCR analyses. The expression of CD14, C3, IL12R, NRAMP1, SOD and IGFBP3 genes was down regulated, whereas the expression of ACTHR, IFNαR, CD1, MCP-1 and GH was increased during LPS challenge. With the exception of C3, qRT-PCR analysis of 7 of these genes confirmed the microarray results and demonstrated that GAPDH is not a suitable housekeeping gene in LPS challenged sheep. Conclusion We have identified several potentially important genes by bovine cDNA microarray and qRT-PCR analyses that are differentially expressed during the ovine hepatic response to systemic LPS challenge. Their potential role in regulating the inflammatory response to LPS warrants further investigation.

  9. Trait specific expression profiling of salt stress responsive genes in diverse rice genotypes as determined by modified Significance Analysis of Microarrays

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    Mohammad Rashed Hossain

    2016-05-01

    Full Text Available Stress responsive gene expression is commonly profiled in a comparative manner involving different stress conditions or genotypes with contrasting reputation of tolerance/resistance. In contrast, this research exploited a wide natural variation in terms of taxonomy, origin and salt sensitivity in eight genotypes of rice to identify the trait specific patterns of gene expression under salt stress. Genome wide transcptomic responses were interrogated by the weighted continuous morpho-physiological trait responses using modified Significance Analysis of Microarrays. More number of genes was found to be differentially expressed under salt stressed compared to that of under unstressed conditions. Higher numbers of genes were observed to be differentially expressed for the traits shoot Na+/K+, shoot Na+, root K+, biomass and shoot Cl-, respectively. The results identified around sixty genes to be involved in Na+, K+ and anion homeostasis, transport and transmembrane activity under stressed conditions. Gene Ontology (GO enrichment analysis identified 1.36% (578 genes of the entire transcriptome to be involved in the major molecular functions such as signal transduction (>150 genes, transcription factor (81 genes and translation factor activity (62 genes etc. under salt stress. Chromosomal mapping of the genes suggests that majority of the genes are located on chromosomes 1, 2, 3, 6 & 7. The gene network analysis showed that the transcription factors and translation initiation factors formed the major gene networks and are mostly active in nucleus, cytoplasm and mitochondria whereas the membrane and vesicle bound proteins formed a secondary network active in plasma membrane and vacuoles. The novel genes and the genes with unknown functions thus identified provide picture of a synergistic salinity response representing the potentially fundamental mechanisms that are active in the wide natural genetic background of rice and will be of greater use once

  10. Assessment of Fusion Gene Status in Sarcomas Using a Custom Made Fusion Gene Microarray

    OpenAIRE

    Lovf, Marthe; Thomassen, Gard O. S.; Mertens, Fredrik; Cerveira, Nuno; Teixeira, Manuel R.; Lothe, Ragnhild A.; Skotheim, Rolf I.

    2013-01-01

    Sarcomas are relatively rare malignancies and include a large number of histological subgroups. Based on morphology alone, the differential diagnoses of sarcoma subtypes can be challenging, but the identification of specific fusion genes aids correct diagnostication. The presence of individual fusion products are routinely investigated in Pathology labs. However, the methods used are time-consuming and based on prior knowledge about the expected fusion gene and often the most likely break-poi...

  11. Short-term arginine deprivation results in large-scale modulation of hepatic gene expression in both normal and tumor cells: microarray bioinformatic analysis

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    Sabo Edmond

    2006-09-01

    Full Text Available Abstract Background We have reported arginine-sensitive regulation of LAT1 amino acid transporter (SLC 7A5 in normal rodent hepatic cells with loss of arginine sensitivity and high level constitutive expression in tumor cells. We hypothesized that liver cell gene expression is highly sensitive to alterations in the amino acid microenvironment and that tumor cells may differ substantially in gene sets sensitive to amino acid availability. To assess the potential number and classes of hepatic genes sensitive to arginine availability at the RNA level and compare these between normal and tumor cells, we used an Affymetrix microarray approach, a paired in vitro model of normal rat hepatic cells and a tumorigenic derivative with triplicate independent replicates. Cells were exposed to arginine-deficient or control conditions for 18 hours in medium formulated to maintain differentiated function. Results Initial two-way analysis with a p-value of 0.05 identified 1419 genes in normal cells versus 2175 in tumor cells whose expression was altered in arginine-deficient conditions relative to controls, representing 9–14% of the rat genome. More stringent bioinformatic analysis with 9-way comparisons and a minimum of 2-fold variation narrowed this set to 56 arginine-responsive genes in normal liver cells and 162 in tumor cells. Approximately half the arginine-responsive genes in normal cells overlap with those in tumor cells. Of these, the majority was increased in expression and included multiple growth, survival, and stress-related genes. GADD45, TA1/LAT1, and caspases 11 and 12 were among this group. Previously known amino acid regulated genes were among the pool in both cell types. Available cDNA probes allowed independent validation of microarray data for multiple genes. Among genes downregulated under arginine-deficient conditions were multiple genes involved in cholesterol and fatty acid metabolism. Expression of low-density lipoprotein receptor was

  12. A microarray analysis of sex- and gonad-biased gene expression in the zebrafish: Evidence for masculinization of the transcriptome

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    Mo Qianxing

    2009-12-01

    Full Text Available Abstract Background In many taxa, males and females are very distinct phenotypically, and these differences often reflect divergent selective pressures acting on the sexes. Phenotypic sexual dimorphism almost certainly reflects differing patterns of gene expression between the sexes, and microarray studies have documented widespread sexually dimorphic gene expression. Although the evolutionary significance of sexual dimorphism in gene expression remains unresolved, these studies have led to the formulation of a hypothesis that male-driven evolution has resulted in the masculinization of animal transcriptomes. Here we use a microarray assessment of sex- and gonad-biased gene expression to test this hypothesis in zebrafish. Results By using zebrafish Affymetrix microarrays to compare gene expression patterns in male and female somatic and gonadal tissues, we identified a large number of genes (5899 demonstrating differences in transcript abundance between male and female Danio rerio. Under conservative statistical significance criteria, all sex-biases in gene expression were due to differences between testes and ovaries. Male-enriched genes were more abundant than female-enriched genes, and expression bias for male-enriched genes was greater in magnitude than that for female-enriched genes. We also identified a large number of genes demonstrating elevated transcript abundance in testes and ovaries relative to male body and female body, respectively. Conclusion Overall our results support the hypothesis that male-biased evolutionary pressures have resulted in male-biased patterns of gene expression. Interestingly, our results seem to be at odds with a handful of other microarray-based studies of sex-specific gene expression patterns in zebrafish. However, ours was the only study designed to address this specific hypothesis, and major methodological differences among studies could explain the discrepancies. Regardless, all of these studies agree

  13. Preparation of oligonucleotide microarray for radiation-associated gene expression detection and its application in lung cancer cell lines

    International Nuclear Information System (INIS)

    Guo Wanfeng; Lin Ruxian; Huang Jian; Guo Guozhen; Wang Shengqi

    2005-01-01

    Objective: The response of tumor cell to radiation is accompanied by complex change in patterns of gene expression. It is highly probable that a better understanding of molecular and genetic changes can help to sensitize the radioresistant tumor cells. Methods: Oligonucleotide microarray provides a powerful tool for high-throughput identifying a wider range of genes involved in the radioresistance. Therefore, the authors designed one oligonucleotide microarray according to the biological effect of IR. By using different radiosensitive lung cancer cell lines, the authors identified genes showing altered expression in lung cancer cell lines. To provide independent confirmation of microarray data, semi-quantitative RT-PCR was performed on a selection of genes. Results: In radioresistant A549 cell lines, a total of 18 genes were selected as having significant fold-changes compared to NCI-H446, 8 genes were up-regulated and 10 genes were down-regulated. Subsequently, A549 and NCI-H446 cells were delivered by ionizing radiation. In A549 cell line, we found 22 (19 up-regulated and 3 down-regulated) and 26 (8 up-regulated and 18 down-regulated) differentially expressed genes at 6h and 24h after ionizing radiation. In NCI-H446 cell line, we identified 17 (9 up-regulated and 8 down-regulated) and 18 (6 up-regulated and 12 down-regulated) differentially expressed genes at 6 h and 24 h after ionizing radiation. The authors tested seven genes (MDM2, p53, XRCC5, Bcl-2, PIM2, NFKBIA and Cyclin B1) for RT-PCR, and found that the results were in good agreement with those from the microarray data except for NFKBIA gene, even though the value for each mRNA level might be different between the two measurements. In present study, the authors identified some genes with cell proliferation and anti-apoptosis, such as MdM2, BCL-2, PKCz and PIM2 expression levels increased in A549 cells and decreased in NCI-H446 cells after radiation, and other genes with DNA repair, such as XRCC5, ERCC5

  14. Multi-platform whole-genome microarray analyses refine the epigenetic signature of breast cancer metastasis with gene expression and copy number.

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    Joseph Andrews

    Full Text Available BACKGROUND: We have previously identified genome-wide DNA methylation changes in a cell line model of breast cancer metastasis. These complex epigenetic changes that we observed, along with concurrent karyotype analyses, have led us to hypothesize that complex genomic alterations in cancer cells (deletions, translocations and ploidy are superimposed over promoter-specific methylation events that are responsible for gene-specific expression changes observed in breast cancer metastasis. METHODOLOGY/PRINCIPAL FINDINGS: We undertook simultaneous high-resolution, whole-genome analyses of MDA-MB-468GFP and MDA-MB-468GFP-LN human breast cancer cell lines (an isogenic, paired lymphatic metastasis cell line model using Affymetrix gene expression (U133, promoter (1.0R, and SNP/CNV (SNP 6.0 microarray platforms to correlate data from gene expression, epigenetic (DNA methylation, and combination copy number variant/single nucleotide polymorphism microarrays. Using Partek Software and Ingenuity Pathway Analysis we integrated datasets from these three platforms and detected multiple hypomethylation and hypermethylation events. Many of these epigenetic alterations correlated with gene expression changes. In addition, gene dosage events correlated with the karyotypic differences observed between the cell lines and were reflected in specific promoter methylation patterns. Gene subsets were identified that correlated hyper (and hypo methylation with the loss (or gain of gene expression and in parallel, with gene dosage losses and gains, respectively. Individual gene targets from these subsets were also validated for their methylation, expression and copy number status, and susceptible gene pathways were identified that may indicate how selective advantage drives the processes of tumourigenesis and metastasis. CONCLUSIONS/SIGNIFICANCE: Our approach allows more precisely profiling of functionally relevant epigenetic signatures that are associated with cancer

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

    International Nuclear Information System (INIS)

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

    2006-01-01

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

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

    Science.gov (United States)

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

    2006-07-21

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

  17. Differential gene expression from microarray analysis distinguishes woven and lamellar bone formation in the rat ulna following mechanical loading.

    Directory of Open Access Journals (Sweden)

    Jennifer A McKenzie

    Full Text Available Formation of woven and lamellar bone in the adult skeleton can be induced through mechanical loading. Although much is known about the morphological appearance and structural properties of the newly formed bone, the molecular responses to loading are still not well understood. The objective of our study was to use a microarray to distinguish the molecular responses between woven and lamellar bone formation induced through mechanical loading. Rat forelimb loading was completed in a single bout to induce the formation of woven bone (WBF loading or lamellar bone (LBF loading. A set of normal (non-loaded rats were used as controls. Microarrays were performed at three timepoints after loading: 1 hr, 1 day and 3 days. Confirmation of microarray results was done for a select group of genes using quantitative real-time PCR (qRT-PCR. The micorarray identified numerous genes and pathways that were differentially regulated for woven, but not lamellar bone formation. Few changes in gene expression were evident comparing lamellar bone formation to normal controls. A total of 395 genes were differentially expressed between formation of woven and lamellar bone 1 hr after loading, while 5883 and 5974 genes were differentially expressed on days 1 and 3, respectively. Results suggest that not only are the levels of expression different for each type of bone formation, but that distinct pathways are activated only for woven bone formation. A strong early inflammatory response preceded an increase in angiogenic and osteogenic gene expression for woven bone formation. Furthermore, at later timepoints there was evidence of bone resorption after WBF loading. In summary, the vast coverage of the microarray offers a comprehensive characterization of the early differences in expression between woven and lamellar bone formation.

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

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    Nicolas M Bertagnolli

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

  19. Genome-Wide Gene Expression Profiling of Nucleus Accumbens Neurons Projecting to Ventral Pallidum Using both Microarray and Transcriptome Sequencing.

    Science.gov (United States)

    Chen, Hao; Liu, Zhimin; Gong, Suzhen; Wu, Xingjun; Taylor, William L; Williams, Robert W; Matta, Shannon G; Sharp, Burt M

    2011-01-01

    The cellular heterogeneity of brain poses a particularly thorny issue in genome-wide gene expression studies. Because laser capture microdissection (LCM) enables the precise extraction of a small area of tissue, we combined LCM with neuronal track tracing to collect nucleus accumbens shell neurons that project to ventral pallidum, which are of particular interest in the study of reward and addiction. Four independent biological samples of accumbens projection neurons were obtained. Approximately 500 pg of total RNA from each sample was then amplified linearly and subjected to Affymetrix microarray and Applied Biosystems sequencing by oligonucleotide ligation and detection (SOLiD) transcriptome sequencing (RNA-seq). A total of 375 million 50-bp reads were obtained from RNA-seq. Approximately 57% of these reads were mapped to the rat reference genome (Baylor 3.4/rn4). Approximately 11,000 unique RefSeq genes and 100,000 unique exons were identified from each sample. Of the unmapped reads, the quality scores were 4.74 ± 0.42 lower than the mapped reads. When RNA-seq and microarray data from the same samples were compared, Pearson correlations were between 0.764 and 0.798. The variances in data obtained for the four samples by microarray and RNA-seq were similar for medium to high abundance genes, but less among low abundance genes detected by microarray. Analysis of 34 genes by real-time polymerase chain reaction showed higher correlation with RNA-seq (0.66) than with microarray (0.46). Further analysis showed 20-30 million 50-bp reads are sufficient to provide estimates of gene expression levels comparable to those produced by microarray. In summary, this study showed that picogram quantities of total RNA obtained by LCM of ∼700 individual neurons is sufficient to take advantage of the benefits provided by the transcriptome sequencing technology, such as low background noise, high dynamic range, and high precision.

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

    Directory of Open Access Journals (Sweden)

    Martinez M Juanita

    2005-05-01

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

  1. Carbon nanoparticles as detection labels in antibody microarrays. Detection of genes encoding virulence factors in Shiga toxin-producing Escherichia coli.

    NARCIS (Netherlands)

    Noguera, P.S.; Posthuma-Trumpie, G.A.; Tuil, Van M.; Wal, van der F.J.; Boer, De A.; Moers, A.P.H.A.; Amerongen, Van A.

    2011-01-01

    The present study demonstrates that carbon nanoparticles (CNPs) can be used as labels in microarrays. CNPs were used in nucleic acid microarray immunoassays (NAMIAs) for the detection of different Shiga toxin-producing Escherichia coli (STEC) virulence factors: four genes specific for STEC (vt1,

  2. Tumor classification and marker gene prediction by feature selection and fuzzy c-means clustering using microarray data

    Directory of Open Access Journals (Sweden)

    Jonassen Inge

    2003-12-01

    Full Text Available Abstract Background Using DNA microarrays, we have developed two novel models for tumor classification and target gene prediction. First, gene expression profiles are summarized by optimally selected Self-Organizing Maps (SOMs, followed by tumor sample classification by Fuzzy C-means clustering. Then, the prediction of marker genes is accomplished by either manual feature selection (visualizing the weighted/mean SOM component plane or automatic feature selection (by pair-wise Fisher's linear discriminant. Results The proposed models were tested on four published datasets: (1 Leukemia (2 Colon cancer (3 Brain tumors and (4 NCI cancer cell lines. The models gave class prediction with markedly reduced error rates compared to other class prediction approaches, and the importance of feature selection on microarray data analysis was also emphasized. Conclusions Our models identify marker genes with predictive potential, often better than other available methods in the literature. The models are potentially useful for medical diagnostics and may reveal some insights into cancer classification. Additionally, we illustrated two limitations in tumor classification from microarray data related to the biology underlying the data, in terms of (1 the class size of data, and (2 the internal structure of classes. These limitations are not specific for the classification models used.

  3. Comparative transcript profiling of gene expression between seedless Ponkan mandarin and its seedy wild type during floral organ development by suppression subtractive hybridization and cDNA microarray

    Directory of Open Access Journals (Sweden)

    Qiu Wen-Ming

    2012-08-01

    Full Text Available Abstract Background Seedlessness is an important agronomic trait for citrus, and male sterility (MS is one main cause of seedless citrus fruit. However, the molecular mechanism of citrus seedlessness remained not well explored. Results An integrative strategy combining suppression subtractive hybridization (SSH library with cDNA microarray was employed to study the underlying mechanism of seedlessness of a Ponkan mandarin seedless mutant (Citrus reticulata Blanco. Screening with custom microarray, a total of 279 differentially expressed clones were identified, and 133 unigenes (43 contigs and 90 singletons were obtained after sequencing. Gene Ontology (GO distribution based on biological process suggested that the majority of differential genes are involved in metabolic process and respond to stimulus and regulation of biology process; based on molecular function they function as DNA/RNA binding or have catalytic activity and oxidoreductase activity. A gene encoding male sterility-like protein was highly up-regulated in the seedless mutant compared with the wild type, while several transcription factors (TFs such as AP2/EREBP, MYB, WRKY, NAC and C2C2-GATA zinc-finger domain TFs were down-regulated. Conclusion Our research highlighted some candidate pathways that participated in the citrus male gametophyte development and could be beneficial for seedless citrus breeding in the future.

  4. Comparing gene discovery from Affymetrix GeneChip microarrays and Clontech PCR-select cDNA subtraction: a case study

    Directory of Open Access Journals (Sweden)

    Wright Paul S

    2004-04-01

    Full Text Available Abstract Background Several high throughput technologies have been employed to identify differentially regulated genes that may be molecular targets for drug discovery. Here we compared the sets of differentially regulated genes discovered using two experimental approaches: a subtracted suppressive hybridization (SSH cDNA library methodology and Affymetrix GeneChip® technology. In this "case study" we explored the transcriptional pattern changes during the in vitro differentiation of human monocytes to myeloid dendritic cells (DC, and evaluated the potential for novel gene discovery using the SSH methodology. Results The same RNA samples isolated from peripheral blood monocyte precursors and immature DC (iDC were used for GeneChip microarray probing and SSH cDNA library construction. 10,000 clones from each of the two-way SSH libraries (iDC-monocytes and monocytes-iDC were picked for sequencing. About 2000 transcripts were identified for each library from 8000 successful sequences. Only 70% to 75% of these transcripts were represented on the U95 series GeneChip microarrays, implying that 25% to 30% of these transcripts might not have been identified in a study based only on GeneChip microarrays. In addition, about 10% of these transcripts appeared to be "novel", although these have not yet been closely examined. Among the transcripts that are also represented on the chips, about a third were concordantly discovered as differentially regulated between iDC and monocytes by GeneChip microarray transcript profiling. The remaining two thirds were either not inferred as differentially regulated from GeneChip microarray data, or were called differentially regulated but in the opposite direction. This underscores the importance both of generating reciprocal pairs of SSH libraries, and of real-time RT-PCR confirmation of the results. Conclusions This study suggests that SSH could be used as an alternative and complementary transcript profiling tool to

  5. Hypoxic transcription gene profiles under the modulation of nitric oxide in nuclear run on-microarray and proteomics

    OpenAIRE

    Igwe, Emeka I.; Essler, Silke; Al-Furoukh, Natalie; Dehne, Nathalie; Brüne, Bernhard

    2009-01-01

    Abstract Background Microarray analysis still is a powerful tool to identify new components of the transcriptosome. It helps to increase the knowledge of targets triggered by stress conditions such as hypoxia and nitric oxide. However, analysis of transcriptional regulatory events remain elusive due to the contribution of altered mRNA stability to gene expression patterns as well as changes in the half-life of mRNAs, which influence mRNA expression levels and their turn over rates. To circumv...

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

    Directory of Open Access Journals (Sweden)

    Liu Johnson M

    2002-11-01

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

  7. Gene expression profiling of whole blood: Comparison of target preparation methods for accurate and reproducible microarray analysis

    Science.gov (United States)

    Vartanian, Kristina; Slottke, Rachel; Johnstone, Timothy; Casale, Amanda; Planck, Stephen R; Choi, Dongseok; Smith, Justine R; Rosenbaum, James T; Harrington, Christina A

    2009-01-01

    Background Peripheral blood is an accessible and informative source of transcriptomal information for many human disease and pharmacogenomic studies. While there can be significant advantages to analyzing RNA isolated from whole blood, particularly in clinical studies, the preparation of samples for microarray analysis is complicated by the need to minimize artifacts associated with highly abundant globin RNA transcripts. The impact of globin RNA transcripts on expression profiling data can potentially be reduced by using RNA preparation and labeling methods that remove or block globin RNA during the microarray assay. We compared four different methods for preparing microarray hybridization targets from human whole blood collected in PAXGene tubes. Three of the methods utilized the Affymetrix one-cycle cDNA synthesis/in vitro transcription protocol but varied treatment of input RNA as follows: i. no treatment; ii. treatment with GLOBINclear; or iii. treatment with globin PNA oligos. In the fourth method cDNA targets were prepared with the Ovation amplification and labeling system. Results We find that microarray targets generated with labeling methods that reduce globin mRNA levels or minimize the impact of globin transcripts during hybridization detect more transcripts in the microarray assay compared with the standard Affymetrix method. Comparison of microarray results with quantitative PCR analysis of a panel of genes from the NF-kappa B pathway shows good correlation of transcript measurements produced with all four target preparation methods, although method-specific differences in overall correlation were observed. The impact of freezing blood collected in PAXGene tubes on data reproducibility was also examined. Expression profiles show little or no difference when RNA is extracted from either fresh or frozen blood samples. Conclusion RNA preparation and labeling methods designed to reduce the impact of globin mRNA transcripts can significantly improve the

  8. A Growth Curve Model with Fractional Polynomials for Analysing Incomplete Time-Course Data in Microarray Gene Expression Studies

    Science.gov (United States)

    Tan, Qihua; Thomassen, Mads; Hjelmborg, Jacob v. B.; Clemmensen, Anders; Andersen, Klaus Ejner; Petersen, Thomas K.; McGue, Matthew; Christensen, Kaare; Kruse, Torben A.

    2011-01-01

    Identifying the various gene expression response patterns is a challenging issue in expression microarray time-course experiments. Due to heterogeneity in the regulatory reaction among thousands of genes tested, it is impossible to manually characterize a parametric form for each of the time-course pattern in a gene by gene manner. We introduce a growth curve model with fractional polynomials to automatically capture the various time-dependent expression patterns and meanwhile efficiently handle missing values due to incomplete observations. For each gene, our procedure compares the performances among fractional polynomial models with power terms from a set of fixed values that offer a wide range of curve shapes and suggests a best fitting model. After a limited simulation study, the model has been applied to our human in vivo irritated epidermis data with missing observations to investigate time-dependent transcriptional responses to a chemical irritant. Our method was able to identify the various nonlinear time-course expression trajectories. The integration of growth curves with fractional polynomials provides a flexible way to model different time-course patterns together with model selection and significant gene identification strategies that can be applied in microarray-based time-course gene expression experiments with missing observations. PMID:21966290

  9. Extending the scope of diagnostic chromosome analysis: detection of single gene defects using high-resolution SNP microarrays.

    Science.gov (United States)

    Bruno, Damien L; Stark, Zornitza; Amor, David J; Burgess, Trent; Butler, Kathy; Corrie, Sylvea; Francis, David; Ganesamoorthy, Devika; Hills, Louise; James, Paul A; O'Rielly, Darren; Oertel, Ralph; Savarirayan, Ravi; Prabhakara, Krishnamurthy; Salce, Nicholas; Slater, Howard R

    2011-12-01

    Microarray analysis has provided significant advances in the diagnosis of conditions resulting from submicroscopic chromosome abnormalities. It has been recommended that array testing should be a "first tier" test in the evaluation of individuals with intellectual disability, developmental delay, congenital anomalies, and autism. The availability of arrays with increasingly high probe coverage and resolution has increased the detection of decreasingly small copy number changes (CNCs) down to the intragenic or even exon level. Importantly, arrays that genotype SNPs also detect extended regions of homozygosity. We describe 14 examples of single gene disorders caused by intragenic changes from a consecutive set of 6,500 tests using high-resolution SNP microarrays. These cases illustrate the increased scope of cytogenetic testing beyond dominant chromosome rearrangements that typically contain many genes. Nine of the cases confirmed the clinical diagnosis, that is, followed a "phenotype to genotype" approach. Five were diagnosed by the laboratory analysis in the absence of a specific clinical diagnosis, that is, followed a "genotype to phenotype" approach. Two were clinically significant, incidental findings. The importance of astute clinical assessment and laboratory-clinician consultation is emphasized to optimize the value of microarrays in the diagnosis of disorders caused by single gene copy number and sequence mutations. © 2011 Wiley-Liss, Inc.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2006-09-15

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

  11. Hypoxic transcription gene profiles under the modulation of nitric oxide in nuclear run on-microarray and proteomics

    Directory of Open Access Journals (Sweden)

    Dehne Nathalie

    2009-09-01

    Full Text Available Abstract Background Microarray analysis still is a powerful tool to identify new components of the transcriptosome. It helps to increase the knowledge of targets triggered by stress conditions such as hypoxia and nitric oxide. However, analysis of transcriptional regulatory events remain elusive due to the contribution of altered mRNA stability to gene expression patterns as well as changes in the half-life of mRNAs, which influence mRNA expression levels and their turn over rates. To circumvent these problems, we have focused on the analysis of newly transcribed (nascent mRNAs by nuclear run on (NRO, followed by microarray analysis. Results We identified 196 genes that were significantly regulated by hypoxia, 85 genes affected by nitric oxide and 292 genes induced by the cotreatment of macrophages with both NO and hypoxia. Fourteen genes (Bnip3, Ddit4, Vegfa, Trib3, Atf3, Cdkn1a, Scd1, D4Ertd765e, Sesn2, Son, Nnt, Lst1, Hps6 and Fxyd5 were common to all treatments but with different levels of expression in each group. We observed that 162 transcripts were regulated only when cells were co-treated with hypoxia and NO but not with either treatment alone, pointing to the importance of a crosstalk between hypoxia and NO. In addition, both array and proteomics data supported a consistent repression of hypoxia-regulated targets by NO. Conclusion By eliminating the interference of steady state mRNA in gene expression profiling, we obtained a smaller number of significantly regulated transcripts in our study compared to published microarray data and identified previously unknown hypoxia-induced targets. Gene analysis profiling corroborated the interplay between NO- and hypoxia-induced signaling.

  12. Methods for interpreting lists of affected genes obstained in a DNA microarray experiment

    OpenAIRE

    Hedegaard, J.; Arce, A.M.G.; Bicciato, S.; Bonnet, A.; Buitenhuis, B.; Collado, M.C.; Conley, L.N.; San Cristobal, M.; Ferrari, F.; Garrido, J.J.; Groenen, M.A.M.; Hornshoj, H.; Hulsegge, B.; Jiang, L.; Jimenez-Marin, A.

    2009-01-01

    Background - The aim of this paper was to describe and compare the methods used and the results obtained by the participants in a joint EADGENE (European Animal Disease Genomic Network of Excellence) and SABRE (Cutting Edge Genomics for Sustainable Animal Breeding) workshop focusing on post analysis of microarray data. The participating groups were provided with identical lists of microarray probes, including test statistics for three different contrasts, and the normalised log-ratios for eac...

  13. Microarray analysis of androgen-regulated gene expression in testis: the use of the androgen-binding protein (ABP-transgenic mouse as a model

    Directory of Open Access Journals (Sweden)

    Grossman Gail

    2005-12-01

    Full Text Available Abstract Background Spermatogenesis is an androgen-dependent process, yet the molecular mechanisms of androgens' actions in testis are poorly understood. Transgenic mice overexpressing rat androgen-binding protein (ABP in their testes have reduced levels of intratesticular androgens and, as a result, show a progressive impairment of spermatogenesis. We used this model to characterize changes in global gene expression in testis in response to reduced bioavailability of androgens. Methods Total RNA was extracted from testes of 30-day old transgenic and wild-type control mice, converted to cRNA, labeled with biotin, and hybridized to oligonucleotide microarrays. Microarray results were confirmed by real-time reverse transcription polymerase chain reaction. Results Three-hundred-eighty-one genes (3.05% of all transcripts represented on the chips were up-regulated and 198 genes (1.59% were down-regulated by at least a factor of 2 in the androgen-deficient animals compared to controls. Genes encoding membrane proteins, intracellular signaling molecules, enzymes, proteins participating in the immune response, and those involved in cytoskeleton organization were significantly overrepresented in the up-regulated group. Among the down-regulated transcripts, those coding for extracellular proteins were overrepresented most dramatically, followed by those related to proteolysis, cell adhesion, immune response, and growth factor, cytokine, and ion channel activities. Transcripts with the greatest potential impact on cellular activities included several transcription factors, intracellular signal transducers, secreted signaling molecules and enzymes, and various cell surface molecules. Major nodes in the up-regulated network were IL-6, AGT, MYC, and A2M, those in the down-regulated network were IL-2, -4, and -10, MAPK8, SOCS1, and CREB1. Conclusion Microarray analysis followed by gene ontology profiling and connectivity analysis identified several functional

  14. Identification of MicroRNAs and target genes involvement in hepatocellular carcinoma with microarray data.

    Science.gov (United States)

    Wang, Dadong; Tan, Jingwang; Xu, Yong; Tan, Xianglong; Han, Mingming; Tu, Yuliang; Zhu, Ziman; Zen, Jianping; Dou, Chunqing; Cai, Shouwang

    2015-01-01

    The aim of the study is to identify the differentially expressed microRNAs (miRNAs) between hepatocellular carcinoma (HCC) samples and controls and provide new diagnostic potential miRNAs for HCC. The miRNAs expression profile data GSE20077 included 7 HCC samples, 1 HeLa sample and 3 controls. Differentially expressed miRNAs (DE-miRNAs) were identified by t-test and wilcox test. The miRNA with significantly differential expression was chosen for further analysis. Target genes for this miRNA were selected using TargetScan and miRbase database. STRING software was applied to construct the target genes interaction network and topology analysis was carried out to identify the hub gene in the network. And we identified the mechanism for affecting miRNA function. A total of 54 differentially expressed miRNAs were identified, in which there were 13 miRNAs published to be related to HCC. The differentially expressed hsa-miR-106b was chosen for further analysis and PTPRT (Receptor-type tyrosine-protein phosphatase T) was its potential target gene. The target genes interaction network was constructed among 33 genes, in which PTPRT was the hub gene. We got the conclusion that the differentially expressed hsa-miR-106b may play an important role in the development of HCC by regulating the expression of its potential target gene PT-PRT.

  15. Comparative RNA-Seq and microarray analysis of gene expression changes in B-cell lymphomas of Canis familiaris.

    Directory of Open Access Journals (Sweden)

    Marie Mooney

    Full Text Available Comparative oncology is a developing research discipline that is being used to assist our understanding of human neoplastic diseases. Companion canines are a preferred animal oncology model due to spontaneous tumor development and similarity to human disease at the pathophysiological level. We use a paired RNA sequencing (RNA-Seq/microarray analysis of a set of four normal canine lymph nodes and ten canine lymphoma fine needle aspirates to identify technical biases and variation between the technologies and convergence on biological disease pathways. Surrogate Variable Analysis (SVA provides a formal multivariate analysis of the combined RNA-Seq/microarray data set. Applying SVA to the data allows us to decompose variation into contributions associated with transcript abundance, differences between the technology, and latent variation within each technology. A substantial and highly statistically significant component of the variation reflects transcript abundance, and RNA-Seq appeared more sensitive for detection of transcripts expressed at low levels. Latent random variation among RNA-Seq samples is also distinct in character from that impacting microarray samples. In particular, we observed variation between RNA-Seq samples that reflects transcript GC content. Platform-independent variable decomposition without a priori knowledge of the sources of variation using SVA represents a generalizable method for accomplishing cross-platform data analysis. We identified genes differentially expressed between normal lymph nodes of disease free dogs and a subset of the diseased dogs diagnosed with B-cell lymphoma using each technology. There is statistically significant overlap between the RNA-Seq and microarray sets of differentially expressed genes. Analysis of overlapping genes in the context of biological systems suggests elevated expression and activity of PI3K signaling in B-cell lymphoma biopsies compared with normal biopsies, consistent with

  16. Identification of self-consistent modulons from bacterial microarray expression data with the help of structured regulon gene sets

    KAUST Repository

    Permina, Elizaveta A.

    2013-01-01

    Identification of bacterial modulons from series of gene expression measurements on microarrays is a principal problem, especially relevant for inadequately studied but practically important species. Usage of a priori information on regulatory interactions helps to evaluate parameters for regulatory subnetwork inference. We suggest a procedure for modulon construction where a seed regulon is iteratively updated with genes having expression patterns similar to those for regulon member genes. A set of genes essential for a regulon is used to control modulon updating. Essential genes for a regulon were selected as a subset of regulon genes highly related by different measures to each other. Using Escherichia coli as a model, we studied how modulon identification depends on the data, including the microarray experiments set, the adopted relevance measure and the regulon itself. We have found that results of modulon identification are highly dependent on all parameters studied and thus the resulting modulon varies substantially depending on the identification procedure. Yet, modulons that were identified correctly displayed higher stability during iterations, which allows developing a procedure for reliable modulon identification in the case of less studied species where the known regulatory interactions are sparse. Copyright © 2013 Taylor & Francis.

  17. cDNA microarray assessment of early gene expression profiles in Escherichia coli cells exposed to a mixture of heavy metals.

    Science.gov (United States)

    Gómez-Sagasti, María T; Becerril, José M; Martín, Iker; Epelde, Lur; Garbisu, Carlos

    2014-08-01

    Many contaminated sites are characterized by the presence of different metals, thus increasing the complexity of toxic responses in exposed organisms. Within toxicogenomics, transcriptomics can be approached through the use of microarrays aimed at producing a genetic fingerprint for the response of model organisms to the presence of chemicals. We studied temporal changes in the early gene expression profiles of Escherichia coli cells exposed to three metal doses of a polymetallic solution over three exposure times, through the application of cDNA microarray technology. In the absence of metals, many genes belonging to a variety of cellular functions were up- and down-regulated over time. At the lowest metal dose, an activation of metal-specific transporters (Cus and ZraP proteins) and a mobilization of glutathione transporters involved in metal sequestration and trafficking was observed over time; this metal dose resulted in the generation of ROS capable of stimulating the transcription of Mn-superoxide dismutase, the assembly of Fe-S clusters and the synthesis of cysteine. At the intermediate dose, an overexpression of ROS scavengers (AhpF, KatG, and YaaA) and heat shock proteins (ClpP, HslV, DnaK, and IbpAB) was observed. Finally, at the highest dose, E. coli cells showed a repression of genes related with DNA mutation correctors (MutY glycopeptidases).

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

    Science.gov (United States)

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

    2011-10-01

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

  19. Identification of genes regulated by Wnt/β-catenin pathway and involved in apoptosis via microarray analysis

    Directory of Open Access Journals (Sweden)

    Chen Quan

    2006-09-01

    Full Text Available Abstract Background Wnt/β-catenin pathway has critical roles in development and oncogenesis. Although significant progress has been made in understanding the downstream signaling cascade of this pathway, little is known regarding Wnt/β-catenin pathway modification of the cellular apoptosis. Methods To identify potential genes regulated by Wnt/β-catenin pathway and involved in apoptosis, we used a stably integrated, inducible RNA interference (RNAi vector to specific inhibit the expression and the transcriptional activity of β-catenin in HeLa cells. Meanwhile, we designed an oligonucleotide microarray covering 1384 apoptosis-related genes. Using oligonucleotide microarrays, a series of differential expression of genes was identified and further confirmed by RT-PCR. Results Stably integrated inducible RNAi vector could effectively suppress β-catenin expression and the transcriptional activity of β-catenin/TCF. Meanwhile, depletion of β-catenin in this manner made the cells more sensitive to apoptosis. 130 genes involved in some important cell-apoptotic pathways, such as PTEN-PI3K-AKT pathway, NF-κB pathway and p53 pathway, showed significant alteration in their expression level after the knockdown of β-catenin. Conclusion Coupling RNAi knockdown with microarray and RT-PCR analyses proves to be a versatile strategy for identifying genes regulated by Wnt/β-catenin pathway and for a better understanding the role of this pathway in apoptosis. Some of the identified β-catenin/TCF directed or indirected target genes may represent excellent targets to limit tumor growth.

  20. Quantitative multiplex quantum dot in-situ hybridisation based gene expression profiling in tissue microarrays identifies prognostic genes in acute myeloid leukaemia

    Energy Technology Data Exchange (ETDEWEB)

    Tholouli, Eleni [Department of Haematology, Manchester Royal Infirmary, Oxford Road, Manchester, M13 9WL (United Kingdom); MacDermott, Sarah [The Medical School, The University of Manchester, Oxford Road, M13 9PT Manchester (United Kingdom); Hoyland, Judith [School of Biomedicine, Faculty of Medical and Human Sciences, The University of Manchester, Oxford Road, M13 9PT Manchester (United Kingdom); Yin, John Liu [Department of Haematology, Manchester Royal Infirmary, Oxford Road, Manchester, M13 9WL (United Kingdom); Byers, Richard, E-mail: richard.byers@cmft.nhs.uk [School of Cancer and Enabling Sciences, Faculty of Medical and Human Sciences, The University of Manchester, Stopford Building, Oxford Road, M13 9PT Manchester (United Kingdom)

    2012-08-24

    Highlights: Black-Right-Pointing-Pointer Development of a quantitative high throughput in situ expression profiling method. Black-Right-Pointing-Pointer Application to a tissue microarray of 242 AML bone marrow samples. Black-Right-Pointing-Pointer Identification of HOXA4, HOXA9, Meis1 and DNMT3A as prognostic markers in AML. -- Abstract: Measurement and validation of microarray gene signatures in routine clinical samples is problematic and a rate limiting step in translational research. In order to facilitate measurement of microarray identified gene signatures in routine clinical tissue a novel method combining quantum dot based oligonucleotide in situ hybridisation (QD-ISH) and post-hybridisation spectral image analysis was used for multiplex in-situ transcript detection in archival bone marrow trephine samples from patients with acute myeloid leukaemia (AML). Tissue-microarrays were prepared into which white cell pellets were spiked as a standard. Tissue microarrays were made using routinely processed bone marrow trephines from 242 patients with AML. QD-ISH was performed for six candidate prognostic genes using triplex QD-ISH for DNMT1, DNMT3A, DNMT3B, and for HOXA4, HOXA9, Meis1. Scrambled oligonucleotides were used to correct for background staining followed by normalisation of expression against the expression values for the white cell pellet standard. Survival analysis demonstrated that low expression of HOXA4 was associated with poorer overall survival (p = 0.009), whilst high expression of HOXA9 (p < 0.0001), Meis1 (p = 0.005) and DNMT3A (p = 0.04) were associated with early treatment failure. These results demonstrate application of a standardised, quantitative multiplex QD-ISH method for identification of prognostic markers in formalin-fixed paraffin-embedded clinical samples, facilitating measurement of gene expression signatures in routine clinical samples.

  1. Using microarrays to identify positional candidate genes for QTL: the case study of ACTH response in pigs

    DEFF Research Database (Denmark)

    Jouffe, Vincent; Rowe, Suzanne; Liaubet, Laurence

    2009-01-01

    of 237 differentially expressed cDNA clones in adrenal tissue from two pig breeds, before and after treatment with adrenocorticotropic hormone (ACTH) Microarray studies can supplement QTL studies by suggesting potential candidate genes in the QTL regions, which by themselves are too large to provide...... this with information on published QTL. The starting point is a set of 237 differentially expressed cDNA clones in adrenal tissue from two pig breeds, before and after treatment with adrenocorticotropic hormone (ACTH) Results: Different approaches to localize the differentially expressed (DE) genes to the pig genome...

  2. The 'PUCE CAFE' Project: the first 15K coffee microarray, a new tool for discovering candidate genes correlated to agronomic and quality traits.

    Science.gov (United States)

    Privat, Isabelle; Bardil, Amélie; Gomez, Aureliano Bombarely; Severac, Dany; Dantec, Christelle; Fuentes, Ivanna; Mueller, Lukas; Joët, Thierry; Pot, David; Foucrier, Séverine; Dussert, Stéphane; Leroy, Thierry; Journot, Laurent; de Kochko, Alexandre; Campa, Claudine; Combes, Marie-Christine; Lashermes, Philippe; Bertrand, Benoit

    2011-01-05

    Understanding the genetic elements that contribute to key aspects of coffee biology will have an impact on future agronomical improvements for this economically important tree. During the past years, EST collections were generated in Coffee, opening the possibility to create new tools for functional genomics. The "PUCE CAFE" Project, organized by the scientific consortium NESTLE/IRD/CIRAD, has developed an oligo-based microarray using 15,721 unigenes derived from published coffee EST sequences mostly obtained from different stages of fruit development and leaves in Coffea Canephora (Robusta). Hybridizations for two independent experiments served to compare global gene expression profiles in three types of tissue matter (mature beans, leaves and flowers) in C. canephora as well as in the leaves of three different coffee species (C. canephora, C. eugenoides and C. arabica). Microarray construction, statistical analyses and validation by Q-PCR analysis are presented in this study. We have generated the first 15 K coffee array during this PUCE CAFE project, granted by Génoplante (the French consortium for plant genomics). This new tool will help study functional genomics in a wide range of experiments on various plant tissues, such as analyzing bean maturation or resistance to pathogens or drought. Furthermore, the use of this array has proven to be valid in different coffee species (diploid or tetraploid), drastically enlarging its impact for high-throughput gene expression in the community of coffee research.

  3. Shared probe design and existing microarray reanalysis using PICKY

    Directory of Open Access Journals (Sweden)

    Chou Hui-Hsien

    2010-04-01

    Full Text Available Abstract Background Large genomes contain families of highly similar genes that cannot be individually identified by microarray probes. This limitation is due to thermodynamic restrictions and cannot be resolved by any computational method. Since gene annotations are updated more frequently than microarrays, another common issue facing microarray users is that existing microarrays must be routinely reanalyzed to determine probes that are still useful with respect to the updated annotations. Results PICKY 2.0 can design shared probes for sets of genes that cannot be individually identified using unique probes. PICKY 2.0 uses novel algorithms to track sharable regions among genes and to strictly distinguish them from other highly similar but nontarget regions during thermodynamic comparisons. Therefore, PICKY does not sacrifice the quality of shared probes when choosing them. The latest PICKY 2.1 includes the new capability to reanalyze existing microarray probes against updated gene sets to determine probes that are still valid to use. In addition, more precise nonlinear salt effect estimates and other improvements are added, making PICKY 2.1 more versatile to microarray users. Conclusions Shared probes allow expressed gene family members to be detected; this capability is generally more desirable than not knowing anything about these genes. Shared probes also enable the design of cross-genome microarrays, which facilitate multiple species identification in environmental samples. The new nonlinear salt effect calculation significantly increases the precision of probes at a lower buffer salt concentration, and the probe reanalysis function improves existing microarray result interpretations.

  4. Senescent vs. non-senescent cells in the human annulus in vivo: Cell harvest with laser capture microdissection and gene expression studies with microarray analysis

    Directory of Open Access Journals (Sweden)

    Ingram Jane A

    2010-01-01

    Full Text Available Abstract Background Senescent cells are well-recognized in the aging/degenerating human disc. Senescent cells are viable, cannot divide, remain metabolically active and accumulate within the disc over time. Molecular analysis of senescent cells in tissue offers a special challenge since there are no cell surface markers for senescence which would let one use fluorescence-activated cell sorting as a method for separating out senescent cells. Methods We employed a novel laser capture microdissection (LCM design to selectively harvest senescent and non-senescent annulus cells in paraffin-embedded tissue, and compared their gene expression with microarray analysis. LCM was used to separately harvest senescent and non-senescent cells from 11 human annulus specimens. Results Microarray analysis revealed significant differences in expression levels in senescent cells vs non-senescent cells: 292 genes were upregulated, and 321 downregulated. Genes with established relationships to senescence were found to be significantly upregulated in senescent cells vs. non-senescent cells: p38 (MPAK14, RB-Associated KRAB zinc finger, Discoidin, CUB and LCCL domain, growth arrest and DNA-damage inducible beta, p28ING5, sphingosine-1-phosphate receptor 2 and somatostatin receptor 3; cyclin-dependent kinase 8 showed significant downregulation in senescent cells. Nitric oxidase synthase 1, and heat shock 70 kDa protein 6, both of which were significantly down-regulated in senescent cells, also showed significant changes. Additional genes related to cytokines, cell proliferation, and other processes were also identified. Conclusions Our LCM-microarray analyses identified a set of genes associated with senescence which were significantly upregulated in senescent vs non-senescent cells in the human annulus. These genes include p38 MAP kinase, discoidin, inhibitor of growth family member 5, and growth arrest and DNA-damage-inducible beta. Other genes, including genes

  5. Microarray analysis of inflammatory response-related gene expression in the uteri of dogs with pyometra.

    Science.gov (United States)

    Bukowska, D; Kempisty, B; Zawierucha, P; Jopek, K; Piotrowska, H; Antosik, P; Ciesiółka, S; Woźna, M; Brüssow, K P; Jaśkowski, J M

    2014-01-01

    Pyometra, which is accompanied by bacterial contamination of the uterus, is defined as a complex disease associated with the activation of several systems, including the immune system. The objective of the study was to evaluate the gene expression profile in dogs with pyometra compared with those that were clinically normal. The study included uteri from 43 mongrel bitches (23 with pyometra, 20 clinically healthy). RNA used for the microarray study was pooled to four separated vials for control and pyometra. A total of 17,138 different transcripts were analyzed on the uteri of female dogs with pyometra and of healthy controls. From 264 inflammatory response-related transcripts, we found 23 transcripts that revealed a 10- to 77-fold increased expression. Thereby, the expression of interleukin 8 (IL8), interleukin-1-beta (IL1B), interleukin 18 receptor (IL18RAP), interleukin 1-alpha (IL1A), interleukin receptor antagonist (IL1RN) and interleukin 6 (IL6) increased 77-, 20-, 17-, 13-, 13- and 11-fold, respectively. Furthermore, the expression of the calcium binding proteins S100A8 was 44-fold higher, and that of S100A12 and S100A9 37-fold, respectively, in the uteri of canines with pyometra compared with that of the controls. Moreover, the expression of the transcripts of toll-like receptors (TLR8 and TLR2), integrin beta 2 (ITGB2), chemokine ligand 3 (CCL3), semaphorin 7A (SEMA7A), CD14 and prostaglandin-endoperoxide synthase 2 (PTGS2) was increased between 10- and 18-fold. Furthermore, after using RT-qPCR we found an increased expression of AOAH, IL1A, IL8, CCL3, IL1RN and SERPINE 1 mRNAs which can be served also as markers of the occurrence of pyometra in domestic bitches. In summary, it is concluded that up-regulation of interleukins may be used as a marker of the inflammatory response in dogs with pyometra. Moreover, all of the 23 up-regulated transcripts may be novel molecular markers of the pathogenesis of canine pyometra. Several proteins--–products of these

  6. Suppression subtractive hybridization coupled with microarray analysis to examine differential expression of genes in virus infected cells

    Directory of Open Access Journals (Sweden)

    Munir Shirin

    2004-01-01

    Full Text Available 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.

  7. Identification of testis-relevant genes using in silico analysis from testis ESTs and cDNA microarray in the black tiger shrimp (Penaeus monodon

    Directory of Open Access Journals (Sweden)

    Wongsurawat Thidathip

    2010-08-01

    Full Text Available Abstract Background Poor reproductive maturation of the black tiger shrimp (Penaeus monodon in captivity is one of the serious threats to sustainability of the shrimp farming industry. Understanding molecular mechanisms governing reproductive maturation processes requires the fundamental knowledge of integrated expression profiles in gonads of this economically important species. In P. monodon, a non-model species for which the genome sequence is not available, expressed sequence tag (EST and cDNA microarray analyses can help reveal important transcripts relevant to reproduction and facilitate functional characterization of transcripts with important roles in male reproductive development and maturation. Results In this study, a conventional testis EST library was exploited to reveal novel transcripts. A total of 4,803 ESTs were unidirectionally sequenced and analyzed in silico using a customizable data analysis package, ESTplus. After sequence assembly, 2,702 unique sequences comprised of 424 contigs and 2,278 singletons were identified; of these, 1,133 sequences are homologous to genes with known functions. The sequences were further characterized according to gene ontology categories (41% biological process, 24% molecular function, 35% cellular component. Through comparison with EST libraries of other tissues of P. monodon, 1,579 transcripts found only in the testis cDNA library were identified. A total of 621 ESTs have not been identified in penaeid shrimp. Furthermore, cDNA microarray analysis revealed several ESTs homologous to testis-relevant genes were more preferentially expressed in testis than in ovary. Representatives of these transcripts, homologs of saposin (PmSap and Dmc1 (PmDmc1, were further characterized by RACE-PCR. The more abundant expression levels in testis than ovary of PmSap and PmDmc1 were verified by quantitative real-time PCR in juveniles and wild broodstock of P. monodon. Conclusions Without a genome sequence, a

  8. Functional Associations by Response Overlap (FARO), a functional genomics approach matching gene expression phenotypes

    DEFF Research Database (Denmark)

    Nielsen, Henrik Bjørn; Mundy, J.; Willenbrock, Hanni

    2007-01-01

    for deriving 'Functional Association(s) by Response Overlap' (FARO) between microarray gene expression studies. The transcriptional response is defined by the set of differentially expressed genes independent from the magnitude or direction of the change. This approach overcomes the limited comparability...... to confirm and further delineate the functions of Arabidopsis MAP kinase 4 in disease and stress responses. Furthermore, we find that a large, well-defined set of genes responds in opposing directions to different stress conditions and predict the effects of different stress combinations. This demonstrates...

  9. Microarray gene expression analysis reveals major differences between Toxocara canis and Toxocara cati neurotoxocarosis and involvement of T. canis in lipid biosynthetic processes.

    Science.gov (United States)

    Janecek, Elisabeth; Wilk, Esther; Schughart, Klaus; Geffers, Robert; Strube, Christina

    2015-06-01

    Toxocara canis and Toxocara cati are globally occurring intestinal nematodes of dogs and cats with a high zoonotic potential. Migrating larvae in the CNS of paratenic hosts, including humans, may cause neurotoxocarosis resulting in a variety of neurological symptoms. Toxocara canis exhibits a stronger affinity to the CNS than T. cati, causing more severe neurological symptoms in the mouse model. Pathomechanisms of neurotoxocarosis as well as host responses towards the respective parasite are mostly unknown. Therefore, the aim of this study was to characterise the pathogenesis at a transcriptional level using whole genome microarray expression analysis and identify differences and similarities between T. canis- and T. cati-infected brains. Microarray analysis was conducted in cerebra and cerebella of infected C57Bl/6J mice 42daysp.i. revealing more differentially transcribed genes for T. canis- than T. cati-infected brains. In cerebra and cerebella of T. canis-infected mice, a total of 2304 and 1954 differentially transcribed genes, respectively, were identified whereas 113 and 760 differentially transcribed genes were determined in cerebra and cerebella of T. cati-infected mice. Functional annotation analysis revealed major differences in host responses in terms of significantly enriched biological modules. Up-regulated genes were mainly associated with the terms "immune and defence response", "sensory perception" as well as "behaviour/taxis" retrieved from the Gene Ontology database. These observations indicate a strong immune response in both infection groups with T. cati-infected brains revealing less severe reactions. Down-regulated genes in T. canis-infected cerebra and cerebella revealed a significant enrichment for the Gene Ontology term "lipid/cholesterol biosynthetic process". Cholesterol is a highly abundant and important component in the brain, representing several functions. Disturbances of synthesis as well as concentration changes may lead to

  10. Identification of differentially-expressed genes potentially implicated in drought response in pitaya (Hylocereus undatus) by suppression subtractive hybridization and cDNA microarray analysis.

    Science.gov (United States)

    Fan, Qing-Jie; Yan, Feng-Xia; Qiao, Guang; Zhang, Bing-Xue; Wen, Xiao-Peng

    2014-01-01

    Drought is one of the most severe threats to the growth, development and yield of plant. In order to unravel the molecular basis underlying the high tolerance of pitaya (Hylocereus undatus) to drought stress, suppression subtractive hybridization (SSH) and cDNA microarray approaches were firstly combined to identify the potential important or novel genes involved in the plant responses to drought stress. The forward (drought over drought-free) and reverse (drought-free over drought) suppression subtractive cDNA libraries were constructed using in vitro shoots of cultivar 'Zihonglong' exposed to drought stress and drought-free (control). A total of 2112 clones, among which half were from either forward or reverse SSH library, were randomly picked up to construct a pitaya cDNA microarray. Microarray analysis was carried out to verify the expression fluctuations of this set of clones upon drought treatment compared with the controls. A total of 309 expressed sequence tags (ESTs), 153 from forward library and 156 from reverse library, were obtained, and 138 unique ESTs were identified after sequencing by clustering and blast analyses, which included genes that had been previously reported as responsive to water stress as well as some functionally unknown genes. Thirty six genes were mapped to 47 KEGG pathways, including carbohydrate metabolism, lipid metabolism, energy metabolism, nucleotide metabolism, and amino acid metabolism of pitaya. Expression analysis of the selected ESTs by reverse transcriptase polymerase chain reaction (RT-PCR) corroborated the results of differential screening. Moreover, time-course expression patterns of these selected ESTs further confirmed that they were closely responsive to drought treatment. Among the differentially expressed genes (DEGs), many are related to stress tolerances including drought tolerance. Thereby, the mechanism of drought tolerance of this pitaya genotype is a very complex physiological and biochemical process, in

  11. Microarray profiling of mononuclear peripheral blood cells identifies novel candidate genes related to chemoradiation response in rectal cancer.

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    Pablo Palma

    Full Text Available Preoperative chemoradiation significantly improves oncological outcome in locally advanced rectal cancer. However there is no effective method of predicting tumor response to chemoradiation in these patients. Peripheral blood mononuclear cells have emerged recently as pathology markers of cancer and other diseases, making possible their use as therapy predictors. Furthermore, the importance of the immune response in radiosensivity of solid organs led us to hypothesized that microarray gene expression profiling of peripheral blood mononuclear cells could identify patients with response to chemoradiation in rectal cancer. Thirty five 35 patients with locally advanced rectal cancer were recruited initially to perform the study. Peripheral blood samples were obtained before neaodjuvant treatment. RNA was extracted and purified to obtain cDNA and cRNA for hybridization of microarrays included in Human WG CodeLink bioarrays. Quantitative real time PCR was used to validate microarray experiment data. Results were correlated with pathological response, according to Mandard´s criteria and final UICC Stage (patients with tumor regression grade 1-2 and downstaging being defined as responders and patients with grade 3-5 and no downstaging as non-responders. Twenty seven out of 35 patients were finally included in the study. We performed a multiple t-test using Significance Analysis of Microarrays, to find those genes differing significantly in expression, between responders (n = 11 and non-responders (n = 16 to CRT. The differently expressed genes were: BC 035656.1, CIR, PRDM2, CAPG, FALZ, HLA-DPB2, NUPL2, and ZFP36. The measurement of FALZ (p = 0.029 gene expression level determined by qRT-PCR, showed statistically significant differences between the two groups. Gene expression profiling reveals novel genes in peripheral blood samples of mononuclear cells that could predict responders and non-responders to chemoradiation in patients with

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

    DEFF Research Database (Denmark)

    Dufva, Martin; Petersen, Jesper; Poulsen, Lena

    2009-01-01

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

  13. Microarray analysis of choroid/RPE gene expression in marmoset eyes undergoing changes in ocular growth and refraction

    Science.gov (United States)

    Shelton, Lilian; Troilo, David; Lerner, Megan R; Gusev, Yuriy; Brackett, Daniel J

    2008-01-01

    Purpose: Visually guided ocular growth is facilitated by scleral extracellular matrix remodeling at the posterior pole of the eye. Coincident with scleral remodeling, significant changes in choroidal morphology, blood flow, and protein synthesis have been shown to occur in eyes undergoing ocular growth changes. The current study is designed to identify gene expression changes that may occur in the choroid/retinal pigment epithelium (RPE) of marmoset eyes during their compensation for hyperopic defocus as compared to eyes compensating for myopic defocus. Methods: Total RNA was isolated from choroid/RPE from four common marmosets (Callithrix jacchus) undergoing binocular lens treatment using extended wear soft contact lenses of equal magnitude but opposite sign (±5 diopter [D]). After reverse transcription, cDNA was labeled and hybridized to a human oligonucleotide microarray and gene transcript expression profiles were determined. Real-time polymerase chain reaction (PCR) and western blot analysis were used to confirm genes and proteins of interest, respectively. Results: Microarray analyses in choroid/RPE indicated 204 genes were significantly changed in minus lens-treated as compared with plus lens-treated eyes (pscleral remodeling. PMID:18698376

  14. Possibility of the Use of Public Microarray Database for Identifying Significant Genes Associated with Oral Squamous Cell Carcinoma

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    Ki-Yeol Kim

    2012-03-01

    Full Text Available There are lots of studies attempting to identify the expression changes in oral squamous cell carcinoma. Most studies include insufficient samples to apply statistical methods for detecting significant gene sets. This study combined two small microarray datasets from a public database and identified significant genes associated with the progress of oral squamous cell carcinoma. There were different expression scales between the two datasets, even though these datasets were generated under the same platforms - Affymetrix U133A gene chips. We discretized gene expressions of the two datasets by adjusting the differences between the datasets for detecting the more reliable information. From the combination of the two datasets, we detected 51 significant genes that were upregulated in oral squamous cell carcinoma. Most of them were published in previous studies as cancer-related genes. From these selected genes, significant genetic pathways associated with expression changes were identified. By combining several datasets from the public database, sufficient samples can be obtained for detecting reliable information. Most of the selected genes were known as cancer-related genes, including oral squamous cell carcinoma. Several unknown genes can be biologically evaluated in further studies.

  15. Microarray and synchronization of neuronal differentiation with pathway changes in the Kyoto Encyclopedia of Genes and Genomes (KEGG) databank in nerve growth factor-treated PC12 cells.

    Science.gov (United States)

    Lin, Chih-Ming; Feng, Wayne

    2012-08-01

    The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database creates networks from interrelations between molecular biology and underlying chemical elements. This allows for analysis of biologic networks, genomic information, and higher-order functional information at a systems level. We performed microarray experiments and used the KEGG database, systems biology analysis, and annotation of pathway function to study nerve growth factor (NGF)-induced differentiation of PC12 cells. Cells were cultured to 70%-80% confluence, treated with NGF for 1 or 3 hours (h), and RNA was extracted. Stage 1 data analysis involved analysis of variance (ANOVA), and stage 2 involved cluster analysis and heat map generation. We identified 2020 NGF-induced PC12 genes (1038 at 1 h and 1554 at 3 h). Results showed changes in gene expression over time. We compared these genes with 6035 genes from the KEGG database. Cross-matching resulted in 830 genes. Among these, we identified 395 altered genes (155 at 1 h and 301 at 3 h; 2-fold increase from 1 h to 3 h). We identified 191 biologic pathways in the KEGG database; the top 15 showed correlations with neuronal differentiation (mitogen-activated protein kinase [MAPK] pathway: 35 genes at 1 h, 54 genes at 3 h; genes associated with axonal guidance: 12 at 1 h, 26 at 3 h; Wnt pathway: 16 at 1 h, 25 at 3 h; neurotrophin pathway: 4 at 1 h, 14 at 3 h). Thus, we identified changes in neuronal differentiation pathways with the KEGG database, which were synchronized with NGF-induced differentiation.

  16. MIDClass: microarray data classification by association rules and gene expression intervals.

    Directory of Open Access Journals (Sweden)

    Rosalba Giugno

    Full Text Available We present a new classification method for expression profiling data, called MIDClass (Microarray Interval Discriminant CLASSifier, based on association rules. It classifies expressions profiles exploiting the idea that the transcript expression intervals better discriminate subtypes in the same class. A wide experimental analysis shows the effectiveness of MIDClass compared to the most prominent classification approaches.

  17. MIDClass: microarray data classification by association rules and gene expression intervals.

    Science.gov (United States)

    Giugno, Rosalba; Pulvirenti, Alfredo; Cascione, Luciano; Pigola, Giuseppe; Ferro, Alfredo

    2013-01-01

    We present a new classification method for expression profiling data, called MIDClass (Microarray Interval Discriminant CLASSifier), based on association rules. It classifies expressions profiles exploiting the idea that the transcript expression intervals better discriminate subtypes in the same class. A wide experimental analysis shows the effectiveness of MIDClass compared to the most prominent classification approaches.

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

    NARCIS (Netherlands)

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

    2008-01-01

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

  19. Extensive innate immune gene activation accompanies brain aging, increasing vulnerability to cognitive decline and neurodegeneration: a microarray study

    Directory of Open Access Journals (Sweden)

    Cribbs David H

    2012-07-01

    Full Text Available Abstract Background This study undertakes a systematic and comprehensive analysis of brain gene expression profiles of immune/inflammation-related genes in aging and Alzheimer’s disease (AD. Methods In a well-powered microarray study of young (20 to 59 years, aged (60 to 99 years, and AD (74 to 95 years cases, gene responses were assessed in the hippocampus, entorhinal cortex, superior frontal gyrus, and post-central gyrus. Results Several novel concepts emerge. First, immune/inflammation-related genes showed major changes in gene expression over the course of cognitively normal aging, with the extent of gene response far greater in aging than in AD. Of the 759 immune-related probesets interrogated on the microarray, approximately 40% were significantly altered in the SFG, PCG and HC with increasing age, with the majority upregulated (64 to 86%. In contrast, far fewer immune/inflammation genes were significantly changed in the transition to AD (approximately 6% of immune-related probesets, with gene responses primarily restricted to the SFG and HC. Second, relatively few significant changes in immune/inflammation genes were detected in the EC either in aging or AD, although many genes in the EC showed similar trends in responses as in the other brain regions. Third, immune/inflammation genes undergo gender-specific patterns of response in aging and AD, with the most pronounced differences emerging in aging. Finally, there was widespread upregulation of genes reflecting activation of microglia and perivascular macrophages in the aging brain, coupled with a downregulation of select factors (TOLLIP, fractalkine that when present curtail microglial/macrophage activation. Notably, essentially all pathways of the innate immune system were upregulated in aging, including numerous complement components, genes involved in toll-like receptor signaling and inflammasome signaling, as well as genes coding for immunoglobulin (Fc receptors and human

  20. Extensive innate immune gene activation accompanies brain aging, increasing vulnerability to cognitive decline and neurodegeneration: a microarray study

    Science.gov (United States)

    2012-01-01

    Background This study undertakes a systematic and comprehensive analysis of brain gene expression profiles of immune/inflammation-related genes in aging and Alzheimer’s disease (AD). Methods In a well-powered microarray study of young (20 to 59 years), aged (60 to 99 years), and AD (74 to 95 years) cases, gene responses were assessed in the hippocampus, entorhinal cortex, superior frontal gyrus, and post-central gyrus. Results Several novel concepts emerge. First, immune/inflammation-related genes showed major changes in gene expression over the course of cognitively normal aging, with the extent of gene response far greater in aging than in AD. Of the 759 immune-related probesets interrogated on the microarray, approximately 40% were significantly altered in the SFG, PCG and HC with increasing age, with the majority upregulated (64 to 86%). In contrast, far fewer immune/inflammation genes were significantly changed in the transition to AD (approximately 6% of immune-related probesets), with gene responses primarily restricted to the SFG and HC. Second, relatively few significant changes in immune/inflammation genes were detected in the EC either in aging or AD, although many genes in the EC showed similar trends in responses as in the other brain regions. Third, immune/inflammation genes undergo gender-specific patterns of response in aging and AD, with the most pronounced differences emerging in aging. Finally, there was widespread upregulation of genes reflecting activation of microglia and perivascular macrophages in the aging brain, coupled with a downregulation of select factors (TOLLIP, fractalkine) that when present curtail microglial/macrophage activation. Notably, essentially all pathways of the innate immune system were upregulated in aging, including numerous complement components, genes involved in toll-like receptor signaling and inflammasome signaling, as well as genes coding for immunoglobulin (Fc) receptors and human leukocyte antigens I

  1. Identification and comprehensive evaluation of reference genes for RT-qPCR analysis of host gene-expression in Brassica juncea-aphid interaction using microarray data.

    Science.gov (United States)

    Ram, Chet; Koramutla, Murali Krishna; Bhattacharya, Ramcharan

    2017-07-01

    Brassica juncea is a chief oil yielding crop in many parts of the world including India. With advancement of molecular techniques, RT-qPCR based study of gene-expression has become an integral part of experimentations in crop breeding. In RT-qPCR, use of appropriate reference gene(s) is pivotal. The virtue of the reference genes, being constant in expression throughout the experimental treatments, needs to be validated case by case. Appropriate reference gene(s) for normalization of gene-expression data in B. juncea during the biotic stress of aphid infestation is not known. In the present investigation, 11 reference genes identified from microarray database of Arabidopsis-aphid interaction at a cut off FDR ≤0.1, along with two known reference genes of B. juncea, were analyzed for their expression stability upon aphid infestation. These included 6 frequently used and 5 newly identified reference genes. Ranking orders of the reference genes in terms of expression stability were calculated using advanced statistical approaches such as geNorm, NormFinder, delta Ct and BestKeeper. The analysis suggested CAC, TUA and DUF179 as the most suitable reference genes. Further, normalization of the gene-expression data of STP4 and PR1 by the most and the least stable reference gene, respectively has demonstrated importance and applicability of the recommended reference genes in aphid infested samples of B. juncea. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

  2. Microarray Analyses of Genes Differentially Expressed by Diet (Black Beans and Soy Flour during Azoxymethane-Induced Colon Carcinogenesis in Rats

    Directory of Open Access Journals (Sweden)

    Elizabeth A. Rondini

    2012-01-01

    Full Text Available We previously demonstrated that black bean (BB and soy flour (SF-based diets inhibit azoxymethane (AOM-induced colon cancer. The objective of this study was to identify genes altered by carcinogen treatment in normal-appearing colonic mucosa and those attenuated by bean feeding. Ninety-five male F344 rats were fed control (AIN diets upon arrival. At 4 and 5 weeks, rats were injected with AOM (15 mg/kg or saline and one week later administered an AIN, BB-, or SF-based diet. Rats were sacrificed after 31 weeks, and microarrays were conducted on RNA isolated from the distal colonic mucosa. AOM treatment induced a number of genes involved in immunity, including several MHC II-associated antigens and innate defense genes (RatNP-3, Lyz2, Pla2g2a. BB- and SF-fed rats exhibited a higher expression of genes involved in energy metabolism and water and sodium absorption and lower expression of innate (RatNP-3, Pla2g2a, Tlr4, Dmbt1 and cell cycle-associated (Cdc2, Ccnb1, Top2a genes. Genes involved in the extracellular matrix (Col1a1, Fn1 and innate immunity (RatNP-3, Pla2g2a were induced by AOM in all diets, but to a lower extent in bean-fed animals. This profile suggests beans inhibit colon carcinogenesis by modulating cellular kinetics and reducing inflammation, potentially by preserving mucosal barrier function.

  3. Assaying multiple restriction endonucleases functionalities and inhibitions on DNA microarray with multifunctional gold nanoparticle probes.

    Science.gov (United States)

    Ma, Lan; Zhu, Zhijun; Li, Tao; Wang, Zhenxin

    2014-02-15

    Herein, a double-stranded (ds) DNA microarray-based resonance light scattering (RLS) assay with multifunctional gold nanoparticle (GNP) probes has been developed for studying restriction endonuclease functionality and inhibition. Because of decreasing significantly melting temperature, the enzyme-cleaved dsDNAs easily unwind to form single-stranded (ss) DNAs. The ssDNAs are hybridized with multiplex complementary ssDNAs functionalized GNP probes followed by silver enhancement and RLS detection. Three restriction endonucleases (EcoRI, BamHI and EcoRV) and three potential inhibitors (doxorubicin hydrochloride (DOX), ethidium bromide (EB) and an EcoRI-derived helical peptide (α4)) were selected to demonstrate capability of the assay. Enzyme activities of restriction endonucleases are detected simultaneously with high specificity down to the limits of 2.0 × 10(-2)U/mL for EcoRI, 1.1 × 10(-2)U/mL for BamHI and 1.6 × 10(-2)U/mL for EcoRV, respectively. More importantly, the inhibitory potencies of three inhibitors are showed quantitatively, indicating that our approach has great promise for high-throughput screening of restriction endonuclease inhibitors. © 2013 Elsevier B.V. All rights reserved.

  4. A quantitative comparison of cell-type-specific microarray gene expression profiling methods in the mouse brain.

    Directory of Open Access Journals (Sweden)

    Benjamin W Okaty

    Full Text Available Expression profiling of restricted neural populations using microarrays can facilitate neuronal classification and provide insight into the molecular bases of cellular phenotypes. Due to the formidable heterogeneity of intermixed cell types that make up the brain, isolating cell types prior to microarray processing poses steep technical challenges that have been met in various ways. These methodological differences have the potential to distort cell-type-specific gene expression profiles insofar as they may insufficiently filter out contaminating mRNAs or induce aberrant cellular responses not normally present in vivo. Thus we have compared the repeatability, susceptibility to contamination from off-target cell-types, and evidence for stress-responsive gene expression of five different purification methods--Laser Capture Microdissection (LCM, Translating Ribosome Affinity Purification (TRAP, Immunopanning (PAN, Fluorescence Activated Cell Sorting (FACS, and manual sorting of fluorescently labeled cells (Manual. We found that all methods obtained comparably high levels of repeatability, however, data from LCM and TRAP showed significantly higher levels of contamination than the other methods. While PAN samples showed higher activation of apoptosis-related, stress-related and immediate early genes, samples from FACS and Manual studies, which also require dissociated cells, did not. Given that TRAP targets actively translated mRNAs, whereas other methods target all transcribed mRNAs, observed differences may also reflect translational regulation.

  5. Integrating Colon Cancer Microarray Data: Associating Locus-Specific Methylation Groups to Gene Expression-Based Classifications

    Directory of Open Access Journals (Sweden)

    Ana Barat

    2015-11-01

    Full Text Available Recently, considerable attention has been paid to gene expression-based classifications of colorectal cancers (CRC and their association with patient prognosis. In addition to changes in gene expression, abnormal DNA-methylation is known to play an important role in cancer onset and development, and colon cancer is no exception to this rule. Large-scale technologies, such as methylation microarray assays and specific sequencing of methylated DNA, have been used to determine whole genome profiles of CpG island methylation in tissue samples. In this article, publicly available microarray-based gene expression and methylation data sets are used to characterize expression subtypes with respect to locus-specific methylation. A major objective was to determine whether integration of these data types improves previously characterized subtypes, or provides evidence for additional subtypes. We used unsupervised clustering techniques to determine methylation-based subgroups, which are subsequently annotated with three published expression-based classifications, comprising from three to six subtypes. Our results showed that, while methylation profiles provide a further basis for segregation of certain (Inflammatory and Goblet-like finer-grained expression-based subtypes, they also suggest that other finer-grained subtypes are not distinctive and can be considered as a single subtype.

  6. Tissue-wide expression profiling using cDNA subtraction and microarrays to identify tumor-specific genes.

    Science.gov (United States)

    Amatschek, Stefan; Koenig, Ulrich; Auer, Herbert; Steinlein, Peter; Pacher, Margit; Gruenfelder, Agnes; Dekan, Gerhard; Vogl, Sonja; Kubista, Ernst; Heider, Karl-Heinz; Stratowa, Christian; Schreiber, Martin; Sommergruber, Wolfgang

    2004-02-01

    With the objective of discovering novel putative intervention sites for anticancer therapy, we compared transcriptional profiles of breast cancer, lung squamous cell cancer (LSCC), lung adenocarcinoma (LAC), and renal cell cancer (RCC). Each of these tumor types still needs improvement in medical treatment. Our intention was to search for genes not only highly expressed in the majority of patient samples but which also exhibit very low or even absence of expression in a comprehensive panel of 16 critical (vital) normal tissues. To achieve this goal, we combined two powerful technologies, PCR-based cDNA subtraction and cDNA microarrays. Seven subtractive libraries consisting of approximately 9250 clones were established and enriched for tumor-specific transcripts. These clones, together with approximately 1750 additional tumor-relevant genes, were used for cDNA microarray preparation. Hybridizations were performed using a pool of 16 critical normal tissues as a reference in all experiments. In total, we analyzed 20 samples of breast cancer, 11 of LSCC, 11 of LAC, and 8 of RCC. To select for genes with low or even no expression in normal tissues, expression profiles of 22 different normal tissues were additionally analyzed. Importantly, this tissue-wide expression profiling allowed us to eliminate genes, which exhibit also high expression in normal tissues. Similarly, expression signatures of genes, which are derived from infiltrating cells of the immune system, were eliminated as well. Cluster analysis resulted in the identification of 527 expressed sequence tags specifically up-regulated in these tumors. Gene-wise hierarchical clustering of these clones clearly separated the different tumor types with RCC exhibiting the most homogeneous and LAC the most diverse expression profile. In addition to already known tumor-associated genes, the majority of identified genes have not yet been brought into context with tumorigenesis such as genes involved in bone matrix

  7. Profiling Ethylene-Responsive Genes Expressed in the Latex of the Mature Virgin Rubber Trees Using cDNA Microarray.

    Science.gov (United States)

    Nie, Zhiyi; Kang, Guijuan; Duan, Cuifang; Li, Yu; Dai, Longjun; Zeng, Rizhong

    2016-01-01

    Ethylene is commonly used as a latex stimulant of Hevea brasiliensis by application of ethephon (chloro-2-ethylphosphonic acid); however, the molecular mechanism by which ethylene increases latex production is not clear. To better understand the effects of ethylene stimulation on the laticiferous cells of rubber trees, a latex expressed sequence tag (EST)-based complementary DNA microarray containing 2,973 unique genes (probes) was first developed and used to analyze the gene expression changes in the latex of the mature virgin rubber trees after ethephon treatment at three different time-points: 8, 24 and 48 h. Transcript levels of 163 genes were significantly altered with fold-change values ≥ 2 or ≤ -2 (q-value latex actin cytoskeleton might play important roles in ethylene-induced increase of latex production. The results may provide useful insights into understanding the molecular mechanism underlying the effect of ethylene on latex metabolism of H. brasiliensis.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2001-12-01

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

  9. A two-genome microarray for the rice pathogens Xanthomonas oryzae pv. oryzae and X. oryzae pv. oryzicola and its use in the discovery of a difference in their regulation of hrp genes

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    Lin Ye

    2008-06-01

    Full Text Available Abstract Background Xanthomonas oryzae pv. oryzae (Xoo and X. oryzae pv. oryzicola (Xoc are bacterial pathogens of the worldwide staple and grass model, rice. Xoo and Xoc are closely related but Xoo invades rice vascular tissue to cause bacterial leaf blight, a serious disease of rice in many parts of the world, and Xoc colonizes the mesophyll parenchyma to cause bacterial leaf streak, a disease of emerging importance. Both pathogens depend on hrp genes for type III secretion to infect their host. We constructed a 50–70 mer oligonucleotide microarray based on available genome data for Xoo and Xoc and compared gene expression in Xoo strains PXO99A and Xoc strain BLS256 grown in the rich medium PSB vs. XOM2, a minimal medium previously reported to induce hrp genes in Xoo strain T7174. Results Three biological replicates of the microarray experiment to compare global gene expression in representative strains of Xoo and Xoc grown in PSB vs. XOM2 were carried out. The non-specific error rate and the correlation coefficients across biological replicates and among duplicate spots revealed that the microarray data were robust. 247 genes of Xoo and 39 genes of Xoc were differentially expressed in the two media with a false discovery rate of 5% and with a minimum fold-change of 1.75. Semi-quantitative-RT-PCR assays confirmed differential expression of each of 16 genes each for Xoo and Xoc selected for validation. The differentially expressed genes represent 17 functional categories. Conclusion We describe here the construction and validation of a two-genome microarray for the two pathovars of X. oryzae. Microarray analysis revealed that using representative strains, a greater number of Xoo genes than Xoc genes are differentially expressed in XOM2 relative to PSB, and that these include hrp genes and other genes important in interactions with rice. An exception was the rax genes, which are required for production of the host resistance elicitor AvrXa21

  10. Not proper ROC curves as new tool for the analysis of differentially expressed genes in microarray experiments

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    Pistoia Vito

    2008-10-01

    Full Text Available Abstract 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.

  11. Cross-species analysis of gene expression in non-model mammals: reproducibility of hybridization on high density oligonucleotide microarrays

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    Pita-Thomas Wolfgang

    2007-04-01

    Full Text Available Abstract Background Gene expression profiles of non-model mammals may provide valuable data for biomedical and evolutionary studies. However, due to lack of sequence information of other species, DNA microarrays are currently restricted to humans and a few model species. This limitation may be overcome by using arrays developed for a given species to analyse gene expression in a related one, an approach known as "cross-species analysis". In spite of its potential usefulness, the accuracy and reproducibility of the gene expression measures obtained in this way are still open to doubt. The present study examines whether or not hybridization values from cross-species analyses are as reproducible as those from same-species analyses when using Affymetrix oligonucleotide microarrays. Results The reproducibility of the probe data obtained hybridizing deer, Old-World primates, and human RNA samples to Affymetrix human GeneChip® U133 Plus 2.0 was compared. The results show that cross-species hybridization affected neither the distribution of the hybridization reproducibility among different categories, nor the reproducibility values of the individual probes. Our analyses also show that a 0.5% of the probes analysed in the U133 plus 2.0 GeneChip are significantly associated to un-reproducible hybridizations. Such probes-called in the text un-reproducible probe sequences- do not increase in number in cross-species analyses. Conclusion Our study demonstrates that cross-species analyses do not significantly affect hybridization reproducibility of GeneChips, at least within the range of the mammal species analysed here. The differences in reproducibility between same-species and cross-species analyses observed in previous studies were probably caused by the analytical methods used to calculate the gene expression measures. Together with previous observations on the accuracy of GeneChips for cross-species analysis, our analyses demonstrate that cross

  12. Identification of novel candidate target genes in amplicons of Glioblastoma multiforme tumors detected by expression and CGH microarray profiling

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    Hernández-Moneo Jose-Luis

    2006-09-01

    Full Text Available Abstract Background Conventional cytogenetic and comparative genomic hybridization (CGH studies in brain malignancies have shown that glioblastoma multiforme (GBM is characterized by complex structural and numerical alterations. However, the limited resolution of these techniques has precluded the precise identification of detailed specific gene copy number alterations. Results We performed a genome-wide survey of gene copy number changes in 20 primary GBMs by CGH on cDNA microarrays. A novel amplicon at 4p15, and previously uncharacterized amplicons at 13q32-34 and 1q32 were detected and are analyzed here. These amplicons contained amplified genes not previously reported. Other amplified regions containg well-known oncogenes in GBMs were also detected at 7p12 (EGFR, 7q21 (CDK6, 4q12 (PDGFRA, and 12q13-15 (MDM2 and CDK4. In order to identify the putative target genes of the amplifications, and to determine the changes in gene expression levels associated with copy number change events, we carried out parallel gene expression profiling analyses using the same cDNA microarrays. We detected overexpression of the novel amplified genes SLA/LP and STIM2 (4p15, and TNFSF13B and COL4A2 (13q32-34. Some of the candidate target genes of amplification (EGFR, CDK6, MDM2, CDK4, and TNFSF13B were tested in an independent set of 111 primary GBMs by using FISH and immunohistological assays. The novel candidate 13q-amplification target TNFSF13B was amplified in 8% of the tumors, and showed protein expression in 20% of the GBMs. Conclusion This high-resolution analysis allowed us to propose novel candidate target genes such as STIM2 at 4p15, and TNFSF13B or COL4A2 at 13q32-34 that could potentially contribute to the pathogenesis of these tumors and which would require futher investigations. We showed that overexpression of the amplified genes could be attributable to gene dosage and speculate that deregulation of those genes could be important in the development

  13. Expression microarray meta-analysis identifies genes associated with Ras/MAPK and related pathways in progression of muscle-invasive bladder transition cell carcinoma.

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    Jonathan A Ewald

    Full Text Available The effective detection and management of muscle-invasive bladder Transition Cell Carcinoma (TCC continues to be an urgent clinical challenge. While some differences of gene expression and function in papillary (Ta, superficial (T1 and muscle-invasive (≥T2 bladder cancers have been investigated, the understanding of mechanisms involved in the progression of bladder tumors remains incomplete. Statistical methods of pathway-enrichment, cluster analysis and text-mining can extract and help interpret functional information about gene expression patterns in large sets of genomic data. The public availability of patient-derived expression microarray data allows open access and analysis of large amounts of clinical data. Using these resources, we investigated gene expression differences associated with tumor progression and muscle-invasive TCC. Gene expression was calculated relative to Ta tumors to assess progression-associated differences, revealing a network of genes related to Ras/MAPK and PI3K signaling pathways with increased expression. Further, we identified genes within this network that are similarly expressed in superficial Ta and T1 stages but altered in muscle-invasive T2 tumors, finding 7 genes (COL3A1, COL5A1, COL11A1, FN1, ErbB3, MAPK10 and CDC25C whose expression patterns in muscle-invasive tumors are consistent in 5 to 7 independent outside microarray studies. Further, we found increased expression of the fibrillar collagen proteins COL3A1 and COL5A1 in muscle-invasive tumor samples and metastatic T24 cells. Our results suggest that increased expression of genes involved in mitogenic signaling may support the progression of muscle-invasive bladder tumors that generally lack activating mutations in these pathways, while expression changes of fibrillar collagens, fibronectin and specific signaling proteins are associated with muscle-invasive disease. These results identify potential biomarkers and targets for TCC treatments, and

  14. Text analysis of MEDLINE for discovering functional relationships among genes: evaluation of keyword extraction weighting schemes.

    Science.gov (United States)

    Liu, Ying; Navathe, Shamkant B; Pivoshenko, Alex; Dasigi, Venu G; Dingledine, Ray; Ciliax, Brian J

    2006-01-01

    One of the key challenges of microarray studies is to derive biological insights from the gene-expression patterns. Clustering genes by functional keyword association can provide direct information about the functional links among genes. However, the quality of the keyword lists significantly affects the clustering results. We compared two keyword weighting schemes: normalised z-score and term frequency-inverse document frequency (TFIDF). Two gene sets were tested to evaluate the effectiveness of the weighting schemes for keyword extraction for gene clustering. Using established measures of cluster quality, the results produced from TFIDF-weighted keywords outperformed those produced from normalised z-score weighted keywords. The optimised algorithms should be useful for partitioning genes from microarray lists into functionally discrete clusters.

  15. Microarray-based gene expression analysis of strong seed dormancy in rice cv. N22 and less dormant mutant derivatives.

    Science.gov (United States)

    Wu, Tao; Yang, Chunyan; Ding, Baoxu; Feng, Zhiming; Wang, Qian; He, Jun; Tong, Jianhua; Xiao, Langtao; Jiang, Ling; Wan, Jianmin

    2016-02-01

    Seed dormancy in rice is an important trait related to the pre-harvest sprouting resistance. In order to understand the molecular mechanisms of seed dormancy, gene expression was investigated by transcriptome analysis using seeds of the strongly dormant cultivar N22 and its less dormant mutants Q4359 and Q4646 at 24 days after heading (DAH). Microarray data revealed more differentially expressed genes in Q4359 than in Q4646 compared to N22. Most genes differing between Q4646 and N22 also differed between Q4359 and N22. GO analysis of genes differentially expressed in both Q4359 and Q4646 revealed that some genes such as those for starch biosynthesis were repressed, whereas metabolic genes such as those for carbohydrate metabolism were enhanced in Q4359 and Q4646 seeds relative to N22. Expression of some genes involved in cell redox homeostasis and chromatin remodeling differed significantly only between Q4359 and N22. The results suggested a close correlation between cell redox homeostasis, chromatin remodeling and seed dormancy. In addition, some genes involved in ABA signaling were down-regulated, and several genes involved in GA biosynthesis and signaling were up-regulated. These observations suggest that reduced seed dormancy in Q4359 was regulated by ABA-GA antagonism. A few differentially expressed genes were located in the regions containing qSdn-1 and qSdn-5 suggesting that they could be candidate genes underlying seed dormancy. Our work provides useful leads to further determine the underling mechanisms of seed dormancy and for cloning seed dormancy genes from N22. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

  16. A probabilistic approach for automated discovery of perturbed genes using expression data from microarray or RNA-Seq.

    Science.gov (United States)

    Sundaramurthy, Gopinath; Eghbalnia, Hamid R

    2015-12-01

    In complex diseases, alterations of multiple molecular and cellular components in response to perturbations are indicative of disease physiology. While expression level of genes from high-throughput analysis can vary among patients, the common path among disease progression suggests that the underlying cellular sub-processes involving associated genes follow similar fates. Motivated by the interconnected nature of sub-processes, we have developed an automated methodology that combines ideas from biological networks, statistical models, and game theory, to probe connected cellular processes. The core concept in our approach uses probability of change (POC) to indicate the probability that a gene's expression level has changed between two conditions. POC facilitates the definition of change at the neighborhood, pathway, and network levels and enables evaluation of the influence of diseases on the expression. The 'connected' disease-related genes (DRG) identified display coherent and concomitant differential expression levels along paths. RNA-Seq and microarray breast cancer subtyping expression data sets were used to identify DRG between subtypes. A machine-learning algorithm was trained for subtype discrimination using the DRG, and the training yielded a set of biomarkers. The discriminative power of the biomarkers was tested using an unseen data set. Biomarkers identified overlaps with disease-specific identified genes, and we were able to classify disease subtypes with 100% and 80% agreement with PAM50, for microarray and RNA-Seq data set respectively. We present an automated probabilistic approach that offers unbiased and reproducible results, thus complementing existing methods in DRG and biomarker discovery for complex diseases. Copyright © 2015. Published by Elsevier Ltd.

  17. Development of a miniaturised microarray-based assay for the rapid identification of antimicrobial resistance genes in Gram-negative bacteria

    NARCIS (Netherlands)

    Batchelor, M.; Hopkins, K.L.; Liebana, E.; Slickers, P.; Ehricht, R.; Mafura, M.; Aerestrup, F.; Mevius, D.J.; Clifton-Hadley, F.A.; Woodward, M.; Davies, R.; Threlfall, J.; Anjum, F.M.

    2008-01-01

    We describe the development of a miniaturised microarray for the detection of antimicrobial resistance genes in Gram-negative bacteria. Included on the array are genes encoding resistance to aminoglycosides, trimethoprim, sulphonamides, tetracyclines and ß-lactams, including extended-spectrum

  18. The use of microarrays in microbial ecology

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-09-15

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

  19. Inhibition of histone deacetylases in rats self-administering cocaine regulates lissencephaly gene-1 and reelin gene expression, as revealed by microarray technique.

    Science.gov (United States)

    Host, Lionel; Anglard, Patrick; Romieu, Pascal; Thibault, Christelle; Dembele, Doulaye; Aunis, Dominique; Zwiller, Jean

    2010-04-01

    Injection of the histone deacetylase inhibitor trichostatin A (TsA) to rats has been shown to decrease their motivation to self-administer cocaine. In the present study, we investigated alterations in gene expression patterns in the anterior cingulate cortex and nucleus accumbens of rats self-administering cocaine and treated with TsA. Using oligonucleotide microarrays, we identified 722 probe sets in the cortex and 136 probe sets in the nucleus accumbens that were differentially expressed between vehicle and TsA-treated rats that self-administered cocaine. Microarray data were validated by real-time PCR for seven genes. Using immunohistochemistry, we further investigated the expression of Lis1 and reelin genes, because (i) they were similarly regulated by TsA at the mRNA level; (ii) they belong to the same signal transduction pathway; (iii) mutations within both genes cause lissencephaly. Cocaine self-injection was sufficient to activate the two genes at both the mRNA and protein levels. TsA treatment was found to up-regulate both Lis1 and reelin protein expression in the cortex and to down-regulate it in the nucleus accumbens of rats self-administering cocaine. The data suggest that the two proteins contribute to establish neurobiological mechanisms underlying brain plasticity whereby TsA lowers the motivation for cocaine.

  20. Comparative Analyses of MicroRNA Microarrays during Cardiogenesis: Functional Perspectives

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    Diego Franco

    2013-04-01

    Full Text Available Cardiovascular development is a complex process in which several transcriptional pathways are operative, providing instructions to the developing cardiomyocytes, while coping with contraction and morphogenetic movements to shape the mature heart. The discovery of microRNAs has added a new layer of complexity to the molecular mechanisms governing the formation of the heart. Discrete genetic ablation of the microRNAs processing enzymes, such as Dicer and Drosha, has highlighted the functional roles of microRNAs during heart development. Importantly, selective deletion of a single microRNA, miR-1-2, results in an embryonic lethal phenotype in which both morphogenetic, as well as impaired conduction, phenotypes can be observed. In an effort to grasp the variability of microRNA expression during cardiac morphogenesis, we recently reported the dynamic expression profile during ventricular development, highlighting the importance of miR-27 on the regulation of a key cardiac transcription factor, Mef2c. In this review, we compare the microRNA expression profile in distinct models of cardiogenesis, such as ventricular chamber development, induced pluripotent stem cell (iPS-derived cardiomyocytes and the aging heart. Importantly, out of 486 microRNAs assessed in the developing heart, 11% (55 displayed increased expression, many of which are also differentially expressed in distinct cardiogenetic experimental models, including iPS-derived cardiomyocytes. A review on the functional analyses of these differentially expressed microRNAs will be provided in the context of cardiac development, highlighting the resolution and power of microarrays analyses on the quest to decipher the most relevant microRNAs in the developing, aging and diseased heart.

  1. Comparative Analyses of MicroRNA Microarrays during Cardiogenesis: Functional Perspectives.

    Science.gov (United States)

    Bonet, Fernando; Hernandez-Torres, Francisco; Esteban, Franciso J; Aranega, Amelia; Franco, Diego

    2013-04-03

    Cardiovascular development is a complex process in which several transcriptional pathways are operative, providing instructions to the developing cardiomyocytes, while coping with contraction and morphogenetic movements to shape the mature heart. The discovery of microRNAs has added a new layer of complexity to the molecular mechanisms governing the formation of the heart. Discrete genetic ablation of the microRNAs processing enzymes, such as Dicer and Drosha, has highlighted the functional roles of microRNAs during heart development. Importantly, selective deletion of a single microRNA, miR-1-2, results in an embryonic lethal phenotype in which both morphogenetic, as well as impaired conduction, phenotypes can be observed. In an effort to grasp the variability of microRNA expression during cardiac morphogenesis, we recently reported the dynamic expression profile during ventricular development, highlighting the importance of miR-27 on the regulation of a key cardiac transcription factor, Mef2c. In this review, we compare the microRNA expression profile in distinct models of cardiogenesis, such as ventricular chamber development, induced pluripotent stem cell (iPS)-derived cardiomyocytes and the aging heart. Importantly, out of 486 microRNAs assessed in the developing heart, 11% (55) displayed increased expression, many of which are also differentially expressed in distinct cardiogenetic experimental models, including iPS-derived cardiomyocytes. A review on the functional analyses of these differentially expressed microRNAs will be provided in the context of cardiac development, highlighting the resolution and power of microarrays analyses on the quest to decipher the most relevant microRNAs in the developing, aging and diseased heart.

  2. THE VALIDATION OF THE RESULTS OF MICROARRAY STUDIES OF ASSOCIATION BETWEEN GENE POLYMORPHISMS AND THE FREQUENCY OF RADIATION EXPOSURE MARKERS

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    M. V. Khalyuzova

    2014-01-01

    Full Text Available The results from the selective validation research into the association between genetic polymorphisms and the frequency of cytogenetic abnormalities on a large independent sample are analyzed. These polymorphisms have been identified previously during own microarray studies. It has been shown an association with the frequency of dicentric and ring chromosomes induced by radiation exposure. The study was conducted among Siberian Group of Chemical Enterprises healthy employees (n = 573 exposed to professional irradiation in a dose range of 40–400 mSv. We have found that 5 SNP are confirmed to be associated with the frequency of dicentric and ring: INSR rs1051690 – insulin receptor gene; WRNrs2725349 – Werner syndrome gene, RecQ helicase-like; VCAM1 rs1041163 – vascular cell adhesion molecule 1 gene; PCTP rs2114443 – phosphatidylcholine transfer protein gene; TNKS rs7462102 – tankyrase gene; TRF1-interacting ankyrin-related ADP-ribose polymerase. IGF1 rs2373721 – insulin-like growth factor 1 gene has not confirmed to be associated with the frequency of dicentric and ring chromosomes.

  3. Identification of genes related to high royal jelly production in the honey bee (Apis mellifera) using microarray analysis.

    Science.gov (United States)

    Nie, Hongyi; Liu, Xiaoyan; Pan, Jiao; Li, Wenfeng; Li, Zhiguo; Zhang, Shaowu; Chen, Shenglu; Miao, Xiaoqing; Zheng, Nenggan; Su, Songkun

    2017-01-01

    China is the largest royal jelly producer and exporter in the world, and high royal jelly-yielding strains have been bred in the country for approximately three decades. However, information on the molecular mechanism underlying high royal jelly production is scarce. Here, a cDNA microarray was used to screen and identify differentially expressed genes (DEGs) to obtain an overview on the changes in gene expression levels between high and low royal jelly producing bees. We developed a honey bee gene chip that covered 11,689 genes, and this chip was hybridised with cDNA generated from RNA isolated from heads of nursing bees. A total of 369 DEGs were identified between high and low royal jelly producing bees. Amongst these DEGs, 201 (54.47%) genes were up-regulated, whereas 168 (45.53%) were down-regulated in high royal jelly-yielding bees. Gene ontology (GO) analyses showed that they are mainly involved in four key biological processes, and pathway analyses revealed that they belong to a total of 46 biological pathways. These results provide a genetic basis for further studies on the molecular mechanisms involved in high royal jelly production.

  4. Identification of genes related to high royal jelly production in the honey bee (Apis mellifera using microarray analysis

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    Hongyi Nie

    2017-10-01

    Full Text Available Abstract China is the largest royal jelly producer and exporter in the world, and high royal jelly-yielding strains have been bred in the country for approximately three decades. However, information on the molecular mechanism underlying high royal jelly production is scarce. Here, a cDNA microarray was used to screen and identify differentially expressed genes (DEGs to obtain an overview on the changes in gene expression levels between high and low royal jelly producing bees. We developed a honey bee gene chip that covered 11,689 genes, and this chip was hybridised with cDNA generated from RNA isolated from heads of nursing bees. A total of 369 DEGs were identified between high and low royal jelly producing bees. Amongst these DEGs, 201 (54.47% genes were up-regulated, whereas 168 (45.53% were down-regulated in high royal jelly-yielding bees. Gene ontology (GO analyses showed that they are mainly involved in four key biological processes, and pathway analyses revealed that they belong to a total of 46 biological pathways. These results provide a genetic basis for further studies on the molecular mechanisms involved in high royal jelly production.

  5. Serotonin transporter, sex, and hypoxia: microarray analysis in the pulmonary arteries of mice identifies genes with relevance to human PAH

    Science.gov (United States)

    White, Kevin; Loughlin, Lynn; Maqbool, Zakia; Nilsen, Margaret; McClure, John; Dempsie, Yvonne; Baker, Andrew H.

    2011-01-01

    Pulmonary arterial hypertension (PAH) is up to threefold more prevalent in women than men. Female mice overexpressing the serotonin transporter (SERT; SERT+ mice) exhibit PAH and exaggerated hypoxia-induced PAH, whereas male SERT+ mice remain unaffected. To further investigate these sex differences, microarray analysis was performed in the pulmonary arteries of normoxic and chronically hypoxic female and male SERT+ mice. Quantitative RT-PCR analysis was employed for validation of the microarray data. In relevant groups, immunoblotting was performed for genes of interest (CEBPβ, CYP1B1, and FOS). To translate clinical relevance to our findings, CEBPβ, CYP1B1, and FOS mRNA and protein expression was assessed in pulmonary artery smooth muscle cells (PASMCs) derived from idiopathic PAH (IPAH) patients and controls. In female SERT+ mice, multiple pathways with relevance to PAH were altered. This was also observed in chronically hypoxic female SERT+ mice. We selected 10 genes of interest for qRT-PCR analysis (FOS, CEBPβ, CYP1B1, MYL3, HAMP2, LTF, PLN, NPPA, UCP1, and C1S), and 100% concordance was reported. Protein expression of three selected genes, CEBPβ, CYP1B1, FOS, was also upregulated in female SERT+ mice. Serotonin and 17β-estradiol increased CEBPβ, CYP1B1, and FOS protein expression in PASMCs. In addition, CEBPβ, CYP1B1, and FOS mRNA and protein expression was also increased in PASMCs derived from IPAH patients. Here, we have identified a number of genes that may predispose female SERT+ mice to PAH, and these findings may also be relevant to human PAH. PMID:21303932

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

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    Burgess Stewart TG

    2012-02-01

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

  7. Fast DNA Serotyping and Antimicrobial Resistance Gene Determination of Salmonella enterica with an Oligonucleotide Microarray-Based Assay

    Science.gov (United States)

    Braun, Sascha D.; Ziegler, Albrecht; Methner, Ulrich; Slickers, Peter; Keiling, Silke; Monecke, Stefan; Ehricht, Ralf

    2012-01-01

    Salmonellosis caused by Salmonella (S.) belongs to the most prevalent food-borne zoonotic diseases throughout the world. Therefore, serotype identification for all culture-confirmed cases of Salmonella infection is important for epidemiological purposes. As a standard, the traditional culture method (ISO 6579:2002) is used to identify Salmonella. Classical serotyping takes 4–5 days to be completed, it is labor-intensive, expensive and more than 250 non-standardized sera are necessary to characterize more than 2,500 Salmonella serovars currently known. These technical difficulties could be overcome with modern molecular methods. We developed a microarray based serogenotyping assay for the most prevalent Salmonella serovars in Europe and North America. The current assay version could theoretically discriminate 28 O-antigens and 86 H-antigens. Additionally, we included 77 targets analyzing antimicrobial resistance genes. The Salmonella assay was evaluated with a set of 168 reference strains representing 132 serovars previously serotyped by conventional agglutination through various reference centers. 117 of 132 (81%) tested serovars showed an unique microarray pattern. 15 of 132 serovars generated a pattern which was shared by multiple serovars (e.g., S. ser. Enteritidis and S. ser. Nitra). These shared patterns mainly resulted from the high similarity of the genotypes of serogroup A and D1. Using patterns of the known reference strains, a database was build which represents the basis of a new PatternMatch software that can serotype unknown Salmonella isolates automatically. After assay verification, the Salmonella serogenotyping assay was used to identify a field panel of 105 Salmonella isolates. All were identified as Salmonella and 93 of 105 isolates (88.6%) were typed in full concordance with conventional serotyping. This microarray based assay is a powerful tool for serogenotyping. PMID:23056321

  8. Assessing the functional coherence of gene sets with metrics based on the Gene Ontology graph.

    Science.gov (United States)

    Richards, Adam J; Muller, Brian; Shotwell, Matthew; Cowart, L Ashley; Rohrer, Bäerbel; Lu, Xinghua

    2010-06-15

    The results of initial analyses for many high-throughput technologies commonly take the form of gene or protein sets, and one of the ensuing tasks is to evaluate the functional coherence of these sets. The study of gene set function most commonly makes use of controlled vocabulary in the form of ontology annotations. For a given gene set, the statistical significance of observing these annotations or 'enrichment' may be tested using a number of methods. Instead of testing for significance of individual terms, this study is concerned with the task of assessing the global functional coherence of gene sets, for which novel metrics and statistical methods have been devised. The metrics of this study are based on the topological properties of graphs comprised of genes and their Gene Ontology annotations. A novel aspect of these methods is that both the enrichment of annotations and the relationships among annotations are considered when determining the significance of functional coherence. We applied our methods to perform analyses on an existing database and on microarray experimental results. Here, we demonstrated that our approach is highly discriminative in terms of differentiating coherent gene sets from random ones and that it provides biologically sensible evaluations in microarray analysis. We further used examples to show the utility of graph visualization as a tool for studying the functional coherence of gene sets. The implementation is provided as a freely accessible web application at: http://projects.dbbe.musc.edu/gosteiner. Additionally, the source code written in the Python programming language, is available under the General Public License of the Free Software Foundation. Supplementary data are available at Bioinformatics online.

  9. Time-course microarray analysis for identifying candidate genes involved in obesity-associated pathological changes in the mouse colon.

    Science.gov (United States)

    Bae, Yun Jung; Kim, Sung-Eun; Hong, Seong Yeon; Park, Taesun; Lee, Sang Gyu; Choi, Myung-Sook; Sung, Mi-Kyung

    2016-01-01

    Obesity is known to increase the risk of colorectal cancer. However, mechanisms underlying the pathogenesis of obesity-induced colorectal cancer are not completely understood. The purposes of this study were to identify differentially expressed genes in the colon of mice with diet-induced obesity and to select candidate genes as early markers of obesity-associated abnormal cell growth in the colon. C57BL/6N mice were fed normal diet (11% fat energy) or high-fat diet (40% fat energy) and were euthanized at different time points. Genome-wide expression profiles of the colon were determined at 2, 4, 8, and 12 weeks. Cluster analysis was performed using expression data of genes showing log 2 fold change of ≥1 or ≤-1 (twofold change), based on time-dependent expression patterns, followed by virtual network analysis. High-fat diet-fed mice showed significant increase in body weight and total visceral fat weight over 12 weeks. Time-course microarray analysis showed that 50, 47, 36, and 411 genes were differentially expressed at 2, 4, 8, and 12 weeks, respectively. Ten cluster profiles representing distinguishable patterns of genes differentially expressed over time were determined. Cluster 4, which consisted of genes showing the most significant alterations in expression in response to high-fat diet over 12 weeks, included Apoa4 (apolipoprotein A-IV), Ppap2b (phosphatidic acid phosphatase type 2B), Cel (carboxyl ester lipase), and Clps (colipase, pancreatic), which interacted strongly with surrounding genes associated with colorectal cancer or obesity. Our data indicate that Apoa4 , Ppap2b , Cel , and Clps are candidate early marker genes associated with obesity-related pathological changes in the colon. Genome-wide analyses performed in the present study provide new insights on selecting novel genes that may be associated with the development of diseases of the colon.

  10. A Latent Variable Approach for Meta-Analysis of Gene Expression Data from Multiple Microarray Experiments

    Directory of Open Access Journals (Sweden)

    Chinnaiyan Arul M

    2007-09-01

    Full Text Available Abstract Background With the explosion in data generated using microarray technology by different investigators working on similar experiments, it is of interest to combine results across multiple studies. Results In this article, we describe a general probabilistic framework for combining high-throughput genomic data from several related microarray experiments using mixture models. A key feature of the model is the use of latent variables that represent quantities that can be combined across diverse platforms. We consider two methods for estimation of an index termed the probability of expression (POE. The first, reported in previous work by the authors, involves Markov Chain Monte Carlo (MCMC techniques. The second method is a faster algorithm based on the expectation-maximization (EM algorithm. The methods are illustrated with application to a meta-analysis of datasets for metastatic cancer. Conclusion The statistical methods described in the paper are available as an R package, metaArray 1.8.1, which is at Bioconductor, whose URL is http://www.bioconductor.org/.

  11. Identification of differentially expressed genes affecting hair and cashmere growth in the Laiwu black goat by microarray.

    Science.gov (United States)

    Zhao, Jinshan; Li, Hegang; Liu, Kaidong; Zhang, Baoxun; Li, Peipei; He, Jianning; Cheng, Ming; De, Wei; Liu, Jifeng; Zhao, Yaofeng; Yang, Lihua; Liu, Nan

    2016-10-01

    Goats are an important source of fibers. In the present study microarray technology was used to investigate the potential genes primarily involved in hair and cashmere growth in the Laiwu black goat. A total of 655 genes differentially expressed in body (hair‑growing) and groin (hairless) skin were identified, and their potential association with hair and cashmere growth was analyzed. The majority of genes associated with hair growth regulation could be assigned to intracellular, intracellular organelle, membrane‑bound vesicle, cytoplasmic vesicle, pattern binding, heparin binding, polysaccharide binding, glycosaminoglycan binding and cytoplasmic membrane‑bound vesicle categories. Numerous genes upregulated in body compared with groin skin contained common motifs for nuclear factor 1A, Yi, E2 factor (E2F) and cyclic adenosine monophosphate response element binding (CREB)/CREBβ binding sites in their promoter region. The promoter region of certain genes downregulated in body compared with groin skin contained three common regions with LF‑A1, Yi, E2F, Collier/Olfactory‑1/early B‑cell factor 1, peroxisome proliferator‑activated receptor α or U sites. Thus, the present study identified molecules in the cashmere‑bearing skin area of the Laiwu black goat, which may contribute to hair and cashmere traits.

  12. Evaluation of current and new biomarkers in severe preeclampsia: a microarray approach reveals the VSIG4 gene as a potential blood biomarker.

    Directory of Open Access Journals (Sweden)

    Julien Textoris

    Full Text Available Preeclampsia is a placental disease characterized by hypertension and proteinuria in pregnant women, and it is associated with a high maternal and neonatal morbidity. However, circulating biomarkers that are able to predict the prognosis of preeclampsia are lacking. Thirty-eight women were included in the current study. They consisted of 19 patients with preeclampsia (13 with severe preeclampsia and 6 with non-severe preeclampsia and 19 gestational age-matched women with normal pregnancies as controls. We measured circulating factors that are associated with the coagulation pathway (including fibrinogen, fibronectin, factor VIII, antithrombin, protein S and protein C, endothelial activation (such as soluble endoglin and CD146, and the release of total and platelet-derived microparticles. These markers enabled us to discriminate the preeclampsia condition from a normal pregnancy but were not sufficient to distinguish severe from non-severe preeclampsia. We then used a microarray to study the transcriptional signature of blood samples. Preeclampsia patients exhibited a specific transcriptional program distinct from that of the control group of women. Interestingly, we also identified a severity-related transcriptional signature. Functional annotation of the upmodulated signature in severe preeclampsia highlighted two main functions related to "ribosome" and "complement". Finally, we identified 8 genes that were specifically upmodulated in severe preeclampsia compared with non-severe preeclampsia and the normotensive controls. Among these genes, we identified VSIG4 as a potential diagnostic marker of severe preeclampsia. The determination of this gene may improve the prognostic assessment of severe preeclampsia.

  13. Korean, Japanese, and Chinese populations featured similar genes encoding drug-metabolizing enzymes and transporters: a DMET Plus microarray assessment.

    Science.gov (United States)

    Yi, SoJeong; An, Hyungmi; Lee, Howard; Lee, Sangin; Ieiri, Ichiro; Lee, Youngjo; Cho, Joo-Youn; Hirota, Takeshi; Fukae, Masato; Yoshida, Kenji; Nagatsuka, Shinichiro; Kimura, Miyuki; Irie, Shin; Sugiyama, Yuichi; Shin, Dong Wan; Lim, Kyoung Soo; Chung, Jae-Yong; Yu, Kyung-Sang; Jang, In-Jin

    2014-10-01

    Interethnic differences in genetic polymorphism in genes encoding drug-metabolizing enzymes and transporters are one of the major factors that cause ethnic differences in drug response. This study aimed to investigate genetic polymorphisms in genes involved in drug metabolism, transport, and excretion among Korean, Japanese, and Chinese populations, the three major East Asian ethnic groups. The frequencies of 1936 variants representing 225 genes encoding drug-metabolizing enzymes and transporters were determined from 786 healthy participants (448 Korean, 208 Japanese, and 130 Chinese) using the Affymetrix Drug-Metabolizing Enzymes and Transporters Plus microarray. To compare allele or genotype frequencies in the high-dimensional data among the three East Asian ethnic groups, multiple testing, principal component analysis (PCA), and regularized multinomial logit model through least absolute shrinkage and selection operator were used. On microarray analysis, 1071 of 1936 variants (>50% of markers) were found to be monomorphic. In a large number of genetic variants, the fixation index and Pearson's correlation coefficient of minor allele frequencies were less than 0.034 and greater than 0.95, respectively, among the three ethnic groups. PCA identified 47 genetic variants with multiple testing, but was unable to discriminate ethnic groups by the first three components. Multinomial least absolute shrinkage and selection operator analysis identified 269 genetic variants that showed different frequencies among the three ethnic groups. However, none of those variants distinguished between the three ethnic groups during subsequent PCA. Korean, Japanese, and Chinese populations are not pharmacogenetically distant from one another, at least with regard to drug disposition, metabolism, and elimination.

  14. Batch correction of microarray data substantially improves the identification of genes differentially expressed in rheumatoid arthritis and osteoarthritis.

    Science.gov (United States)

    Kupfer, Peter; Guthke, Reinhard; Pohlers, Dirk; Huber, Rene; Koczan, Dirk; Kinne, Raimund W

    2012-06-08

    Batch effects due to sample preparation or array variation (type, charge, and/or platform) may influence the results of microarray experiments and thus mask and/or confound true biological differences. Of the published approaches for batch correction, the algorithm "Combating Batch Effects When Combining Batches of Gene Expression Microarray Data" (ComBat) appears to be most suitable for small sample sizes and multiple batches. Synovial fibroblasts (SFB; purity > 98%) were obtained from rheumatoid arthritis (RA) and osteoarthritis (OA) patients (n = 6 each) and stimulated with TNF-α or TGF-β1 for 0, 1, 2, 4, or 12 hours. Gene expression was analyzed using Affymetrix Human Genome U133 Plus 2.0 chips, an alternative chip definition file, and normalization by Robust Multi-Array Analysis (RMA). Data were batch-corrected for different acquiry dates using ComBat and the efficacy of the correction was validated using hierarchical clustering. In contrast to the hierarchical clustering dendrogram before batch correction, in which RA and OA patients clustered randomly, batch correction led to a clear separation of RA and OA. Strikingly, this applied not only to the 0 hour time point (i.e., before stimulation with TNF-α/TGF-β1), but also to all time points following stimulation except for the late 12 hour time point. Batch-corrected data then allowed the identification of differentially expressed genes discriminating between RA and OA. Batch correction only marginally modified the original data, as demonstrated by preservation of the main Gene Ontology (GO) categories of interest, and by minimally changed mean expression levels (maximal change 4.087%) or variances for all genes of interest. Eight genes from the GO category "extracellular matrix structural constituent" (5 different collagens, biglycan, and tubulointerstitial nephritis antigen-like 1) were differentially expressed between RA and OA (RA > OA), both constitutively at time point 0, and at all time

  15. Batch correction of microarray data substantially improves the identification of genes differentially expressed in Rheumatoid Arthritis and Osteoarthritis

    Directory of Open Access Journals (Sweden)

    Kupfer Peter

    2012-06-01

    Full Text Available Abstract Background Batch effects due to sample preparation or array variation (type, charge, and/or platform may influence the results of microarray experiments and thus mask and/or confound true biological differences. Of the published approaches for batch correction, the algorithm “Combating Batch Effects When Combining Batches of Gene Expression Microarray Data” (ComBat appears to be most suitable for small sample sizes and multiple batches. Methods Synovial fibroblasts (SFB; purity > 98% were obtained from rheumatoid arthritis (RA and osteoarthritis (OA patients (n = 6 each and stimulated with TNF-α or TGF-β1 for 0, 1, 2, 4, or 12 hours. Gene expression was analyzed using Affymetrix Human Genome U133 Plus 2.0 chips, an alternative chip definition file, and normalization by Robust Multi-Array Analysis (RMA. Data were batch-corrected for different acquiry dates using ComBat and the efficacy of the correction was validated using hierarchical clustering. Results In contrast to the hierarchical clustering dendrogram before batch correction, in which RA and OA patients clustered randomly, batch correction led to a clear separation of RA and OA. Strikingly, this applied not only to the 0 hour time point (i.e., before stimulation with TNF-α/TGF-β1, but also to all time points following stimulation except for the late 12 hour time point. Batch-corrected data then allowed the identification of differentially expressed genes discriminating between RA and OA. Batch correction only marginally modified the original data, as demonstrated by preservation of the main Gene Ontology (GO categories of interest, and by minimally changed mean expression levels (maximal change 4.087% or variances for all genes of interest. Eight genes from the GO category “extracellular matrix structural constituent” (5 different collagens, biglycan, and tubulointerstitial nephritis antigen-like 1 were differentially expressed between RA and OA (RA

  16. Kernelized partial least squares for feature reduction and classification of gene microarray data

    Directory of Open Access Journals (Sweden)

    Land Walker H

    2011-12-01

    Full Text Available Abstract Background The primary objectives of this paper are: 1. to apply Statistical Learning Theory (SLT, specifically Partial Least Squares (PLS and Kernelized PLS (K-PLS, to the universal "feature-rich/case-poor" (also known as "large p small n", or "high-dimension, low-sample size" microarray problem by eliminating those features (or probes that do not contribute to the "best" chromosome bio-markers for lung cancer, and 2. quantitatively measure and verify (by an independent means the efficacy of this PLS process. A secondary objective is to integrate these significant improvements in diagnostic and prognostic biomedical applications into the clinical research arena. That is, to devise a framework for converting SLT results into direct, useful clinical information for patient care or pharmaceutical research. We, therefore, propose and preliminarily evaluate, a process whereby PLS, K-PLS, and Support Vector Machines (SVM may be integrated with the accepted and well understood traditional biostatistical "gold standard", Cox Proportional Hazard model and Kaplan-Meier survival analysis methods. Specifically, this new combination will be illustrated with both PLS and Kaplan-Meier followed by PLS and Cox Hazard Ratios (CHR and can be easily extended for both the K-PLS and SVM paradigms. Finally, these previously described processes are contained in the Fine Feature Selection (FFS component of our overall feature reduction/evaluation process, which consists of the following components: 1. coarse feature reduction, 2. fine feature selection and 3. classification (as described in this paper and prediction. Results Our results for PLS and K-PLS showed that these techniques, as part of our overall feature reduction process, performed well on noisy microarray data. The best performance was a good 0.794 Area Under a Receiver Operating Characteristic (ROC Curve (AUC for classification of recurrence prior to or after 36 months and a strong 0.869 AUC for

  17. Generation of EST and Microarray Resources for Functional Genomic Studies on Chicken Intestinal Health

    NARCIS (Netherlands)

    Hemert, van S.; Ebbelaar, B.H.; Smits, M.A.; Rebel, J.M.J.

    2003-01-01

    Expressed sequenced tags (ESTs) and microarray resources have a great impact on the ability to study host response in mice and humans. Unfortunately, these resources are not yet available for domestic farm animals. The aim of this study was to provide genomic resources to study chicken intestinal

  18. "Hook"-calibration of GeneChip-microarrays: Chip characteristics and expression measures

    Directory of Open Access Journals (Sweden)

    Krohn Knut

    2008-08-01

    Full Text Available Abstract Background Microarray experiments rely on several critical steps that may introduce biases and uncertainty in downstream analyses. These steps include mRNA sample extraction, amplification and labelling, hybridization, and scanning causing chip-specific systematic variations on the raw intensity level. Also the chosen array-type and the up-to-dateness of the genomic information probed on the chip affect the quality of the expression measures. In the accompanying publication we presented theory and algorithm of the so-called hook method which aims at correcting expression data for systematic biases using a series of new chip characteristics. Results In this publication we summarize the essential chip characteristics provided by this method, analyze special benchmark experiments to estimate transcript related expression measures and illustrate the potency of the method to detect and to quantify the quality of a particular hybridization. It is shown that our single-chip approach provides expression measures responding linearly on changes of the transcript concentration over three orders of magnitude. In addition, the method calculates a detection call judging the relation between the signal and the detection limit of the particular measurement. The performance of the method in the context of different chip generations and probe set assignments is illustrated. The hook method characterizes the RNA-quality in terms of the 3'/5'-amplification bias and the sample-specific calling rate. We show that the proper judgement of these effects requires the disentanglement of non-specific and specific hybridization which, otherwise, can lead to misinterpretations of expression changes. The consequences of modifying probe/target interactions by either changing the labelling protocol or by substituting RNA by DNA targets are demonstrated. Conclusion The single-chip based hook-method provides accurate expression estimates and chip-summary characteristics

  19. Differential gene expression from genome-wide microarray analyses distinguishes Lohmann Selected Leghorn and Lohmann Brown layers.

    Directory of Open Access Journals (Sweden)

    Christin Habig

    Full Text Available The Lohmann Selected Leghorn (LSL and Lohmann Brown (LB layer lines have been selected for high egg production since more than 50 years and belong to the worldwide leading commercial layer lines. The objectives of the present study were to characterize the molecular processes that are different among these two layer lines using whole genome RNA expression profiles. The hens were kept in the newly developed small group housing system Eurovent German with two different group sizes. Differential expression was observed for 6,276 microarray probes (FDR adjusted P-value <0.05 among the two layer lines LSL and LB. A 2-fold or greater change in gene expression was identified on 151 probe sets. In LSL, 72 of the 151 probe sets were up- and 79 of them were down-regulated. Gene ontology (GO enrichment analysis accounting for biological processes evinced 18 GO-terms for the 72 probe sets with higher expression in LSL, especially those taking part in immune system processes and membrane organization. A total of 32 enriched GO-terms were determined among the 79 down-regulated probe sets of LSL. Particularly, these terms included phosphorus metabolic processes and signaling pathways. In conclusion, the phenotypic differences among the two layer lines LSL and LB are clearly reflected in their gene expression profiles of the cerebrum. These novel findings provide clues for genes involved in economically important line characteristics of commercial laying hens.

  20. Microarray and RT-PCR screening for white spot syndrome virus immediate-early genes in cycloheximide-treated shrimp

    International Nuclear Information System (INIS)

    Liu Wangjing; Chang Yunshiang; Wang Chunghsiung; Kou, Guang-Hsiung; Lo Chufang

    2005-01-01

    Here, we report for the first time the successful use of cycloheximide (CHX) as an inhibitor to block de novo viral protein synthesis during WSSV (white spot syndrome virus) infection. Sixty candidate IE (immediate-early) genes were identified using a global analysis microarray technique. RT-PCR showed that the genes corresponding to ORF126, ORF242 and ORF418 in the Taiwan isolate were consistently CHX-insensitive, and these genes were designated ie1, ie2 and ie3, respectively. The sequences for these IE genes also appear in the two other WSSV isolates that have been sequenced. Three corresponding ORFs were identified in the China WSSV isolate, but only an ORF corresponding to ie1 was predicted in the Thailand isolate. In a promoter activity assay in Sf9 insect cells using EGFP (enhanced green fluorescence protein) as a reporter, ie1 showed very strong promoter activity, producing higher EGFP signals than the insect Orgyia pseudotsugata multicapsid nuclear polyhedrosis virus (OpMNPV) ie2 promoter

  1. DNA Microarray Technology; TOPICAL

    International Nuclear Information System (INIS)

    WERNER-WASHBURNE, MARGARET; DAVIDSON, GEORGE S.

    2002-01-01

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

  2. Regulation of Microtubule, Apoptosis, and Cell Cycle-Related Genes by Taxotere in Prostate Cancer Cells Analyzed by Microarray

    Directory of Open Access Journals (Sweden)

    Yiwei Li

    2004-03-01

    Full Text Available Taxotere showed antitumor activity against solid tumors including prostate cancer. However, the molecular mechanism(s of action of Taxotere has not been fully elucidated. In order to establish such molecular mechanism(s in both hormone-insensitive (PC3 and hormone-sensitive (LNCaP prostate cancer cells, comprehensive gene expression profiles were obtained by Affymetrix Human Genome U133A Array. The RNA from the cells treated with 2 nM Taxotere was subjected to microarray analysis. We found that a total of 166, 365, and 1785 genes showed greater than twofold change in PC3 cells after 6, 36, and 72 hours of treatment, respectively compared to 57, 823, and 964 genes in LNCaP cells. The expression of tubulin was decreased, whereas the expression of microtubuleassociated proteins was increased in Taxotere-treated prostate cancer cells, confirming the microtubuletargeting effect of Taxotere. Clustering analysis showed downregulation of some genes for cell proliferation and cell cycle. In contrast, Taxotere upregulated some genes that are related to induction of apoptosis and cell cycle arrest. From these results, we conclude that Taxotere caused alterations of a large number of genes, many of which may contribute to the molecular mechanism(s by which Taxotere affects prostate cancer cells. Further molecular studies are needed in order to determine the cause and effect relationships between these genes altered by Taxotere. Nevertheless, our results could be further exploited for devising strategies to optimize therapeutic effects of Taxotere for the treatment of prostate cancer.

  3. Ranking, selecting, and prioritising genes with desirability functions

    Directory of Open Access Journals (Sweden)

    Stanley E. Lazic

    2015-11-01

    Full Text Available In functional genomics experiments, researchers often select genes to follow-up or validate from a long list of differentially expressed genes. Typically, sharp thresholds are used to bin genes into groups such as significant/non-significant or fold change above/below a cut-off value, and ad hoc criteria are also used such as favouring well-known genes. Binning, however, is inefficient and does not take the uncertainty of the measurements into account. Furthermore, p-values, fold-changes, and other outcomes are treated as equally important, and relevant genes may be overlooked with such an approach. Desirability functions are proposed as a way to integrate multiple selection criteria for ranking, selecting, and prioritising genes. These functions map any variable to a continuous 0–1 scale, where one is maximally desirable and zero is unacceptable. Multiple selection criteria are then combined to provide an overall desirability that is used to rank genes. In addition to p-values and fold-changes, further experimental results and information contained in databases can be easily included as criteria. The approach is demonstrated with a breast cancer microarray data set. The functions and an example data set can be found in the desiR package on CRAN (https://cran.r-project.org/web/packages/desiR/ and the development version is available on GitHub (https://github.com/stanlazic/desiR.

  4. Carbohydrate microarrays

    DEFF Research Database (Denmark)

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

    2012-01-01

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

  5. miRNA-mediated functional changes through co-regulating function related genes.

    Directory of Open Access Journals (Sweden)

    Jie He

    Full Text Available BACKGROUND: MicroRNAs play important roles in various biological processes involving fairly complex mechanism. Analysis of genome-wide miRNA microarray demonstrate that a single miRNA can regulate hundreds of genes, but the regulative extent on most individual genes is surprisingly mild so that it is difficult to understand how a miRNA provokes detectable functional changes with such mild regulation. RESULTS: To explore the internal mechanism of miRNA-mediated regulation, we re-analyzed the data collected from genome-wide miRNA microarray with bioinformatics assay, and found that the transfection of miR-181b and miR-34a in Hela and HCT-116 tumor cells regulated large numbers of genes, among which, the genes related to cell growth and cell death demonstrated high Enrichment scores, suggesting that these miRNAs may be important in cell growth and cell death. MiR-181b induced changes in protein expression of most genes that were seemingly related to enhancing cell growth and decreasing cell death, while miR-34a mediated contrary changes of gene expression. Cell growth assays further confirmed this finding. In further study on miR-20b-mediated osteogenesis in hMSCs, miR-20b was found to enhance osteogenesis by activating BMPs/Runx2 signaling pathway in several stages by co-repressing of PPARγ, Bambi and Crim1. CONCLUSIONS: With its multi-target characteristics, miR-181b, miR-34a and miR-20b provoked detectable functional changes by co-regulating functionally-related gene groups or several genes in the same signaling pathway, and thus mild regulation from individual miRNA targeting genes could have contributed to an additive effect. This might also be one of the modes of miRNA-mediated gene regulation.

  6. A Review of Feature Extraction Software for Microarray Gene Expression Data

    Directory of Open Access Journals (Sweden)

    Ching Siang Tan

    2014-01-01

    Full Text Available When gene expression data are too large to be processed, they are transformed into a reduced representation set of genes. Transforming large-scale gene expression data into a set of genes is called feature extraction. If the genes extracted are carefully chosen, this gene set can extract the relevant information from the large-scale gene expression data, allowing further analysis by using this reduced representation instead of the full size data. In this paper, we review numerous software applications that can be used for feature extraction. The software reviewed is mainly for Principal Component Analysis (PCA, Independent Component Analysis (ICA, Partial Least Squares (PLS, and Local Linear Embedding (LLE. A summary and sources of the software are provided in the last section for each feature extraction method.

  7. Hepatic gene expression changes in pigs experimentally infected with the lung pathogen Actinobacillus pleuropneumoniae as analysed with an innate immunity focused microarray

    DEFF Research Database (Denmark)

    Skovgaard, Kerstin; Mortensen, Shila; Boye, Mette

    2010-01-01

    Knowledge on gene expression in the liver during respiratory infections is limited although it is well-established that this organ is an important site of synthesis of several systemic innate immune components as response to infections. In the present study, the early transcriptional hepatic...... response of genes associated with innate immune responses was studied in pigs 14–18 h after intranasal inoculation with Actinobacillus pleuropneumoniae, using innate immune focused microarrays and quantitative real-time PCR (qPCR). The microarray analysis of liver tissue established that 51 genes were......, transferrin and albumin which were down-regulated. Additional genes associated with innate immune responses were investigated using qPCR; genes encoding interleukin (IL)1, IL6, IL8, lipopolysaccharide binding protein, lactotransferrin, and PigMAP were up-regulated and interferon 1a, a1-acid glycoprotein...

  8. In vivo corrosion, tumor outcome, and microarray gene expression for two types of muscle-implanted tungsten alloys

    International Nuclear Information System (INIS)

    Schuster, B.E.; Roszell, L.E.; Murr, L.E.; Ramirez, D.A.; Demaree, J.D.; Klotz, B.R.; Rosencrance, A.B.; Dennis, W.E.; Bao, W.; Perkins, E.J.; Dillman, J.F.; Bannon, D.I.

    2012-01-01

    Tungsten alloys are composed of tungsten microparticles embedded in a solid matrix of transition metals such as nickel, cobalt, or iron. To understand the toxicology of these alloys, male F344 rats were intramuscularly implanted with pellets of tungsten/nickel/cobalt, tungsten/nickel/iron, or pure tungsten, with tantalum pellets as a negative control. Between 6 and 12 months, aggressive rhabdomyosarcomas formed around tungsten/nickel/cobalt pellets, while those of tungsten/nickel/iron or pure tungsten did not cause cancers. Electron microscopy showed a progressive corrosion of the matrix phase of tungsten/nickel/cobalt pellets over 6 months, accompanied by high urinary concentrations of nickel and cobalt. In contrast, non-carcinogenic tungsten/nickel/iron pellets were minimally corroded and urinary metals were low; these pellets having developed a surface oxide layer in vivo that may have restricted the mobilization of carcinogenic nickel. Microarray analysis of tumors revealed large changes in gene expression compared with normal muscle, with biological processes involving the cell cycle significantly up‐regulated and those involved with muscle development and differentiation significantly down‐regulated. Top KEGG pathways disrupted were adherens junction, p53 signaling, and the cell cycle. Chromosomal enrichment analysis of genes showed a highly significant impact at cytoband 7q22 (chromosome 7) which included mouse double minute (MDM2) and cyclin‐dependant kinase (CDK4) as well as other genes associated with human sarcomas. In conclusion, the tumorigenic potential of implanted tungsten alloys is related to mobilization of carcinogenic metals nickel and cobalt from corroding pellets, while gene expression changes in the consequent tumors are similar to radiation induced animal sarcomas as well as sporadic human sarcomas. -- Highlights: ► Tungsten/nickel/cobalt, tungsten/nickel/iron, and pure tungsten were studied. ► Male Fischer rats implanted with

  9. In vivo corrosion, tumor outcome, and microarray gene expression for two types of muscle-implanted tungsten alloys

    Energy Technology Data Exchange (ETDEWEB)

    Schuster, B.E. [U.S. Army Research Laboratory, Weapons and Materials Research Directorate, B434 Mulberry Road, Aberdeen Proving Ground, MD 21005-5609 (United States); Roszell, L.E. [U.S. Army Institute of Public Health, 5158 Blackhawk Road, Aberdeen Proving Ground, MD 21010‐5403 (United States); Murr, L.E.; Ramirez, D.A. [Department of Metallurgical and Materials Engineering, University of Texas, El Paso, TX 79968 (United States); Demaree, J.D. [U.S. Army Research Laboratory, Weapons and Materials Research Directorate, B434 Mulberry Road, Aberdeen Proving Ground, MD 21005-5609 (United States); Klotz, B.R. [Dynamic Science Inc., Aberdeen Proving Ground, MD 21005‐5609 (United States); Rosencrance, A.B.; Dennis, W.E. [U.S. Army Center for Environmental Health Research, Department of Chemistry, Ft. Detrick, MD 21702‐5010 (United States); Bao, W. [SAS Institute, Inc. SAS Campus Drive, Cary, NC 27513 (United States); Perkins, E.J. [U.S. Army Engineer Research and Development Center, 3909 Hall Ferry Road, Vicksburg MS 39180 (United States); Dillman, J.F. [U.S. Army Medical Research Institute of Chemical Defense, 3100 Ricketts Point Road, Aberdeen Proving Ground, MD 21010‐5400 (United States); Bannon, D.I., E-mail: desmond.bannon@us.army.mil [U.S. Army Institute of Public Health, 5158 Blackhawk Road, Aberdeen Proving Ground, MD 21010‐5403 (United States)

    2012-11-15

    Tungsten alloys are composed of tungsten microparticles embedded in a solid matrix of transition metals such as nickel, cobalt, or iron. To understand the toxicology of these alloys, male F344 rats were intramuscularly implanted with pellets of tungsten/nickel/cobalt, tungsten/nickel/iron, or pure tungsten, with tantalum pellets as a negative control. Between 6 and 12 months, aggressive rhabdomyosarcomas formed around tungsten/nickel/cobalt pellets, while those of tungsten/nickel/iron or pure tungsten did not cause cancers. Electron microscopy showed a progressive corrosion of the matrix phase of tungsten/nickel/cobalt pellets over 6 months, accompanied by high urinary concentrations of nickel and cobalt. In contrast, non-carcinogenic tungsten/nickel/iron pellets were minimally corroded and urinary metals were low; these pellets having developed a surface oxide layer in vivo that may have restricted the mobilization of carcinogenic nickel. Microarray analysis of tumors revealed large changes in gene expression compared with normal muscle, with biological processes involving the cell cycle significantly up‐regulated and those involved with muscle development and differentiation significantly down‐regulated. Top KEGG pathways disrupted were adherens junction, p53 signaling, and the cell cycle. Chromosomal enrichment analysis of genes showed a highly significant impact at cytoband 7q22 (chromosome 7) which included mouse double minute (MDM2) and cyclin‐dependant kinase (CDK4) as well as other genes associated with human sarcomas. In conclusion, the tumorigenic potential of implanted tungsten alloys is related to mobilization of carcinogenic metals nickel and cobalt from corroding pellets, while gene expression changes in the consequent tumors are similar to radiation induced animal sarcomas as well as sporadic human sarcomas. -- Highlights: ► Tungsten/nickel/cobalt, tungsten/nickel/iron, and pure tungsten were studied. ► Male Fischer rats implanted with

  10. Sulforaphane Enhances the Ability of Human Retinal Pigment Epithelial Cell against Oxidative Stress, and Its Effect on Gene Expression Profile Evaluated by Microarray Analysis

    Directory of Open Access Journals (Sweden)

    Liang Ye

    2013-01-01

    Full Text Available To gain further insights into the molecular basis of Sulforaphane (SF mediated retinal pigment epithelial (RPE 19 cell against oxidative stress, we investigated the effects of SF on the regulation of gene expression on a global scale and tested whether SF can endow RPE cells with the ability to resist apoptosis. The data revealed that after exposure to H2O2, RPE 19 cell viability was increased in the cells pretreated with SF compared to the cell not treated with SF. Microarray analysis revealed significant changes in the expression of 69 genes in RPE 19 cells after 6 hours of SF treatment. Based on the functional relevance, eight of the SF-responsive genes, that belong to antioxidant redox system, and inflammatory responsive factors were validated. The up-regulating translation of thioredoxin-1 (Trx1 and the nuclear translocation of Nuclear factor-like2 (Nrf2 were demonstrated by immunoblot analysis in SF treated RPE cells. Our data indicate that SF increases the ability of RPE 19 cell against oxidative stress through up-regulating antioxidative enzymes and down-regulating inflammatory mediators and chemokines. The results suggest that the antioxidant, SF, may be a valuable supplement for preventing and retarding the development of Age Related Macular Degeneration.

  11. Identification of genes highly downregulated in pancreatic cancer through a meta-analysis of microarray datasets: implications for discovery of novel tumor-suppressor genes and therapeutic targets.

    Science.gov (United States)

    Goonesekere, Nalin C W; Andersen, Wyatt; Smith, Alex; Wang, Xiaosheng

    2018-02-01

    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 5-year survival rate of about 7%. Recent failures of targeted therapies inhibiting kinase activity in clinical trials have highlighted the need for new approaches towards combating this deadly disease. In this study, we have identified genes that are significantly downregulated in PC, through a meta-analysis of large number of microarray datasets. We have used qRT-PCR to confirm the downregulation of selected genes in a panel of PC cell lines. This study has yielded several novel candidate tumor-suppressor genes (TSGs) including GNMT, CEL, PLA2G1B and SERPINI2. We highlight the role of GNMT, a methyl transferase associated with the methylation potential of the cell, and CEL, a lipase, as potential therapeutic targets. We have uncovered genetic links to risk factors associated with PC such as smoking and obesity. Genes important for patient survival and prognosis are also discussed, and we confirm the dysregulation of metabolic pathways previously observed in PC. While many of the genes downregulated in our dataset are associated with protein products normally produced by the pancreas for excretion, we have uncovered some genes whose downregulation appear to play a more causal role in PC. These genes will assist in providing a better understanding of the disease etiology of PC, and in the search for new therapeutic targets and biomarkers.

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

    LENUS (Irish Health Repository)

    McNicholas, Sinead

    2011-12-01

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

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

    LENUS (Irish Health Repository)

    McNicholas, Sinead

    2012-02-01

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

  14. Microarray-based mutation analysis of the ABCA4 (ABCR) gene in autosomal recessive cone-rod dystrophy and retinitis pigmentosa.

    NARCIS (Netherlands)

    Klevering, B.J.; Ijzer, S.; Rohrschneider, K.; Zonneveld-Vrieling, M.N.; Allikmets, R.; Born, L.I. van den; Maugeri, A.; Hoyng, C.B.; Cremers, F.P.M.

    2004-01-01

    Mutations in the ABCA4 gene have been associated with autosomal recessive Stargardt disease (STGD1), cone-rod dystrophy (CRD), and retinitis pigmentosa (RP). We employed a recently developed genotyping microarray, the ABCR400-chip, to search for known ABCA4 mutations in patients with isolated or

  15. Microarray gene cluster identification and annotation through cluster ensemble and EM-based informative textual summarization.

    Science.gov (United States)

    Hu, Xiaohua; Park, E K; Zhang, Xiaodan

    2009-09-01

    Generating high-quality gene clusters and identifying the underlying biological mechanism of the gene clusters are the important goals of clustering gene expression analysis. To get high-quality cluster results, most of the current approaches rely on choosing the best cluster algorithm, in which the design biases and assumptions meet the underlying distribution of the dataset. There are two issues for this approach: 1) usually, the underlying data distribution of the gene expression datasets is unknown and 2) there are so many clustering algorithms available and it is very challenging to choose the proper one. To provide a textual summary of the gene clusters, the most explored approach is the extractive approach that essentially builds upon techniques borrowed from the information retrieval, in which the objective is to provide terms to be used for query expansion, and not to act as a stand-alone summary for the entire document sets. Another drawback is that the clustering quality and cluster interpretation are treated as two isolated research problems and are studied separately. In this paper, we design and develop a unified system Gene Expression Miner to address these challenging issues in a principled and general manner by integrating cluster ensemble, text clustering, and multidocument summarization and provide an environment for comprehensive gene expression data analysis. We present a novel cluster ensemble approach to generate high-quality gene cluster. In our text summarization module, given a gene cluster, our expectation-maximization based algorithm can automatically identify subtopics and extract most probable terms for each topic. Then, the extracted top k topical terms from each subtopic are combined to form the biological explanation of each gene cluster. Experimental results demonstrate that our system can obtain high-quality clusters and provide informative key terms for the gene clusters.

  16. Gamma-Tocotrienol Modulated Gene Expression in Senescent Human Diploid Fibroblasts as Revealed by Microarray Analysis

    Directory of Open Access Journals (Sweden)

    Suzana Makpol

    2013-01-01

    Full Text Available The effect of γ-tocotrienol, a vitamin E isomer, in modulating gene expression in cellular aging of human diploid fibroblasts was studied. Senescent cells at passage 30 were incubated with 70 μM of γ-tocotrienol for 24 h. Gene expression patterns were evaluated using Sentrix HumanRef-8 Expression BeadChip from Illumina, analysed using GeneSpring GX10 software, and validated using quantitative RT-PCR. A total of 100 genes were differentially expressed (P<0.001 by at least 1.5 fold in response to γ-tocotrienol treatment. Amongst the genes were IRAK3, SelS, HSPA5, HERPUD1, DNAJB9, SEPR1, C18orf55, ARF4, RINT1, NXT1, CADPS2, COG6, and GLRX5. Significant gene list was further analysed by Gene Set Enrichment Analysis (GSEA, and the Normalized Enrichment Score (NES showed that biological processes such as inflammation, protein transport, apoptosis, and cell redox homeostasis were modulated in senescent fibroblasts treated with γ-tocotrienol. These findings revealed that γ-tocotrienol may prevent cellular aging of human diploid fibroblasts by modulating gene expression.

  17. A systems biology approach to construct the gene regulatory network of systemic inflammation via microarray and databases mining

    Directory of Open Access Journals (Sweden)

    Lan Chung-Yu

    2008-09-01

    Full Text Available Abstract Background Inflammation is a hallmark of many human diseases. Elucidating the mechanisms underlying systemic inflammation has long been an important topic in basic and clinical research. When primary pathogenetic events remains unclear due to its immense complexity, construction and analysis of the gene regulatory network of inflammation at times becomes the best way to understand the detrimental effects of disease. However, it is difficult to recognize and evaluate relevant biological processes from the huge quantities of experimental data. It is hence appealing to find an algorithm which can generate a gene regulatory network of systemic inflammation from high-throughput genomic studies of human diseases. Such network will be essential for us to extract valuable information from the complex and chaotic network under diseased conditions. Results In this study, we construct a gene regulatory network of inflammation using data extracted from the Ensembl and JASPAR databases. We also integrate and apply a number of systematic algorithms like cross correlation threshold, maximum likelihood estimation method and Akaike Information Criterion (AIC on time-lapsed microarray data to refine the genome-wide transcriptional regulatory network in response to bacterial endotoxins in the context of dynamic activated genes, which are regulated by transcription factors (TFs such as NF-κB. This systematic approach is used to investigate the stochastic interaction represented by the dynamic leukocyte gene expression profiles of human subject exposed to an inflammatory stimulus (bacterial endotoxin. Based on the kinetic parameters of the dynamic gene regulatory network, we identify important properties (such as susceptibility to infection of the immune system, which may be useful for translational research. Finally, robustness of the inflammatory gene network is also inferred by analyzing the hubs and "weak ties" structures of the gene network

  18. Advances in metaheuristics for gene selection and classification of microarray data.

    Science.gov (United States)

    Duval, Béatrice; Hao, Jin-Kao

    2010-01-01

    Gene selection aims at identifying a (small) subset of informative genes from the initial data in order to obtain high predictive accuracy for classification. Gene selection can be considered as a combinatorial search problem and thus be conveniently handled with optimization methods. In this article, we summarize some recent developments of using metaheuristic-based methods within an embedded approach for gene selection. In particular, we put forward the importance and usefulness of integrating problem-specific knowledge into the search operators of such a method. To illustrate the point, we explain how ranking coefficients of a linear classifier such as support vector machine (SVM) can be profitably used to reinforce the search efficiency of Local Search and Evolutionary Search metaheuristic algorithms for gene selection and classification.

  19. [Screening of common deafness gene mutations in 17 000 Chinese newborns from Chengdu based on microarray analysis].

    Science.gov (United States)

    Lyu, Kangmo; Xiong, Yehua; Yu, Hao; Zou, Ling; Ran, Longrong; Liu, Deshun; Yin, Qin; Xu, Yingwen; Fang, Xue; Song, Zuling; Huang, Lijia; Tan, Dayong; Zhang, Zhiwei

    2014-10-01

    To achieve early diagnosis for inheritable hearing loss and determine carrier rate of deafness causing gene mutations in order to provide information for premarital, prenatal and postnatal genetic counseling. A total of 17 000 dried heel blood spots of normal newborns in Chengdu were collected with informed consent obtained from their parents. Genomic DNA was extracted from dried blood spots using Qiagen DNA extraction kits. Microarrays with 9 common mutation loci of 4 deafness-associated genes in Chinese population were used. Nine hot mutations including GJB2 (35delG, 176del16, 235delC and 299delAT), GJB3 (538C> T), SLC26A4 (IVS 7-2A> G, 2168A> G), and mitochondrial DNA 12S rRNA (1555A> G, 1494C> T) were detected by PCR amplification and microarray hybridization. Mutations detected by microarray were verified by Sanger DNA sequencing. Of the 17 000 new-borns, 542 neonates had mutations of the 4 genes. Heterozygous mutations of GJB2, at 235delC, 299delAT, and 176del16 were identified in 254, 55, and 15 newborns, respectively. Two newborns had homozygous mutation of GJB2, 235delC. Heterozygous mutations at 538C> T of GJB3, 2168A> G and IVS 7-2A> G of SLC26A4 were found in 23, 17 and 128 newborns, respectively. For mutation analysis of mitochondrial DNA 12S rRNA, 1494C> T and 1555A> G were homogeneous mutations in 4 and 42 neonates, respectively. In addition, 6 complexity mutations were detected, which demonstrated that one newborn had heterozygous mutations at GJB2 235delC and SLC26A4, IVS7-2A> G, one had heterozygous mutation GJB2 235delC and 12S rRNA homogeneous mutation, 1555 A> G, one heterozygous mutations at GJB2, 299delAT, and GJB3, 538C> T, one at GJB2, 299delAT and 12S rRNA, 1555 A> G, two at GJB2, 299delAT, and SLC26A4, IVS7-2A> G. All mutations as above were confirmed by DNA sequencing. The total mutation carrier rate of the 4 deafness genes is 3.19% in healthy newborns at Chengdu. Mutations of GJB2 and SLAC26A4 are major ones (86.5% of total). The

  20. Microarray Analyses of Peripheral Blood Cells Identifies Unique Gene Expression Signature in Psoriatic Arthritis

    Science.gov (United States)

    Batliwalla, Franak M.; Li, Wentian; Ritchlin, Christopher T.; Xiao, Xiangli; Brenner, Max; Laragione, Teresina; Shao, Tianmeng; Durham, Robert; Kemshetti, Sunil; Schwarz, Edward; Coe, Rodney; Kern, Marlena; Baechler, Emily C.; Behrens, Timothy W.; Gregersen, Peter K.

    2005-01-01

    Psoriatic arthritis (PsA) is a chronic and erosive form of arthritis of unknown cause. We aimed to characterize the PsA phenotype using gene expression profiling and comparing it with healthy control subjects and patients rheumatoid arthritis (RA). Peripheral blood cells (PBCs) of 19 patients with active PsA and 19 age- and sex-matched control subjects were used in the analyses of PsA, with blood samples collected in PaxGene tubes. A significant alteration in the pattern of expression of 313 genes was noted in the PBCs of PsA patients on Affymetrix U133A arrays: 257 genes were expressed at reduced levels in PsA, and 56 genes were expressed at increased levels, compared with controls. Downregulated genes tended to cluster to certain chromosomal regions, including those containing the psoriasis susceptibility loci PSORS1 and PSORS2. Among the genes with the most significantly reduced expression were those involved in downregulation or suppression of innate and acquired immune responses, such as SIGIRR, STAT3, SHP1, IKBKB, IL-11RA, and TCF7, suggesting inappropriate control that favors proin-flammatory responses. Several members of the MAPK signaling pathway and tumor suppressor genes showed reduced expression. Three proinflammatory genes—S100A8, S100A12, and thioredoxin—showed increased expression. Logistic regression and recursive partitioning analysis determined that one gene, nucleoporin 62 kDa, could correctly classify all controls and 94.7% of the PsA patients. Using a dataset of 48 RA samples for comparison, the combination of two genes, MAP3K3 followed by CACNA1S, was enough to correctly classify all RA and PsA patients. Thus, PBC gene expression profiling identified a gene expression signature that differentiated PsA from RA, and PsA from controls. Several novel genes were differentially expressed in PsA and may prove to be diagnostic biomarkers or serve as new targets for the development of therapies. PMID:16622521

  1. Analysis of promoter regions of co-expressed genes identified by microarray analysis

    Directory of Open Access Journals (Sweden)

    Höglund Mattias

    2006-08-01

    Full Text Available Abstract Background The use of global gene expression profiling to identify sets of genes with similar expression patterns is rapidly becoming a widespread approach for understanding biological processes. A logical and systematic approach to study co-expressed genes is to analyze their promoter sequences to identify transcription factors that may be involved in establishing specific profiles and that may be experimentally investigated. Results We introduce promoter clustering i.e. grouping of promoters with respect to their high scoring motif content, and show that this approach greatly enhances the identification of common and significant transcription factor binding sites (TFBS in co-expressed genes. We apply this method to two different dataset, one consisting of micro array data from 108 leukemias (AMLs and a second from a time series experiment, and show that biologically relevant promoter patterns may be obtained using phylogenetic foot-printing methodology. In addition, we also found that 15% of the analyzed promoter regions contained transcription factors start sites for additional genes transcribed in the opposite direction. Conclusion Promoter clustering based on global promoter features greatly improve the identification of shared TFBS in co-expressed genes. We believe that the outlined approach may be a useful first step to identify transcription factors that contribute to specific features of gene expression profiles.

  2. Function analysis of unknown genes

    DEFF Research Database (Denmark)

    Rogowska-Wrzesinska, A.

    2002-01-01

      This thesis entitled "Function analysis of unknown genes" presents the use of proteome analysis for the characterisation of yeast (Saccharomyces cerevisiae) genes and their products (proteins especially those of unknown function). This study illustrates that proteome analysis can be used...... be obtained using proteome analysis. Chapter 1 and 2 provide the basic theoretical aspects of proteome analysis, its principles, the main techniques involved and their use in the studies of the molecular biology of yeast cells. Chapter 3 presents the methods and tools involved in proteome analysis and used...... presents a comparison of the proteomes of three yeast wild type strains CEN.PK2, FY1679 and W303 that are widely used in function analysis projects and proves that FY1679 and W303 strains are more similar to each other than to the CEN.PK2 strain. This study identifies 62 proteins that are differentially...

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

    African Journals Online (AJOL)

    catalase and peroxidase), and ion transporters (Na+- driven multidrug efflux pump, vacuolar ATPase, and others) were induced. The ACC oxidase and ethylene-responsive gene tomato homologs had higher transcript level after salt treatment.

  4. Identification of Candidate Breast Cancer Susceptibility Genes Using a cDNA Microarray/CGH Approach

    National Research Council Canada - National Science Library

    Godwin, Andrew

    2003-01-01

    ...; the most notorious are the BRCA1 and BRCA2 genes. However, it has become evident that not all (or even the majority) of familial breast cancer families can be attributed to mutations in BRCA1 and BRCA2...

  5. Identification of Candidate Breast Cancer Susceptibility Genes Using a cDNA Microarray/CGH Approach

    National Research Council Canada - National Science Library

    Godwin, Andrew

    2002-01-01

    ...; the most notorious are the BRCAl and BRCA2 genes. However, it has become evident that not all (or even the majority) of familial breast cancer families can be attributed to mutations in BRCAl and BRCA2...

  6. Microarray expression analysis of genes involved in innate immune memory in peritoneal macrophages

    Directory of Open Access Journals (Sweden)

    Keisuke Yoshida

    2016-03-01

    Full Text Available Immunological memory has been believed to be a feature of the adaptive immune system for long period, but recent reports suggest that the innate immune system also exhibits memory-like reaction. Although evidence of innate immune memory is accumulating, no in vivo experimental data has clearly implicated a molecular mechanism, or even a cell-type, for this phenomenon. In this study of data deposited into Gene Expression Omnibus (GEO under GSE71111, we analyzed the expression profile of peritoneal macrophages isolated from mice pre-administrated with toll-like receptor (TLR ligands, mimicking pathogen infection. In these macrophages, increased expression of a group of innate immunity-related genes was sustained over a long period of time, and these genes overlapped with ATF7-regulated genes. We conclude that ATF7 plays an important role in innate immune memory in macrophages.

  7. XENOBIOTIC INDUCED ORGAN-SPECIFIC GENE EXPRESSION AND MACRO/MICROARRAY DEVELOPMENT IN MEDAKA (ORYZIAS LATIPES)

    Science.gov (United States)

    As part of an ongoing effort to understand and address the short and long-term consequences of increasing levels of environmental contaminants, we used suppressive subtractive hydridization (SSH) to develop gene expression profiles from Japanese medaka (Oryzias latipes) exposed ...

  8. Microarray gene expression during early healing of GBR-treated calvarial critical size defects.

    Science.gov (United States)

    Al-Kattan, R; Retzepi, M; Calciolari, E; Donos, N

    2017-10-01

    To investigate the gene expression and molecular pathways implicated in the regulation of the osseous healing process following guided bone regeneration (GBR). Six 6-month-old Wistar male rats were used. Standardized 5-mm critical size defects were created in the parietal bones of each animal and treated with an extracranial and intracranial ePTFE membrane, according to the GBR principle. Three animals were randomly sacrificed after 7 and 15 days of healing. Total RNA was extracted from each sample and prepared for gene expression analysis. RNA quality and quantity were assessed, followed by hybridization of the cRNA to Affymetrix GeneChip Rat Genome 230 2.0 Arrays. The Affymetrix data were processed, and first-order analysis, quality control and statistical analysis were performed. Biological interpretation was performed via pathway and Gene Ontology (GO) analysis. Between the 7- and 15-day samples, 538 genes were differently regulated. At day 7, inflammatory and immune responses were clearly upregulated. In addition, GO terms related to angiogenesis and cell cycle regulation were overexpressed. At day 15, a more complex cellular activity and cell metabolism were evident. The bone formation processes were significantly overexpressed, with several genes encoding growth factors, enzyme activity, and extracellular matrix formation found as upregulated. Remarkably, a negative regulation of Wnt signalling pathway was observed at 15 days. The gene expression profile of the cells participating in osseous formation varied depending on the healing stage. A number of candidate genes that seem differentially expressed during early stages of intramembranous bone regeneration was suggested. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  9. Microarray based analysis of gene regulation by mesenchymal stem cells in breast cancer

    OpenAIRE

    Zhang, Ming; Gao, Chang E.; Li, Wen Hui; Yang, Yi; Chang, Li; Dong, Jian; Ren, Yan Xin; Chen, De Dian

    2017-01-01

    Breast cancer is one of the most common malignant tumors with a high case-fatality rate among women. The present study aimed to investigate the effects of mesenchymal stem cells (MSCs) on breast cancer by exploring the potential underlying molecular mechanisms. The expression profile of GSE43306, which refers to MDA-MB-231 cells with or without a 1:1 ratio of MSCs, was downloaded from Gene Expression Omnibus database for differentially expressed gene (DEG) screening. The Database for Annotati...

  10. Microarray-based analysis of gene expression profiles in peripheral blood of patients with acute primary angle closure.

    Science.gov (United States)

    Jeoung, Jin Wook; Ko, Jung Hwa; Kim, Yu Jeong; Kim, Yong Woo; Park, Ki Ho; Oh, Joo Youn

    2017-12-01

    We investigated the expression of molecules in peripheral blood mononuclear cells (PBMCs) and plasma of patients with acute primary angle closure (APAC). Peripheral blood was collected from patients with APAC (n = 10) and age-matched controls (n = 5). The gene transcription profile was analyzed in PBMCs using microarrays and validated by real-time reverse transcription polymerase chain reaction (RT-PCR). The levels of secreted proteins were evaluated in plasma by ELISA. 347 gene transcripts were up-regulated by 2-fold or more, and 696 transcripts down-regulated 2-fold or more in PBMCs from patients compared to controls. The most highly up-regulated gene was thrombospondin-1 (TSP-1, 8.66-fold increase), and the most down-regulated gene was prostaglandin-endoperoxide synthase 2 (PTGS2, 9.09-fold decrease). Real-time RT-PCR assay confirmed the increase of TSP-1 and the decrease of PTGS2 in PBMCs of patients. ELISA revealed that the levels of TSP-1 and active transforming growth factor (TGF)-β1 that is activated by TSP-1 were elevated in plasma of patients, while the level of prostaglandin E2 (PGE2) that is converted by PTGS2 was reduced. The plasma level of TSP-1 was positively correlated with that of active TGF-β1. Our data suggest that the molecular network including TSP-1, TGF-β1, and PGE2 might be involved in the pathogenesis of APAC and PACG.

  11. Microarray-based analysis of the differential expression of melanin synthesis genes in dark and light-muzzle Korean cattle.

    Directory of Open Access Journals (Sweden)

    Sang Hwan Kim

    Full Text Available The coat color of mammals is determined by the melanogenesis pathway, which is responsible for maintaining the balance between black-brown eumelanin and yellow-reddish pheomelanin. It is also believed that the color of the bovine muzzle is regulated in a similar manner; however, the molecular mechanism underlying pigment deposition in the dark-muzzle has yet to be elucidated. The aim of the present study was to identify melanogenesis-associated genes that are differentially expressed in the dark vs. light muzzle of native Korean cows. Using microarray clustering and real-time polymerase chain reaction techniques, we observed that the expression of genes involved in the mitogen-activated protein kinase (MAPK and Wnt signaling pathways is distinctively regulated in the dark and light muzzle tissues. Differential expression of tyrosinase was also noticed, although the difference was not as distinct as those of MAPK and Wnt. We hypothesize that emphasis on the MAPK pathway in the dark-muzzle induces eumelanin synthesis through the activation of cAMP response element-binding protein and tyrosinase, while activation of Wnt signaling counteracts this process and raises the amount of pheomelanin in the light-muzzle. We also found 2 novel genes (GenBank No. NM-001076026 and XM-588439 with increase expression in the black nose, which may provide additional information about the mechanism of nose pigmentation. Regarding the increasing interest in the genetic diversity of cattle stocks, genes we identified for differential expression in the dark vs. light muzzle may serve as novel markers for genetic diversity among cows based on the muzzle color phenotype.

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

    Science.gov (United States)

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

    2013-12-27

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

  13. Virulence Characterization of Salmonella enterica by a New Microarray: Detection and Evaluation of the Cytolethal Distending Toxin Gene Activity in the Unusual Host S. Typhimurium.

    Directory of Open Access Journals (Sweden)

    Rui Figueiredo

    Full Text Available Salmonella enterica is a zoonotic foodborne pathogen that causes acute gastroenteritis in humans. We assessed the virulence potential of one-hundred and six Salmonella strains isolated from food animals and products. A high through-put virulence genes microarray demonstrated Salmonella Pathogenicity Islands (SPI and adherence genes were highly conserved, while prophages and virulence plasmid genes were variably present. Isolates were grouped by serotype, and virulence plasmids separated S. Typhimurium in two clusters. Atypical microarray results lead to whole genome sequencing (WGS of S. Infantis Sal147, which identified deletion of thirty-eight SPI-1 genes. Sal147 was unable to invade HeLa cells and showed reduced mortality in Galleria mellonella infection model, in comparison to a SPI-1 harbouring S. Infantis. Microarray and WGS of S. Typhimurium Sal199, established for the first time in S. Typhimurium presence of cdtB and other Typhi-related genes. Characterization of Sal199 showed cdtB genes were upstream of transposase IS911, and co-expressed with other Typhi-related genes. Cell cycle arrest, cytoplasmic distension, and nuclear enlargement were detected in HeLa cells infected by Sal199, but not with S. Typhimurium LT2. Increased mortality of Galleria was detected on infection with Sal199 compared to LT2. Thus, Salmonella isolates were rapidly characterized using a high through-put microarray; helping to identify unusual virulence features which were corroborated by further characterisation. This work demonstrates that the use of suitable screening methods for Salmonella virulence can help assess the potential risk associated with certain Salmonella to humans. Incorporation of such methodology into surveillance could help reduce the risk of emergence of epidemic Salmonella strains.

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

    Science.gov (United States)

    Fernandez, Paula; Di Rienzo, Julio; Fernandez, Luis; Hopp, H Esteban; Paniego, Norma; Heinz, Ruth A

    2008-01-26

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

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

    Directory of Open Access Journals (Sweden)

    Paniego Norma

    2008-01-01

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

  16. Microarray analysis of gene expression in peripheral blood mononuclear cells from dioxin-exposed human subjects

    International Nuclear Information System (INIS)

    McHale, Cliona M.; Zhang, Luoping; Hubbard, Alan E.; Zhao, Xin; Baccarelli, Andrea; Pesatori, Angela C.; Smith, Martyn T.; Landi, Maria Teresa

    2007-01-01

    Tetrachlorodibenzo-p-dioxin (TCDD) is classified as a human carcinogen and exerts toxic effects on the skin (chloracne). Effects on reproductive, immunological, and endocrine systems have also been observed in animal models. TCDD acts through the aryl hydrocarbon receptor (AhR) pathway influencing largely unknown gene networks. An industrial accident in Seveso, Italy in 1976 exposed thousands of people to substantial quantities of TCDD. Twenty years after the exposure, this study examines global gene expression in the mononuclear cells of 26 Seveso female never smokers, with similar age, alcohol consumption, use of medications, and background plasma levels of 22 dioxin congeners unrelated to the Seveso accident. Plasma dioxin levels were still elevated in the exposed subjects. We performed analyses in two different comparison groups. The first included high-exposed study subjects compared with individuals with background TCDD levels (average plasma levels 99.4 and 6.7 ppt, respectively); the second compared subjects who developed chloracne after the accident, and those who did not develop this disease. Overall, we observed a modest alteration of gene expression based on dioxin levels or on chloracne status. In the comparison between high levels and background levels of TCDD, four histone genes were up-regulated and modified expression of HIST1H3H was confirmed by real-time PCR. In the comparison between chloracne case-control subjects, five hemoglobin genes were up-regulated. Pathway analysis revealed two major networks for each comparison, involving cell proliferation, apoptosis, immunological and hematological disease, and other pathways. Further examination of the role of these genes in dioxin induced-toxicity is warranted

  17. Progressive obesity leads to altered ovarian gene expression in the Lethal Yellow mouse: a microarray study

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    Brannian John

    2009-08-01

    Full Text Available Abstract Background Lethal yellow (LY; C57BL/6J Ay/a mice exhibit adult-onset obesity, altered metabolic regulation, and early reproductive senescence. The present study was designed to test the hypothesis that obese LY mice possess differences in expression of ovarian genes relative to age-matched lean mice. Methods 90- and 180-day-old LY and lean black (C57BL/6J a/a mice were suppressed with GnRH antagonist (Antide®, then stimulated with 5 IU eCG. cRNA derived from RNA extracts of whole ovarian homogenates collected 36 h post-eCG were run individually on Codelink Mouse Whole Genome Bioarrays (GE Healthcare Life Sciences. Results Fifty-two genes showed ≥ 2-fold differential (p Cyp51, and steroidogenic acute regulatory protein (Star. Fewer genes showed lower expression in LY mice, e.g. angiotensinogen. In contrast, none of these genes showed differential expression in 90-day-old LY and black mice, which are of similar body weight. Interestingly, 180-day-old LY mice had a 2-fold greater expression of 11beta-hydroxysteroid dehydrogenase type 1 (Hsd11b1 and a 2-fold lesser expression of 11beta-hydroxysteroid dehydrogenase type 2 (Hsd11b2, differences not seen in 90-day-old mice. Consistent with altered Hsd11b gene expression, ovarian concentrations of corticosterone (C were elevated in aging LY mice relative to black mice, but C levels were similar in young LY and black mice. Conclusion The data suggest that reproductive dysfunction in aging obese mice is related to modified intraovarian gene expression that is directly related to acquired obesity.

  18. Functional microarray analysis suggests repressed cell-cell signaling and cell survival-related modules inhibit progression of head and neck squamous cell carcinoma

    Directory of Open Access Journals (Sweden)

    Soares Fernando A

    2011-04-01

    Full Text Available Abstract Background Cancer shows a great diversity in its clinical behavior which cannot be easily predicted using the currently available clinical or pathological markers. The identification of pathways associated with lymph node metastasis (N+ and recurrent head and neck squamous cell carcinoma (HNSCC may increase our understanding of the complex biology of this disease. Methods Tumor samples were obtained from untreated HNSCC patients undergoing surgery. Patients were classified according to pathologic lymph node status (positive or negative or tumor recurrence (recurrent or non-recurrent tumor after treatment (surgery with neck dissection followed by radiotherapy. Using microarray gene expression, we screened tumor samples according to modules comprised by genes in the same pathway or functional category. Results The most frequent alterations were the repression of modules in negative lymph node (N0 and in non-recurrent tumors rather than induction of modules in N+ or in recurrent tumors. N0 tumors showed repression of modules that contain cell survival genes and in non-recurrent tumors cell-cell signaling and extracellular region modules were repressed. Conclusions The repression of modules that contain cell survival genes in N0 tumors reinforces the important role that apoptosis plays in the regulation of metastasis. In addition, because tumor samples used here were not microdissected, tumor gene expression data are represented together with the stroma, which may reveal signaling between the microenvironment and tumor cells. For instance, in non-recurrent tumors, extracellular region module was repressed, indicating that the stroma and tumor cells may have fewer interactions, which disable metastasis development. Finally, the genes highlighted in our analysis can be implicated in more than one pathway or characteristic, suggesting that therapeutic approaches to prevent tumor progression should target more than one gene or pathway

  19. Rotavirus gene structure and function.

    OpenAIRE

    Estes, M K; Cohen, J

    1989-01-01

    Knowledge of the structure and function of the genes and proteins of the rotaviruses has expanded rapidly. Information obtained in the last 5 years has revealed unexpected and unique molecular properties of rotavirus proteins of general interest to virologists, biochemists, and cell biologists. Rotaviruses share some features of replication with reoviruses, yet antigenic and molecular properties of the outer capsid proteins, VP4 (a protein whose cleavage is required for infectivity, possibly ...

  20. Identification of Yellow Pigmentation Genes in Brassica rapa ssp. pekinensis Using Br300 Microarray

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    Hee-Jeong Jung

    2014-01-01

    Full Text Available The yellow color of inner leaves in Chinese cabbage depends on its lutein and carotene content. To identify responsible genes for yellow pigmentation in leaves, the transcriptome profiles of white (Kenshin and yellow leaves (Wheessen were examined using the Br300K oligomeric chip in Chinese cabbage. In yellow leaves, genes involved in carotene synthesis (BrPSY, BrPDS, BrCRTISO, and BrLCYE, lutein, and zeaxanthin synthesis (BrCYP97A3 and BrHYDB were upregulated, while those associated with carotene degradation (BrNCED3, BrNCED4, and BrNCED6 were downregulated. These expression patterns might support that the content of both lutein and total carotenoid was much higher in the yellow leaves than that in the white leaves. These results indicate that the yellow leaves accumulate high levels of both lutein and β-carotene due to stimulation of synthesis and that the degradation rate is inhibited. A large number of responsible genes as novel genes were specifically expressed in yellow inner leaves, suggesting the possible involvement in pigment synthesis. Finally, we identified three transcription factors (BrA20/AN1-like, BrBIM1, and BrZFP8 that are specifically expressed and confirmed their relatedness in carotenoid synthesis from Arabidopsis plants.

  1. Microarray based analysis of gene regulation by mesenchymal stem cells in breast cancer.

    Science.gov (United States)

    Zhang, Ming; Gao, Chang E; Li, Wen Hui; Yang, Yi; Chang, Li; Dong, Jian; Ren, Yan Xin; Chen, De Dian

    2017-04-01

    Breast cancer is one of the most common malignant tumors with a high case-fatality rate among women. The present study aimed to investigate the effects of mesenchymal stem cells (MSCs) on breast cancer by exploring the potential underlying molecular mechanisms. The expression profile of GSE43306, which refers to MDA-MB-231 cells with or without a 1:1 ratio of MSCs, was downloaded from Gene Expression Omnibus database for differentially expressed gene (DEG) screening. The Database for Annotation, Visualization and Integrated Discovery was used for gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for DEGs. The protein-protein interactional (PPI) network of DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins. The data was subsequently analyzed using molecular complex detection for sub-network mining of modules. Finally, DEGs in modules were analyzed using GO and KEGG pathway enrichment analyses. A total of 291 DEGs including 193 upregulated and 98 downregulated DEGs were obtained. Upregulated DEGs were primarily enriched in pathways including response to wounding (P=5.92×10 -7 ), inflammatory response (P=5.92×10 -4 ) and defense response (P=1.20×10 -2 ), whereas downregulated DEGs were enriched in pathways including the cell cycle (P=7.13×10 -4 ), mitotic cell cycle (P=6.81×10 -3 ) and M phase (P=1.72 ×10 -2 ). The PPI network, which contained 156 nodes and 289 edges, was constructed, and Fos was the hub node with the degree of 29. A total of 3 modules were mined from the PPI network. In total, 14 DEGs in module A were primarily enriched in GO terms, including response to wounding (P=4.77×10 -6 ), wounding healing (P=6.25×10 -7 ) and coagulation (P=1.13 ×10 -7 ), and these DEGs were also enriched in 1 KEGG pathway (complement and coagulation cascades; P=0.0036). Therefore, MSCs were demonstrated to exhibit potentially beneficial effects for breast cancer therapy. In

  2. Microarray based study on virulence-associated genes and resistance determinants of Staphylococcus aureus isolates from cattle.

    Science.gov (United States)

    Monecke, Stefan; Kuhnert, Peter; Hotzel, Helmut; Slickers, Peter; Ehricht, Ralf

    2007-11-15

    Staphylococcus aureus is a common pathogen which can colonise and infect not only man, but also domestic animals. Especially, infection of cattle is of high economic relevance as S. aureus is an important causal agent of bovine mastitis. In the present contribution, a DNA microarray was applied for the study of 144 different gene targets, including resistance genes and genes encoding exotoxins, in S. aureus isolated from cows. One hundred and twenty-eight isolates from Germany and Switzerland were tested. These isolates were assigned to 20 different strains and nine clonal complexes. The majority of isolates belonged either to apparently closely related clonal complexes 8, 25, and 97 (together 34.4%) or were related to the sequenced bovine strain RF122 (48.4%). Notable characteristics of S. aureus of bovine origin are the carriage of intact haemolysin beta (in 82% of isolates tested), the absence of staphylokinase (in 89.1%), the presence of allelic variants of several exotoxins such as toxic shock syndrome toxin and enterotoxin N, and the occurrence of the leukocidin lukF-P83/lukM (in 53.1%). Two isolates were methicillin-resistant S. aureus (MRSA). One of them was a clonal complex 8 MRSA related to the epidemic MRSA strain Irish 01. The other one belonged to ST398/spa-type 34 resembling a newly emerging MRSA strain which has been described to occur in humans as well as in domestic animals. The presence of these two strains highlights the possibility of transfers of S. aureus strains between different host species.

  3. Comparative ovarian microarray analysis of juvenile hormone-responsive genes in water flea Daphnia magna: potential targets for toxicity.

    Science.gov (United States)

    Toyota, Kenji; Williams, Timothy D; Sato, Tomomi; Tatarazako, Norihisa; Iguchi, Taisen

    2017-03-01

    The freshwater zooplankton Daphnia magna has been extensively employed in chemical toxicity tests such as OECD Test Guidelines 202 and 211. Previously, it has been demonstrated that the treatment of juvenile hormones (JHs) or their analogues to female daphnids can induce male offspring production. Based on this finding, a rapid screening method for detection of chemicals with JH-activity was recently developed using adult D. magna. This screening system determines whether a chemical has JH-activity by investigating the male offspring inducibility. Although this is an efficient high-throughput short-term screening system, much remains to be discovered about JH-responsive pathways in the ovary, and whether different JH-activators act via the same mechanism. JH-responsive genes in the ovary including developing oocytes are still largely undescribed. Here, we conducted comparative microarray analyses using ovaries from Daphnia magna treated with fenoxycarb (Fx; artificial JH agonist) or methyl farnesoate (MF; a putative innate JH in daphnids) to elucidate responses to JH agonists in the ovary, including developing oocytes, at a JH-sensitive period for male sex determination. We demonstrate that induction of hemoglobin genes is a well-conserved response to JH even in the ovary, and a potential adverse effect of JH agonist is suppression of vitellogenin gene expression, that might cause reduction of offspring number. This is the first report demonstrating different transcriptomics profiles from MF and an artificial JH agonist in D. magna ovary, improving understanding the tissue-specific mode-of-action of JH. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  4. Microarray analysis of Foxa2 mutant mouse embryos reveals novel gene expression and inductive roles for the gastrula organizer and its derivatives

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    Rossant Janet

    2008-10-01

    Full Text Available Abstract Background The Spemann/Mangold organizer is a transient tissue critical for patterning the gastrula stage vertebrate embryo and formation of the three germ layers. Despite its important role during development, there are still relatively few genes with specific expression in the organizer and its derivatives. Foxa2 is a forkhead transcription factor that is absolutely required for formation of the mammalian equivalent of the organizer, the node, the axial mesoderm and the definitive endoderm (DE. However, the targets of Foxa2 during embryogenesis, and the molecular impact of organizer loss on the gastrula embryo, have not been well defined. Results To identify genes specific to the Spemann/Mangold organizer, we performed a microarray-based screen that compared wild-type and Foxa2 mutant embryos at late gastrulation stage (E7.5. We could detect genes that were consistently down-regulated in replicate pools of mutant embryos versus wild-type, and these included a number of known node and DE markers. We selected 314 genes without previously published data at E7.5 and screened for expression by whole mount in situ hybridization. We identified 10 novel expression patterns in the node and 5 in the definitive endoderm. We also found significant reduction of markers expressed in secondary tissues that require interaction with the organizer and its derivatives, such as cardiac mesoderm, vasculature, primitive streak, and anterior neuroectoderm. Conclusion The genes identified in this screen represent novel Spemann/Mangold organizer genes as well as potential Foxa2 targets. Further investigation will be needed to define these genes as novel developmental regulatory factors involved in organizer formation and function. We have placed these genes in a Foxa2-dependent genetic regulatory network and we hypothesize how Foxa2 may regulate a molecular program of Spemann/Mangold organizer development. We have also shown how early loss of the organizer

  5. Gene masking - a technique to improve accuracy for cancer classification with high dimensionality in microarray data.

    Science.gov (United States)

    Saini, Harsh; Lal, Sunil Pranit; Naidu, Vimal Vikash; Pickering, Vincel Wince; Singh, Gurmeet; Tsunoda, Tatsuhiko; Sharma, Alok

    2016-12-05

    High dimensional feature space generally degrades classification in several applications. In this paper, we propose a strategy called gene masking, in which non-contributing dimensions are heuristically removed from the data to improve classification accuracy. Gene masking is implemented via a binary encoded genetic algorithm that can be integrated seamlessly with classifiers during the training phase of classification to perform feature selection. It can also be used to discriminate between features that contribute most to the classification, thereby, allowing researchers to isolate features that may have special significance. This technique was applied on publicly available datasets whereby it substantially reduced the number of features used for classification while maintaining high accuracies. The proposed technique can be extremely useful in feature selection as it heuristically removes non-contributing features to improve the performance of classifiers.

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

    OpenAIRE

    REN, ZHONGLU; WANG, WENHUI; LI, JINMING

    2015-01-01

    Identifying colon cancer subtypes based on molecular signatures may allow for a more rational, patient-specific approach to therapy in the future. Classifications using gene expression data have been attempted before with little concordance between the different studies carried out. In this study we aimed to uncover subtypes of colon cancer that have distinct biological characteristics and identify a set of novel biomarkers which could best reflect the clinical and/or biological characteristi...

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

    Science.gov (United States)

    Ren, Zhonglu; Wang, Wenhui; Li, Jinming

    2016-02-01

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

  8. Patterns of gene expression in carp liver after exposure to a mixture of waterborne and dietary cadmium using a custom-made microarray

    International Nuclear Information System (INIS)

    Reynders, Hans; Ven, Karlijn van der; Moens, Lotte N.; Remortel, Piet van; De Coen, Wim M.; Blust, Ronny

    2006-01-01

    Gene expression changes in carp liver tissue were studied after acute (3 and 24 h) and subchronic (7 and 28 days) exposure to a mixture of waterborne (9, 105 and 480 μg/l) and dietary (9.5, 122 and 144 μg/g) cadmium, using a custom-made microarray. Suppression subtractive hybridization-PCR (SSH-PCR) was applied to isolate a set of 643 liver genes, involved in multiple biological pathways, such as energy metabolism (e.g. glucokinase), immune response (e.g. complement C3) and stress and detoxification (e.g. cytochrome P450 2F2, glutathione-S-transferase pi). These genes were subsequently spotted on glass-slides for the construction of a custom-made microarray. Resulting microarray hybridizations indicated a highly dynamic response to cadmium exposure. At low exposure concentrations (9 μg/l through water and 9.5 μg/g dry weight through food) mostly energy-related genes (e.g. glucokinase, elastase) were influenced, while a general stress response was obvious through induction of several stress-related genes, including hemopexin and cytochrome P450 2F2, at high cadmium concentrations. In addition, fish exposed to the highest cadmium concentrations showed liver damage after 7 days of exposure, as measured by elevated alanine transaminase activity in plasma and increased liver water content (wet-to-dry weight ratio). Moreover, decreased hematocrit and growth were found at the end of the experiment. Altogether this study clearly demonstrated the importance of varying exposure conditions for the characterization of the molecular impact of cadmium and showed that microarray results can provide important information, required to unravel the molecular events and responses related to cadmium exposure

  9. Concordance analysis of microarray studies identifies representative gene expression changes in Parkinson's disease: a comparison of 33 human and animal studies.

    Science.gov (United States)

    Oerton, Erin; Bender, Andreas

    2017-03-23

    As the popularity of transcriptomic analysis has grown, the reported lack of concordance between different studies of the same condition has become a growing concern, raising questions as to the representativeness of different study types, such as non-human disease models or studies of surrogate tissues, to gene expression in the human condition. In a comparison of 33 microarray studies of Parkinson's disease, correlation and clustering analyses were used to determine the factors influencing concordance between studies, including agreement between different tissue types, different microarray platforms, and between neurotoxic and genetic disease models and human Parkinson's disease. Concordance over all studies is low, with correlation of only 0.05 between differential gene expression signatures on average, but increases within human patients and studies of the same tissue type, rising to 0.38 for studies of human substantia nigra. Agreement of animal models, however, is dependent on model type. Studies of brain tissue from Parkinson's disease patients (specifically the substantia nigra) form a distinct group, showing patterns of differential gene expression noticeably different from that in non-brain tissues and animal models of Parkinson's disease; while comparison with other brain diseases (Alzheimer's disease and brain cancer) suggests that the mixed study types display a general signal of neurodegenerative disease. A meta-analysis of these 33 microarray studies demonstrates the greater ability of studies in humans and highly-affected tissues to identify genes previously known to be associated with Parkinson's disease. The observed clustering and concordance results suggest the existence of a 'characteristic' signal of Parkinson's disease found in significantly affected human tissues in humans. These results help to account for the consistency (or lack thereof) so far observed in microarray studies of Parkinson's disease, and act as a guide to the selection of

  10. Patterns of gene expression in carp liver after exposure to a mixture of waterborne and dietary cadmium using a custom-made microarray

    Energy Technology Data Exchange (ETDEWEB)

    Reynders, Hans [Department of Biology, Research Unit Ecophysiology, Biochemistry and Toxicology Group, University of Antwerp, Groenenborgerlaan 171, B-2020 Antwerp (Belgium)]. E-mail: hans.reynders@ua.ac.be; Ven, Karlijn van der [Department of Biology, Research Unit Ecophysiology, Biochemistry and Toxicology Group, University of Antwerp, Groenenborgerlaan 171, B-2020 Antwerp (Belgium); Moens, Lotte N. [Department of Biology, Research Unit Ecophysiology, Biochemistry and Toxicology Group, University of Antwerp, Groenenborgerlaan 171, B-2020 Antwerp (Belgium); Remortel, Piet van [Department of Mathematics and Informatics, Intelligent Systems Laboratory, University of Antwerp, Middelheimlaan 1, B-2020 Antwerp (Belgium); De Coen, Wim M. [Department of Biology, Research Unit Ecophysiology, Biochemistry and Toxicology Group, University of Antwerp, Groenenborgerlaan 171, B-2020 Antwerp (Belgium); Blust, Ronny [Department of Biology, Research Unit Ecophysiology, Biochemistry and Toxicology Group, University of Antwerp, Groenenborgerlaan 171, B-2020 Antwerp (Belgium)

    2006-11-16

    Gene expression changes in carp liver tissue were studied after acute (3 and 24 h) and subchronic (7 and 28 days) exposure to a mixture of waterborne (9, 105 and 480 {mu}g/l) and dietary (9.5, 122 and 144 {mu}g/g) cadmium, using a custom-made microarray. Suppression subtractive hybridization-PCR (SSH-PCR) was applied to isolate a set of 643 liver genes, involved in multiple biological pathways, such as energy metabolism (e.g. glucokinase), immune response (e.g. complement C3) and stress and detoxification (e.g. cytochrome P450 2F2, glutathione-S-transferase pi). These genes were subsequently spotted on glass-slides for the construction of a custom-made microarray. Resulting microarray hybridizations indicated a highly dynamic response to cadmium exposure. At low exposure concentrations (9 {mu}g/l through water and 9.5 {mu}g/g dry weight through food) mostly energy-related genes (e.g. glucokinase, elastase) were influenced, while a general stress response was obvious through induction of several stress-related genes, including hemopexin and cytochrome P450 2F2, at high cadmium concentrations. In addition, fish exposed to the highest cadmium concentrations showed liver damage after 7 days of exposure, as measured by elevated alanine transaminase activity in plasma and increased liver water content (wet-to-dry weight ratio). Moreover, decreased hematocrit and growth were found at the end of the experiment. Altogether this study clearly demonstrated the importance of varying exposure conditions for the characterization of the molecular impact of cadmium and showed that microarray results can provide important information, required to unravel the molecular events and responses related to cadmium exposure.

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

    Directory of Open Access Journals (Sweden)

    Bihoreau Marie-Thérèse

    2009-02-01

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

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

    LENUS (Irish Health Repository)

    Walsh, Fiona

    2010-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Nobumasa Hitoshi

    2007-04-01

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

  14. A Microarray Study of Carpet-Shell Clam (Ruditapes decussatus Shows Common and Organ-Specific Growth-Related Gene Expression Differences in Gills and Digestive Gland

    Directory of Open Access Journals (Sweden)

    Carlos Saavedra

    2017-11-01

    Full Text Available Growth rate is one of the most important traits from the point of view of individual fitness and commercial production in mollusks, but its molecular and physiological basis is poorly known. We have studied differential gene expression related to differences in growth rate in adult individuals of the commercial marine clam Ruditapes decussatus. Gene expression in the gills and the digestive gland was analyzed in 5 fast-growing and five slow-growing animals by means of an oligonucleotide microarray containing 14,003 probes. A total of 356 differentially expressed genes (DEG were found. We tested the hypothesis that differential expression might be concentrated at the growth control gene core (GCGC, i.e., the set of genes that underlie the molecular mechanisms of genetic control of tissue and organ growth and body size, as demonstrated in model organisms. The GCGC includes the genes coding for enzymes of the insulin/insulin-like growth factor signaling pathway (IIS, enzymes of four additional signaling pathways (Raf/Ras/Mapk, Jnk, TOR, and Hippo, and transcription factors acting at the end of those pathways. Only two out of 97 GCGC genes present in the microarray showed differential expression, indicating a very little contribution of GCGC genes to growth-related differential gene expression. Forty eight DEGs were shared by both organs, with gene ontology (GO annotations corresponding to transcription regulation, RNA splicing, sugar metabolism, protein catabolism, immunity, defense against pathogens, and fatty acid biosynthesis. GO term enrichment tests indicated that genes related to growth regulation, development and morphogenesis, extracellular matrix proteins, and proteolysis were overrepresented in the gills. In the digestive gland overrepresented GO terms referred to gene expression control through chromatin rearrangement, RAS-related small GTPases, glucolysis, and energy metabolism. These analyses suggest a relevant role of, among others

  15. Alignment of gene expression profiles from test samples against a reference database: New method for context-specific interpretation of microarray data

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    Kilpinen Sami K

    2011-03-01

    Full Text Available Abstract Background Gene expression microarray data have been organized and made available as public databases, but the utilization of such highly heterogeneous reference datasets in the interpretation of data from individual test samples is not as developed as e.g. in the field of nucleotide sequence comparisons. We have created a rapid and powerful approach for the alignment of microarray gene expression profiles (AGEP from test samples with those contained in a large annotated public reference database and demonstrate here how this can facilitate interpretation of microarray data from individual samples. Methods AGEP is based on the calculation of kernel density distributions for the levels of expression of each gene in each reference tissue type and provides a quantitation of the similarity between the test sample and the reference tissue types as well as the identity of the typical and atypical genes in each comparison. As a reference database, we used 1654 samples from 44 normal tissues (extracted from the Genesapiens database. Results Using leave-one-out validation, AGEP correctly defined the tissue of origin for 1521 (93.6% of all the 1654 samples in the original database. Independent validation of 195 external normal tissue samples resulted in 87% accuracy for the exact tissue type and 97% accuracy with related tissue types. AGEP analysis of 10 Duchenne muscular dystrophy (DMD samples provided quantitative description of the key pathogenetic events, such as the extent of inflammation, in individual samples and pinpointed tissue-specific genes whose expression changed (SAMD4A in DMD. AGEP analysis of microarray data from adipocytic differentiation of mesenchymal stem cells and from normal myeloid cell types and leukemias provided quantitative characterization of the transcriptomic changes during normal and abnormal cell differentiation. Conclusions The AGEP method is a widely applicable method for the rapid comprehensive interpretation

  16. Contributions to Statistical Problems Related to Microarray Data

    Science.gov (United States)

    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…

  17. Matching of array CGH and gene expression microarray features for the purpose of integrative genomic analyses

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    van Wieringen Wessel N

    2012-05-01

    Full Text Available Abstract Background An increasing number of genomic studies interrogating more than one molecular level is published. Bioinformatics follows biological practice, and recent years have seen a surge in methodology for the integrative analysis of genomic data. Often such analyses require knowledge of which elements of one platform link to those of another. Although important, many integrative analyses do not or insufficiently detail the matching of the platforms. Results We describe, illustrate and discuss six matching procedures. They are implemented in the R-package sigaR (available from Bioconductor. The principles underlying the presented matching procedures are generic, and can be combined to form new matching approaches or be applied to the matching of other platforms. Illustration of the matching procedures on a variety of data sets reveals how the procedures differ in the use of the available data, and may even lead to different results for individual genes. Conclusions Matching of data from multiple genomics platforms is an important preprocessing step for many integrative bioinformatic analysis, for which we present six generic procedures, both old and new. They have been implemented in the R-package sigaR, available from Bioconductor.

  18. Semi-supervised learning for the identification of syn-expressed genes from fused microarray and in situ image data.

    Science.gov (United States)

    Costa, Ivan G; Krause, Roland; Opitz, Lennart; Schliep, Alexander

    2007-01-01

    Gene expression measurements during the development of the fly Drosophila melanogaster are routinely used to find functional modules of temporally co-expressed genes. Complimentary large data sets of in situ RNA hybridization images for different stages of the fly embryo elucidate the spatial expression patterns. Using a semi-supervised approach, constrained clustering with mixture models, we can find clusters of genes exhibiting spatio-temporal similarities in expression, or syn-expression. The temporal gene expression measurements are taken as primary data for which pairwise constraints are computed in an automated fashion from raw in situ images without the need for manual annotation. We investigate the influence of these pairwise constraints in the clustering and discuss the biological relevance of our results. Spatial information contributes to a detailed, biological meaningful analysis of temporal gene expression data. Semi-supervised learning provides a flexible, robust and efficient framework for integrating data sources of differing quality and abundance.

  19. Microarray Gene Expression Analysis of Murine Tumor Heterogeneity Defined by Dynamic Contrast-Enhanced MRI

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    Nick G. Costouros

    2002-07-01

    Full Text Available Current methods of studying angiogenesis are limited in their ability to serially evaluate in vivo function throughout a target tissue. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI and pharmacokinetic modeling provide a useful method for evaluating tissue vasculature based on contrast accumulation and washout. While it is often assumed that areas of high contrast enhancement and washout comprise areas of increased angiogenesis and tumor activity, the actual molecular pathways that are active in such areas are poorly understood. Using DCE-MRI in a murine subcutaneous tumor model, we were able to perform pharmacokinetic functional analysis of a tumor, coregistration of MRI images with histological cross-sections, immunohistochemistry, laser capture microdissection, and genetic profiling of tumor heterogeneity based on pharmacokinetic parameters. Using imaging as a template for biologic investigation, we have not found evidence of increased expression of proangiogenic modulators at the transcriptional level in either distinct pharmacokinetic region. Furthermore, these regions show no difference on histology and CD31 immunohistochemistry. However, the expression of ribosomal proteins was greatly increased in high enhancement and washout regions, implying increased protein translation and consequent increased cellular activity. Together, these findings point to the potential importance of posttranscriptional regulation in angiogenesis and the need for the development of angiogenesis-specific contrast agents to evaluate in vivo angiogenesis at a molecular level.

  20. How does exposure to nickel and cadmium affect the transcriptome of yellow perch (Perca flavescens) – Results from a 1000 candidate-gene microarray

    Energy Technology Data Exchange (ETDEWEB)

    Bougas, Bérénice, E-mail: Berenice.Bougas@ete.inrs.ca [Institut National de la Recherche Scientifique, Centre INRS Eau Terre et Environnement, 490, rue de la Couronne, Québec, Québec G1K 9A9 (Canada); Département de biologie, Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, Québec G1V 0A6 (Canada); Normandeau, Eric [Département de biologie, Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, Québec G1V 0A6 (Canada); Pierron, Fabien [Université de Bordeaux, EPOC, UMR 5805, F-33400 Talence (France); CNRS, EPOC, UMR 5805, F-33400 Talence (France); Campbell, Peter G.C. [Institut National de la Recherche Scientifique, Centre INRS Eau Terre et Environnement, 490, rue de la Couronne, Québec, Québec G1K 9A9 (Canada); Bernatch